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COMPUTATIONALDRUG DESIGN

A Guide for Computational andMedicinal Chemists

DAVID C. YOUNGComputer Sciences Corporation

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COMPUTATIONALDRUG DESIGN

COMPUTATIONALDRUG DESIGN

A Guide for Computational andMedicinal Chemists

DAVID C. YOUNGComputer Sciences Corporation

Copyright # 2009 by John Wiley & Sons, Inc. All rights reserved

Published by John Wiley & Sons, Inc., Hoboken, New JerseyPublished simultaneously in Canada

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Library of Congress Cataloging-in-Publication Data:

Young, David C., 1964–Computational drug design / David C. Young.

p.; cm.Includes bibliographical references and index.ISBN 978-0-470-12685-1 (cloth/CD)

1. Drugs—Design—Mathematical models. 2. Drugs—Design—Data processing.I. Title.[DNLM: 1. Computational Biology—methods. 2. Drug Design. 3. Biochemical Phenomena.

4. Chemistry, Pharmaceutical—methods. 5. Drug Delivery Systems.6. Models, Chemical. QV 744 Y69c 2009]RS420. Y68 20096150.190285--dc22 2008041828

Printed in the United States of America

10 9 8 7 6 5 4 3 2 1

http://www.copyright.comhttp://www.wiley.com/go/permissionhttp://www.wiley.com

This book is dedicated to my grandfathers, Harvey Turner and Ray Young.

Harvey Turner had the intelligence to work his way up from a draftsman toChief Engineer at Donaldsons. Then he had the wisdom to leave that high

pressure career behind and spend the next two decades teaching art.

Ray Young dropped out of high school to help make ends meet during the greatdepression. He never returned to school, but was the most widely read and

knowledgeable person I have every met.

CONTENTS

PREFACE xv

ACKNOWLEDGMENTS xix

ABOUT THE AUTHOR xxi

SYMBOLS USED IN THIS BOOK xxiii

BOOK ABSTRACT xxix

1 Introduction 1

1.1 A Difficult Problem, 11.2 An Expensive Problem, 21.3 Where Computational Techniques are Used, 3Bibliography, 5

PART I THE DRUG DESIGN PROCESS 7

2 Properties that Make a Molecule a Good Drug 9

2.1 Compound Testing, 102.1.1 Biochemical Assays, 112.1.2 Cell-Based Assays, 13

vii

2.1.3 Animal Testing, 142.1.4 Human Clinical Trials, 15

2.2 Molecular Structure, 162.2.1 Activity, 162.2.2 Bioavailability and Toxicity, 242.2.3 Drug Side Effects, 262.2.4 Multiple Drug Interactions, 26

2.3 Metrics for Drug-Likeness, 272.4 Exceptions to the Rules, 33Bibliography, 35

3 Target Identification 41

3.1 Primary Sequence and Metabolic Pathway, 413.2 Crystallography, 433.3 2D NMR, 443.4 Homology Models, 453.5 Protein Folding, 45Bibliography, 46

4 Target Characterization 47

4.1 Analysis of Target Mechanism, 474.1.1 Kinetics and Crystallography, 484.1.2 Automated Crevice Detection, 484.1.3 Transition Structures and Reaction

Coordinates, 494.1.4 Molecular Dynamics Simulations, 49

4.2 Where the Target is Expressed, 504.3 Pharmacophore Identification, 504.4 Choosing an Inhibitor Mechanism, 51Bibliography, 52

5 The Drug Design Process for a Known Protein Target 53

5.1 The Structure-Based Design Process, 535.2 Initial Hits, 555.3 Compound Refinement, 565.4 ADMET, 675.5 Drug Resistance, 67Bibliography, 68

viii CONTENTS

6 The Drug Design Process for an Unknown Target 71

6.1 The Ligand-Based Design Process, 716.2 Initial Hits, 726.3 Compound Refinement, 736.4 ADMET, 74Bibliography, 74

7 Drug Design for Other Targets 75

7.1 DNA Binding, 767.2 RNA as a Target, 787.3 Allosteric Sites, 797.4 Receptor Targets, 807.5 Steroids, 817.6 Targets inside Cells, 827.7 Targets within the Central Nervous System, 837.8 Irreversibly Binding Inhibitors, 847.9 Upregulating Target Activity, 84Bibliography, 85

