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Docking and Drug Design Dr. Andrew C.R. Martin, UCL With thanks to Dr. Marketa Zvelebil, LICR, Breakthrough Breast Cancer Aims and Objectives • • • • • Understand the nature of drugs Know the steps in rational drug design Understand forms of docking Using docking for virtual screening Describe principles of de novo drug design What is a drug? • Ligands that bind to a specific protein • Either increase its activity (an agonist) or decrease/block its activity (an antagonist) • Many problems… solubility, stability, selectivity • Most drugs are not very selective… side effects • Rational drug design… exploit structure of the protein and its natural ligands Steps in drug design • Having a protein structure to dock into (Xray, model) • Defining the pocket • Having a database of ligands or designing a specific ligand(s) • Docking • Sorting the docked structures • Minimization and Dynamics • Analysis Defining the pocket Two types of interactions: • (1) Protein protein/peptide/DNA usually relatively flat on the surface • (2) Protein smallligand usually clefts/pockets Defining the pocket Type 1 usually defined manually • Known interactions sites • Explore the protein surface • Multiple alignment conserved hydrophobics on the surface patches of conserved residues Also automated methods... Predicting protein binding sites P53 analyzed by ProMate. Predicted region shown in RED. Corresponds to known binding site for ASPP2 (YELLOW) ProMate: http://bioportal.weizmann.ac.il/promate/promate.html Predicting protein binding sites P53 analyzed by PPI_PRED. Predicted regions shown in RED. ASPP2 shown in YELLOW PPIPRED: http://www.bioinformatics.leeds.ac.uk/ppi_pred/ Peptide binding sites Peptide interface Finding pockets and clefts Small ligand binding sites are usually clefts or pockets Search the surface for pockets. • Define the solventaccessible surface • Identify clefts and cavities • Usually the largest pocket is the binding site Finding pockets and clefts Pocketfinder Potential binding sites based only on geometry QsiteFinder and Grid Find regions with favourable interaction energy with a probe group Pocketfinder: http://www.bioinformatics.leeds.ac.uk/pocketfinder/ QsiteFinder: http://www.bioinformatics.leeds.ac.uk/qsitefinder/ Grid: http://www.moldiscovery.com/soft_grid.php Virtual Docking Surface complementarity Van der Waals forces Electrostatic (Salt bridge) Interaction Hydrogen bonds Hydrophobic bonding + + + + + + + + Docking can be between... • • • • Protein / small ligand Protein / peptide Protein / protein Protein / nucleotide Difficulties in docking Both molecules are flexible: • Hundreds of degrees of freedom • Astronomical number of possible conformations Protein / ligand • Often treat protein as rigid Docking methods rigid body Six degrees of freedom protein and ligand both treated as rigid 3 rotations / 3 translations Just like docking the space shuttle with a satellite Image from NASA Docking methods flexible ligand Treat receptor as static / ligand as flexible Dock ligand into binding pocket generate large number of possible orientations Evaluate and select by energy function Automated docking Many programs available • Make use of: • cavities • surface complementarity • electrostatics • full energy function DOCK: AUTODOCK: FTDOCK: HOTDOCK: http://www.cmpharm.ucsf.edu/kuntz/dock.html http://www.scripps.edu/pub/olsonweb/doc/autodock/ http://www.bmm.icnet.uk/ftdock/ http://www.unipaderborn.de/~lst/HotDock/features.html DOCK Generate molecular surface for the receptor HIV1 protease as the target receptor Active site aspartyl groups shown in red. Connolly's molecular surface (MS) Shown in yellow DOCK Generate spheres to fill the active site Cavities in the receptor used to define spheres Sphere centres become potential locations for ligand atoms DOCK Ligand Matching • Match sphere centres against ligand atoms • Find possible ligand orientations • Often >10,000 orientations possible Find the transformation (rotation + translation) to maximize sphere matching Scoring docked models Each orientation is scored Dock provides 3 scoring schemes: • Shape scoring • Electrostatic scoring uses DELPHI to calculate electrostatic potential • Forcefield scoring uses the AMBER potential Scoring docked models Shape complementarity is key! Protein/ligand surfaces are complementary a simple geometric descriptor Evaluation differs between methods two basic approaches: • use surface curvature or surface areas (based on Connolly surface) • gridbased evaluation of surface packing Energy scoring 1.Best binding site is not always lowest energy 2.True binding site often has an energy barrier around the site 1.Need more energy to leave the true site than other potential sites. Energy 15 kcal/mol 8 kcal/mol 10 kcal/mol Potential Site Real Site Lowest Energy Potential Site Performance of DOCK Topscoring orientation for thioketal docked to HIV1protease (forcefield scoring). Comparison with crystal structure… GOLD flexible genetic algorithm docking Inhibitor docked into Dihydrofolate reductase (DHFR) using pocket identified by PocketFinder 7 of 10 final orientations fit well with crystal structure 3 fit in NADPH binding site Virtual Screening • Docking can be used for virtual screening • Scan a library of potential drug molecules • Identify leads De Novo Drug Design LUDI (InsightII) find fragments that can bind GRID uses molecular mechanics potential to find interaction sites for probe groups Xsite uses an empirical potential to find interaction sites for probe groups Designing specific ligands Relenza First designed drug was Relenza (influenza). Identified molecules to bind to conserved regions of neuraminidase Retinovir and Indinavir Drugs to treat HIV Designed to inhibit viral proteases Side effects Side effects can be interesting... • A drug designed for heart problems had unexpected sideeffects… • Viagra! Summary • Find pockets • Principles for docking complementarity • Docking – rigid body / ligand flexibility • Virtual screening • Identifying probe interaction sites – build ligands de novo