BUDE. A General Purpose Molecular Docking Program Using OpenCL. Richard B Sessions
|
|
- Myron Austin
- 6 years ago
- Views:
Transcription
1 BUDE A General Purpose Molecular Docking Program Using OpenCL Richard B Sessions 1
2 The molecular docking problem receptor ligand Proteins typically O(1000) atoms Ligands typically O(100) atoms predicted complex 1 Sampling (6-degrees of freedom) EMC 2 Binding affinity prediction EFE-FF 2
3 An atom-atom based forcefield parameterised according to atom type, analagous to standard molecular mechanics 3
4 Empirical Free Energy Forcefield McIntosh-Smith, S., et al., Benchmarking Energy Efficiency, Power Costs and Carbon Emissions on Heterogeneous Systems. Computer Journal, (2): p soft core
5 Re-docking a ligand into the Xray Structure (good prediction == low RMSD) 1CIL (Human carbonic anhydrase II) RMSD ~ 0.2 Å 5
6 Another example 1EZQ (Human Factor XA) RMSD ~ 1.2 Å 6
7 Accuracy of Pose Prediction (re-docking the BindingDB validation set, 84 complexes) 7
8 Binding Energy Prediction: is BUDE any better? Mike Hann s 2006 test of docking software Yes better but not perfect! 8
9 BUDE Simplified Flow Diagram (C++/OpenCL) Start BUDE Enter Initial Data End BUDE Yes Print Help Error(s)? Yes Data Reading Error(s)? No Write Control File Info No Docking Type Prepare Data for Docking End BUDE Act on Option Docking Small Large No Error(s)? Yes Site Docking Surface Docking Print Results Calculate Energies Rank Energies Host Job Do Docking No Generate Surface Pairs Do Generation Score Results EMC Accelerated Job Yes Parallel Code? Yes Last Generation No 9
10 BUDE s heterogeneous approach 1. Discover all OpenCL platforms/devices, inc. both CPUs and GPUs 2. Run a micro benchmark on each device, ideally a short piece of real work 3. Load balance using micro benchmark results 4. Re-run micro benchmark at regular intervals in case load changes 10
11 BUDE s Three Docking Modes Virtual Screening by Docking Binding Site Prediction Protein-Protein Docking in real space 11
12 Virtual Screening by Docking 12
13 Virtual Screening by Docking of NDM-1 New Delhi metallo-β-lactamase-1 8 million ZINC8 candidate drug molecules 20 conformers each 160M dockings EMERALD (STFC funded machine in Oxford) 372 GPU 2.4x10 17 atom-atom energies calculated ~60 hours actual wall-time 13
14 BUDE s EMC in Action 14
15 Virtual Screening for Ligands to Stabilise a Protein Screened 160 million conformations of the 8 million ZINC database against 5 different conformations of the protein on EMERALD Selected and tested 58 compounds with two types of experimental assays and found 18 compounds binding between 10 and 100 µm 31% hit rate 15
16 A New Virtual Screen against a key protein from the Malaria Parasite BlueCrystal P3 EMERALD 76 Nvidia K20s 372 Nvidia M2090s 16
17 Binding Site Identification Full rotation and limited translation of the ligand at each receptor surface vector
18 Location of the Binding Site of PI3P to a Protein (homology model) Involved in Insulin Signalling Thomas & Tavare 18
19 Protein-Protein Docking (in real space) Each point on ligand offered to each point on receptor with a local mini-dock: complete rotation in Z, rock in X & Y, small translations in X, Y & Z 19
20 Protein-Protein Docking Example the leucine zipper coiled coil Best energy -> RMSD = 0.2 Å In a real case with Pete Cullen s group we have mapped a proteinprotein interface using BUDE and confirmed it experimentally. This took only 20 site-directed mutations, instead of the hundreds required by full alanine-scanning mutagenesis 20
21 Performance across devices GHz High performance in silico virtual drug screening on many-core processors. Simon McIntosh-Smith, James Price, Richard B. Sessions & Amaurys A. Ibarra International Journal of High Performance Computing Applications (accepted for publication) 21
22 Main Optimisations Conditional accumulation Predicated accumulation Instruction mix in the innermost loop of the energy calculation High performance in silico virtual drug screening on many-core processors. Simon McIntosh-Smith, James Price, Richard B. Sessions & Amaurys A. Ibarra International Journal of High Performance Computing Applications (accepted for publication) 22