8 Compound Library Design 87

8.1 Targeted Libraries versus Diverse Libraries, 878.2 From Fragments versus from Reactions, 898.3 Non-Enumerative Techniques, 908.4 Drug-Likeness and Synthetic Accessibility, 918.5 Analyzing Chemical Diversity and Spanning

known Chemistries, 938.6 Compound Selection Techniques, 96Bibliography, 99

PART II COMPUTATIONAL TOOLSAND TECHNIQUES 103

9 Homology Model Building 105

9.1 How much Similarity is Enough?, 1069.2 Steps for Building a Homology Model, 107

9.2.1 Step 1: Template Identification, 1089.2.2 Step 2: Alignment between the Unknown and

the Template, 108

CONTENTS ix

9.2.3 Step 3: Manual Adjustments to the Alignment, 1109.2.4 Step 4: Replace Template Side Chains with Model

Side Chains, 1119.2.5 Step 5: Adjust Model for Insertions and Deletions, 1119.2.6 Step 6: Optimization of the Model, 1129.2.7 Step 7: Model Validation, 1129.2.8 Step 8: If Errors are Found, Iterate Back to

Previous Steps, 1159.3 Reliability of Results, 116Bibliography, 117

10 Molecular Mechanics 119

10.1 A Really Brief Introduction to Molecular Mechanics, 11910.2 Force Fields for Drug Design, 121Bibliography, 123

11 Protein Folding 125

11.1 The Difficulty of the Problem, 12511.2 Algorithms, 12711.3 Reliability of Results, 12911.4 Conformational Analysis, 130Bibliography, 131

12 Docking 133

12.1 Introduction, 13312.2 Search Algorithms, 135

12.2.1 Searching the Entire Space, 13512.2.2 Grid Potentials versus Full Force Field, 13712.2.3 Flexible Active Sites, 13812.2.4 Ligands Covalently Bound to the Active Site, 13812.2.5 Hierarchical Docking Algorithms, 139

12.3 Scoring, 14112.3.1 Energy Expressions and Consensus Scoring, 14112.3.2 Binding Free Energies, 14112.3.3 Solvation, 14412.3.4 Ligands Covalently Bound to the Active Site, 14412.3.5 Metrics for Goodness of Fit, 144

12.4 Validation of Results, 14512.5 Comparison of Existing Search and Scoring Methods, 14612.6 Special Systems, 153

x CONTENTS

12.7 The Docking Process, 15512.7.1 Protein Preparation, 15612.7.2 Building the Ligand, 15612.7.3 Setting the Bounding Box, 15712.7.4 Docking Options, 15712.7.5 Running the Docking Calculation, 15812.7.6 Analysis of Results, 158

Bibliography, 159

13 Pharmacophore Models 161

13.1 Components of a Pharmacophore Model, 16313.2 Creating a Pharmacophore Model from

Active Compounds, 16413.3 Creating a Pharmacophore Model from the Active Site, 16613.4 Searching Compound Databases, 16713.5 Reliability of Results, 168Bibliography, 169

14 QSAR 171

14.1 Conventional QSAR versus 3D-QSAR, 17114.2 The QSAR Process, 17214.3 Descriptors, 17514.4 Automated QSAR Programs, 17614.5 QSAR versus Other Fitting Methods, 177Bibliography, 178

15 3D-QSAR 181

15.1 The 3D-QSAR Process, 18215.2 3D-QSAR Software Packages, 18415.3 Summary, 184Bibliography, 184

16 Quantum Mechanics in Drug Design 187

16.1 Quantum Mechanics Algorithms and Software, 18816.2 Modeling Systems with Metal Atoms, 19116.3 Increased Accuracy, 19116.4 Computing Reaction Paths, 19316.5 Computing Spectra, 193Bibliography, 194

