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Virtual library screening strategies

Virtual library screening strategies



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    Vls Vls Presentation Transcript

    • S.Prasanth Kumar, Bioinformatician Virtual library screening (VLS) in the Drug Discovery Process Molecular Modeling & Drug Design S.Prasanth Kumar Dept. of Bioinformatics Applied Botany Centre (ABC) Gujarat University, Ahmedabad, INDIA www.facebook.com/Prasanth Sivakumar FOLLOW ME ON ACCESS MY RESOURCES IN SLIDESHARE prasanthperceptron CONTACT ME [email_address]
    • Outlines of the Presentation
      • Virtual Library Screening (VLS)
      • VLS Paradigm
      • Small molecule virtual libraries
      • Target selection
      • Binding site identification
      • Docking
      • Evaluation
      • ORVIL-ORganic Virtual Library (MY WORK)
    • Virtual screening Virtual screening : a computational approach to assess the interaction of an in silico library of small molecules and the structure of a target macromolecule to rapidly identify new drug leads. Merits Computational Only high scoring ligands goes to assay Demerits Molecular Complexity/Diversity False Positives Synthesis Issue
    • VLS Paradigm Library Diverse Compounds, Synthetically accessible compounds Target Protein, Structure Determination Method ADME, Pharmacophore Interaction Site Docking Scoring & Evaluation Lead Optimization
    • Small Molecule Virtual Libraries Descriptors for chemical libraries (evaluate how much of chemical space is Sampled ) = diversity of a given library Structural properties: VDW, electrostatic, H-bond donor/acceptor = energetically favorable contacts Similarity/Dissimilarity Measures: Tanimoto Coefficient PubChem, CCD, ZINC, NCI, ACD, chEBI, Drug Bank
    • Tanimoto Coefficient N A is the number of features in A, N B is the number of features in B, and N AB is the number of features common to A and B.
      • 5 4
      • = 4/(5+5-4)
      • =0. 67
    • ADME/T properties Lipinski’s RO5 and Ghose et al, 1999 profiling for druglikeness e.g.QikProp,FAF-Drugs,ACDLabs Toxicity Analysis Toolkit a high possibility of complete absorption Topological polar surface area (TPSA) > 60 Å2 and < 140 Å2 An indicator of lipophilicity of a drug; high level of metabolic clearance by P450 enzymes of liver were expected logD pH (7.4) > 0 low level of toxicity, non-specific binding and possible oral administration logP value < 5 circumvent non-specific binding Hydrogen bond donors and acceptors < 5 and 10 better absorption and low level of allergic reactions MW < 500
    • Pharmacophore Mapping Ensemble of steric and electronic features required for interaction of ligand with biological target to triggers a biological response PHASE ReScore Daylight H HBD HBA R Query Database
    • Target selection Protein’s as Target : XRD, NMR, Homology Modeling PDB, Swiss Modeler, Modeller 9v7, WHATIF Human Estrogen Receptor (2P7Z)
    • Ligand Binding Site Modulate Protein’s Function SiteMap, CastP Binding Site Identification 3-Hydroxy Tamoxifen (Co-crystallized ligand)
      • The library must be docked
      • into the target site and
      • evaluated for goodness-of-fit.
      • docking – the search for the conformation and configuration of the ligand in the binding site
      • scoring – the evaluation of the interaction energy between
      • the target and ligand
      Docking Docking of CDK6 Analogue Docking and in silico Bioavailability Analysis of CDK6 Flavonol Inhibitors and its Analogues for Acute Lymphoblastic Leukemia. (Under Review: Journal of Computational Intelligence in Bioinformatics) Glide,HEX 6,AutoDock,FlexX,DOCK 6.0,ArgusLab,GOLD
    • The scoring process evaluates and ranks each ligand pose in the target site Energetically Favorable Gibb’s Energy H-Bond Formation Other Scores The GScore is a combination of different parameters. GScore = 0.065 * van der Waal energy + 0.130 * Coulomb energy + Lipophilic term + Hydrogen-bonding term + Metal-binding term + Buried polar groups penalty + Freezing rotatable bonds penalty + Active site polar interactions. Scoring & Evaluation