23 Optimisations High performance in silico virtual drug screening on many-core processors. Simon McIntosh-Smith, James Price, Richard B. Sessions & Amaurys A. Ibarra International Journal of High Performance Computing Applications (accepted for publication) 23
24 Summary GPUs and machines like Emerald are enabling new science BUDE is promising a step-change in Molecular Docking But plenty more developments and improvements are possible! 24
25 Acknowledgements Amaurys Avila Ibarra Simon N McIntosh-Smith James Price Debbie K Shoemark On the shoulders of giants... Emil Fischer ( ) Lock and Key Willard Gibbs ( ) Gibbs Free Energy G = H T S EMERALD and the einfrastructure South Consortium UK BlueCrystal and the Advanced Computing Research Centre (Bristol) 25
26 Supplementary Slides 26
27 Structure and Binding Energy Prediction speed vs accuracy tradeoff Speed Accuracy Typical docking scoring functions Empirical Free Energy Forcefield BUDE Free Energy calculations MM 1,2 QM/MM 3 Entropy: solvation configurational Electrostatics All atom Explicit solvent No Yes Yes Approx Approx Yes? Approx Yes No Yes Yes No No Yes 1. MD Tyka, AR Clarke, RB Sessions, J. Phys. Chem. B (2006) 2. MD Tyka, RB Sessions, AR Clarke, J. Phys. Chem. B (2007) 3. CJ Woods, FR Manby, AJ Mulholland, J. Chem. Phys (2008) 27
28 EMC Genetic Algorithm minimiser 28
29 On the shoulders of giants... Emil Fischer ( ) Lock and Key Willard Gibbs ( ) Gibbs Free Energy G = H T S
30 Receptor and Ligand Flexibility Full flexibility: would be Molecular Dynamics Limited flexibility: is appropriate for Molecular Docking: Protein: Backbone dock to selected Xray or MD structures Sidechains sample side chain rotamers during docking Small molecule: generate and dock many different conformations e.g. ZINC database of 8 M drug-like compounds 160 M conformers 30
31 EMC Genetic Algorithm Seed Parents Selected By Flag Generation Size Output Output Mutation Parameter Parameter Parameter Descriptors Coordinates Method N M R * True X Y Z U K% R* R*
32 BUDE Algorithm 32
33 33
Adaptive Heterogeneous Computing with OpenCL: Harnessing hundreds of GPUs and CPUs
Adaptive Heterogeneous Computing with OpenCL: Harnessing hundreds of GPUs and CPUs Simon McIntosh-Smith simonm@cs.bris.ac.uk Head of Microelectronics Research University of Bristol, UK 1 ! Collaborators
More informationAdaptive Heterogeneous Computing with OpenCL: Harnessing hundreds of GPUs and CPUs
Adaptive Heterogeneous Computing with OpenCL: Harnessing hundreds of GPUs and CPUs Simon McIntosh-Smith simonm@cs.bris.ac.uk Head of Microelectronics Research University of Bristol, UK 1 ! A brief biography
More informationMechanisms for exploiting heterogeneous computing: Harnessing hundreds of GPUs and CPUs
Mechanisms for exploiting heterogeneous computing: Harnessing hundreds of GPUs and CPUs Simon McIntosh-Smith simonm@cs.bris.ac.uk Head of Microelectronics Research University of Bristol, UK 1 ! Collaborators
More informationDocking. GBCB 5874: Problem Solving in GBCB
Docking Benzamidine Docking to Trypsin Relationship to Drug Design Ligand-based design QSAR Pharmacophore modeling Can be done without 3-D structure of protein Receptor/Structure-based design Molecular
More informationDISCRETE TUTORIAL. Agustí Emperador. Institute for Research in Biomedicine, Barcelona APPLICATION OF DISCRETE TO FLEXIBLE PROTEIN-PROTEIN DOCKING:
DISCRETE TUTORIAL Agustí Emperador Institute for Research in Biomedicine, Barcelona APPLICATION OF DISCRETE TO FLEXIBLE PROTEIN-PROTEIN DOCKING: STRUCTURAL REFINEMENT OF DOCKING CONFORMATIONS Emperador
More informationest Drive K20 GPUs! Experience The Acceleration Run Computational Chemistry Codes on Tesla K20 GPU today
est Drive K20 GPUs! Experience The Acceleration Run Computational Chemistry Codes on Tesla K20 GPU today Sign up for FREE GPU Test Drive on remotely hosted clusters www.nvidia.com/gputestd rive Shape Searching
More informationStructural Bioinformatics (C3210) Molecular Docking
Structural Bioinformatics (C3210) Molecular Docking Molecular Recognition, Molecular Docking Molecular recognition is the ability of biomolecules to recognize other biomolecules and selectively interact
More informationSoftwares for Molecular Docking. Lokesh P. Tripathi NCBS 17 December 2007