CONTENTS xi

17 De novo and Other AI Techniques 197

17.1 De novo Building of Compounds, 19817.2 Nonquantitative Predictions, 20117.3 Quantitative Predictions, 203Bibliography, 205

18 Cheminformatics 207

18.1 Smiles, SLN, and Other Chemical StructureRepresentations, 208

18.2 Similarity and Substructure Searching, 20918.3 2D-to-3D Structure Generation, 21318.4 Clustering Algorithms, 21418.5 Screening Results Analysis, 21718.6 Database Systems, 222Bibliography, 223

19 ADMET 225

19.1 Oral Bioavailability, 22719.2 Drug Half-Life in the Bloodstream, 22919.3 Blood–Brain Barrier Permeability, 23119.4 Toxicity, 231Bibliography, 234

20 Multiobjective Optimization 237

Bibliography, 240

21 Automation of Tasks 241

21.1 Built-In Automation Capabilities, 24121.2 Automation Using External Utilities, 243Bibliography, 244

PART III RELATED TOPICS 245

22 Bioinformatics 247

Bibliography, 251

xii CONTENTS

23 Simulations at the Cellular and Organ Level 253

23.1 Cellular Simulations, 25323.2 Organ Simulations, 256Bibliography, 256

24 Synthesis Route Prediction 259

Bibliography, 262

25 Proteomics 263

Bibliography, 264

26 Prodrug Approaches 267

Bibliography, 270

27 Future Developments in Drug Design 273

27.1 Individual Patient Genome Sequencing, 27327.2 Analysis of the Entire Proteome, 27427.3 Drugs Customized for Ethnic Group or Individual

Patient, 27427.4 Genetic Manipulation, 27527.5 Cloning, 27627.6 Stem Cells, 27727.7 Longevity, 278Bibliography, 279

Appendix: About the CD 281

GLOSSARY 285

INDEX 301

CONTENTS xiii

PREFACE

A pharmaceutical company utilizing computational drug design is like anorganic chemist utilizing an NMR. It won’t solve all of your problems, butyou are much better off with it than without it.

The design of a new drug is an incredibly difficult and frustrating task. If itweren’t for the potential to earn equally incredible profits, the massive costsand aggravation over failed experiments would dissuade any reasonableperson from undertaking such a career. There is no one scientific techniqueused to design a new pharmaceutical product. It is instead a collaborativeprocess in which every available technique, and a few more invented on thespur of the moment, are utilized in order to achieve the desired results.

There are books that talk about drug design tools, algorithms, and math-ematical functions, and books that give some results showing that onecompound worked better than another for inhibiting a particular enzyme.However, these books spend surprisingly little time discussing the processthat the chemist goes through to actually design a new drug molecule. Thisbook is oriented around the way that computational techniques are utilizedin the drug design process.

Typical design processes for a number of drug development scenarios arepresented in the first part of the book. Multiple drug design processes arepresented, because the process itself changes depending upon whether thedrug target is a protein, DNA, a target within the central nervous system,etc. The design processes presented in this text do not reflect the process atany one specific pharmaceutical company, but are rather typical work flowsincorporating the elements that are used in one way or another at almost all

xv

pharmaceutical research campuses. The chapters on the drug design processare intended to show how each of the computational techniques are typicallyutilized. The comparison of different drug design processes illustrates wherespecific computational tools would and would not be appropriate. The textpresents many rules of thumb for choosing which tools are best utilizedunder certain situations.

The second part of the book has a series of chapters, each focusing on onecomputational technique. The chapters on each of the computational tech-niques are intended to give a solid understanding of the strengths and weak-nesses of the method. The underlying theory is discussed in concept, butwith little if any mathematical derivation. The processes for using the softwareand important issues that tend to arise are described. Where there are signi-ficant differences between available software packages, those issues are dis-cussed. However, the text is not specific to one manufacturer’s software.The relative merits of various methods are discussed, and, where possible,a table with quantitative comparisons is presented.

