S-Adenosyl-l-methionine (SAM)-dependent methyltransferases (MTs) are highly chemoselective enzymes grouped in C-, N-, O-, S- and halide MTs, depending on the (hetero) atom that acts as the methyl group acceptor. So far, OMTs present the largest group, including many well investigated candidates. The catechol OMT from mammals such as from Rattus norvegicus (RnCOMT) is involved in the metabolism of neurotransmitters like dopamine. It is known to methylate the hydroxyl of the catechol ring in the 3 position. There are also reports showing that the regioselectivity of different COMTs can vary leading to different products with methyl groups in the 3 and or 4 positions. Nevertheless, there was only O-methylation reported for COMTs. Another related MT, the caffeate OMT involved in the lignin biosynthesis of plants has also been reported as a chemoselective enzyme. In nature, S-methylation is a rare phenomenon with different methyl donors being involved in the methyl transfer onto sulfur atoms. Several SAM-dependent MTs are identified as S-methyltransferases (SMTs), these are involved in salvaging pathways and xenobiotic metabolism of cells. Here, we report a new function of three OMTs; RnCOMT, a COMT from Myxococcus xanthus (MxSafC), and a CaOMT from Prunus persica (PpCaOMT) with acceptance towards different aromatic thiol substrates with up to full conversion.

A conserved intracellular allosteric binding site (IABS) was recently identified at several G protein-coupled receptors (GPCRs). This target site allows the binding of allosteric modulators and enables a new mode of GPCR inhibition. Herein, we report the development of a NanoBRET-based assay platform based on the fluorescent ligand LT221 (5), to detect intracellular binding to CCR6 and CXCR1, two chemokine receptors that have been pursued as promising drug targets in inflammation and immuno-oncology. Our assay platform enables cell-free as well as cellular NanoBRET-based binding studies in a nonisotopic and straightforward manner. By combining this screening platform with a previously reported CXCR2 assay, we investigated CXCR1/CXCR2/CCR6 selectivity profiles for both known and novel squaramide analogues derived from navarixin, a known intracellular CXCR1/CXCR2 antagonist and phase II clinical candidate for the treatment of pulmonary diseases. By means of these studies we identified compound 10, a previously reported tert-butyl analogue of navarixin, as a low nanomolar intracellular CCR6 antagonist. Further, our assay platform clearly indicated intracellular binding of the CCR6 antagonist PF-07054894, currently evaluated in phase I clinical trials for the treatment of ulcerative colitis, thereby providing profound evidence for the existence and the pharmacological relevance of a druggable IABS at CCR6.

In order to classify histopathology images into 11 classes of cancerous and non-cancerous skin diseases, the pharmaceutical bioinformatics research group at University Freiburg implemented a pipeline based on the TransMIL model [1]. To improve the general performance, we compared four different CNNs for feature extraction in the TransMIL preprocessing pipeline CLAM [2]. Comprehensive evaluations, including detailed analyses of loss, accuracy, F1 score, and attention focus, indicate that ConvNextV2 [3] falls short in comparison to ResNet50 [4], DenseNet201 [5], and EfficientNet [6], which demonstrate nearly equal performance across classes and achieve higher average accuracy. Surprisingly, despite its size, EfficientNet showed slightly better results compared to DenseNet201 and ResNet50. Moreover, the present pipeline exhibits uneven performance across various disease classes, with particular difficulty in distinguishing between the three classes, likely due to the inherent complexities associated with these categories. Despite these challenges, the EfficientNet model remains the most balanced among all those evaluated.

Unlike aquaporins or potassium channels, ammonium transporters (Amts) uniquely discriminate ammonium from potassium and water. This feature has certainly contributed to their repurposing as ammonium receptors during evolution. Here, we describe the ammonium receptor Sd-Amt1, where an Amt module connects to a cytoplasmic diguanylate cyclase transducer module via an HAMP domain. Structures of the protein with and without bound ammonium were determined to 1.7- and 1.9-Ångstrom resolution, depicting the ON and OFF states of the receptor and confirming the presence of a binding site for two ammonium cations that is pivotal for signal perception and receptor activation. The transducer domain was disordered in the crystals, and an AlphaFold2 prediction suggests that the helices linking both domains are flexible. While the sensor domain retains the trimeric fold formed by all Amt family members, the HAMP domains interact as pairs and serve to dimerize the transducer domain upon activation.

Despite substantial heterogeneity of studies, there is evidence that antibiotics commonly used in primary care influence the composition of the gastrointestinal microbiota in terms of changing their composition and/or diversity. Benzyl isothiocyanate (BITC) from the food and medicinal plant nasturtium (Tropaeolum majus) is known for its antimicrobial activity and is used for the treatment of infections of the draining urinary tract and upper respiratory tract. Against this background, we raised the question of whether a 14 d nasturtium intervention (3 g daily, N = 30 healthy females) could also impact the normal gut microbiota composition. Spot urinary BITC excretion highly correlated with a weak but significant antibacterial effect against Escherichia coli. A significant increase in human beta defensin 1 as a parameter for host defense was seen in urine and exhaled breath condensate (EBC) upon verum intervention. Pre-to-post analysis revealed that mean gut microbiome composition did not significantly differ between groups, nor did the circulating serum metabolome. On an individual level, some large changes were observed between sampling points, however. Explorative Spearman rank correlation analysis in subgroups revealed associations between gut microbiota and the circulating metabolome, as well as between changes in blood markers and bacterial gut species.

The application of traditional medicine by humans for the treatment of ailments as well as improving the quality of life far outdates recorded history. To date, a significant percentage of humans, especially those living in developing/underprivileged communities still rely on traditional medicine for primary healthcare needs. In silico-based methods have been shown to play a pivotal role in modern pharmaceutical drug discovery processes. The application of these methods in identifying natural product (NP)-based hits has been successful. This is very much observed in many research set-ups that use rationally in silico-based methods in combination with experimental validation techniques. The combination has rendered the use of in silico-based approaches even more popular and successful in the investigation of NPs. However, identifying and proposing novel NP-based hits for experimental validation comes with several challenges such as the availability of compounds by suppliers, the huge task of separating pure compounds from complex mixtures, the quantity of samples available from the natural source to be tested, not to mention the potential ecological impact if the natural source is exhausted. Because most peer-reviewed publications are biased towards "positive results", these challenges are generally not discussed in publications. In this review, we highlight and discuss these challenges. The idea is to give interested scientists in this field of research an idea of what they can come across or should be expecting as well as prompting them on how to avoid or fix these issues.

The cysteine side chain has a free thiol group, making it the amino acid residue most often covalently modified by small molecules possessing weakly electrophilic warheads, thereby prolonging on-target residence time and reducing the risk of idiosyncratic drug toxicity. However, not all cysteines are equally reactive or accessible. Hence, to identify targetable cysteines, we propose a novel ensemble stacked machine learning (ML) model to predict hyper-reactive druggable cysteines, named HyperCys. First, the pocket, conservation, structural and energy profiles, and physicochemical properties of (non)covalently bound cysteines were collected from both protein sequences and 3D structures of protein-ligand complexes. Then, we established the HyperCys ensemble stacked model by integrating six different ML models, including K-nearest neighbors, support vector machine, light gradient boost machine, multi-layer perceptron classifier, random forest, and the meta-classifier model logistic regression. Finally, based on the hyper-reactive cysteines' classification accuracy and other metrics, the results for different feature group combinations were compared. The results show that the accuracy, F1 score, recall score, and ROC AUC values of HyperCys are 0.784, 0.754, 0.742, and 0.824, respectively, after performing 10-fold CV with the best window size. Compared to traditional ML models with only sequenced-based features or only 3D structural features, HyperCys is more accurate at predicting hyper-reactive druggable cysteines. It is anticipated that HyperCys will be an effective tool for discovering new potential reactive cysteines in a wide range of nucleophilic proteins and will provide an important contribution to the design of targeted covalent inhibitors with high potency and selectivity.

For a long time, the development of bromodomain (BD) inhibitors (BDi) was almost exclusively related to the BET family. More recently, BDi for BDs outside the BET family have also been developed. Here we present a novel pan-BDi with micromolar affinities to various BDs, and nanomolar affinities to representatives of BD families I, II (Bromodomain and Extra-Terminal Domain (BET) family), III, and IV. The inhibitor shows a broad activity profile with nanomolar growth inhibition (GI50) values on various cancer cell lines. Subsequently, we were able to control the selectivity of the inhibitor by simple modifications and turned it into a highly selective BRD9 inhibitor.

Host cell entry of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is facilitated via priming of its spike glycoprotein by the human transmembrane protease serine 2 (TMPRSS2). Although camostat and nafamostat are two highly potent covalent TMPRSS2 inhibitors, they nevertheless did not hold promise in COVID-19 clinical trials, presumably due to their short plasma half-lives. Herein, we report an integrative chemogenomics approach based on computational modeling and in vitro enzymatic assays, for repurposing serine-targeted covalent inhibitors. This led to the identification of BC-11 as a covalent TMPRSS2 inhibitor displaying a unique selectivity profile for serine proteases, ascribable to its boronic acid warhead. BC-11 showed modest inhibition of SARS-CoV-2 (omicron variant) spike pseudotyped particles in a cell-based entry assay, and a combination of BC-11 and AHN 1-055 (a spike glycoprotein inhibitor) demonstrated better viral entry inhibition than either compound alone. Given its low molecular weight and good activity against TMPRSS2, BC-11 qualifies as a good starting point for further structural optimizations.

Newly discovered functional relationships of (bio-)molecules are a key component in molecular biology and life science research. Especially in the drug discovery field, knowledge of how small molecules associate with proteins plays a fundamental role in understanding how drugs or metabolites can affect cells, tissues, and human metabolism. Finding relevant information about these relationships among the huge number of published articles is becoming increasingly challenging and time-consuming. On average, more than 25,000 new (bio-)medical articles are added to the literature database PubMed weekly. In this work, we present a new web server (CPRiL) which provides information on functional relationships between small molecules and proteins in literature. Currently, CPRiL contains ∼465,000 unique names and synonyms of small molecules, ∼100,000 unique proteins, and more than 9 million described functional relationships between these entities. The applied BioBERT machine learning model for the determination of functional relationships between small molecules and proteins in texts was extensively trained and tested. On a related benchmark, CPRiL yielded a high performance, with an F1-score of 84.3%, precision of 82.9%, and recall of 85.7%. Availability: CPRiL is freely available at https://www.pharmbioinf.uni-freiburg.de/cpril.

Energy-converting NADH:ubiquinone oxidoreductase, respiratory complex I, is essential for cellular energy metabolism coupling NADH oxidation to proton translocation. The mechanism of proton translocation by complex I is still under debate. Its membrane arm contains an unusual central axis of polar and charged amino acid residues connecting the quinone binding site with the antiporter-type subunits NuoL, NuoM, and NuoN, proposed to catalyze proton translocation. Quinone chemistry probably causes conformational changes and electrostatic interactions that are propagated through these subunits by a conserved pattern of predominantly lysine, histidine, and glutamate residues. These conserved residues are thought to transfer protons along and across the membrane arm. The distinct charge distribution in the membrane arm is a prerequisite for proton translocation. Remarkably, the central subunit NuoM contains a conserved glutamate residue in a position that is taken by a lysine residue in the two other antiporter-type subunits. It was proposed that this charge asymmetry is essential for proton translocation, as it should enable NuoM to operate asynchronously with NuoL and NuoN. Accordingly, we exchanged the conserved glutamate in NuoM for a lysine residue, introducing charge symmetry in the membrane arm. The stably assembled variant pumps protons across the membrane, but with a diminished H+/e- stoichiometry of 1.5. Thus, charge asymmetry is not essential for proton translocation by complex I, casting doubts on the suggestion of an asynchronous operation of NuoL, NuoM, and NuoN. Furthermore, our data emphasize the importance of a balanced charge distribution in the protein for directional proton transfer.