Softwares for Molecular Docking Lokesh P. Tripathi NCBS 17 December 2007 Molecular Docking Attempt to predict structures of an intermolecular complex between two or more molecules Receptor-ligand (or drug)
More informationDr. Sander B. Nabuurs. Computational Drug Discovery group Center for Molecular and Biomolecular Informatics Radboud University Medical Centre
Dr. Sander B. Nabuurs Computational Drug Discovery group Center for Molecular and Biomolecular Informatics Radboud University Medical Centre The road to new drugs. How to find new hits? High Throughput
More informationKd = koff/kon = [R][L]/[RL]
Taller de docking y cribado virtual: Uso de herramientas computacionales en el diseño de fármacos Docking program GLIDE El programa de docking GLIDE Sonsoles Martín-Santamaría Shrödinger is a scientific
More informationCheminformatics platform for drug discovery application
EGI-InSPIRE Cheminformatics platform for drug discovery application Hsi-Kai, Wang Academic Sinica Grid Computing EGI User Forum, 13, April, 2011 1 Introduction to drug discovery Computing requirement of
More informationMM-GBSA for Calculating Binding Affinity A rank-ordering study for the lead optimization of Fxa and COX-2 inhibitors
MM-GBSA for Calculating Binding Affinity A rank-ordering study for the lead optimization of Fxa and COX-2 inhibitors Thomas Steinbrecher Senior Application Scientist Typical Docking Workflow Databases
More informationPROTEIN-PROTEIN DOCKING REFINEMENT USING RESTRAINT MOLECULAR DYNAMICS SIMULATIONS
TASKQUARTERLYvol.20,No4,2016,pp.353 360 PROTEIN-PROTEIN DOCKING REFINEMENT USING RESTRAINT MOLECULAR DYNAMICS SIMULATIONS MARTIN ZACHARIAS Physics Department T38, Technical University of Munich James-Franck-Str.
More informationHigh Throughput In-Silico Screening Against Flexible Protein Receptors
John von Neumann Institute for Computing High Throughput In-Silico Screening Against Flexible Protein Receptors H. Sánchez, B. Fischer, H. Merlitz, W. Wenzel published in From Computational Biophysics
More informationProtein-Ligand Docking Evaluations
Introduction Protein-Ligand Docking Evaluations Protein-ligand docking: Given a protein and a ligand, determine the pose(s) and conformation(s) minimizing the total energy of the protein-ligand complex
More informationMD Simulation in Pose Refinement and Scoring Using AMBER Workflows
MD Simulation in Pose Refinement and Scoring Using AMBER Workflows Yuan Hu (On behalf of Merck D3R Team) D3R Grand Challenge 2 Webinar Department of Chemistry, Modeling & Informatics Merck Research Laboratories,
More informationProtein Structure Prediction and Protein-Ligand Docking
Protein Structure Prediction and Protein-Ligand Docking Björn Wallner bjornw@ifm.liu.se Jan. 24, 2014 Todays topics Protein Folding Intro Protein structure prediction How can we predict the structure of
More informationReceptor Based Drug Design (1)
Induced Fit Model For more than 100 years, the behaviour of enzymes had been explained by the "lock-and-key" mechanism developed by pioneering German chemist Emil Fischer. Fischer thought that the chemicals
More informationUser Guide for LeDock
User Guide for LeDock Hongtao Zhao, PhD Email: htzhao@lephar.com Website: www.lephar.com Copyright 2017 Hongtao Zhao. All rights reserved. Introduction LeDock is flexible small-molecule docking software,
More informationThe PhilOEsophy. There are only two fundamental molecular descriptors
The PhilOEsophy There are only two fundamental molecular descriptors Where can we use shape? Virtual screening More effective than 2D Lead-hopping Shape analogues are not graph analogues Molecular alignment
More informationUsing AutoDock for Virtual Screening
Using AutoDock for Virtual Screening CUHK Croucher ASI Workshop 2011 Stefano Forli, PhD Prof. Arthur J. Olson, Ph.D Molecular Graphics Lab Screening and Virtual Screening The ultimate tool for identifying
More informationMolecular Interactions F14NMI. Lecture 4: worked answers to practice questions
Molecular Interactions F14NMI Lecture 4: worked answers to practice questions http://comp.chem.nottingham.ac.uk/teaching/f14nmi jonathan.hirst@nottingham.ac.uk (1) (a) Describe the Monte Carlo algorithm
More informationToward an Understanding of GPCR-ligand Interactions. Alexander Heifetz
