EDULISS: a small-molecule database with data-mining and pharmacophore searching capabilities

SimilarityLab: Molecular Similarity for SAR Exploration and Target Prediction on the Web

Exploration of chemical space around hit, experimental, and known active compounds is an important step in the early stages of drug discovery. In academia, where access to chemical synthesis efforts is restricted in comparison to the pharma-industry, hits from primary screens are typically followed up through purchase and testing of similar compounds, before further funding is sought to begin medicinal chemistry efforts. Rapid exploration of druglike similars and structure–activity relationship profiles can be achieved through our new webservice SimilarityLab. In addition to searching for commercially available molecules similar to a query compound, SimilarityLab also enables the search of compounds with recorded activities, generating consensus counts of activities, which enables target and off-target prediction. In contrast to other online offerings utilizing the USRCAT similarity measure, SimilarityLab’s set of commercially available small molecules is consistently updated, currently containing over 12.7 million unique small molecules, and not relying on published databases which may be many years out of date. This ensures researchers have access to up-to-date chemistries and synthetic processes enabling greater diversity and access to a wider area of commercial chemical space. All source code is available in the SimilarityLab source repository.

Computational resources associating diseases with genotypes, phenotypes and exposures

The causes of a disease and its therapies are not only related to genotypes, but also associated with other factors, including phenotypes, environmental exposures, drugs and chemical molecules. Distinguishing disease-related factors from many neutral factors is critical as well as difficult. Over the past two decades, bioinformaticians have developed many computational resources to integrate the omics data and discover associations among these factors. However, researchers and clinicians are experiencing difficulties in choosing appropriate resources from hundreds of relevant databases and software tools. Here, in order to assist the researchers and clinicians, we systematically review the public computational resources of human diseases related to genotypes, phenotypes, environment factors, drugs and chemical exposures. We briefly describe the development history of these computational resources, followed by the details of the relevant databases and software tools. We finally conclude with a discussion of current challenges and future opportunities as well as prospects on this topic.

Open-Access Activity Prediction Tools for Natural Products. Case Study: hERG Blockers

Interference with the hERG potassium ion channel may cause cardiac arrhythmia and can even lead to death. Over the last few decades, several drugs, already on the market, and many more investigational drugs in various development stages, have had to be discontinued because of their hERG-associated toxicity. To recognize potential hERG activity in the early stages of drug development, a wide array of computational tools, based on different principles, such as 3D QSAR, 2D and 3D similarity, and machine learning, have been developed and are reviewed in this chapter. The various available prediction tools Similarity Ensemble Approach, SuperPred, SwissTargetPrediction, HitPick, admetSAR, PASSonline, Pred-hERG, and VirtualToxLab™ were used to screen a dataset of known hERG synthetic and natural product actives and inactives to quantify and compare their predictive power. This contribution will allow the reader to evaluate the suitability of these computational methods for their own related projects. There is an unmet need for natural product-specific prediction tools in this field.

USR-VS: a web server for large-scale prospective virtual screening using ultrafast shape recognition techniques

Ligand-based Virtual Screening (VS) methods aim at identifying molecules with a similar activity profile across phenotypic and macromolecular targets to that of a query molecule used as search template. VS using 3D similarity methods have the advantage of biasing this search toward active molecules with innovative chemical scaffolds, which are highly sought after in drug design to provide novel leads with improved properties over the query molecule (e.g. patentable, of lower toxicity or increased potency). Ultrafast Shape Recognition (USR) has demonstrated excellent performance in the discovery of molecules with previously-unknown phenotypic or target activity, with retrospective studies suggesting that its pharmacophoric extension (USRCAT) should obtain even better hit rates once it is used prospectively. Here we present USR-VS (http://usr.marseille.inserm.fr/), the first web server using these two validated ligand-based 3D methods for large-scale prospective VS. In about 2 s, 93.9 million 3D conformers, expanded from 23.1 million purchasable molecules, are screened and the 100 most similar molecules among them in terms of 3D shape and pharmacophoric properties are shown. USR-VS functionality also provides interactive visualization of the similarity of the query molecule against the hit molecules as well as vendor information to purchase selected hits in order to be experimentally tested.