Bone marrow haematopoietic stem cells (HSCs) are vital for lifelong maintenance of healthy haematopoiesis. In inbred mice housed in gnotobiotic facilities, the top of the haematopoietic hierarchy is occupied by dormant HSCs, which reversibly exit quiescence during stress. Whether HSC dormancy exists in humans remains debatable. Here, using single-cell RNA sequencing, we show a continuous landscape of highly purified human bone marrow HSCs displaying varying degrees of dormancy. We identify the orphan receptor GPRC5C, which enriches for dormant human HSCs. GPRC5C is also essential for HSC function, as demonstrated by genetic loss- and gain-of-function analyses. Through structural modelling and biochemical assays, we show that hyaluronic acid, a bone marrow extracellular matrix component, preserves dormancy through GPRC5C. We identify the hyaluronic acid-GPRC5C signalling axis controlling the state of dormancy in mouse and human HSCs.

In-silico methods for the prediction of epitopes can support and improve workflows for vaccine design, antibody production, and disease therapy. So far, the scope of B cell and T cell epitope prediction has been directed exclusively towards peptidic antigens. Nevertheless, various non-peptidic molecular classes can be recognized by immune cells. These compounds have not been systematically studied yet, and prediction approaches are lacking. The ability to predict the epitope activity of non-peptidic compounds could have vast implications; for example, for immunogenic risk assessment of the vast number of drugs and other xenobiotics. Here we present the first general attempt to predict the epitope activity of non-peptidic compounds using the Immune Epitope Database (IEDB) as a source for positive samples. The molecules stored in the Chemical Entities of Biological Interest (ChEBI) database were chosen as background samples. The molecules were clustered into eight homogeneous molecular groups, and classifiers were built for each cluster with the aim of separating the epitopes from the background. Different molecular feature encoding schemes and machine learning models were compared against each other. For those models where a high performance could be achieved based on simple decision rules, the molecular features were then further investigated. Additionally, the findings were used to build a web server that allows for the immunogenic investigation of non-peptidic molecules (http://tools-staging.iedb.org/np_epitope_predictor). The prediction quality was tested with samples from independent evaluation datasets, and the implemented method received noteworthy Receiver Operating Characteristic-Area Under Curve (ROC-AUC) values, ranging from 0.69-0.96 depending on the molecule cluster.

In recent years, the drug discovery paradigm has shifted toward compounds that covalently modify disease-associated target proteins, because they tend to possess high potency, selectivity, and duration of action. The rational design of novel targeted covalent inhibitors (TCIs) typically starts from resolved macromolecular structures of target proteins in their apo or holo forms. However, the existing TCI databases contain only a paucity of covalent protein–ligand (cP–L) complexes. Herein, we report CovPDB, the first database solely dedicated to high-resolution cocrystal structures of biologically relevant cP–L complexes, curated from the Protein Data Bank. For these curated complexes, the chemical structures and warheads of pre-reactive electrophilic ligands as well as the covalent bonding mechanisms to their target proteins were expertly manually annotated. Totally, CovPDB contains 733 proteins and 1,501 ligands, relating to 2,294 cP–L complexes, 93 reactive warheads, 14 targetable residues, and 21 covalent mechanisms. Users are provided with an intuitive and interactive web interface that allows multiple search and browsing options to explore the covalent interactome at a molecular level in order to develop novel TCIs. CovPDB is freely accessible at http://www.pharmbioinf.uni-freiburg.de/covpdb/ and its contents are available for download as flat files of various formats.

Cytochrome bd quinol:O2 oxidoreductases are respiratory terminal oxidases so far only identified in prokaryotes, including several pathogenic bacteria. Escherichia coli contains two bd oxidases of which only the bd-I type is structurally characterized. Here, we report the structure of the Escherichia coli cytochrome bd-II type oxidase with the bound inhibitor aurachin D as obtained by electron cryo-microscopy at 3 Å resolution. The oxidase consists of subunits AppB, C and X that show an architecture similar to that of bd-I. The three heme cofactors are found in AppC, while AppB is stabilized by a structural ubiquinone-8 at the homologous positions. A fourth subunit present in bd-I is lacking in bd-II. Accordingly, heme b595 is exposed to the membrane but heme d embedded within the protein and showing an unexpectedly high redox potential is the catalytically active centre. The structure of the Q-loop is fully resolved, revealing the specific aurachin binding.

While aromatic cages have extensively been investigated in the context of structural biology, molecular recognition, and drug discovery, there exist to date no comprehensive resource for proteins sharing this conserved structural motif. To this end, we parsed the Protein Data Bank and thus constructed the Aromatic Cage Database (AroCageDB), a database for investigating the binding pocket descriptors and ligand binding space of aromatic-cage-containing proteins (ACCPs). AroCageDB contains 487 unique ACCPs bound to 890 unique ligands, for a total of 1636 complexes. This web-accessible database provides a user-friendly interface for the interactive visualization of ligand-bound ACCP structures, with a variety of search options that will open up opportunities for structural analyses and drug discovery campaigns. AroCageDB is freely available at http://www.pharmbioinf.uni-freiburg.de/arocagedb/.

NADH:ubiquinone oxidoreductase, respiratory complex I, plays a central role in cellular energy metabolism. As a major source of reactive oxygen species (ROS) it affects ageing and mitochondrial dysfunction. The novel inhibitor NADH-OH specifically blocks NADH oxidation and ROS production by complex I in nanomolar concentrations. Attempts to elucidate its structure by NMR spectroscopy have failed. Here, by using X-ray crystallographic analysis, we report the structure of NADH-OH bound in the active site of a soluble fragment of complex I at 2.0 Å resolution. We have identified key amino acid residues that are specific and essential for binding NADH-OH. Furthermore, the structure sheds light on the specificity of NADH-OH towards the unique Rossmann-fold of complex I and indicates a regulatory role in mitochondrial ROS generation. In addition, NADH-OH acts as a lead-structure for the synthesis of a novel class of ROS suppressors.

The T cell antigen receptor (TCR) is expressed on T cells, which orchestrate adaptive immune responses. It is composed of the ligand-binding clonotypic TCRαβ heterodimer and the non-covalently bound invariant signal-transducing CD3 complex. Among the CD3 subunits, the CD3ε cytoplasmic tail contains binding motifs for the Src family kinase, Lck, and the adaptor protein, Nck. Lck binds to a receptor kinase (RK) motif and Nck binds to a proline-rich sequence (PRS). Both motifs only become accessible upon ligand binding to the TCR and facilitate the recruitment of Lck and Nck independently of phosphorylation of the TCR. Mutations in each of these motifs cause defects in TCR signaling and T cell activation. Here, we investigated the role of Nck in proximal TCR signaling by silencing both Nck isoforms, Nck1 and Nck2. In the absence of Nck, TCR phosphorylation, ZAP70 recruitment, and ZAP70 phosphorylation was impaired. Mechanistically, this is explained by loss of Lck recruitment to the stimulated TCR in cells lacking Nck. Hence, our data uncover a previously unknown cooperative interaction between Lck and Nck to promote optimal TCR signaling.

Multitarget drugs are an emerging alternative to combination therapies. In three iterative cycles of design, synthesis, and biological evaluation, we developed a novel type of potent hybrid inhibitors of bromodomain, and extra-terminal (BET) proteins and histone deacetylases (HDACs) based on the BET inhibitor XD14 and well-established HDAC inhibitors. The most promising new hybrids, 49 and 61, displayed submicromolar inhibitory activity against HDAC1-3 and 6, and BRD4(1), and possess potent antileukemia activity. 49 induced apoptosis more effectively than the combination of ricolinostat and birabresib (1:1). The most balanced dual inhibitor, 61, induced significantly more apoptosis than the related control compounds 62 (no BRD4(1) affinity) and 63 (no HDAC inhibition) as well as the 1:1 combination of both. Additionally, 61 was well tolerated in an in vivo zebrafish toxicity model. Overall, our data suggest an advantage of dual HDAC/BET inhibitors over the combination of two single targeted compounds.

Bioactive compounds oftentimes bind to several target proteins, thereby exhibiting polypharmacology. Experimentally determining these interactions is however laborious, and structure-based virtual screening (SBVS) of bioactive compounds could expedite drug discovery by prioritizing hits for experimental validation. Here, we present ePharmaLib, a library of 15,148 e-pharmacophores modeled from solved structures of pharmaceutically relevant protein-ligand complexes of the screening Protein Data Bank (sc-PDB). ePharmaLib can be used for target fishing of phenotypic hits, side effect predictions, drug repurposing, and scaffold hopping. In retrospective SBVS, a good balance was obtained between computational efficiency and predictive accuracy. As a proof of concept, we carried out prospective SBVS in conjunction with a photometric assay, which inferred that the mechanism of action of neopterin (an endogenous immunomodulator) putatively stems from its inhibition (IC50 = 18 μM) of the human purine nucleoside phosphorylase. This ready-to-use library is freely available at http://www.pharmbioinf.uni-freiburg.de/epharmalib.

Cyperus rotundus L. (Nutgrass, family Cyperaceae) is a notorious weed which is widespread in temperate tropical and subtropical regions of the world. Owing to its richness and potent pharmacological activities, efforts have been devoted to identify its bioactive constituents. Since 1965, a total of about 192 compounds including terpenoids, flavonoids, stilbenes, aromatics and aliphatic fatty acids have been characterized. This review summarizes the bioactivities and mechanism of action of some of the compounds from C. rotundus L.

Rishirilides are a group of PKS II secondary metabolites produced by Streptomyces bottropensis Gö C4/4. Biosynthetic studies in the past have elucidated early and late steps of rishirilide biosynthesis. This work is aiming to solve the remaining steps in the rishirilide biosynthesis. Inactivation of the cyclase gene rslC3 in Streptomyces bottropensis resulted in an interruption of rishirilide production. Instead, accumulation of the tricyclic aromatic galvaquinones was observed. Similar results were observed after deletion of rslO4. Closer inspection into RslO4 crystal structure in addition to site-directed mutagenesis and molecular dynamic simulations revealed that RslO4 might be responsible for quinone formation on the third ring. The RslO1 three-dimensional structure shows a high similarity to FMN-dependent luciferase-like monooxygenases such as the epoxy-forming MsnO8 which acts with the flavin reductase MsnO3 in mensacarcin biosynthesis in the same strain. The high sequence similarity between RslO2 and MsnO3 suggests that RslO2 provides RslO1 with reduced FMN to form an epoxide that serves as substrate for RslO5.

Antimicrobial resistance is an emerging global health threat necessitating the rapid development of novel antimicrobials. Remarkably, the vast majority of currently available antibiotics are natural products (NPs) isolated from streptomycetes, soil-dwelling bacteria of the genus Streptomyces. However, there is still a huge reservoir of streptomycetes NPs which remains pharmaceutically untapped and a compendium thereof could serve as a source of inspiration for the rational design of novel antibiotics. Initially released in 2012, StreptomeDB (http://www.pharmbioinf.uni-freiburg.de/streptomedb) is the first and only public online database that enables the interactive phylogenetic exploration of streptomycetes and their isolated or mutasynthesized NPs. In this third release, there are substantial improvements over its forerunners, especially in terms of data content. For instance, about 2500 unique NPs were newly annotated through manual curation of about 1300 PubMed-indexed articles, published in the last five years since the second release. To increase interoperability, StreptomeDB entries were hyperlinked to several spectral, (bio)chemical and chemical vendor databases, and also to a genome-based NP prediction server. Moreover, predicted pharmacokinetic and toxicity profiles were added. Lastly, some recent real-world use cases of StreptomeDB are highlighted, to illustrate its applicability in life sciences.