Toward an Understanding of GPCR-ligand Interactions Alexander Heifetz UK QSAR and ChemoInformatics Group Conference, Cambridge, UK October 6 th, 2015 Agenda Fragment Molecular Orbitals (FMO) for GPCR exploration
More informationSupporting Online Material for
www.sciencemag.org/cgi/content/full/309/5742/1868/dc1 Supporting Online Material for Toward High-Resolution de Novo Structure Prediction for Small Proteins Philip Bradley, Kira M. S. Misura, David Baker*
More informationChemical properties that affect binding of enzyme-inhibiting drugs to enzymes
Chemical properties that affect binding of enzyme-inhibiting drugs to enzymes Introduction The production of new drugs requires time for development and testing, and can result in large prohibitive costs
More informationStructure based drug design and LIE models for GPCRs
Structure based drug design and LIE models for GPCRs Peter Kolb kolb@docking.org Shoichet Lab ACS 237 th National Meeting, March 24, 2009 p.1/26 [Acknowledgements] Brian Shoichet John Irwin Mike Keiser
More informationIn silico pharmacology for drug discovery
In silico pharmacology for drug discovery In silico drug design In silico methods can contribute to drug targets identification through application of bionformatics tools. Currently, the application of
More informationChemical properties that affect binding of enzyme-inhibiting drugs to enzymes
Introduction Chemical properties that affect binding of enzyme-inhibiting drugs to enzymes The production of new drugs requires time for development and testing, and can result in large prohibitive costs
More informationHit Finding and Optimization Using BLAZE & FORGE
Hit Finding and Optimization Using BLAZE & FORGE Kevin Cusack,* Maria Argiriadi, Eric Breinlinger, Jeremy Edmunds, Michael Hoemann, Michael Friedman, Sami Osman, Raymond Huntley, Thomas Vargo AbbVie, Immunology
More informationThermodynamic Integration with Enhanced Sampling (TIES)
Thermodynamic Integration with Enhanced Sampling (TIES) A. P. Bhati, S. Wan, D. W. Wright and P. V. Coveney agastya.bhati.14@ucl.ac.uk Centre for Computational Science Department of Chemistry University
More informationHomology modeling. Dinesh Gupta ICGEB, New Delhi 1/27/2010 5:59 PM
Homology modeling Dinesh Gupta ICGEB, New Delhi Protein structure prediction Methods: Homology (comparative) modelling Threading Ab-initio Protein Homology modeling Homology modeling is an extrapolation
More informationLigand Scout Tutorials
Ligand Scout Tutorials Step : Creating a pharmacophore from a protein-ligand complex. Type ke6 in the upper right area of the screen and press the button Download *+. The protein will be downloaded and
More informationSchrodinger ebootcamp #3, Summer EXPLORING METHODS FOR CONFORMER SEARCHING Jas Bhachoo, Senior Applications Scientist
Schrodinger ebootcamp #3, Summer 2016 EXPLORING METHODS FOR CONFORMER SEARCHING Jas Bhachoo, Senior Applications Scientist Numerous applications Generating conformations MM Agenda http://www.schrodinger.com/macromodel
More informationSupplementary Methods
Supplementary Methods MMPBSA Free energy calculation Molecular Mechanics/Poisson Boltzmann Surface Area (MM/PBSA) has been widely used to calculate binding free energy for protein-ligand systems (1-7).
More informationUltra High Throughput Screening using THINK on the Internet
Ultra High Throughput Screening using THINK on the Internet Keith Davies Central Chemistry Laboratory, Oxford University Cathy Davies Treweren Consultants, UK Blue Sky Objectives Reduce Development Failures
More informationAlchemical free energy calculations in OpenMM
Alchemical free energy calculations in OpenMM Lee-Ping Wang Stanford Department of Chemistry OpenMM Workshop, Stanford University September 7, 2012 Special thanks to: John Chodera, Morgan Lawrenz Outline
More informationMachine-learning scoring functions for docking
Machine-learning scoring functions for docking Dr Pedro J Ballester MRC Methodology Research Fellow EMBL-EBI, Cambridge, United Kingdom EBI is an Outstation of the European Molecular Biology Laboratory.
More informationAn introduction to Molecular Dynamics. EMBO, June 2016
An introduction to Molecular Dynamics EMBO, June 2016 What is MD? everything that living things do can be understood in terms of the jiggling and wiggling of atoms. The Feynman Lectures in Physics vol.