Structure- and ligand-based virtual screening identifies new scaffolds for inhibitors of the oncoprotein MDM2

A major challenge in the field of ligand discovery is to identify chemically useful fragments that can be developed into inhibitors of specific protein-protein interactions. Low molecular weight fragments (with molecular weight less than 250 Da) are likely to bind weakly to a protein’s surface. Here we use a new virtual screening procedure which uses a combination of similarity searching and docking to identify chemically tractable scaffolds that bind to the p53-interaction site of MDM2. The binding has been verified using capillary electrophoresis which has proven to be an excellent screening method for such small, weakly binding ligands.

UFSRAT: Ultra-fast Shape Recognition with Atom Types--the discovery of novel bioactive small molecular scaffolds for FKBP12 and 11βHSD1

MOTIVATION

Using molecular similarity to discover bioactive small molecules with novel chemical scaffolds can be computationally demanding. We describe Ultra-fast Shape Recognition with Atom Types (UFSRAT), an efficient algorithm that considers both the 3D distribution (shape) and electrostatics of atoms to score and retrieve molecules capable of making similar interactions to those of the supplied query.

RESULTS

Computational optimization and pre-calculation of molecular descriptors enables a query molecule to be run against a database containing 3.8 million molecules and results returned in under 10 seconds on modest hardware. UFSRAT has been used in pipelines to identify bioactive molecules for two clinically relevant drug targets; FK506-Binding Protein 12 and 11β-hydroxysteroid dehydrogenase type 1. In the case of FK506-Binding Protein 12, UFSRAT was used as the first step in a structure-based virtual screening pipeline, yielding many actives, of which the most active shows a KD, app of 281 µM and contains a substructure present in the query compound. Success was also achieved running solely the UFSRAT technique to identify new actives for 11β-hydroxysteroid dehydrogenase type 1, for which the most active displays an IC50 of 67 nM in a cell based assay and contains a substructure radically different to the query. This demonstrates the valuable ability of the UFSRAT algorithm to perform scaffold hops.

AVAILABILITY AND IMPLEMENTATION

A web-based implementation of the algorithm is freely available at http://opus.bch.ed.ac.uk/ufsrat/.

The forecast of anticancer targets of cryptotanshinone based on reverse pharmacophore-based screening technology

Anticancer targets of cryptotanshinone were evaluated and rapidly forecasted with PharmMapper, a reverse pharmacophore-based screening platform, as well as drug target databases, including PDTD, DrugBank and TTD. The pathway analyses for the collection of anticancer targets screened were carried out based on the KEGG pathway database, followed by the forecast of potential pharmacological activities and pathways of the effects of cryptotanshinone, and verification of some of the targets screened using whole cell tests. The results showed that a total of eight targets with anticancer potential were screened, including MAP2K1, RARα, RXRα, PDK1, CHK1, AR, Ang-1 R, and Kif11. These targets are mainly related to four aspects of the cancer growth: the cell cycle, angiogenesis, apoptosis, and androgen receptor. The cell tests showed that cryptotanshinone can inhibit the viability of human hepatoma cells SMMC-7721, which is related to the reduction of expression of MAP2K1 mRNA. This method provides a strong clue for the study of the anticancer effects and mechanisms of action of cryptotanshinone in the future.

MACE: mutation-oriented profiling of chemical response and gene expression in cancers

SUMMARY

The mutational status of specific cancer lineages can affect the sensitivity to or resistance against cancer drugs. The MACE database provides web-based interactive tools for interpreting large chemical screening and gene expression datasets of cancer cell lines in terms of mutation and lineage categories. GI50 data of chemicals against individual NCI60 cell lines were normalized and organized to statistically identify mutation- or lineage-specific chemical responses. Similarly, DNA microarray data on NCI60 cell lines were processed to analyze mutation- or lineage-specific gene expression signatures. A combined analysis of GI50 and gene expression data to find potential associations between chemicals and genes is also a capability of this system. This database will provide extensive, systematic information to identify lineage- or mutation-specific anticancer agents and related gene targets.

AVAILABILITY AND IMPLEMENTATION

The MACE web database is available at http://mace.sookmyung.ac.kr/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

CONTACT

yoonsj@sookmyung.ac.kr.