The third part of the book gives a few chapters discussing related topics.These are topics that drug design chemists should have some familiaritywith, but are not usually engaged in on a daily basis. Fields of research sonew that they are still being defined at the time this book was written arealso introduced here. Since any detailed information on such subjects wouldbe obsolete before the ink on this book is dry, some of these introductionsare kept intentionally broad and conceptual.

In a book that covers a broad subject area, it is always difficult to choosewhich references to include for each chapter. For this text, I have taken a two-fold approach. Key references are listed at the end of each chapter in an anno-tated bibliography. These references tend to be the next place that readersshould look for additional information on the topics discussed in the chapter.This is supplemented by a longer reference list included on the accompanyingCD. Readers wishing to delve very deeply into a particular subject will findthis larger list of references valuable.

This book is very industry-centric. The discussions of when and how toolsare used is based on a typical pharmaceutical industry drug design process. Assuch, I have intentionally avoided using cartoon-like illustrations of geometricfigures fitting together. The majority of the figures in this book are screen shotsof actual software packages that drug designers might use on a daily basis. Thisis the environment that a drug designer in the pharmaceutical industry mustlearn to work in.

For students interested in pursuing a career in the drug design field, this textis intended to give an ideal starting point for their studies. The text assumes asolid background in chemistry, a basic understanding of biochemistry, andonly minimal previous exposure to computational chemistry.

xvi PREFACE

Researchers already employed in the drug design field will be particularlyinterested in the tables comparing accuracies of docking methods. There isalso a fairly large table of bioisosteric substitutions. Providing an overviewof the whole field may turn out to be this book’s greatest contribution.

I wish you the best of success in pursuing your drug design activities.

DAVID C. YOUNG

PREFACE xvii

ACKNOWLEDGMENTS

There is a popular myth that books are written by solitary people typing awayin a lonely, deserted house. Indeed, there are many hours spent in front ofa keyboard. However, a book would never come into being without thehelp, support, and hard work of the author’s family, colleagues, co-workers,editors, graphic artists, and random other people saying, “Wow, that soundscomplicated.”

My family has been exceptionally tolerant of my ever-present laptop in thecar, during swimming lessons, in front of the TV, and at this very minute sit-ting off to the side as my wife Natalie displays her stained glass work at an artshow. My oldest son Gregory is a man of very few words, but the occasional“cool dad” speaks volumes. My daughter Ariel thinks it is neat that her dad is ascientist, but still won’t ask for help with her college freshman chemistryhomework. My youngest, Isaac, has little interest in anything that doesn’tinvolve video games or reptiles, but he seems to consider docking calculationswith solvation and entropy corrections to be dad’s form of video game.

My current job at the Alabama Supercomputer Center allows me the chanceto interact with faculty and students of many different disciplines throughoutthe state of Alabama. Randy Fulmer and the Alabama SupercomputerAuthority staff are always interested to hear about the scientific researchutilizing the supercomputers here. I’ve had bosses both good and bad, andDavid Ivey at CSC is definitely the best. Charles Wright and Derek Gottliebalways think of me as the software guy. They won’t forget the day theyasked about quantum chemistry software and got way more than theybargained for (the rest of the staff is afraid to ask).

xix

This is my second book with JohnWiley & Sons. I wouldn’t consider work-ing with any other publisher as long as Wiley will have me. Anita Lekhwaniand Rebecka Ramos have been wonderful to work with. There are manyothers at Wiley who contribute to creating a high quality book as they formatthe tables, integrate the artwork, and lovingly cover the manuscript in red ink.

Within the pharmaceutical field, I have had the pleasure of working withsome excellent people. Andy Peek, now at Integrated DNA TechnologiesInc., manages to be top notch at bioinformatics without succumbing to thehigh pressure of the drug design world. It has also been my privilege towork with Brad Poland, now at Pfizer, who is a wonderful crystallographerand co-worker. Working with Stephan Reiling, now at Aventis, and theentire SARNavigator development team was the most enjoyment I evergot from my job. Mitch Polley, who left Tripos to return home to Australia,has become a good friend as well as teaching me much about drug design.