Microorganisms produce secondary metabolites with a remarkable range of bioactive properties. The constantly increasing amount of published genomic data provides the opportunity for efficient identification of biosynthetic gene clusters by genome mining. On the other hand, for many natural products with resolved structures, the encoding biosynthetic gene clusters have not been identified yet. Of those secondary metabolites, the scaffolds of nonribosomal peptides and polyketides (type I modular) can be predicted due to their building block-like assembly. SeMPI v2 provides a comprehensive prediction pipeline, which includes the screening of the scaffold in publicly available natural compound databases. The screening algorithm was designed to detect homologous structures even for partial, incomplete clusters. The pipeline allows linking of gene clusters to known natural products and therefore also provides a metric to estimate the novelty of the cluster if a matching scaffold cannot be found. Whereas currently available tools attempt to provide comprehensive information about a wide range of gene clusters, SeMPI v2 aims to focus on precise predictions. Therefore, the cluster detection algorithm, including building block generation and domain substrate prediction, was thoroughly refined and benchmarked, to provide high-quality scaffold predictions. In a benchmark based on 559 gene clusters, SeMPI v2 achieved comparable or better results than antiSMASH v5. Additionally, the SeMPI v2 web server provides features that can help to further investigate a submitted gene cluster, such as the incorporation of a genome browser, and the possibility to modify a predicted scaffold in a workbench before the database screening.

Nearly half of the world's population relies on combustion of solid biofuels to cover fundamental energy demands. Epidemiologic data demonstrate that particularly long-term emissions adversely affect human health. However, pathological molecular mechanisms are insufficiently characterized. Here we demonstrate that long-term exposure to fine particulate matter (PM2.5) from biomass combustion had no impact on cellular viability and proliferation but increased intracellular reactive oxygen species (ROS) levels in bronchial epithelial BEAS-2B cells. Exposure to PM2.5 induced the nuclear factor erythroid 2-related factor 2 (Nrf2) and mediated an anti-oxidative response, including enhanced levels of intracellular glutathione (GSH) and nuclear accumulation of heme oxygenase-1 (HO-1). Activation of Nrf2 was promoted by the c-Jun N-terminal kinase JNK1/2, but not p38 or Akt, which were also induced by PM2.5. Furthermore, cells exposed to PM2.5 acquired chemoresistance to doxorubicin, which was associated with inhibition of apoptosis and elevated levels of GSH in these cells. Our findings propose that exposure to PM2.5 induces molecular defense mechanisms, which prevent cellular damage and may thus explain the initially relative rare complications associated with PM2.5. However, consistent induction of pro-survival pathways may also promote the progression of diseases. Environmental conditions inducing anti-oxidative responses may have the potential to promote a chemoresistant cellular phenotype.

Various malignant human diseases show disturbed signaling pathways due to increased activity of proteins within the epigenetic machinery. Recently, various novel inhibitors for epigenetic regulation have been introduced which promise a great therapeutic benefit. Inhibitors for the bromo- and extra-terminal domain (BET) family were of particular interest after inhibitors had shown a strong antiproliferative effect. More recently, the focus has increasingly shifted to bromodomains (BDs) outside the BET family. Based on previously developed inhibitors, we have optimized a small series of 4-acyl pyrroles, which we further analyzed by ITC, X-ray crystallography, selectivity studies, the NCI60 cell-panel, and GI50 determinations for several cancer cell lines. The inhibitors address both, BET and BRD7/9 BDs, with very high affinity and show a strong antiproliferative effect on various cancer cell lines that could not be observed for BD family selective inhibitors. Furthermore, a synergistic effect on breast cancer (MCF-7) and melanoma (SK-MEL-5) was proven.

Medicinal plants have widely been used in the traditional treatment of ailments and have been proven effective. Their contribution still holds an important place in modern drug discovery due to their chemical, and biological diversities. However, the poor documentation of traditional medicine, in developing African countries for instance, can lead to the loss of knowledge related to such practices. In this study, we present the Eastern Africa Natural Products Database (EANPDB) containing the structural and bioactivity information of 1870 unique molecules isolated from about 300 source species from the Eastern African region. This represents the largest collection of natural products (NPs) from this geographical region, covering literature data of the period from 1962 to 2019. The computed physicochemical properties and toxicity profiles of each compound have been included. A comparative analysis of some physico‐chemical properties like molecular weight, H‐bond donor/acceptor, logPo/w, etc. as well scaffold diversity analysis has been carried out with other published NP databases. EANPDB was combined with the previously published Northern African Natural Products Database (NANPDB), to form a merger African Natural Products Database (ANPDB), containing ∼6500 unique molecules isolated from about 1000 source species (freely available at http://african‐compounds.org). As a case study, latrunculins A and B isolated from the sponge Negombata magnifica (Podospongiidae) with previously reported antitumour activities, were identified via substructure searching as molecules to be explored as putative binders of histone deacetylases (HDACs).

Histone methylation reader proteins (HMRPs) regulate gene transcription by recognizing, at their "aromatic cage" domains, various Lys/Arg methylation states on histone tails. Because epigenetic dysregulation underlies a wide range of diseases, HMRPs have become attractive drug targets. However, structure-based efforts in targeting them are still in their infancy. Structural information from functionally unrelated aromatic-cage-containing proteins (ACCPs) and their cocrystallized ligands could be a good starting point. In this light, we mined the Protein Data Bank to retrieve the structures of ACCPs in complex with cationic peptidic/small-molecule ligands. Our analysis revealed that the vast majority of retrieved ACCPs belong to three classes: transcription regulators (chiefly HMRPs), signaling proteins, and hydrolases. Although acyclic (and monocyclic) amines and quats are the typical cation-binding functional groups found in HMRP small-molecule inhibitors, numerous atypical cationic groups were identified in non-HMRP inhibitors, which could serve as potential bioisosteres to methylated Lys/Arg on histone tails. Also, as HMRPs are involved in protein-protein interactions, they possess large binding sites, and thus, their selective inhibition might only be achieved by large and more flexible (beyond rule of five) ligands. Hence, the ligands of the collected dataset represent suitable versatile templates for further elaboration into potent and selective HMRP inhibitors.

Initiation of T cell antigen receptor (TCR) signaling involves phosphorylation of CD3 cytoplasmic tails by the tyrosine kinase Lck. How Lck is recruited to the TCR to initiate signaling is not well known. We report a previously unknown binding motif in the CD3ε cytoplasmic tail that interacts in a noncanonical mode with the Lck SH3 domain: the receptor kinase (RK) motif. The RK motif is accessible only upon TCR ligation, demonstrating how ligand binding leads to Lck recruitment. Binding of the Lck SH3 domain to the exposed RK motif resulted in local augmentation of Lck activity, CD3 phosphorylation, T cell activation and thymocyte development. Introducing the RK motif into a well-characterized 41BB-based chimeric antigen receptor enhanced its antitumor function in vitro and in vivo. Our findings underscore how a better understanding of the functioning of the TCR might promote rational improvement of chimeric antigen receptor design for the treatment of cancer.

Histone modifying proteins, specifically histone deacetylases (HDACs) and bromodomains, have emerged as novel promising targets for anticancer therapy. In the current work, based on available crystal structures and docking studies, we designed dual inhibitors of both HDAC6/8 and the bromodomain and PHD finger containing protein 1 (BRPF1). Biochemical and biophysical tests showed that compounds 23a,b and 37 are nanomolar inhibitors of both target proteins. Detailed structure-activity relationships were deduced for the synthesized inhibitors which were supported by extensive docking and molecular dynamics studies. Cellular testing in acute myeloid leukemia (AML) cells showed only a weak effect, most probably because of the poor permeability of the inhibitors. We also aimed to analyse the target engagement and the cellular activity of the novel inhibitors by determining the protein acetylation levels in cells by western blotting (tubulin vs histone acetylation), and by assessing their effects on various cancer cell lines.

MOTIVATION: Much effort has been invested in the identification of protein-protein interactions using text mining and machine learning methods. The extraction of functional relationships between chemical compounds and proteins from literature has received much less attention, and no ready-to-use open-source software is so far available for this task. METHOD: We created a new benchmark dataset of 2,613 sentences from abstracts containing annotations of proteins, small molecules, and their relationships. Two kernel methods were applied to classify these relationships as functional or non-functional, named shallow linguistic and all-paths graph kernel. Furthermore, the benefit of interaction verbs in sentences was evaluated. RESULTS: The cross-validation of the all-paths graph kernel (AUC value: 84.6%, F1 score: 79.0%) shows slightly better results than the shallow linguistic kernel (AUC value: 82.5%, F1 score: 77.2%) on our benchmark dataset. Both models achieve state-of-the-art performance in the research area of relation extraction. Furthermore, the combination of shallow linguistic and all-paths graph kernel could further increase the overall performance slightly. We used each of the two kernels to identify functional relationships in all PubMed abstracts (29 million) and provide the results, including recorded processing time. AVAILABILITY: The software for the tested kernels, the benchmark, the processed 29 million PubMed abstracts, all evaluation scripts, as well as the scripts for processing the complete PubMed database are freely available at https://github.com/KerstenDoering/CPI-Pipeline.

One major challenge in natural product (NP) discovery is the determination of the chemical structure of unknown metabolites using automated software tools from either GC–mass spectrometry (MS) or liquid chromatography–MS/MS data only. This chapter reviews the existing spectral libraries and predictive computational tools used in MS-based untargeted metabolomics, which is currently a hot topic in NP structure elucidation. We begin by focusing on spectral databases and the general workflow of MS annotation. We then describe software and tools used in MS, particularly those used to predict fragmentation patterns, mass spectral classifiers, and tools for fragmentation trees analysis. We then round up the chapter by looking at more advanced approaches implemented in tools for competitive fragmentation modeling and quantum chemical approaches.

The kinetics of featured interactions (KOFFI) database is a novel tool and resource for binding kinetics data from biomolecular interactions. While binding kinetics data are abundant in literature, finding valuable information is a laborious task. We used text extraction methods to store binding rates (association, dissociation) as well as corresponding meta-information (e.g. methods, devices) in a novel database. To date, over 270 articles were manually curated and binding data on over 1705 interactions was collected and stored in the (KOFFI) database. Moreover, the KOFFI database application programming interface was implemented in Anabel (open-source software for the analysis of binding interactions), enabling users to directly compare their own binding data analyses with related experiments described in the database.

Natural products (NPs) are an indispensable source of drugs and they have a better coverage of the pharmacological space than synthetic compounds, owing to their high structural diversity. The prediction of their interaction profiles with druggable protein targets remains a major challenge in modern drug discovery. Experimental (off-)target predictions of NPs are cost- and time-consuming, whereas computational methods, on the other hand, are much faster and cheaper. As a result, computational predictions are preferentially used in the first instance for NP profiling, prior to experimental validations. This review covers recent advances in computational approaches which have been developed to aid the annotation of unknown drug-target interactions (DTIs), by focusing on three broad classes, namely: ligand-based, target-based, and target-ligand-based (hybrid) approaches. Computational DTI prediction methods have the potential to significantly advance the discovery and development of novel selective drugs exhibiting minimal side effects. We highlight some inherent caveats of these methods which must be overcome to enable them to realize their full potential, and a future outlook is given.