Biochemical evaluation of virtual screening methods reveals a cell-active inhibitor of the cancer-promoting phosphatases of regenerating liver

Computationally supported development of small molecule inhibitors has successfully been applied to protein tyrosine phosphatases in the past, revealing a number of cell-active compounds. Similar approaches have also been used to screen for small molecule inhibitors for the cancer-related phosphatases of regenerating liver (PRL) family. Still, selective and cell-active compounds are of limited availability. Since especially PRL-3 remains an attractive drug target due to its clear role in cancer metastasis, such compounds are highly demanded. In this study, we investigated various virtual screening approaches for their applicability to identify novel small molecule entities for PRL-3 as target. Biochemical evaluation of purchasable compounds revealed ligand-based approaches as well suited for this target, compared to docking-based techniques that did not perform well in this context. The best hit of this study, a 2-cyano-2-ene-ester and hence a novel chemotype targeting the PRLs, was further optimized by a structure–activity-relationship (SAR) study, leading to a low micromolar PRL inhibitor with acceptable selectivity over other protein tyrosine phosphatases. The compound is active in cells, as shown by its ability to specifically revert PRL-3 induced cell migration, and exhibits similar effects on PRL-1 and PRL-2. It is furthermore suitable for fluorescence microscopy applications, and it is commercially available. These features make it the only purchasable, cell-active and acceptably selective PRL inhibitor to date that can be used in various cellular applications.

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Computational ligand- and docking-based approaches were tested for PRL-3 as a target.

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Ligand-based screening was proven a feasible approach for PRL-3 inhibitor discovery.

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A low micromolar, non-competitive inhibitor with novel chemotype for PRLs was discovered.

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The inhibitor efficiently blocks PRL induced cell migration.

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The inhibitor is non-cytotoxic, commercially available and suitable for fluorescence microscopy applications.

Development of a natural products database from the biodiversity of Brazil

We describe herein the design and development of an innovative tool called the NuBBE database (NuBBEDB), a new Web-based database, which incorporates several classes of secondary metabolites and derivatives from the biodiversity of Brazil. This natural product database incorporates botanical, chemical, pharmacological, and toxicological compound information. The NuBBEDB provides specialized information to the worldwide scientific community and can serve as a useful tool for studies on the multidisciplinary interfaces related to chemistry and biology, including virtual screening, dereplication, metabolomics, and medicinal chemistry. The NuBBEDB site is at http://nubbe.iq.unesp.br/nubbeDB.html .

ChemBioServer: a web-based pipeline for filtering, clustering and visualization of chemical compounds used in drug discovery

SUMMARY

ChemBioServer is a publicly available web application for effectively mining and filtering chemical compounds used in drug discovery. It provides researchers with the ability to (i) browse and visualize compounds along with their properties, (ii) filter chemical compounds for a variety of properties such as steric clashes and toxicity, (iii) apply perfect match substructure search, (iv) cluster compounds according to their physicochemical properties providing representative compounds for each cluster, (v) build custom compound mining pipelines and (vi) quantify through property graphs the top ranking compounds in drug discovery procedures. ChemBioServer allows for pre-processing of compounds prior to an in silico screen, as well as for post-processing of top-ranked molecules resulting from a docking exercise with the aim to increase the efficiency and the quality of compound selection that will pass to the experimental test phase.

AVAILABILITY

The ChemBioServer web application is available at: http://bioserver-3.bioacademy.gr/Bioserver/ChemBioServer/.

CONTACT

gspyrou@bioacademy.gr

ZINCPharmer: pharmacophore search of the ZINC database

ZINCPharmer (http://zincpharmer.csb.pitt.edu) is an online interface for searching the purchasable compounds of the ZINC database using the Pharmer pharmacophore search technology. A pharmacophore describes the spatial arrangement of the essential features of an interaction. Compounds that match a well-defined pharmacophore serve as potential lead compounds for drug discovery. ZINCPharmer provides tools for constructing and refining pharmacophore hypotheses directly from molecular structure. A search of 176 million conformers of 18.3 million compounds typically takes less than a minute. The results can be immediately viewed, or the aligned structures may be downloaded for off-line analysis. ZINCPharmer enables the rapid and interactive search of purchasable chemical space.

