3D-e-Chem-VM: Structural Cheminformatics Research Infrastructure in a Freely Available Virtual Machine

3D-e-Chem-VM is an open source, freely available Virtual Machine (http://3d-e-chem.github.io/3D-e-Chem-VM/) that integrates cheminformatics and bioinformatics tools for the analysis of protein–ligand interaction data. 3D-e-Chem-VM consists of software libraries, and database and workflow tools that can analyze and combine small molecule and protein structural information in a graphical programming environment. New chemical and biological data analytics tools and workflows have been developed for the efficient exploitation of structural and pharmacological protein–ligand interaction data from proteomewide databases (e.g., ChEMBLdb and PDB), as well as customized information systems focused on, e.g., G protein-coupled receptors (GPCRdb) and protein kinases (KLIFS). The integrated structural cheminformatics research infrastructure compiled in the 3D-e-Chem-VM enables the design of new approaches in virtual ligand screening (Chemdb4VS), ligand-based metabolism prediction (SyGMa), and structure-based protein binding site comparison and bioisosteric replacement for ligand design (KRIPOdb).

[1]  J. Janetka,et al.  Discovery of novel hedgehog antagonists from cell-based screening: Isosteric modification of p38 bisamides as potent inhibitors of SMO. , 2012, Bioorganic & medicinal chemistry letters.

[2]  Jordi Mestres,et al.  PharmaTrek: A Semantic Web Explorer for Open Innovation in Multitarget Drug Discovery , 2012, Molecular informatics.

[3]  Niu Huang,et al.  Life beyond kinases: structure-based discovery of sorafenib as nanomolar antagonist of 5-HT receptors. , 2012, Journal of medicinal chemistry.

[4]  Saskia Nijmeijer,et al.  Development of a Profiling Strategy for Metabolic Mixtures by Combining Chromatography and Mass Spectrometry with Cell-Based GPCR Signaling , 2012, Journal of biomolecular screening.

[5]  Gilles Marcou,et al.  Optimizing Fragment and Scaffold Docking by Use of Molecular Interaction Fingerprints , 2007, J. Chem. Inf. Model..

[6]  Lars Ridder,et al.  SyGMa: Combining Expert Knowledge and Empirical Scoring in the Prediction of Metabolites , 2008, ChemMedChem.

[7]  W. Humphreys,et al.  Identification of the Human Enzymes Involved in the Oxidative Metabolism of Dasatinib: An Effective Approach for Determining Metabolite Formation Kinetics , 2008, Drug Metabolism and Disposition.

[8]  Gang Fu,et al.  PubChem Substance and Compound databases , 2015, Nucleic Acids Res..

[9]  Egon L. Willighagen,et al.  The Chemistry Development Kit (CDK): An Open-Source Java Library for Chemo-and Bioinformatics , 2003, J. Chem. Inf. Comput. Sci..

[10]  Inaki Morao,et al.  Drug discovery applications for KNIME: an open source data mining platform. , 2012, Current topics in medicinal chemistry.

[11]  Gert Vriend,et al.  GPCRDB information system for G protein-coupled receptors , 2003, Nucleic Acids Res..

[12]  J. Peters.  Polypharmacology - foe or friend? , 2013, Journal of medicinal chemistry.

[13]  George Papadatos,et al.  The ChEMBL bioactivity database: an update , 2013, Nucleic Acids Res..

[14]  Tina Ritschel,et al.  Pharmacophore Fingerprint-Based Approach to Binding Site Subpocket Similarity and Its Application to Bioisostere Replacement , 2012, J. Chem. Inf. Model..

[15]  Thorsten Meinl,et al.  KNIME-CDK: Workflow-driven cheminformatics , 2013, BMC Bioinformatics.

[16]  Barend Mons,et al.  Open PHACTS: semantic interoperability for drug discovery. , 2012, Drug discovery today.

[17]  Chris Morley,et al.  Open Babel: An open chemical toolbox , 2011, J. Cheminformatics.

[18]  G. Manfroni,et al.  A Comprehensive Structural Overview of p38α MAPK in Complex with Type I Inhibitors , 2015, ChemMedChem.

[19]  Bas Vroling,et al.  GPCRdb: an information system for G protein-coupled receptors , 2015, Nucleic Acids Res..

[20]  George Papadatos,et al.  myChEMBL: a virtual machine implementation of open data and cheminformatics tools , 2014, Bioinform..

[21]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[22]  George Papadatos,et al.  A document classifier for medicinal chemistry publications trained on the ChEMBL corpus , 2014, Journal of Cheminformatics.

[23]  Chris de Graaf,et al.  Function-specific virtual screening for GPCR ligands using a combined scoring method , 2016, Scientific Reports.

[24]  Chris de Graaf,et al.  Generic GPCR residue numbers - aligning topology maps while minding the gaps. , 2015, Trends in pharmacological sciences.

[25]  Isidro Cortes-Ciriano,et al.  Chemically Aware Model Builder (camb): an R package for property and bioactivity modelling of small molecules , 2015, Journal of Cheminformatics.

[26]  I. D. de Esch,et al.  KLIFS: a knowledge-based structural database to navigate kinase-ligand interaction space. , 2014, Journal of medicinal chemistry.

[27]  T. Hunter,et al.  The Protein Kinase Complement of the Human Genome , 2002, Science.

[28]  Xin Wen,et al.  BindingDB: a web-accessible database of experimentally determined protein–ligand binding affinities , 2006, Nucleic Acids Res..

[29]  R. Leurs,et al.  A structural chemogenomics analysis of aminergic GPCRs: lessons for histamine receptor ligand design , 2013, British journal of pharmacology.

[30]  Joseph S. Verducci,et al.  A Modification of the Jaccard–Tanimoto Similarity Index for Diverse Selection of Chemical Compounds Using Binary Strings , 2002, Technometrics.

[31]  T. N. Bhat,et al.  The Protein Data Bank , 2000, Nucleic Acids Res..

[32]  Chris de Graaf,et al.  KLIFS: a structural kinase-ligand interaction database , 2015, Nucleic Acids Res..

[33]  Thorsten Meinl,et al.  KNIME: The Konstanz Information Miner , 2007, GfKl.

[34]  Ross McGuire,et al.  Data-driven medicinal chemistry in the era of big data. , 2014, Drug discovery today.

[35]  Tina Ritschel,et al.  Molecular interaction fingerprint approaches for GPCR drug discovery. , 2016, Current opinion in pharmacology.

[36]  William L. Jorgensen,et al.  Journal of Chemical Information and Modeling , 2005, J. Chem. Inf. Model..

[37]  C. Gabel,et al.  Benzimidazolone p38 inhibitors. , 2004, Bioorganic & medicinal chemistry letters.

[38]  David Rogers,et al.  Extended-Connectivity Fingerprints , 2010, J. Chem. Inf. Model..

[39]  J. Bajorath,et al.  Learning from 'big data': compounds and targets. , 2014, Drug discovery today.

[40]  Thomas Sander,et al.  DataWarrior: An Open-Source Program For Chemistry Aware Data Visualization And Analysis , 2015, J. Chem. Inf. Model..

[41]  Vincent Le Guilloux,et al.  Fpocket: An open source platform for ligand pocket detection , 2009, BMC Bioinformatics.

[42]  Katrin Stierand,et al.  The Internet as Scientific Knowledge Base: Navigating the Chem-Bio Space , 2012, Molecular informatics.