On the Integration of In Silico Drug Design Methods for Drug Repurposing

Drug repurposing has become an important branch of drug discovery. Several computational approaches that help to uncover new repurposing opportunities and aid the discovery process have been put forward, or adapted from previous applications. A number of successful examples are now available. Overall, future developments will greatly benefit from integration of different methods, approaches and disciplines. Steps forward in this direction are expected to help to clarify, and therefore to rationally predict, new drug–target, target–disease, and ultimately drug–disease associations.

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

[2]  Jordi Mestres,et al.  Chemoisosterism in the Proteome , 2013, J. Chem. Inf. Model..

[3]  Michael J. Barratt,et al.  Evaluation of phenoxybenzamine in the CFA model of pain following gene expression studies and connectivity mapping , 2010, Molecular pain.

[4]  Rong Chen,et al.  Systematic analyses of drugs and disease indications in RepurposeDB reveal pharmacological, biological and epidemiological factors influencing drug repositioning , 2017, Briefings Bioinform..

[5]  Didier Rognan,et al.  Binding of Protein Kinase Inhibitors to Synapsin I Inferred from Pair-Wise Binding Site Similarity Measurements , 2010, PloS one.

[6]  Steven J. M. Jones,et al.  A Computational Approach to Finding Novel Targets for Existing Drugs , 2011, PLoS Comput. Biol..

[7]  S. Vasudevan,et al.  Shape-based reprofiling of FDA-approved drugs for the H₁ histamine receptor. , 2012, Journal of medicinal chemistry.

[8]  W. Patrick Walters,et al.  Prediction of Protein Pairs Sharing Common Active Ligands Using Protein Sequence, Structure, and Ligand Similarity , 2016, J. Chem. Inf. Model..

[9]  Kathrin Heikamp,et al.  Computational Polypharmacology Analysis of the Heat Shock Protein 90 Interactome , 2015, J. Chem. Inf. Model..

[10]  Paul A Clemons,et al.  The Connectivity Map: Using Gene-Expression Signatures to Connect Small Molecules, Genes, and Disease , 2006, Science.

[11]  Fabrício F. Costa.  Big data in biomedicine. , 2014, Drug discovery today.

[12]  Guanghui Hu,et al.  Human Disease-Drug Network Based on Genomic Expression Profiles , 2009, PloS one.

[13]  Kathryn M Hart,et al.  Discovery of multiple hidden allosteric sites by combining Markov state models and experiments , 2015, Proceedings of the National Academy of Sciences.

[14]  J. Mestres,et al.  A ligand-based approach to mining the chemogenomic space of drugs. , 2008, Combinatorial chemistry & high throughput screening.

[15]  Matthias Rarey,et al.  Index-Based Searching of Interaction Patterns in Large Collections of Protein-Ligand Interfaces , 2017, J. Chem. Inf. Model..

[16]  George Papadatos,et al.  The ChEMBL database in 2017 , 2016, Nucleic Acids Res..

[17]  Karen Lackey,et al.  Synthesis and SAR of potent EGFR/erbB2 dual inhibitors. , 2004, Bioorganic & medicinal chemistry letters.

[18]  C. Ehrt,et al.  Impact of Binding Site Comparisons on Medicinal Chemistry and Rational Molecular Design. , 2016, Journal of medicinal chemistry.

[19]  Salvatore Alaimo,et al.  Recommendation Techniques for Drug-Target Interaction Prediction and Drug Repositioning. , 2016, Methods in molecular biology.

[20]  Oakland J. Peters,et al.  Predicting new indications for approved drugs using a proteochemometric method. , 2012, Journal of medicinal chemistry.

[21]  Andreas Bender,et al.  Target prediction utilising negative bioactivity data covering large chemical space , 2015, Journal of Cheminformatics.

[22]  Dima Kozakov,et al.  Lessons from Hot Spot Analysis for Fragment-Based Drug Discovery. , 2015, Trends in pharmacological sciences.