More informationPhysical Chemistry Final Take Home Fall 2003
Physical Chemistry Final Take Home Fall 2003 Do one of the following questions. These projects are worth 30 points (i.e. equivalent to about two problems on the final). Each of the computational problems
More informationComputational chemical biology to address non-traditional drug targets. John Karanicolas
Computational chemical biology to address non-traditional drug targets John Karanicolas Our computational toolbox Structure-based approaches Ligand-based approaches Detailed MD simulations 2D fingerprints
More informationBioengineering & Bioinformatics Summer Institute, Dept. Computational Biology, University of Pittsburgh, PGH, PA
Pharmacophore Model Development for the Identification of Novel Acetylcholinesterase Inhibitors Edwin Kamau Dept Chem & Biochem Kennesa State Uni ersit Kennesa GA 30144 Dept. Chem. & Biochem. Kennesaw
More informationBiologically Relevant Molecular Comparisons. Mark Mackey
Biologically Relevant Molecular Comparisons Mark Mackey Agenda > Cresset Technology > Cresset Products > FieldStere > FieldScreen > FieldAlign > FieldTemplater > Cresset and Knime About Cresset > Specialist
More informationComputational Chemistry in Drug Design. Xavier Fradera Barcelona, 17/4/2007
Computational Chemistry in Drug Design Xavier Fradera Barcelona, 17/4/2007 verview Introduction and background Drug Design Cycle Computational methods Chemoinformatics Ligand Based Methods Structure Based
More informationFlexibility and Constraints in GOLD
Flexibility and Constraints in GOLD Version 2.1 August 2018 GOLD v5.6.3 Table of Contents Purpose of Docking... 3 GOLD s Evolutionary Algorithm... 4 GOLD and Hermes... 4 Handling Flexibility and Constraints
More informationBuild_model v User Guide
Build_model v.2.0.1 User Guide MolTech Build_model User Guide 2008-2011 Molecular Technologies Ltd. www.moltech.ru Please send your comments and suggestions to contact@moltech.ru. Table of Contents Input
More informationVirtual Screening: How Are We Doing?
Virtual Screening: How Are We Doing? Mark E. Snow, James Dunbar, Lakshmi Narasimhan, Jack A. Bikker, Dan Ortwine, Christopher Whitehead, Yiannis Kaznessis, Dave Moreland, Christine Humblet Pfizer Global
More informationSTRUCTURAL BIOINFORMATICS II. Spring 2018
STRUCTURAL BIOINFORMATICS II Spring 2018 Syllabus Course Number - Classification: Chemistry 5412 Class Schedule: Monday 5:30-7:50 PM, SERC Room 456 (4 th floor) Instructors: Ronald Levy, SERC 718 (ronlevy@temple.edu)
More informationProgress of Compound Library Design Using In-silico Approach for Collaborative Drug Discovery
21 th /June/2018@CUGM Progress of Compound Library Design Using In-silico Approach for Collaborative Drug Discovery Kaz Ikeda, Ph.D. Keio University Self Introduction Keio University, Tokyo, Japan (Established
More informationTable 1. Kinetic data obtained from SPR analysis of domain 11 mutants interacting with IGF-II. Kinetic parameters K D 1.
Kinetics and Thermodynamics of the Insulin-like Growth Factor II (IGF-II) Interaction with IGF-II/Mannose 6-phosphate Receptor and the function of CD and AB Loop Solvent-exposed Residues. Research Team:
More informationMolecular Modeling Lecture 7. Homology modeling insertions/deletions manual realignment
Molecular Modeling 2018-- Lecture 7 Homology modeling insertions/deletions manual realignment Homology modeling also called comparative modeling Sequences that have similar sequence have similar structure.