Bromodomains (BRDs) are functional modules which recognize acetylated lysines on the surface of proteins. Such post‐translational modifications exist in thousands of human proteins and play a crucial role in diverse signaling networks. It has been shown that by recognizing acetylated lysines on histone tails, BRDs regulate the transcription of specific genes. Their potential as drug targets was demonstrated in 2010 when JQ1, presented as an inhibitor of the BRD containing protein BRD4, was shown to suppress cancer cell proliferation. The knowledge about BRDs and their role in signaling and diseases has dramatically increased over the past few years and many of them are now accepted as promising drug targets for various diseases. This chapter provides an overview of the structure and function of BRDs, their role in diseases, inhibitors known to date, and the different strategies used for targeting BRDs.

Streptomyces asterosporus DSM 41452 is a producer of the polyketide annimycin and the non-ribosomal depsipeptide WS9326A. This strain is also notable for exhibiting a bald phenotype that is devoid of spores and aerial mycelium when grown on solid media. Based on the similarity of the 16S rRNA sequence to Streptomyces calvus, the only known producer of the fluorometabolite nucleocidin, the genome of S. asterosporus DSM 41452 was sequenced and analyzed. Twenty-nine natural product gene clusters were detected in the genome, including a gene cluster predicted to encode the fluorometabolite nucleocidin. Through genome analysis and gene complementation experiments, we demonstrate that the bald phenotype arises from a transposon gene inserted within the promoter sequence for the pleiotropic regulator adpA. Complementation of S. asterosporus DSM 41452 with a functional adpA sequence restored morphological differentiation and promoted the production of nucleocidin.

Enzymes often convert both physiological and non-physiological substrates with high stereoselectivity - yet, for some enzymes, opposite product chirality is observed. A possible explanation is the existence of hidden specificities becoming apparent when non-physiological substrates confer different substrate-enzyme interactions than the physiological substrate. To test this hypothesis, a series of α-methylated β-keto esters were converted with Tyl-KR1, a ketoreductase from polyketide synthesis in Streptomyces fradiae. The conversions of six substrates with different physicochemical properties exhibited enantioselectivities ranging from 84% ee for R,R to 84% ee for S,S, yet high and uniform diastereoselectivity (anti, dr >9:1). The exchange of a single atom, namely an oxygen ester instead of a thioester, led to almost complete loss of enantioselectivity (<5% ee). An additional S,S-selective binding mode as a hidden specificity in Tyl-KR1 has been identified through molecular modeling and site-directed mutagenesis.

With the bromodomain (BRD) inhibitor JQ1, a remarkable success story of BRD4 as a novel drug target has been set off that yielded many anti-cancer drugs that are now in clinical trials. But not all of the great prospects of BRDs as drug targets may become true. First evaluations of ongoing clinical trials revealed that treatment with BET-inhibitors can be accompanied with significant toxic side effects and the validation of the therapeutic benefit of BET-inhibitors compared to existing therapies is still pending. New strategies that may overcome possible obstacles in BRD drug discovery include combination therapies with other agents, dual target inhibitors, and proteolysis targeting chimeras (PROTACs). Furthermore, non-BET proteins seem promising drug targets as well. Most recently, BRDs have been identified as putative targets to treat parasitic diseases such as malaria. Milestones in BRD drug discovery are reviewed and promising new developments are evaluated.

In this work, we study the dynamics and the energetics of the all-atom structure of a neuronal-specific serine/threonine kinase c-Jun N-terminal kinase 3 (JNK3) in three states: unphosphorylated, phosphorylated, and ATP-bound phosphorylated. A series of 2 µs atomistic simulations followed by a conformational landscape mapping and a principal component analysis supports the mechanistic understanding of the JNK3 inactivation/activation process and also indicates key structural intermediates. Our analysis reveals that the unphosphorylated JNK3 undergoes the ‘open-to-closed’ movement via a two-step mechanism. Furthermore, the phosphorylation and ATP-binding allow the JNK3 kinase to attain a fully active conformation. JNK3 is a widely studied target for small-drugs used to treat a variety of neurological disorders. We believe that the mechanistic understanding of the large-conformational changes upon the activation of JNK3 will aid the development of novel targeted therapeutics.

One-third of the world's population relies on solid biomass fuels for domestic energy demands. In contrast to industrial or traffic related emissions, only a limited number of studies focus on the adverse health effects of particulate matter (PM) from biomass combustion. We conducted Affymetrix Human Genome U133 Plus 2.0 arrays, bioinformatic analysis, qRT-PCR and immunoblotting to determine the molecular impact of fuelwood-derived PM2.5 on lung epithelial BEAS-2B cells. In the presence of PM2.5 175 differentially regulated genes were identified. Gene ontology (GO), pathway and functional enrichment analysis allocated these genes to cellular development, metabolism, inflammation, cancer and the immune system. Analysis of enriched transcription factor binding sites extracted 15 PM2.5 responsive transcription factors, including the polycyclic aromatic hydrocarbon (PAH)-activated aryl hydrocarbon receptor (AhR). Accordingly, a complex mixture of PAHs was detected in the PM2.5 fraction using APLI and AhR-inhibitors reduced the up-regulation of CYP1A1, EREG, GREM1, IL1B and IL6, indicating that PAHs are involved in PM2.5 specific gene deregulation. We also provide evidence, that HIF-1α might be responsive to PM2.5. To analyze the impact of microbial infections, PM2.5 predisposed cells were incubated with LPS or dsRNA. We identified 40 LPS and 380 dsRNA specific genes in PM2.5 predisposed cells. GO allocated these genes with chemokine dependent and inflammatory pathways, viral responses and xenobiotic metabolism. A disease ontology allocated lung and lung associated diseases to PM2.5 exposed cells. In some cases LPS or dsRNA increased significance of probability of diseases. Altogether our studies enhance our knowledge on the mechanism promoting harmful effects of PM.

Within endocrine disruptor research, evaluation and interpretation of mixture effects and the predictive value for downstream responses still warrant more in-depth investigations. We used an estrogen receptor (ER)-mediated reporter gene assay (ER-CALUX®) and a cell proliferation assay (WST-1 assay), both based on the T47D breast cancer cell line, to test mixtures of heterogeneous xenoestrogens. Observed concentration-response curves were compared to those predicted by the concepts of concentration addition (CA), generalized concentration addition (GCA), and a novel full logistic model (FLM). CA performed better regarding mixture potency (EC50 values), whereas GCA was superior in predicting mixture efficacy (maximal response). In comparison, FLM proved to be highly suitable for in silico mixture effect prediction, combining advantages of both CA and GCA. The inter-assay comparison revealed that ER activation is not necessarily predictive for induction of cell proliferation. The results support the use of models like CA, GCA, or FLM in mixture effect evaluation. However, we conclude that reliable estimations regarding the disruptive potential of mixtures of endocrine active substances require an integrative approach considering more than one assay/endpoint to avoid misinterpretations. The formazan-based WST-1 proliferation assay might be a possible alternative to commonly used proliferation assays in endocrine disrupter research.

The secondary metabolism of bacteria, fungi and plants yields a vast number of bioactive substances. The constantly increasing amount of published genomic data provides the opportunity for an efficient identification of gene clusters by genome mining. Conversely, for many natural products with resolved structures, the encoding gene clusters have not been identified yet. Even though genome mining tools have become significantly more efficient in the identification of biosynthetic gene clusters, structural elucidation of the actual secondary metabolite is still challenging, especially due to as yet unpredictable post-modifications. Here, we introduce SeMPI, a web server providing a prediction and identification pipeline for natural products synthesized by polyketide synthases of type I modular. In order to limit the possible structures of PKS products and to include putative tailoring reactions, a structural comparison with annotated natural products was introduced. Furthermore, a benchmark was designed based on 40 gene clusters with annotated PKS products. The web server of the pipeline (SeMPI) is freely available at: http://www.pharmaceutical-bioinformatics.de/sempi.

Natural products (NPs) are often regarded as sources of drugs or drug leads or simply as a “source of inspiration” for the discovery of novel drugs. We have built the Northern African Natural Products Database (NANPDB) by collecting information on ∼4500 NPs, covering literature data for the period from 1962 to 2016. The data cover compounds isolated mainly from plants, with contributions from some endophyte, animal (e.g., coral), fungal, and bacterial sources. The compounds were identified from 617 source species, belonging to 146 families. Computed physicochemical properties, often used to predict drug metabolism and pharmacokinetics, as well as predicted toxicity information, have been included for each compound in the data set. This is the largest collection of annotated natural compounds produced by native organisms from Northern Africa. While the database includes well-known drugs and drug leads, the medical potential of a majority of the molecules is yet to be investigated. The database could be useful for drug discovery efforts, analysis of the bioactivity of selected compounds, or the discovery of synthesis routes toward secondary metabolites. The current version of NANPDB is available at http://african-compounds.org/nanpdb/.

We present an overview of computational approaches for the prediction of metabolic path ways by which plants biosynthesise compounds, with a focus on selected very promising anticancer secondary metabolites from the African flora. We also provide an overview of databases for the retrieval of useful genomic data, discussing the strengths and limitations of selected prediction software and the main computational tools (and methods), which could be employed for the investigation of the uncharted routes towards the biosynthesis of some of the identified anticancer metabolites from plant sources, eventually using specific examples to address some knowledge gaps when using these approaches. Computational studies and biosynthesis of natural products with promising anticancer properties.

BET bromodomain inhibitors are widely used both as chemical tools to study the biological role of their targets in living organisms, and as candidates for drug development against several cancer variants and human disorders. However, non-BET bromodomains such as those in p300 and CBP are less studied. Here, we introduce XDM-CBP, a highly potent and selective inhibitor for the bromodomains of CBP and p300 derived from a pan-selective BET BRD-binding fragment. In addition to X-ray crystal structure analysis and thermodynamic profiling, we used XDM-CBP in in vitro cell screenings of several cancer cell lines to study its inhibitory potential on cancer cell proliferation. Our results demonstrate that XDM-CBP is a potent and selective CBP/p300 inhibitor that acts on specific cancer cell lines, in particular malignant melanoma, breast cancer, and leukemia.

Exposure to particulate matter (PM) is recognized as a major health hazard, but molecular responses are still insufficiently described. We analyzed the epigenetic impact of ambient PM2.5 from biomass combustion on the methylome of primary human bronchial epithelial BEAS-2B cells using the Illumina HumanMethylation450 BeadChip. The transcriptome was determined by the Affymetrix HG-U133 Plus 2.0 Array. PM2.5 induced genome wide alterations of the DNA methylation pattern, including differentially methylated CpGs in the promoter region associated with CpG islands. Gene ontology analysis revealed that differentially methylated genes were significantly clustered in pathways associated with the extracellular matrix, cellular adhesion, GTPases function, and responses to extracellular stimuli, or were involved in ion binding and shuttling. Differential methylations also affected tandem repeats. Additionally, 45 different miRNA CpG loci showed differential DNA methylation, most of them proximal to their promoter. These miRNAs are functionally relevant for lung cancer, inflammation, asthma, and other PM-associated diseases. Correlation of the methylome and transcriptome demonstrated a clear bias towards transcriptional activation by hypomethylation. Genes that exhibited both differential methylation and expression were functionally linked to cytokine and immune responses, cellular motility, angiogenesis, inflammation, wound healing, cell growth, differentiation and development, or responses to exogenous matter. Disease ontology of differentially methylated and expressed genes indicated their prominent role in lung cancer and their participation in dominant cancer related signaling pathways. Thus, in lung epithelial cells, PM2.5 alters the methylome of genes and noncoding transcripts or elements that might be relevant for PM- and lung-associated diseases.