[23]  Lihua Huang,et al.  Mechanisms of resistance to EGFR tyrosine kinase inhibitors , 2015, Acta pharmaceutica Sinica. B.

[24]  Giulio Rastelli,et al.  Application of a post-docking procedure based on MM-PBSA and MM-GBSA on single and multiple protein conformations. , 2012, European journal of medicinal chemistry.

[25]  J. Bajorath,et al.  Docking and scoring in virtual screening for drug discovery: methods and applications , 2004, Nature Reviews Drug Discovery.

[26]  J. Bajorath,et al.  Compound promiscuity: what can we learn from current data? , 2013, Drug discovery today.

[27]  Michael J. Keiser,et al.  Relating protein pharmacology by ligand chemistry , 2007, Nature Biotechnology.

[28]  Yoshihiro Yamanishi,et al.  Target-Based Drug Repositioning Using Large-Scale Chemical-Protein Interactome Data , 2015, J. Chem. Inf. Model..

[29]  Jürgen Bajorath,et al.  Exploring activity cliffs in medicinal chemistry. , 2012, Journal of medicinal chemistry.

[30]  Kai Huang,et al.  PharmMapper server: a web server for potential drug target identification using pharmacophore mapping approach , 2010, Nucleic Acids Res..

[31]  Andreas Mayr,et al.  Deep Learning as an Opportunity in Virtual Screening , 2015 .

[32]  Scott Boyer,et al.  Ligand-Based Approach to In Silico Pharmacology: Nuclear Receptor Profiling , 2006, J. Chem. Inf. Model..

[33]  Stephen T. C. Wong,et al.  A novel method of transcriptional response analysis to facilitate drug repositioning for cancer therapy. , 2012, Cancer research.

[34]  Yoshihiro Yamanishi,et al.  Systematic Drug Repositioning for a Wide Range of Diseases with Integrative Analyses of Phenotypic and Molecular Data , 2015, J. Chem. Inf. Model..

[35]  David S. Wishart,et al.  DrugBank: a comprehensive resource for in silico drug discovery and exploration , 2005, Nucleic Acids Res..

[36]  Alessandra Bulotta,et al.  Mechanisms of resistance to EGFR tyrosine kinase inhibitors gefitinib/erlotinib and to ALK inhibitor crizotinib. , 2013, Lung cancer.

[37]  Ping Zhang,et al.  Towards Drug Repositioning: A Unified Computational Framework for Integrating Multiple Aspects of Drug Similarity and Disease Similarity , 2014, AMIA.

[38]  Jordi Mestres,et al.  Identification of Similar Binding Sites to Detect Distant Polypharmacology , 2013, Molecular informatics.

[39]  Philip E. Bourne,et al.  Drug Discovery Using Chemical Systems Biology: Repositioning the Safe Medicine Comtan to Treat Multi-Drug and Extensively Drug Resistant Tuberculosis , 2009, PLoS Comput. Biol..

[40]  Katarzyna H. Kaminska,et al.  Characterization of drug-induced transcriptional modules: towards drug repositioning and functional understanding , 2013, Molecular systems biology.

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

[42]  Natalia Novac,et al.  Challenges and opportunities of drug repositioning. , 2013, Trends in pharmacological sciences.

[43]  Michael J. Keiser,et al.  Predicting new molecular targets for known drugs , 2009, Nature.

[44]  Chirag J Patel,et al.  A standard database for drug repositioning , 2017, Scientific Data.

[45]  Yanli Wang,et al.  PubChem BioAssay: 2017 update , 2016, Nucleic Acids Res..

[46]  Alasdair T. R. Laurie,et al.  Methods for the prediction of protein-ligand binding sites for structure-based drug design and virtual ligand screening. , 2006, Current protein & peptide science.

[47]  A. Bender,et al.  Analysis of Pharmacology Data and the Prediction of Adverse Drug Reactions and Off‐Target Effects from Chemical Structure , 2007, ChemMedChem.