I wanted the majority of the figures in the book to show commercial drugdesign software, which is the environment that drug designers must learn towork in. I greatly appreciate getting demo copies of software from ACD,Accelrys, Cambridge Crystallographic Data Centre, Chemical ComputingGroup, Conflex, COSMOlogic, SimBioSys, Simulations Plus, Tripos, andWavefunction for this purpose. Those same companies were invited to contrib-ute product literature, white papers, and demo software to the accompanyingCD.

DAVID C. YOUNG

xx ACKNOWLEDGMENTS

ABOUT THE AUTHOR

David Young’s career has taken him to the far corners of computationalchemistry. He was assistant director of drug design for a now nonexistentstartup company, eXegenics. David once taught introductory science andgraduate computer programming courses at Auburn University. He has alsowritten quite a bit of software for Tripos and others. Dr Young is currentlyemployed by Computer Sciences Corporation (CSC) as a chemistry softwareexpert, under contract to the Alabama Supercomputer Authority. Much earlierin his life, he ran the nuclear reactor aboard a ballistic missile submarine.

Dr Young received his PhD in chemistry from Michigan State University,under the direction of James Harrison. He also has degrees in computationalmathematics and business. His previous book, Computational Chemistry: APractical Guide for Applying Techniques to Real World Problems, has beenon the John Wiley & Sons bestseller list.

David currently lives in Huntsville, Alabama, where he provides softwaretechnical support to users of the Alabama Supercomputer Center.

xxi

SYMBOLS AND ACRONYMSUSED IN THIS BOOK

1D one-dimensional2D two-dimensional2.5D two-and-a-half-dimensional3D three-dimensional3D-QSAR three-dimensional quantitative structure–activity

relationshipÅ ångströmACD Advanced Chemistry DevelopmentACE angiotensin-converting enzymeAcrB multidrug efflux pump proteinADAM a docking method from the Institute of Medicinal Molecular

DesignADME absorption, distribution, metabolization, excretionADMET absorption, distribution, metabolization, excretion, and

toxicityAI artificial intelligenceAMBER Assisted Model Building and Energy RefinementAMOEBA a force field for proteinsAPI applications programming interfaceASP atomic solvation parameterAZT azidothymidineBBB blood–brain barrierBCI Barnard Chemical InformationCþþ a computer programming language

xxiii

CAESA Computer Assisted Estimation of Synthetic AccessibilityCAMEO Computer Assisted Mechanistic Evaluation of Organic

ReactionsCAOS computer-aided organic synthesisCASINO Computer-Aided Synthesis Inference for Organic

CompoundsCASP Critical Assessment of Techniques for Protein Structure

PredictionCATH Class, Architecture, Topology, HomologyCC coupled clusterCFD computational fluid dynamicsCFF Consistent Force FieldCFF93 Consistent Force Field 1993CFR Code of Federal RegulationsCHARMM Chemistry at Harvard Macromolecular MechanicsCHEAT Carbohydrate Hydroxyls represented by Extended

AtomsCHIRON Chiral SynthonCI configuration interactionCLIX a docking methodClogP method for predicting log PCMC Comprehensive Medicinal ChemistryCNS central nervous systemCoMFA Comparative Molecular Field AnalysisCoMSIA Comparative Molecular Shape Indices AnalysisCPE Chemical Potential EqualizationCPU central processing unitCSI Carbó Similarity IndexCVFF Consistent Valence Force FieldDEREK Deductive Estimation of Risk from Existing KnowledgeDFT density functional theoryDRF90 Direct Reaction Field 90DNA deoxyribonucleic acidEFF Electron Force FieldEROS Elaboration of Reactions for Organic SynthesisEVB Empirical Valence BondFDA Food and Drug AdministrationFEP free energy perturbationFEP-MD Free Energy Perturbation Molecular DynamicsFLOG Flexible Ligands Oriented on GridFRED Fast Rigid Exhaustive Docking

xxiv SYMBOLS AND ACRONYMS USED IN THIS BOOK

FSSP Fold Classification based on Structure–Structure Alignmentof Proteins/Families of Structurally Similar Proteins

