Drug Informatics for Chemical Genomics...
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1 Drug Informatics for Chemical Genomics... An Overview First Annual ChemGen IGERT Retreat Sept 2005 Drug Informatics for Chemical Genomics... p.
2 Topics ChemGen Informatics The ChemMine Project Library Comparison Drug Informatics for Chemical Genomics... p.
3 ChemGen Informatics A Multidisciplinary Symbiosis Cheminformatics Drug Informatics Network Analysis & Modeling Structural Informatics Bioinformatics Drug Informatics for Chemical Genomics... p.
4 Cheminformatics Structure formats & format rendering Property descriptor generation Similarity searching Substructure & similarity Property searches Model-based searches Pharmacophore & QSAR 3D conformer calculation Library design & analysis Library comparison Structure & descriptor clustering Diversity analysis Data management: databases Drug Informatics for Chemical Genomics... p.
5 Drug Informatics Screening database Bioactivity data Lead prioritization QSAR analyses Pharmacophore modeling Structural informatics Docking Rational drug design Virtual screening Drug Informatics for Chemical Genomics... p.
6 Bioinformatics and Network Analysis Bioinformatics Sequences & mrna/protein profiling Protein-protein interaction data Pathways & Ontologies Mutant analysis Network Analysis Clustering (HC, KM, PCA, MDS, NN, etc ) Systems modeling Statistics for everything Drug Informatics for Chemical Genomics... p.
7 Dilemma for Academic Institutions Current infrastructure Very limited open-source resources Dominance of commercial software Decision: commercial vs. public Black boxes for a lot of $ Focus on public resources with internal development time Advantage of Public Resource Approach Higher educational value Transparent, modifiable and shareable Higher public impact Drug Informatics for Chemical Genomics... p.
8 ChemMine: Chemical Genomics DB Compound mining and screening database for drug and chemical genomics discovery Current functionality Activity- & property-based searching Structure-based searching Online clustering Upload and retrieval of screening data Long term goals Central depository of internal and external screening data Online service for mining of drug-like compounds Ontologies for bioactives and screening data In silico discovery Training set for predictive approaches Property-focused libraries Systems approaches Predictive process modeling Publication: Plant Physiol (2005) 138, Drug Informatics for Chemical Genomics... p.
9 Functionality Overview URL: Over 2.5 million structures Screening libraries Bioactives & natural CMPs Metabolic compounds Activity information Screening data Target proteins Literature Web services Clustering Chemical descriptors Structure formats Drug Informatics for Chemical Genomics... p.
10 Similarity Searching Drug Informatics for Chemical Genomics... p. 1
11 2D Fragment Similarity Searching Most commonly used for large database searching. 3D approaches used in pharmacophore searching. Advantages Fast and accurate Involves 2 major steps Structural descriptors Similarity coefficients/measures Structural descriptors in similarity searching Atom pairs: C12N03_06 Atom sequences: C12C13C13C02C02N03 Fingerprints: rules to enumerate all fragments in common structures Sample Structure Substructure searching Similar to atom sequences Drug Informatics for Chemical Genomics... p. 1
12 Online Clustering Similarity-based Descriptor-based Hierarchical or binning clustering All-against-all similarity Distance matrix Clustering Drug Informatics for Chemical Genomics... p. 1
13 Preclustered Libraries Drug Informatics for Chemical Genomics... p. 1
14 Descriptor Clustering Drug Informatics for Chemical Genomics... p. 1