Structure-based and ligand-based virtual screening of novel methyltransferase inhibitors of the dengue virus

Background

The dengue virus is the most significant arthropod-borne human pathogen, and an increasing number of cases have been reported over the last few decades. Currently neither vaccines nor drugs against the dengue virus are available. NS5 methyltransferase (MTase), which is located on the surface of the dengue virus and assists in viral attachment to the host cell, is a promising antiviral target. In order to search for novel inhibitors of NS5 MTase, we performed a computer-aided virtual screening of more than 5 million commercially available chemical compounds using two approaches: i) structure-based screening using the crystal structure of NS5 MTase and ii) ligand-based screening using active ligands of NS5 MTase. Structure-based screening was performed using the LIDAEUS (LIgand Discovery At Edinburgh UniverSity) program. The ligand-based screening was carried out using the EDULISS (EDinburgh University LIgand Selection System) program.

Results

The selection of potential inhibitors of dengue NS5 MTase was based on two criteria: the compounds must bind to NS5 MTase with a higher affinity than that of active NS5 MTase ligands, such as ribavirin triphosphate (RTP) and S-adenosyl-L-homocysteine (SAH); and the compounds must interact with residues that are catalytically important for the function of NS5 MTase. We found several compounds that bind strongly to the RNA cap site and the S-adenosyl-L-methionine (SAM) binding site of NS5 MTase with better binding affinities than that of RTP and SAH. We analyzed the mode of binding for each compound to its binding site, and our results suggest that all compounds bind to their respective binding sites by interacting with, and thus blocking, residues that are vital for maintaining the catalytic activity of NS5 MTase.

Conclusions

We discovered several potential compounds that are active against dengue virus NS5 MTase through virtual screening using structure-based and ligand-based methods. These compounds were predicted to bind into the SAM binding site and the RNA cap site with higher affinities than SAH and RTP. These compounds are commercially available and can be purchased for further biological activity tests.

SuperTarget goes quantitative: update on drug-target interactions

There are at least two good reasons for the on-going interest in drug–target interactions: first, drug-effects can only be fully understood by considering a complex network of interactions to multiple targets (so-called off-target effects) including metabolic and signaling pathways; second, it is crucial to consider drug-target-pathway relations for the identification of novel targets for drug development. To address this on-going need, we have developed a web-based data warehouse named SuperTarget, which integrates drug-related information associated with medical indications, adverse drug effects, drug metabolism, pathways and Gene Ontology (GO) terms for target proteins. At present, the updated database contains >6000 target proteins, which are annotated with >330 000 relations to 196 000 compounds (including approved drugs); the vast majority of interactions include binding affinities and pointers to the respective literature sources. The user interface provides tools for drug screening and target similarity inclusion. A 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 proteins within a certain affinity range. SuperTarget is available at http://bioinformatics.charite.de/supertarget.

The trypanocidal drug suramin and other trypan blue mimetics are inhibitors of pyruvate kinases and bind to the adenosine site

Ehrlich's pioneering chemotherapeutic experiments published in 1904 (Ehrlich, P., and Shiga, K. (1904) Berlin Klin. Wochenschrift 20, 329-362) described the efficacy of a series of dye molecules including trypan blue and trypan red to eliminate trypanosome infections in mice. The molecular structures of the dyes provided a starting point for the synthesis of suramin, which was developed and used as a trypanocidal drug in 1916 and is still in clinical use. Despite the biological importance of these dye-like molecules, the mode of action on trypanosomes has remained elusive. Here we present crystal structures of suramin and three related dyes in complex with pyruvate kinases from Leishmania mexicana or from Trypanosoma cruzi. The phenyl sulfonate groups of all four molecules (suramin, Ponceau S, acid blue 80, and benzothiazole-2,5-disulfonic acid) bind in the position of ADP/ATP at the active sites of the pyruvate kinases (PYKs). The binding positions in the two different trypanosomatid PYKs are nearly identical. We show that suramin competitively inhibits PYKs from humans (muscle, tumor, and liver isoenzymes, K(i) = 1.1-17 μM), T. cruzi (K(i) = 108 μM), and L. mexicana (K(i) = 116 μM), all of which have similar active sites. Synergistic effects were observed when examining suramin inhibition in the presence of an allosteric effector molecule, whereby IC(50) values decreased up to 2-fold for both trypanosomatid and human PYKs. These kinetic and structural analyses provide insight into the promiscuous inhibition observed for suramin and into the mode of action of the dye-like molecules used in Ehrlich's original experiments.