More informationContents 1 Open-Source Tools, Techniques, and Data in Chemoinformatics
Contents 1 Open-Source Tools, Techniques, and Data in Chemoinformatics... 1 1.1 Chemoinformatics... 2 1.1.1 Open-Source Tools... 2 1.1.2 Introduction to Programming Languages... 3 1.2 Chemical Structure
More informationIntroduction. OntoChem
Introduction ntochem Providing drug discovery knowledge & small molecules... Supporting the task of medicinal chemistry Allows selecting best possible small molecule starting point From target to leads
More informationMURCIA: Fast parallel solvent accessible surface area calculation on GPUs and application to drug discovery and molecular visualization
MURCIA: Fast parallel solvent accessible surface area calculation on GPUs and application to drug discovery and molecular visualization Eduardo J. Cepas Quiñonero Horacio Pérez-Sánchez Wolfgang Wenzel
More informationDevelopment of Pharmacophore Model for Indeno[1,2-b]indoles as Human Protein Kinase CK2 Inhibitors and Database Mining
Development of Pharmacophore Model for Indeno[1,2-b]indoles as Human Protein Kinase CK2 Inhibitors and Database Mining Samer Haidar 1, Zouhair Bouaziz 2, Christelle Marminon 2, Tiomo Laitinen 3, Anti Poso
More informationStructural biology and drug design: An overview
Structural biology and drug design: An overview livier Taboureau Assitant professor Chemoinformatics group-cbs-dtu otab@cbs.dtu.dk Drug discovery Drug and drug design A drug is a key molecule involved
More informationMolecular modeling with InsightII
Molecular modeling with InsightII Yuk Sham Computational Biology/Biochemistry Consultant Phone: (612) 624 7427 (Walter Library) Phone: (612) 624 0783 (VWL) Email: shamy@msi.umn.edu How to run InsightII
More informationIntroduction to Structure Preparation and Visualization
Introduction to Structure Preparation and Visualization Created with: Release 2018-4 Prerequisites: Release 2018-2 or higher Access to the internet Categories: Molecular Visualization, Structure-Based
More informationPortal. User Guide Version 1.0. Contributors
Portal www.dockthor.lncc.br User Guide Version 1.0 Contributors Diogo A. Marinho, Isabella A. Guedes, Eduardo Krempser, Camila S. de Magalhães, Hélio J. C. Barbosa and Laurent E. Dardenne www.gmmsb.lncc.br
More informationChemogenomic: Approaches to Rational Drug Design. Jonas Skjødt Møller
Chemogenomic: Approaches to Rational Drug Design Jonas Skjødt Møller Chemogenomic Chemistry Biology Chemical biology Medical chemistry Chemical genetics Chemoinformatics Bioinformatics Chemoproteomics
More informationRetrieving hits through in silico screening and expert assessment M. N. Drwal a,b and R. Griffith a
Retrieving hits through in silico screening and expert assessment M.. Drwal a,b and R. Griffith a a: School of Medical Sciences/Pharmacology, USW, Sydney, Australia b: Charité Berlin, Germany Abstract:
More informationBuilding 3D models of proteins
Building 3D models of proteins Why make a structural model for your protein? The structure can provide clues to the function through structural similarity with other proteins With a structure it is easier
More informationAnalyzing Molecular Conformations Using the Cambridge Structural Database. Jason Cole Cambridge Crystallographic Data Centre
Analyzing Molecular Conformations Using the Cambridge Structural Database Jason Cole Cambridge Crystallographic Data Centre 1 The Cambridge Structural Database (CSD) 905,284* USOPEZ a natural product intermediate,
More informationStructure to Function. Molecular Bioinformatics, X3, 2006
Structure to Function Molecular Bioinformatics, X3, 2006 Structural GeNOMICS Structural Genomics project aims at determination of 3D structures of all proteins: - organize known proteins into families
More informationStructure-Based Drug Discovery An Overview
Structure-Based Drug Discovery An Overview Edited by Roderick E. Hubbard University of York, Heslington, York, UK and Vernalis (R&D) Ltd, Abington, Cambridge, UK RSC Publishing Contents Chapter 1 3D Structure
More informationLife Science Webinar Series
Life Science Webinar Series Elegant protein- protein docking in Discovery Studio Francisco Hernandez-Guzman, Ph.D. November 20, 2007 Sr. Solutions Scientist fhernandez@accelrys.com Agenda In silico protein-protein
More informationBinding Response: A Descriptor for Selecting Ligand Binding Site on Protein Surfaces
J. Chem. Inf. Model. 2007, 47, 2303-2315 2303 Binding Response: A Descriptor for Selecting Ligand Binding Site on Protein Surfaces Shijun Zhong and Alexander D. MacKerell, Jr.* Computer-Aided Drug Design
More informationJoana Pereira Lamzin Group EMBL Hamburg, Germany. Small molecules How to identify and build them (with ARP/wARP)
Joana Pereira Lamzin Group EMBL Hamburg, Germany Small molecules How to identify and build them (with ARP/wARP) The task at hand To find ligand density and build it! Fitting a ligand We have: electron
More informationLecture 2 and 3: Review of forces (ctd.) and elementary statistical mechanics. Contributions to protein stability
Lecture 2 and 3: Review of forces (ctd.) and elementary statistical mechanics. Contributions to protein stability Part I. Review of forces Covalent bonds Non-covalent Interactions: Van der Waals Interactions
More informationL718Q mutant EGFR escapes covalent inhibition by stabilizing. a non-reactive conformation of the lung cancer drug. osimertinib
Electronic Supplementary Material (ESI) for Chemical Science. This journal is The Royal Society of Chemistry 2018 Electronic Supplementary Information (ESI) for L718Q mutant EGFR escapes covalent inhibition
More informationschematic diagram; EGF binding, dimerization, phosphorylation, Grb2 binding, etc.