Information extraction from biomedical literature is continuously growing in scope and importance. Many tools exist that perform named entity recognition, e.g. of proteins, chemical compounds, and diseases. Furthermore, several approaches deal with the extraction of relations between identified entities. The BioCreative community supports these developments with yearly open challenges, which led to a standardised XML text annotation format called BioC. PubMed provides access to the largest open biomedical literature repository, but there is no unified way of connecting its data to natural language processing tools. Therefore, an appropriate data environment is needed as a basis to combine different software solutions and to develop customised text mining applications. PubMedPortable builds a relational database and a full text index on PubMed citations. It can be applied either to the complete PubMed data set or an arbitrary subset of downloaded PubMed XML files. The software provides the infrastructure to combine stand-alone applications by exporting different data formats, e.g. BioC. The presented workflows show how to use PubMedPortable to retrieve, store, and analyse a disease-specific data set. The provided use cases are well documented in the PubMedPortable wiki. The open-source software library is small, easy to use, and scalable to the user's system requirements. It is freely available for Linux on the web at https://github.com/KerstenDoering/PubMedPortable and for other operating systems as a virtual container. The approach was tested extensively and applied successfully in several projects.

Several human diseases, including cancer, show altered signaling pathways resulting from changes in the activity levels of epigenetic modulators. In the past few years, small-molecule inhibitors against specific modulators, including the bromodomain and extra-terminal (BET) bromodomain family of acetylation readers, have shown early promise in the treatment of the genetically defined midline carcinoma and hematopoietic malignancies. We have recently developed a novel potent inhibitor of BET proteins, 1 (XD14[ Angew. Chem., Int. Ed. 2013, 52, 14055]), which exerts a strong inhibitory potential on the proliferation of specific leukemia cell lines. In the study presented here, we designed analogues of 1 to study the potential of substitutions on the 4-acyl pyrrole backbone to occupy additional sites within the substrate recognition site of BRD4(1). The compounds were profiled using ITC, DSF, and X-ray crystallography. We could introduce several substitutions that address previously untargeted areas of the substrate recognition site. This work may substantially contribute to the development of therapeutics with increased target specificity against BRD4-related malignancies.

This article presents detailed purification procedures for the bromodomains BRD3(1), BRD3(2), BRD4(1), and BRPF1B. In addition we provide crystallization protocols for apo BRD4(1) and BRD4(1) in complex with numerous inhibitors. The protocols described here were successfully applied to obtain affinity data by isothermal titration calorimetry (ITC) and by differential scanning fluorimetry (DSF) as well as structural characterizations of BRD4(1) inhibitor complexes (PDB codes: PDB: 4LYI, PDB: 4LZS, PDB: 4LYW, PDB: 4LZR, PDB: 4LYS, PDB: 5D24, PDB: 5D25, PDB: 5D26, PDB: 5D3H, PDB: 5D3J, PDB: 5D3L, PDB: 5D3N, PDB: 5D3P, PDB: 5D3R, PDB: 5D3S, PDB: 5D3T). These data have been reported previously and are discussed in more detail elsewhere [1,2].

Over the last decades, the genus Streptomyces has stirred huge interest in the scientific community as a source of bioactive compounds. The majority of all known antibiotics is isolated from these bacterial strains, as well as a variety of other drugs such as antitumor agents, immunosuppressants and antifungals. To the best of our knowledge, StreptomeDB was the first database focusing on compounds produced by streptomycetes. The new version presented herein represents a major step forward: its content has been increased to over 4000 compounds and more than 2500 host organisms. In addition, we have extended the background information and included hundreds of new manually curated references to literature. The latest update features a unique scaffold-based navigation system, which enables the exploration of the chemical diversity of StreptomeDB on a structural basis. We have included a phylogenetic tree, based on 16S rRNA sequences, which comprises more than two-thirds of the included host organisms. It enables visualizing the frequency, appearance, and persistence of compounds and scaffolds in an evolutionary context. Additionally, we have included predicted MS- and NMR-spectra of thousands of compounds for assignment of experimental data. The database is freely accessible via http://www.pharmaceutical-bioinformatics.org/streptomedb.

Traditional medicinal practices have a profound influence on the daily lives of people living in developing countries, particularly in Africa, since the populations cannot generally afford the cost of Western medicines. We have undertaken to investigate the correlation between the uses of plants in Traditional African medicine and the biological activities of the derived natural products, with the aim to validate the use of traditional medicine in Northern African communities. The literature is covered for the period 1959-2015 and part III of this review series focuses on plant families with names beginning with letters T to Z. The authors have focused on curating data from journals in natural products and phytomedicine. Within each journal home page, a query search based on country name was conducted. All articles "hits" were then verified, one at a time, that the species was harvested within the Northern African geographical regions. The current data partly constitutes the bases for the development of the Northern African natural compounds database. The review discusses 284 plant-based natural compounds from 34 species and 11 families. It was observed that the ethnobotanical uses of less than 40 \% of the plant species surveyed correlated with the bioactivities of compounds identified.

XD14 is a 4-acyl pyrrole derivative, which was discovered by a high-throughput virtual screening experiment. XD14 inhibits bromodomain and extra-terminal domain (BET) proteins (BRD2, BRD3, BRD4 and BRDT) and consequently suppresses cell proliferation. In this study, metabolic profiling reveals the molecular effects in the human breast cancer cell line MCF-7 (Michigan Cancer Foundation-7) treated by XD14. A three-day time series experiment with two concentrations of XD14 was performed. Gas chromatography-mass spectrometry (GC-MS) was applied for untargeted profiling of treated and non-treated MCF-7 cells. The gained data sets were evaluated by several statistical methods: analysis of variance (ANOVA), clustering analysis, principle component analysis (PCA), and partial least squares discriminant analysis (PLS-DA). Cell proliferation was strongly inhibited by treatment with 50 µM XD14. Samples could be discriminated by time and XD14 concentration using PLS-DA. From the 117 identified metabolites, 67 were significantly altered after XD14 treatment. These metabolites include amino acids, fatty acids, Krebs cycle and glycolysis intermediates, as well as compounds of purine and pyrimidine metabolism. This massive intervention in energy metabolism and the lack of available nucleotides could explain the decreased proliferation rate of the cancer cells.

Echinocandins are nonribosomal lipopeptides produced by ascommycete fungi. Due to their strong inhibitory effect on fungal cell wall biosynthesis and lack of human toxicity, they have been developed to an important class of antifungal drugs. Since 2012, the biosynthetic gene clusters of most of the main echinocandin variants have been characterized. Especially the comparison of the clusters allows a deeper insight for the biosynthesis of these complex structures.In the genome of the echinocandin B producer Aspergillus nidulans NRRL 8112 we have identified a gene cluster (Ani) that encodes echinocandin biosynthesis. Sequence analyses showed that Ani is clearly delimited from the genomic context and forms a monophyletic lineage with the other echinocandin gene clusters. Importantly, we found that the disjunct genomic location of the echinocandin B gene cluster in A. pachycristatus NRRL 11440 on two separate subclusters, Ecd and Hty, at two loci was likely an artifact of genome misassembly in the absence of a reference sequence. We show that both sequences can be aligned resulting a single cluster with a gene arrangement collinear compared to other clusters of Aspergillus section Nidulantes. The reassembled gene cluster (Ecd/Hty) is identical to a putative gene cluster (AE) that was previously deposited at the NCBI as a sequence from A. delacroxii NRRL 3860. PCR amplification of a part of the gene cluster resulted a sequence that was very similar (97 \% identity), but not identical to that of AE.The Echinocandin B biosynthetic cluster from A. nidulans NRRL 8112 (Ani) is particularly similar to that of A. pachycristatus NRRL 11440 (Ecd/Hty). Ecd/Hty was originally reported as two disjunct sub-clusters Ecd and Hty, but is in fact a continuous sequence with the same gene order as in Ani. According to sequences of PCR products amplified from genomic DNA, the echinocandin B producer A. delacroxii NRRL 3860 is closely related to A. pachycristatus NRRL 11440. A PCR-product from the gene cluster was very similar, but clearly distinct from the sequence published for A. delacroxii NRRL 3860 at the NCBI (No. AB720074). As the NCBI entry is virtually identical with the re-assembled Ecd/Hty cluster, it is likely that it originates from A. pachycristatus NRRL 11440 rather than A. delacroxii NRRL 3860.

The screening of a reduced yet diverse and synthesizable region of the chemical space is a critical step in drug discovery. The ZINC database is nowadays routinely used to freely access and screen millions of commercially available compounds. We collected ∼125 million compounds from chemical catalogs and the ZINC database, yielding more than 68 million unique molecules, including a large portion of described natural products (NPs) and drugs. The data set was filtered using advanced medicinal chemistry rules to remove potentially toxic, promiscuous, metabolically labile, or reactive compounds. We studied the physicochemical properties of this compilation and identified millions of NP-like, fragment-like, inhibitors of protein–protein interactions (i-PPIs) like, and drug-like compounds. The related focused libraries were subjected to a detailed scaffold diversity analysis and compared to reference NPs and marketed drugs. This study revealed thousands of diverse chemotypes with distinct representations of building block combinations among the data sets. An analysis of the stereogenic and shape complexity properties of the libraries also showed that they present well-defined levels of complexity, following the tendency: i-PPIs-like < drug-like < fragment-like < NP-like. As the collected compounds have huge interest in drug discovery and particularly virtual screening and library design, we offer a freely available collection comprising over 37 million molecules under: http://pbox.pharmaceutical-bioinformatics.org, as well as the filtering rules used to build the focused libraries described herein.

Drugs may have polypharmacological phenomena, that is, in addition to the desired target, they may also bind to many undesired or unknown physiological targets. As a result, they often exert side effects. In some cases, off-target interactions may lead to drug repositioning or to explaining a drug's mode of action. Herein we present an in silico approach for target fishing by cross-docking as a method to identify new drug-protein interactions. As an example and proof of concept, this method predicted the peroxisome proliferator-activated receptor (PPAR)-γ as a target of ethacrynic acid, which may explain the hyperglycemic effect brought on by this molecule. The antagonistic effect of ethacrynic acid on PPAR-γ was validated in a transient transactivation assay using human HEK293 cells. The cross-docking approach also predicted the potential mechanisms of many other drug side effects and discloses new drug repositioning opportunities. These putative interactions are described herein, and can be readily used to discover therapeutically relevant drug effects.

The heart is a highly specialized organ with essential function for the organism throughout life. The significance of DNA methylation in shaping the phenotype of the heart remains only partially known. Here we generate and analyse DNA methylomes from highly purified cardiomyocytes of neonatal, adult healthy and adult failing hearts. We identify large genomic regions that are differentially methylated during cardiomyocyte development and maturation. Demethylation of cardiomyocyte gene bodies correlates strongly with increased gene expression. Silencing of demethylated genes is characterized by the polycomb mark H3K27me3 or by DNA methylation. De novo methylation by DNA methyltransferases 3A/B causes repression of fetal cardiac genes, including essential components of the cardiac sarcomere. Failing cardiomyocytes partially resemble neonatal methylation patterns. This study establishes DNA methylation as a highly dynamic process during postnatal growth of cardiomyocytes and their adaptation to pathological stress in a process tightly linked to gene regulation and activity.

