Data Mining in Drug Discovery

PrefaceA Personal ForewordPART ONE: Data SourcesPROTEIN STRUCTURAL DATABASES IN DRUG DISCOVERYThe Protein Data Bank: The Unique Public Archive of Protein StructuresPDB-Related Databases for Exploring Ligand-Protein RecognitionThe sc-PDB, A Collection of Pharmacologically Relevant Protein-Ligand ComplexesConclusionsPUBLIC DOMAIN DATABASES FOR MEDICINAL CHEMISTRYIntroductionDatabases of Small Molecule Binding and BioactivityTrends in Medicinal Chemistry DataDirectionsSummaryCHEMICAL ONTOLOGIES FOR STANDARDIZATION, KNOWLEDGE DISCOVERY, AND DATA MININGIntroductionBackgroundChemical OntologiesStandardizationKnowledge DiscoveryData MiningConclusionsBUILDING A CORPORATE CHEMICAL DATABASE TOWARD SYSTEMS BIOLOGYIntroductionSetting the SceneDealing with Chemical StructuresIncreased Accuracy of the Registration of DataImplementation of the PlatformLinking Chemical Information to Analytical DataLinking Chemicals to Bioactivity DataConclusionsPART TWO: Analysis and EnrichmentDATA MINING OF PLANT METABOLIC PATHWAYSIntroductionPathway RepresentationPathway Management PlatformsObtaining Pathway InformationConstructing Organism-Specific Pathway DatabasesConclusionsTHE ROLE OF DATA MINING IN THE IDENTIFICATION OF BIOACTIVE COMPOUNDS VIA HIGH-THROUGHPUT SCREENINGIntroduction to the HTS Process: The Role of Data MiningRelevant Data Architectures for the Analysis of HTS DataAnalysis of HTS DataIdentification of New Compounds via Compound Set Enrichment and DockingConclusionsTHE VALUE OF INTERACTIVE VISUAL ANALYTICS IN DRUG DISCOVERY: AN OVERVIEWCreating Informative VisualizationsLead Discovery and OptimizationGenomicsUSING CHEMOINFORMATICS TOOLS FROM RIntroductionSystem CallShared Library CallWrappingJava ArchivesConclusionsPART THREE: Applications to PolypharmacologyCONTENT DEVELOPMENT STRATEGIES FOR THE SUCCESSFUL IMPLEMENTATION OF DATA MINING TECHNOLOGIESIntroductionKnowledge Challenges in Drug DiscoveryCase StudiesKnowledge-Based Data Mining TechnologiesFuture Trends and

Currently VP of Business Development at Prestwick Chemical SAS, Rémy Hoffmann studied pharmacy at the University Louis Pasteur in Strasbourg, France, and gained his doctorate in medicinal chemistry. After 17 years spent at what is now Accelrys, where he worked on pharmacophore perception methods, he joined Thomson Reuters as a regional sales manager. Here he learnt the importance of curated scientific data, and the need to develop methods for mining this data so as to extract accurate information to support the decisionmaking process, and thus arrive at the knowledge stage. In his current role, Dr. Hoffmann oversees the deployment of Prestwick Chemical?s products and services to the drug discovery community, both in the pharma and biotech industries, as well as within the academic scientific community.Arnaud Gohier studied organic chemistry at the University of Le Mans and Nantes (France). He received his PhD in Molecular Modeling from the University of Joseph Fourier in Grenoble (France). In 1999, he joined the french pharmaceutical company Servier. Dr Gohier?s main areas of interest are drug design and chemoinformatics.Pavel Pospisil has been Manager of Computational Chemistry at Philip Morris International, R&D in Neuchatel, Switzerland, since 2008. He holds a BSc in biochemistry from the University of Joseph Fourier in Grenoble, France, and an MSc in biochemical engineering from the Institute of Chemical Technology in Prague, Czech Republic, and received his PhDin natural sciences from the Swiss Federal Institute of Technology (ETH), Zurich. He carried out his postdoctoral studies at ETH Zurich and with the pharmaceutical company, Arpida, now Evolva. In 2004, Dr. Pospisil became a postdoctoral fellow and research associate at Harvard Medical School, Boston, USA, where he focused on data mining for cancer targets and the discovery of low molecular radiolabeled cancer imaging analogs. In 2008, he took up a position as consultant at Hoffmann-La-Roche, Basel,

"In summary, the book reflects the state-of-the-art for a rapidly changing field, with key emergent themes being the accessibility of public data, multiassay end-points for compounds, and the need to interpret these in the context of complex biological systems. It also usefully highlights some of the research challenges, with pointers to key likely future progress." ( ChemMedChem , 1 June 2014)