Lecture 1: Noncovalent Biomolecular Interactions Bioengineering and Modeling of biological processes -e.g. tissue engineering, cancer, autoimmune disease Example: RTK signaling, e.g. EGFR Growth responses
More informationExamples of Protein Modeling. Protein Modeling. Primary Structure. Protein Structure Description. Protein Sequence Sources. Importing Sequences to MOE
Examples of Protein Modeling Protein Modeling Visualization Examination of an experimental structure to gain insight about a research question Dynamics To examine the dynamics of protein structures To
More informationScoring functions for of protein-ligand docking: New routes towards old goals
3nd Strasbourg Summer School on Chemoinformatics Strasbourg, June 25-29, 2012 Scoring functions for of protein-ligand docking: New routes towards old goals Christoph Sotriffer Institute of Pharmacy and
More informationVirtual screening in drug discovery
Virtual screening in drug discovery Pavel Polishchuk Institute of Molecular and Translational Medicine Palacky University pavlo.polishchuk@upol.cz Drug development workflow Vistoli G., et al., Drug Discovery
More informationCSD. Unlock value from crystal structure information in the CSD
CSD CSD-System Unlock value from crystal structure information in the CSD The Cambridge Structural Database (CSD) is the world s most comprehensive and up-todate knowledge base of crystal structure data,
More informationHow is molecular dynamics being used in life sciences? Davide Branduardi
How is molecular dynamics being used in life sciences? Davide Branduardi davide.branduardi@schrodinger.com Exploring molecular processes with MD Drug discovery and design Protein-protein interactions Protein-DNA
More informationFlexPepDock In a nutshell
FlexPepDock In a nutshell All Tutorial files are located in http://bit.ly/mxtakv FlexPepdock refinement Step 1 Step 3 - Refinement Step 4 - Selection of models Measure of fit FlexPepdock Ab-initio Step
More informationUsing Bayesian Statistics to Predict Water Affinity and Behavior in Protein Binding Sites. J. Andrew Surface
Using Bayesian Statistics to Predict Water Affinity and Behavior in Protein Binding Sites Introduction J. Andrew Surface Hampden-Sydney College / Virginia Commonwealth University In the past several decades
More informationA Deep Convolutional Neural Network for Bioactivity Prediction in Structure-based Drug Discovery
AtomNet A Deep Convolutional Neural Network for Bioactivity Prediction in Structure-based Drug Discovery Izhar Wallach, Michael Dzamba, Abraham Heifets Victor Storchan, Institute for Computational and
More informationTHE TANGO ALGORITHM: SECONDARY STRUCTURE PROPENSITIES, STATISTICAL MECHANICS APPROXIMATION
THE TANGO ALGORITHM: SECONDARY STRUCTURE PROPENSITIES, STATISTICAL MECHANICS APPROXIMATION AND CALIBRATION Calculation of turn and beta intrinsic propensities. A statistical analysis of a protein structure
More informationRanking of HIV-protease inhibitors using AutoDock
Ranking of HIV-protease inhibitors using AutoDock 1. Task Calculate possible binding modes and estimate the binding free energies for 1 3 inhibitors of HIV-protease. You will learn: Some of the theory
More informationAutodock tutorial VINA with UCSF Chimera
Autodock tutorial VINA with UCSF Chimera José R. Valverde CNB/CSIC jrvalverde@cnb.csic.es José R. Valverde, 2014 CC-BY-NC-SA Loading the receptor Open UCSF Chimera and then load the protein: File Open
More informationConformational Searching using MacroModel and ConfGen. John Shelley Schrödinger Fellow
Conformational Searching using MacroModel and ConfGen John Shelley Schrödinger Fellow Overview Types of conformational searching applications MacroModel s conformation generation procedure General features
More informationImproving Protein Function Prediction with Molecular Dynamics Simulations. Dariya Glazer Russ Altman
Improving Protein Function Prediction with Molecular Dynamics Simulations Dariya Glazer Russ Altman Motivation Sometimes the 3D structure doesn t score well for a known function. The experimental structure
More informationOpenDiscovery: Automated Docking of Ligands to Proteins and Molecular Simulation
OpenDiscovery: Automated Docking of Ligands to Proteins and Molecular Simulation Gareth Price Computational MiniProject OpenDiscovery Aims + Achievements Produce a high-throughput protocol to screen a
More informationWhat is Protein-Ligand Docking?