RATIONALE: A rapid and precise analytical method for the investigation of natural products is required for pathway monitoring of the biosynthesis of secondary metabolites. Phenalinolactones, used in antibiotic research, are produced by Streptomyces sp. Tü6071. For the analysis of those compounds, prior to mass spectrometric analysis, an efficient separation technique is required. METHODS: For the identification of phenalinolactones from liquid cultures of Streptomyces sp. Tü6071, a new method comprising the combination of solid-phase extraction (SPE) prior to liquid chromatography/electrospray ionization tandem mass spectrometry (LC/ESI-MS/MS) was established. MS/MS product ion scans were applied for phenalinolactone detection and structure elucidation, performed in negative mode and optimized for sensitivity and specificity. For the discovery of new intermediates, a MS/MS precursor ion scan was applied. RESULTS: Analysis of the extracts revealed that the Oasis® MAX cartridge, containing a quaternary amine functionality, is the most efficient SPE material for purification of phenalinolactones, since it allowed sufficient enrichment and detection of intermediates from the biosynthetic pathway by LC/ESI-MS/MS. Using the precursor ion scan technique, two new secondary metabolites, PL IM1 with m/z 672.6 and PL IM2 with m/z 433.3, have been detected. The structures of the new intermediates are postulated and arranged into the biosynthetic pathway of phenalinolactones. CONCLUSIONS: A precise analytical method was established for the identification of phenalinolactones by combining purification from Streptomyces using SPE prior to LC/ESI-MS/MS. By optimising LC/ESI-MS/MS settings, this method has been successfully applied for pathway monitoring of secondary metabolites. Application of a precursor ion scan allowed for the identification of unknown intermediates in biosynthetic pathways.

The content of chiral carbon atoms or structural complexity, which is known to correlate well with relevant physicochemical properties of small molecules, represents a promising descriptor that could fill the gap in existing drug discovery between ligand library filtering rules and the corresponding properties of the target's recognition site. Herein, we present an in silico study on the yet unclear underlying correlations between molecular complexity and other more sophisticated physicochemical and biological properties. By analyzing thousands of protein–ligand complexes from DrugBank, we show that increasing molecular complexity of drugs is an approach to addressing particularly low-druggability and polar recognition sites. We also show that biologically relevant protein classes characteristically bind molecules with a certain degree of structural complexity. Three distinct behaviors toward drug recognition are described. The reported results set the basis for a better understanding of protein–drug recognition, and open the possibility of including target information in the filtering of large ligand libraries for screening.

SUMMARY: Conserved water molecules play a crucial role in protein structure, stabilization of secondary structure, protein activity, flexibility and ligand binding. Clustering of water molecules in superimposed protein structures, obtained by x-ray crystallography at high resolution is an established method to identify consensus water molecules in all known protein structures of the same family. PyWATER is an easy to use PyMOL plugin and identifies conserved water molecules in the protein structure of interest. PyWATER can be installed via the user interface of PyMOL. No programming or command line knowledge is required for its use. AVAILABILITY AND IMPLEMENTATION: PyWATER and a tutorial are available at https://github.com/hiteshpatel379/PyWATER. PyMOL is available at http://www.pymol.org or http://sourceforge.net/projects/pymol.

Intermolecular oxidative phenol coupling is the main process in nature for the formation of atroposelective biaryl compounds. Although well defined in plants and fungi, this type of dimerization reaction in bacteria is poorly understood. Therefore, the biosynthesis of julichromes, spectomycins, and setomimycin was investigated. The monomeric subunits of these biarylic pre-anthraquinones are derived from a common polyketidic precursor, yet the coupling reaction proceeds in a regioselective manner, with the position of attachment of the two subunits depending on the specific streptomycete strain. By using genome analysis and deletion experiments, the biosynthetic gene clusters were identified. Furthermore, it was established that cytochrome P450 enzymes are fundamentally involved during dimerization of the polyketide monomers.

Proteasomes are cellular proteases involved in the degradation of numerous cellular proteins. The 20S proteasome is a cylindrical 28-mer protein complex composed of two outer heptameric α-rings forming the entrance for the protein substrate and two inner heptameric β-rings carrying the catalytic sites. Numerous in vitro studies have provided evidence that the 20S proteasome may degrade peptides of various lengths and even unfolded full-length polypeptide chains. However, a direct demonstration that the 20S proteasome may also cleave surface-attached immobilized peptides is lacking so far. To this end, we used a model system by coupling peptides from different source proteins covalently to the surface of glass beads and applied nanoLC/MS analysis to monitor the generation of proteolytic fragments in the presence of the 20S proteasome. Detectable amounts of cleavage products occurred within a few minutes indicating a much higher cleavage rate than observed with the same substrates in solution. Our finding lends support to the idea that proteasomes may directly degrade segments of membrane-bound proteins protruding into the aqueous phase. Copyright © 2013 European Peptide Society and John Wiley & Sons, Ltd.

Bacteria from the genus Streptomyces are very important for the production of natural bioactive compounds such as antibiotic, antitumour or immunosuppressant drugs. Around two-thirds of all known natural antibiotics are produced by these bacteria. An enormous quantity of crucial data related to this genus has been generated and published, but so far no freely available and comprehensive database exists. Here, we present StreptomeDB (http://www.pharmaceutical-bioinformatics.de/streptomedb/). To the best of our knowledge, this is the largest database of natural products isolated from Streptomyces. It contains >2400 unique and diverse compounds from >1900 different Streptomyces strains and substrains. In addition to names and molecular structures of the compounds, information about source organisms, references, biological role, activities and synthesis routes (e.g. polyketide synthase derived and non-ribosomal peptides derived) is included. Data can be accessed through queries on compound names, chemical structures or organisms. Extraction from the literature was performed through automatic text mining of thousands of articles from PubMed, followed by manual curation. All annotated compound structures can be downloaded from the website and applied for in silico screenings for identifying new active molecules with undiscovered properties.

P-glycoprotein is capable of effluxing a broad range of cytosolic and membrane penetrating xenobiotic substrates, thus leading to multi-drug resistance and posing a threat for the therapeutic treatment of several diseases, including cancer and central nervous disorders. Herein, a virtual screening campaign followed by experimental validation in Caco-2, MDKCII, and MDKCII mdr1 transfected cell lines has been conducted for the identification of novel phospholipids with P-gp transportation inhibitory activity. Phosphatidylinositol-(1,2-dioctanoyl)-sodium salt (8∶0 PI) was found to significantly inhibit transmembrane P-gp transportation in vitro in a reproducible-, cell line-, and substrate-independent manner. Further tests are needed to determine whether this and other phosphatidylinositols could be co-administered with oral drugs to successfully increase their bioavailability. Moreover, as phosphatidylinositols and phosphoinositides are present in the human diet and are known to play an important role in signal transduction and cell motility, our finding could be of substantial interest for nutrition science as well.

Bromodomains are acetyllysine epigenetic mark reader proteins. Small molecules inhibiting them have potential as anti-inflammatory, antiviral, and anticancer agents. A 4-acyl pyrrole derivative (see yellow structure in recognition pocket) has been identified that potently inhibits specific bromodomains and exhibits antiproliferative activity against leukemia cell lines.

Background: Glarea lozoyensis is a filamentous fungus used for the industrial production of non-ribosomal peptide pneumocandin B0. In the scope of a whole genome sequencing the complete mitochondrial genome of the fungus has been assembled and annotated. It is the first one of the large polyphyletic Helotiaceae family. A phylogenetic analysis was performed based on conserved proteins of the oxidative phosphorylation system in mitochondrial genomes. Results: The total size of the mitochondrial genome is 45,038 bp. It contains the expected 14 genes coding for proteins related to oxidative phosphorylation,two rRNA genes, six hypothetical proteins, three intronic genes of which two are homing endonucleases and a ribosomal protein rps3. Additionally there is a set of 33 tRNA genes. All genes are located on the same strand. Phylogenetic analyses based on concatenated mitochondrial protein sequences confirmed that G. lozoyensis belongs to the order of Helotiales and that it is most closely related to Phialocephala subalpina. However, a comparison with the three other mitochondrial genomes known from Helotialean species revealed remarkable differences in size, gene content and sequence. Moreover, it was found that the gene order found in P. subalpina and Sclerotinia sclerotiorum is not conserved in G. lozoyensis. Conclusion: The arrangement of genes and other differences found between the mitochondrial genome of G. lozoyensis and those of other Helotiales indicates a broad genetic diversity within this large order. Further mitochondrial genomes are required in order to determine whether there is a continuous transition between the different forms of mitochondrial genomes or G. lozoyensis belongs to a distinct subgroup within Helotiales.

Here we present the draft genome sequence of Streptomyces viridochromogenes Tü57. This strain is a producer of avilamycin A, an oligosaccharide antibiotic from the orthosomycin group, which is active against Gram-positive bacteria.

The identification of novel drug targets is one of the major challenges in proteomics. Computational methods developed over the last decade have enhanced the process of drug design in both terms of time and quality. The main task is the design of selective compounds, which bind targets more specifically, dependent on the desired mode of action of the particular drug. This makes it necessary to create compounds, which either exhibit their functions on one single protein to exclude undesired cross-reactivity or to use the advantageous effect of less selective drugs that target numerous proteins and therefore exhibit their functions on whole protein classes. Main aspects in the assignment of interactions between ligands and putative targets involve the amino acid composition of the binding site, evolutionary conservation and similarity in sequence and structure of known targets. Similarities or differences within classified protein families can be the key to their function and give first hints to functional drug design. Hereby, binding site-based classification outnumbers sequence-based classifications since similar binding sites can also be found in more distant proteins. Membrane proteins are 'difficult targets', because of their special physicochemical characteristics and the general lack of structural information. Here, we describe recent advances in modeling methods dedicated to membrane proteins. Different descriptors of similarity between compounds and the similarity between binding sites are under development and elucidate important aspects like dynamics or entropy. The importance of computational drug design is undisputable. Nevertheless, the process of design is complicated by increasing complexity, which underlines the importance of accurate knowledge about the addressed target class(es) and particularly their binding sites. One main objective by considering named topics is to predict putative side effects and errant functions (off-target effects) of novel drugs, which requires a holistic (systems biology) view on drug-target-pathway relations. In the following, we give a brief summary about the recent discussion on drug-target interactions with emphasis on membrane proteins.

Abietane diterpenes, especially those containing quinone moieties, are often reported to have cytotoxic effects on cancer cell lines. They deserve greater attention because several cancer chemotherapeutic agents also possess the quinone structural feature. To date, very little is known about their cytotoxic molecular modes of action. In the present study, five diterpenes, 7 alpha-acetoxyroyleanone, horminone, royleanone, 7-ketoroyleanone and sugiol which have been previously isolated from the medicinal plant Peltodon longipes were shown to possess cytotoxic activity against the human pancreatic cancer cell line MIA PaCa-2. 7 alpha-Acetoxyroyleanone, horminone and royleanone were demonstrated to possess alkylating properties using the nucleophile 4-(4-nitrobenzyl)pyridine. However, no clear correlation between the alkylating properties and cytotoxicity of these diterpenes was observed. Furthermore, the relaxation activity of human DNA topoisomerases I and II was found to be influenced by these compounds, with 7-ketoroyleanone and sugiol being the most active. These two diterpenes preferentially inhibited topoisomerase I and exhibited lower IC(50) values than the classical topoisomerase I inhibitor camptothecin. Molecular docking studies revealed possible interactions of diterpenes with topoisomerase I, indicating that these compounds do not form the drug-enzyme-DNA covalent ternary complex as observed with camptothecin. A binding pocket located at the surface of the DNA-interaction site was proposed. Moreover, the ability of the five diterpenes to generate DNA-strand breaks in single cells was confirmed using the alkaline comet assay. As expected, these diterpenes also influenced cell cycle progression and arrested cells in different phases of the cell cycle, primarily the G1/G0 and S-phases. Interestingly, the diterpenes only exhibited a slight ability to induce apoptotic cell death and failed to generate intracellular reactive oxygen species. These results provide additional understanding of the cytotoxic effects of abietane diterpenes. Depending on their functional groups, we propose that abietane diterpenes utilise different mechanisms to induce cell death.