15 Future Updates Management of screening data Upload of bioactivity information from external and internal screens Diverse data types Compound upload Quantitative data forms Image data User-specific data? Development of ontology for bioactives, screening data and phenotypes Routines for publishing user data including mandatory curation system Interoperability with other screeing projects: ChemBank, PubChem, etc. Chem/drug informatics utilities QSAR analysis tools Expansion of drug-likeness and descriptor predictions Drug informatics R/BioConductor libraries Size-insensitive similarity searching Combinatorial searches, e.g. similarity plus descriptors IUPAC/InChI names 3D conformer generation Drug Informatics for Chemical Genomics... p. 1
16 Library Comparisons Assemble collection of K diverse drug-like compounds Selection Criteria Screening compounds, bioactives and natural products Minimum overlap within and between libraries Vendor diversity (J Chem Inf Comput Sci 44: ) Majority drug-like: plant Lipinski rules (Pest Manag Sci 58: ) Elimination of undesirable side groups (filters) Recommendations (ICCB, etc.) Literature (e.g. Tudor Oprea: Curr Drug Disc Technol 1: ) Resupply situation Price Drug Informatics for Chemical Genomics... p. 1
17 Analyzed Libraries Quantity conversions First library: 0.1mg [20µl], 5µg/µl [10-20mM] Final assay conc: 5-10ng/µl [10-40µM] Number of screens: 100 screens with 100µl end volume Analyzed collections ChemBridge: Microformat, 10,000 CMPs (0.1mg) ChemBridge: DIVERSet, 50,000 CMPs (0.25mg) Chemical Diversity: ICCB set, 15,000 CMPs (0.5mg) Sigma/TimTec: MyriaScreen, 10,000 CMPs (0.25mg) Microsource: Spectrum, 2,000 CMPs (0.25mg) On waiting list ChemBridge: NOVACore (parallel DOS), 40,000 CMPs, 0.25mg Biomol/TimTec: MaxiVerse, 9,600 CMPs, 0.25mg World Molecules/MDD Inc: x CMPs Enamine: 10,000-20,000 CMPs, 0.25mg Analyticon Discovery: MEGAbolite & NatDiverse, 3000 CMPs, 0.25mg Drug Informatics for Chemical Genomics... p. 1
18 Clustering Methods Principal component analysis Reduction technique of multivariate data to principal compoments to identify hidden variances Multidimensional scaling Displays distance matrix of objects in spacial plot Single linkage binning Uses provided similarity cutoff for grouping of items Drug Informatics for Chemical Genomics... p. 1
19 Similarity Clustering 100% Ident APs 90% Ident APs 80% Ident APs 70% Ident APs 60% Ident APs CB10 CB50 CD15 MY10 SP2 Drug Informatics for Chemical Genomics... p. 1
20 Property PCA Diversity relative to 80 complex bioactives in MS Spec Tannic Acid (MW 1600) (MW 270) Colistimethate (MW 1400) (MW 390) Cobalamine (MW 1100) CB10 CB50 CD15 MY10 SP2 Drug Informatics for Chemical Genomics... p. 2
21 Property Differences Compound Plots Property Plot CB10 CB50 CD15 MY10 SP2 Drug Informatics for Chemical Genomics... p. 2
22 Lipinski Descriptors Molecular Weight LogP Rotatable Bonds Hydrogen Bond Donors Hydrogen Bond Acceptors Drug Informatics for Chemical Genomics... p. 2
23 Similarity Clustering #2 100% Ident APs 90% Ident APs 80% Ident APs 70% Ident APs 60% Ident APs CB10 NC38 CD15 MY10 ADH1 SP2 Drug Informatics for Chemical Genomics... p. 2
24 Property Differences #2 Compound Plots Property Plot CB10 NC38 MY10 ADH1 SP2 Drug Informatics for Chemical Genomics... p. 2
25 Lipinski Descriptors #2 Molecular Weight LogP Rotatable Bonds Hydrogen Bond Donors Hydrogen Bond Acceptors Drug Informatics for Chemical Genomics... p. 2
26 Conclusions Low overlap in high similarity ranges (>80%) Strong overlap in low similarity ranges (<70%) Small differences in property spectrum Property spectrum clusters around known drugs Base decision on: Price Resupply Vendor diversity Drug Informatics for Chemical Genomics... p. 2
27 Lab Members Center for Plant Cell Biology, UCR Julian Krause, Undergraduate S. (CS) Josh Lauricha, Systems Admin (CS) Kevin Horan, Programmer (Math/CS) Li-Chang Cheng, Undergraduate (CS) Charles Jang, Graduate S. (CG) Colleen Knoth, Graduate S. (CG) Jack Cui, Temp (BCH/CS) Thomas Girke, AC & PR (BCH/MolB/BI) Drug Informatics for Chemical Genomics... p. 2
28 Questions? Drug Informatics for Chemical Genomics... p. 2
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