MOLECULAR DOCKING Definition: What is Protein-Ligand Docking? Computationally predict the structures of protein-ligand complexes from their conformations and orientations. The orientation that maximizes
More informationMechanistic insight into inhibition of two-component system signaling
Supporting Information Mechanistic insight into inhibition of two-component system signaling Samson Francis, a Kaelyn E. Wilke, a Douglas E. Brown a and Erin E. Carlson a,b* a Department of Chemistry,
More informationAtomistic Modeling of Small-Angle Scattering Data Using SASSIE-web
Course Introduction Atomistic Modeling of Small-Angle Scattering Data Using SASSIE-web September 21-23, 2016 Advanced Photon Source Argonne National Laboratory, Argonne, IL ccpsas.org Scatters & Simulators
More informationNext Generation Computational Chemistry Tools to Predict Toxicity of CWAs
Next Generation Computational Chemistry Tools to Predict Toxicity of CWAs William (Bill) Welsh welshwj@umdnj.edu Prospective Funding by DTRA/JSTO-CBD CBIS Conference 1 A State-wide, Regional and National
More informationImportance of Accurate Charges in Molecular Docking: Quantum Mechanical/Molecular Mechanical (QM/MM) Approach
Importance of Accurate Charges in Molecular Docking: Quantum Mechanical/Molecular Mechanical (QM/MM) Approach ART E. CHO, VICTOR GUALLAR,* BRUCE J. BERNE, RICHARD FRIESNER Center for Biomolecular Simulations,
More informationThe basics of structural biology. And Why we use synchrotron sources Sean McSweeney ESRF Structural Biology Group
The basics of structural biology And Why we use synchrotron sources Sean McSweeney ESRF Structural Biology Group The rise and rise of structural biology. 2 The aim of the game 3 What information does structure
More informationTopology based deep learning for biomolecular data
Topology based deep learning for biomolecular data Guowei Wei Departments of Mathematics Michigan State University http://www.math.msu.edu/~wei American Institute of Mathematics July 23-28, 2017 Grant
More informationThe Molecular Dynamics Method
The Molecular Dynamics Method Thermal motion of a lipid bilayer Water permeation through channels Selective sugar transport Potential Energy (hyper)surface What is Force? Energy U(x) F = d dx U(x) Conformation
More informationJCICS Major Research Areas
JCICS Major Research Areas Chemical Information Text Searching Structure and Substructure Searching Databases Patents George W.A. Milne C571 Lecture Fall 2002 1 JCICS Major Research Areas Chemical Computation
More informationMolecular Mechanics, Dynamics & Docking
Molecular Mechanics, Dynamics & Docking Lawrence Hunter, Ph.D. Director, Computational Bioscience Program University of Colorado School of Medicine Larry.Hunter@uchsc.edu http://compbio.uchsc.edu/hunter
More informationProtein structure prediction. CS/CME/BioE/Biophys/BMI 279 Oct. 10 and 12, 2017 Ron Dror
Protein structure prediction CS/CME/BioE/Biophys/BMI 279 Oct. 10 and 12, 2017 Ron Dror 1 Outline Why predict protein structure? Can we use (pure) physics-based methods? Knowledge-based methods Two major
More information5.1. Hardwares, Softwares and Web server used in Molecular modeling
5. EXPERIMENTAL The tools, techniques and procedures/methods used for carrying out research work reported in this thesis have been described as follows: 5.1. Hardwares, Softwares and Web server used in
More informationUsing Phase for Pharmacophore Modelling. 5th European Life Science Bootcamp March, 2017
Using Phase for Pharmacophore Modelling 5th European Life Science Bootcamp March, 2017 Phase: Our Pharmacohore generation tool Significant improvements to Phase methods in 2016 New highly interactive interface
More informationMolecular dynamics simulation. CS/CME/BioE/Biophys/BMI 279 Oct. 5 and 10, 2017 Ron Dror
Molecular dynamics simulation CS/CME/BioE/Biophys/BMI 279 Oct. 5 and 10, 2017 Ron Dror 1 Outline Molecular dynamics (MD): The basic idea Equations of motion Key properties of MD simulations Sample applications
More informationPractical QSAR and Library Design: Advanced tools for research teams
DS QSAR and Library Design Webinar Practical QSAR and Library Design: Advanced tools for research teams Reservationless-Plus Dial-In Number (US): (866) 519-8942 Reservationless-Plus International Dial-In
More informationDOCKING TUTORIAL. A. The docking Workflow
2 nd Strasbourg Summer School on Chemoinformatics VVF Obernai, France, 20-24 June 2010 E. Kellenberger DOCKING TUTORIAL A. The docking Workflow 1. Ligand preparation It consists in the standardization
More information