Piecing it together: Aspergillus niger produces kotanin by dimerization of the monomeric, polyketide-synthase-derived (PKS) 7-demethylsiderin. A combined approach, comprising bioinformatics and gene-deletion experiments, identified the biosynthetic cluster responsible for kotanin production. Homology modeling and substrate docking provide a rationale for the regio- and stereoselective phenol coupling reaction.

In reduced circumstances: tetrahydroxynaphthalene reductase shows a broad substrate range including alternate phenolic compounds and cyclic ketones. Structural modeling reveals major enzyme-substrate interactions; C-terminal truncation of the enzyme causes an altered substrate preference, in accordance with stabilization of the substrate by the C-terminal carboxylate. This effect allows the identification of a homologous enzyme.

Specific information on newly discovered proteins is often difficult to find in literature. Particularly if only sequences and no common names of proteins or genes are available, preceding sequence similarity searches can be crucial for the process of information collection. In drug research, it is important to know whether a small molecule targets only one specific protein or whether similar or homologous proteins are also influenced that may account for possible side effects.prolific (protein-literature investigation for interacting compounds) provides a one-step solution to investigate available information on given protein names, sequences, similar proteins or sequences on the gene level. Co-occurrences of UniProtKB/Swiss-Prot proteins and PubChem compounds in all PubMed abstracts are retrievable. Concise 'heat-maps' and tables display frequencies of co-occurrences. They provide links to processed literature with highlighted found protein and compound synonyms. Evaluation with manually curated drug-protein relationships showed that up to 69\% could be discovered by automatic text-processing. Examples are presented to demonstrate the capabilities of prolific.The web-application is available at http://prolific.pharmaceutical-bioinformatics.de and a web service at http://www.pharmaceutical-bioinformatics.de/prolific/soap/prolific.wsdl.stefan.guenther@pharmazie.uni-freiburg.deSupplementary data are available at Bioinformatics online.

The anamorphic fungus Glarea lozoyensis mutant strain 74030 is an overproducer of pneumocandin B(0), which is chemically converted into Cancidas, a potent antibiotic against clinically important fungal pathogens. Pneumocandins are acylated, cyclic hexapeptides with unusual hydroxylated amino acids. With the Glarea lozoyensis genome, the first species from the large polyphyletic family Helotiaceae has been sequenced.

Several lines of evidence indicate that prefibrillar assemblies of amyloid-β (Aβ) polypeptides, such as soluble oligomers or protofibrils, rather than mature, end-stage amyloid fibrils cause neuronal dysfunction and memory impairment in Alzheimer's disease. These findings suggest that reducing the prevalence of transient intermediates by small molecule-mediated stimulation of amyloid polymerization might decrease toxicity. Here we demonstrate the acceleration of Aβ fibrillogenesis through the action of the orcein-related small molecule O4, which directly binds to hydrophobic amino acid residues in Aβ peptides and stabilizes the self-assembly of seeding-competent, β-sheet-rich protofibrils and fibrils. Notably, the O4-mediated acceleration of amyloid fibril formation efficiently decreases the concentration of small, toxic Aβ oligomers in complex, heterogeneous aggregation reactions. In addition, O4 treatment suppresses inhibition of long-term potentiation by Aβ oligomers in hippocampal brain slices. These results support the hypothesis that small, diffusible prefibrillar amyloid species rather than mature fibrillar aggregates are toxic for mammalian cells.

Streptomyces sp. Tü6071 is a soil-dwelling bacterium which has a highly active isoprenoid biosynthesis. Isoprenoids are important precursors for biopharmaceutical molecules such as antibiotics or anticancer agents, e.g., landomycin. Streptomyces sp. Tü6071 produces the industrially important terpene glycosides phenalinolactones, which have antibacterial activity against several Gram-positive bacteria. The availability of the genome sequence of Streptomyces sp. Tü6071 allows for understanding the biosynthesis of these pharmaceutical molecules and will facilitate rational genome modification to improve industrial use.

Searching for certain compounds in literature can be an elaborate task, with many compounds having several different synonyms. Often, only the structure is known but not its name. Furthermore, rarely investigated compounds may not be described in the available literature at all. In such cases, preceding searches for described similar compounds facilitate literature mining. Highlighted names of proteins in selected texts may further accelerate the time-consuming process of literary research. Compounds In Literature (CIL) provides a web interface to automatically find names, structures, and similar structures in over 28 million compounds of PubChem and more than 18 million citations provided by the PubMed service. CIL's pre-calculated database contains more than 56 million parent compound-abstract relations. Found compounds, relatives and abstracts are related to proteins in a concise 'heat map'-like overview. Compounds and proteins are highlighted in their respective abstracts, and are provided with links to PubChem and UniProt.An easy-to-use web interface with detailed descriptions, help and statistics is available from http://cil.pharmaceutical-bioinformatics.de.stefan.guenther@pharmazie.uni-freiburg.de.

Because the sugar moieties of natural products are primarily O-linked, the hydrolytic sensitivity of the glycosidic linkage limits their therapeutic application. One potential solution to this problem is to replace the labile O-glycosidic bond with an enzymatically and chemically stable C-glycosidic bond. In this study, computational analysis of the O-glycosyltransferase LanGT2 and the C-glycosyltransferase UrdGT2 was used to predict the changes necessary to switch the O-glycosylating enzyme to a C-glycosyltransferase. By screening rationally designed LanGT2 mutants a number of LanGT2 variants with C-glycosyltransferase activity were identified. One variant, having 10 amino acid substitutions, revealed the primary region that determines O- versus C-glycosylation. By modeling the active site of this mutant and probing the role of active site residues with alanine substitutions, this work also illuminates the mechanistic features of O- and C-glycosylation.

Solved structures of protein-protein complexes give fundamental insights into protein function and molecular recognition. Although the determination of protein-protein complexes is generally more difficult than solving individual proteins, the number of experimentally determined complexes increased conspicuously during the last decade. Here, the interfaces of 750 transient protein-protein interactions as well as 2,000 interactions between domains of the same protein chain (obligate interactions) were analyzed to obtain a better understanding of molecular recognition and to identify features applicable for protein binding site prediction. Calculation of knowledge-based potentials showed a preference of contacts between amino acids having complementary physicochemical properties. The analysis of amino acid conservation of the entire interface area showed a weak but significant tendency to a higher evolutionary conservation of protein binding sites compared to surface areas that are permanently exposed to solvent. Remarkably, contact frequencies between outstandingly conserved residues are much higher than expected confirming the so-called "hot spot" theory. The comparisons between obligate and transient domain contacts reveal differences and point out that structural diversification and molecular recognition of protein-protein interactions are subjected to other evolutionary aspects than obligate domain-domain interactions.

Much of the information on the Cytochrome P450 enzymes (CYPs) is spread across literature and the internet. Aggregating knowledge about CYPs into one database makes the search more efficient. Text mining on 57 CYPs and drugs led to a mass of papers, which were screened manually for facts about metabolism, SNPs and their effects on drug degradation. Information was put into a database, which enables the user not only to look up a particular CYP and all metabolized drugs, but also to check tolerability of drug-cocktails and to find alternative combinations, to use metabolic pathways more efficiently. The SuperCYP database contains 1170 drugs with more than 3800 interactions including references. Approximately 2000 SNPs and mutations are listed and ordered according to their effect on expression and/or activity. SuperCYP (http://bioinformatics.charite.de/supercyp) is a comprehensive resource focused on CYPs and drug metabolism. Homology-modeled structures of the CYPs can be downloaded in PDB format and related drugs are available as MOL-files. Within the resource, CYPs can be aligned with each other, drug-cocktails can be 'mixed', SNPs, protein point mutations, and their effects can be viewed and corresponding PubMed IDs are given. SuperCYP is meant to be a platform and a starting point for scientists and health professionals for furthering their research.

The increasing structural information about target-bound compounds provide a rich basis to study the binding mechanisms of metabolites and drugs. SuperSite is a database, which combines the structural information with various tools for the analysis of molecular recognition. The main data is made up of 8000 metabolites including 1300 drugs, bound to about 290,000 different receptor binding sites. The analysis tools include features, like the highlighting of evolutionary conserved receptor residues, the marking of putative binding pockets and the superpositioning of different binding sites of the same ligand. User-defined compounds can be edited or uploaded and will be superimposed with the most similar co-crystallized ligand. The user can examine all results online with the molecule viewer Jmol. An implemented search algorithm allows the screening of uploaded proteins, in order to detect potential drug binding sites, which are similar to known binding pockets. The huge data set of target-bound compounds in combination with the provided analysis tools allow to inspect the characteristics of molecular recognition, especially for drug target interactions. SuperSite is publicly available at: http://bioinformatics.charite.de/supersite.

The increasing number of solved macromolecules provides a solid number of 3D interfaces, if all types of molecular contacts are being considered. JAIL annotates three different kinds of macromolecular interfaces, those between interacting protein domains, interfaces of different protein chains and interfaces between proteins and nucleic acids. This results in a total number of about 184,000 database entries. All the interfaces can easily be identified by a detailed search form or by a hierarchical tree that describes the protein domain architectures classified by the SCOP database. Visual inspection of the interfaces is possible via an interactive protein viewer. Furthermore, large scale analyses are supported by an implemented sequential and by a structural clustering. Similar interfaces as well as non-redundant interfaces can be easily picked out. Additionally, the sequential conservation of binding sites was also included in the database and is retrievable via Jmol. A comprehensive download section allows the composition of representative data sets with user defined parameters. The huge data set in combination with various search options allow a comprehensive view on all interfaces between macromolecules included in the Protein Data Bank (PDB). The download of the data sets supports numerous further investigations in macromolecular recognition. JAIL is publicly available at http://bioinformatics.charite.de/jail.

The drug classification scheme of the World Health Organization (WHO) [Anatomical Therapeutic Chemical (ATC)-code] connects chemical classification and therapeutic approach. It is generally accepted that compounds with similar physicochemical properties exhibit similar biological activity. If this hypothesis holds true for drugs, then the ATC-code, the putative medical indication area and potentially the medical target should be predictable on the basis of structural similarity. We have validated that the prediction of the drug class is reliable for WHO-classified drugs. The reliability of the predicted medical effects of the compounds increases with a rising number of (physico-) chemical properties similar to a drug with known function. The web-server translates a user-defined molecule into a structural fingerprint that is compared to about 6300 drugs, which are enriched by 7300 links to molecular targets of the drugs, derived through text mining followed by manual curation. Links to the affected pathways are provided. The similarity to the medical compounds is expressed by the Tanimoto coefficient that gives the structural similarity of two compounds. A similarity score higher than 0.85 results in correct ATC prediction for 81\% of all cases. As the biological effect is well predictable, if the structural similarity is sufficient, the web-server allows prognoses about the medical indication area of novel compounds and to find new leads for known targets. Availability: the system is freely accessible at http://bioinformatics.charite.de/superpred. SuperPred can be obtained via a Creative Commons Attribution Noncommercial-Share Alike 3.0 License.

The molecular basis of drug action is often not well understood. This is partly because the very abundant and diverse information generated in the past decades on drugs is hidden in millions of medical articles or textbooks. Therefore, we developed a one-stop data warehouse, SuperTarget that integrates drug-related information about medical indication areas, adverse drug effects, drug metabolization, pathways and Gene Ontology terms of the target proteins. An easy-to-use query interface enables the user to pose complex queries, for example to find drugs that target a certain pathway, interacting drugs that are metabolized by the same cytochrome P450 or drugs that target the same protein but are metabolized by different enzymes. Furthermore, we provide tools for 2D drug screening and sequence comparison of the targets. The database contains more than 2500 target proteins, which are annotated with about 7300 relations to 1500 drugs; the vast majority of entries have pointers to the respective literature source. A subset of these drugs has been annotated with additional binding information and indirect interactions and is available as a separate resource called Matador. SuperTarget and Matador are available at http://insilico.charite.de/supertarget and http://matador.embl.de.

The recent structural elucidation of about one dozen channels (in which we include transporters) has provided further evidence that these membrane proteins typically undergo large movements during their function. However, it is still not well understood how these proteins achieve the necessary trade-off between stability and mobility. To identify specific structural properties of channels, we compared the helix-packing and hydrogen-bonding patterns of channels with those of membrane coils; the latter is a class of membrane proteins whose structures are expected to be more rigid. We describe in detail how in channels, helix pairs are usually arranged in packing motifs with large crossing angles (|tau| approximately 40 degrees ), where the (small) side chains point away from the packing core and the backbones of the two helices are in close contact. We found that this contributes to a significant enrichment of Calpha-H...O bonds and to a packing geometry where right-handed parallel (tau = -40 degrees +/- 10 degrees ) and antiparallel (tau = +140 degrees +/- 25 degrees ) arrangements are equally preferred. By sharp contrast, the interdigitation and hydrogen bonding of side chains in helix pairs of membrane coils results in narrowly distributed left-handed antiparallel arrangements with crossing angles tau = -160 degrees +/- 10 degrees (|tau| approximately 20 degrees ). In addition, we show that these different helix-packing modes of the two types of membrane proteins correspond to specific hydrogen-bonding patterns. In particular, in channels, three times as many of the hydrogen-bonded helix pairs are found in parallel right-handed motifs than are non-hydrogen-bonded helix pairs. Finally, we discuss how the presence of weak hydrogen bonds, water-containing cavities, and right-handed crossing angles may facilitate the required conformational flexibility between helix pairs of channels while maintaining sufficient structural stability.

In mice, different alleles of the mNAIP5 (murine neuronal apoptosis inhibitory protein-5)/mBirc1e gene determine whether macrophages restrict or support intracellular replication of Legionella pneumophila, and whether a mouse is resistant or (moderately) susceptible to Legionella infection. In the resistant mice strains, the nucleotide-binding oligomerization domain (Nod)-like receptor (NLR) family member mNAIP5/mBirc1e, as well as the NLR protein mIpaf (murine ICE protease-activating factor), are involved in recognition of Legionella flagellin and in restriction of bacterial replication. Human macrophages and lung epithelial cells support L. pneumophila growth, and humans can develop severe pneumonia (Legionnaires disease) after Legionella infection. The role of human orthologs to mNAIP5/mBirc1e and mIpaf in this bacterial infection has not been elucidated. Herein we demonstrate that flagellin-deficient L. pneumophila replicate more efficiently in human THP-1 macrophages, primary monocyte-derived macrophages, and alveolar macrophages, and in A549 lung epithelial cells compared with wild-type bacteria. Additionally, we note expression of the mNAIP5 ortholog hNAIP in all cell types examined, and expression of hIpaf in human macrophages. Gene silencing of hNAIP or hIpaf in macrophages or of hNAIP in lung epithelial cells leads to an enhanced bacterial growth, and overexpression of both molecules strongly reduces Legionella replication. In contrast to experiments with wild-type L. pneumophila, hNAIP or hIpaf knock-down affects the (enhanced) replication of flagellin-deficient Legionella only marginally. In conclusion, hNAIP and hIpaf mediate innate intracellular defense against flagellated Legionella in human cells.

After the sequencing of the human genome, the publication of the genome of our nearest relative, the chimpanzee (Pan troglodytes) provided groundbreaking data improving the understanding of the recent human evolution. There are about forty million changes, most of them single nucleotide substitutions, which teach us about ourselves, both in terms of similarities and differences with chimpanzees. From a medical point of view differences in incidence and severity of diseases are of special importance to pinpoint novel targets and to develop innovative therapies. This analysis focuses on the cognition that chimpanzees rarely suffer from cancer. To elucidate possible reasons for this finding, we compare differences regarding apoptosis and DNA-repair on different levels of chromosome organization, gene structure, post-transcriptional and post-translational modifications to functional changes in protein structures. The result is a complex pattern of subtle variances and a few large-scale changes.

The immune system protects organisms from foreign proteins, peptide epitopes and a multitude of chemical compounds. Among these, haptens are small molecules, eliciting an immune response when conjugated with carrier molecules. Known haptens are xenobiotics or natural compounds, which can induce a number of autoimmune diseases like contact dermatitis or asthma. Furthermore, haptens are utilized in the development of biosensors, immunomodulators and new vaccines. Although hapten-induced allergies account for 6-10\% of all adverse drug effects, the understanding of the correlation between structural and haptenic properties is rather fragmentary. We have developed a manually curated hapten database, SuperHapten, integrating information from literature and web resources. The current version of the database compiles 2D/3D structures, physicochemical properties and references for about 7500 haptens and 25,000 synonyms. The commercial availability is documented for about 6300 haptens and 450 related antibodies, enabling experimental approaches on cross-reactivity. The haptens are classified regarding their origin: pesticides, herbicides, insecticides, drugs, natural compounds, etc. Queries allow identification of haptens and associated antibodies according to functional class, carrier protein, chemical scaffold, composition or structural similarity. SuperHapten is available online at http://bioinformatics.charite.de/superhapten.

The increasing number of solved protein structures provides a solid number of interfaces, if protein-protein interactions, domain-domain contacts, and contacts between biological units are taken into account. An interface library gives us the opportunity to identify surface regions on a target molecule that are similar by local structure and residue composition. If both unbound components of a possible protein complex exhibit structural similarities to a known interface, the unbound structures can be superposed onto the known interfaces. The approach is accompanied by two mathematical problems. Protein surfaces have to be quickly screened by thousands of patches, and similarity has to be evaluated by a suitable scoring scheme. The used algorithm (NeedleHaystack) identifies similar patches within minutes. Structurally related sites are recognized even if only parts of the template patches are structurally related to the interface region. A successful prediction of the protein complex depends on a suitable template of the library. However, the performed tests indicate that interaction sites are identified even if the similarity is very low. The approach complements existing ab initio methods and provides valuable results on standard benchmark sets.

The pharmaceutical industry is hunting for high-affinity inhibitors of medical targets, but most of them fail in clinical trials because of severe side effects. On the other hand, there is a growing knowledge about multiple targets and their role in various signalling pathways. Therefore, the integration of experimental data, literature knowledge about drugs, targets, their metabolism, ontology, and related pathways is an important task to achieve better understanding of drug mechanisms on a systems biological level.

Allergic contact dermatitis occurs with increasing incidence and is a common environmental health problem. The undesirable immune response is triggered by small molecules denoted as haptens. Known haptens are synthetic or natural compounds that are present in everyday items like cosmetics or textiles. Certain compounds ([`]superhaptens') are of particular importance because of their outstanding immunogenic potential. In this article, the processes underlying such hypersensitivities are summarized and therapeutic options will be discussed.

In living cells protein-DNA interactions are fundamental processes. Here, we compare the 3D structures of several DNA-binding proteins frequently determined with and without attached DNA. We studied the global structure (backbone-traces) as well as the local structure (binding sites) by comparing pair-wise the related atoms. The DNA-interaction sites of uncomplexed proteins show conspicuously high local structural flexibility. Binding to DNA results in specific local conformations, which are clearly distinct from the unbound states. The adaptation of the protein's binding site to DNA can never be described by the lock and key model but in all cases by the induced fit model. Conformational changes in the seven protein backbone traces take place in different ways. Two of them dock onto DNA without a significant change, while the other five proteins are characterized by a backbone conformation change caused by DNA docking. In the case of three proteins of the latter group the DNA-complexed conformation also occurs in a few uncomplexed structures. This behavior can be described by a conformational ensemble, which is narrowed down by DNA docking until only one single DNA-complexed conformation occurs. Different docking models are discussed and each of the seven proteins is assigned to one of them.

BACKGROUND: The increasing number of known protein structures provides valuable information about pharmaceutical targets. Drug binding sites are identifiable and suitable lead compounds can be proposed. The flexibility of ligands is a critical point for the selection of potential drugs. Since computed 3D structures of millions of compounds are available, the knowledge of their binding conformations would be a great benefit for the development of efficient screening methods. RESULTS: Integration of two public databases allowed superposition of conformers for 193 approved drugs with 5507 crystallised target-bound counterparts. The generation of 9600 drug conformers using an atomic force field was carried out to obtain an optimal coverage of the conformational space. Bioactive conformations are best described by a conformational ensemble: half of all drugs exhibit multiple active states, distributed over the entire range of the reachable energy and conformational space.A number of up to 100 conformers per drug enabled us to reproduce the bound states within a similarity threshold of 1.0 angstroms in 70\% of all cases. This fraction rises to about 90\% for smaller or average sized drugs. CONCLUSION: Single drugs adopt multiple bioactive conformations if they interact with different target proteins. Due to the structural diversity of binding sites they adopt conformations that are distributed over a broad conformational space and wide energy range. Since the majority of drugs is well represented by a predefined low number of conformers (up to 100) this procedure is a valuable method to compare compounds by three-dimensional features or for fast similarity searches starting with pharmacophores. The underlying 9600 generated drug conformers are downloadable from the Super Drug Web site 1. All superpositions are visualised at the same source. Additional conformers (110,000) of 2400 classified WHO-drugs are also available.

Legionella pneumophila, a Gram-negative facultative intracellular bacterium, causes severe pneumonia (Legionnaires' disease). Type I interferons (IFNs) were so far associated with antiviral immunity, but recent studies also indicated a role of these cytokines in immune responses against (intracellular) bacteria. Here we show that wild-type L. pneumophila and flagellin-deficient Legionella, but not L. pneumophila lacking a functional type IV secretion system Dot/Icm, or heat-inactivated Legionella induced IFNbeta expression in human lung epithelial cells. We found that factor (IRF)-3 and NF-kappaB-p65 translocated into the nucleus and bound to the IFNbeta gene enhancer after L. pneumophila infection of lung epithelial cells. RNA interference demonstrated that in addition to IRF3, the caspase recruitment domain (CARD)-containing adapter molecule IPS-1 (interferon-beta promoter stimulator 1) is crucial for L. pneumophila-induced IFNbeta expression, whereas other CARD-possessing molecules, such as RIG-I (retinoic acid-inducible protein I), MDA5 (melanoma differentiation-associated gene 5), Nod27 (nucleotide-binding oligomerization domain protein 27), and ASC (apoptosis-associated speck-like protein containing a CARD) seemed not to be involved. Finally, bacterial multiplication assays in small interfering RNA-treated cells indicated that IPS-1, IRF3, and IFNbeta were essential for the control of intracellular replication of L. pneumophila in lung epithelial cells. In conclusion, we demonstrated a critical role of IPS-1, IRF3, and IFNbeta in Legionella infection of lung epithelium.