GA genetic algorithmGB/SA Generalized Born Solvent AccessibleGLUT2 glucose transporter 2GPCR G-protein-coupled receptorGROMACS Groningen Machine for Chemical SimulationsHADDOCK High Ambiguity Driven Biomolecular DockingHASL Hypothetical Active Site LatticehERG human ether-a-go-go related geneHF Hartree–FockHOLOWin Holosynthon and WindowsHOMO highest occupied molecular orbitalhPEPT1 human intestinal small peptide carrierHQSAR hologram quantitative structure–activity relationshipHTVS high throughput virtual screeningHUPO Human Proteome OrganisationIC50 concentration at which activity is decreased by 50%ICM a docking program from MOLSOFTIGOR Interactive Generation of Organic ReactionsInChI IUPAC International Chemical IdentifierIRC intrinsic reaction coordinateKd dissociation constantKI inhibition constantKM Michaelis constantLBDD ligand-based drug designLD50 lethal dose for 50% of test subjectsLHASA Logical and Heuristics Applied to Synthetic AnalysisLIE Linear Interaction EnergyLIGIN a docking programlogD log P for ionization state at a specific pHlog P octanol–water partition coefficientlog S aqueous solubilitylog Sw intrinsic water solubilityLOO leave one outLR linear regressionLUDI a scoring method for docking and de novo designLUMO lowest unoccupied molecular orbitalMAb monoclonal antibodyMCASE Multi-Computer Automated Structure EvaluationMCS maximal common subgraph

SYMBOLS AND ACRONYMS USED IN THIS BOOK xxv

MD molecular dynamicsMEP Molecular Electrostatic PotentialMFA Molecular Field AnalysisMlogP a method for predicting log PMLP molecular lipophilic potentialMM molecular mechanicsMMþ a molecular mechanics force fieldMM1 a molecular mechanics force fieldMM2 a molecular mechanics force fieldMM2X a molecular mechanics force fieldMM3 a molecular mechanics force fieldMM4 a molecular mechanics force fieldMMFF Merck Molecular Force FieldMMX a molecular mechanics force fieldMOGA Multiobjective Genetic AlgorithmMOMEC Molecular MechanicsMPn Møller–Plesset Perturbation Theory (n ¼ 2, 3, . . .)MRSA methicillin-resistant Staphylococcus aureusMSA molecular shape analysisMVP Molecular Visualization and Processing EnvironmentNBTI Non-Boltzmann Thermodynamic IntegrationNLM nonlinear mapNMR nuclear magnetic resonanceNOE nuclear Overhauser effectOCSS Organic Chemistry Synthesis SimulatorOPLS Optimized Potential for Liquid SimulationsOPLS-2001 Optimized Potential for Liquid Simulations 2001OPLS-2005 Optimized Potential for Liquid Simulations 2005OPLS-AA Optimized Potential for Liquid Simulations All AtomOPLS-UA Optimized Potential for Liquid Simulations United AtomOSET Organic Synthesis Exploration ToolOWFEG One Window Free Energy GridPAMPA parallel artificial membrane permeability assayPBE Poisson–Boltzmann EquationPB/SA Poisson Boltzmann Solvent AccessiblePCA principal components analysisPFF Polarizable Force Fieldp (pi) electron orbitals or bonds perpendicular to the sigma bondpKa acidity equilibrium constantPLP piecewise linear potentialPLS partial least squares

xxvi SYMBOLS AND ACRONYMS USED IN THIS BOOK

PMF potential of mean forcePTMs posttranslational modificationsQCFF/PI Quantum Consistent Force Field for Pi electronsQM quantum mechanicsQMFF Quantum Mechanical Force FieldQM/MM a method combining quantum mechanics and molecular

mechanicsQPLD Quantum-Polarized Ligand DockingQSAR quantitative structure–activity relationshipQSM Quantum Similarity MeasureQXP a force field-based docking programReaxFF Reactive Force FieldRFF Reaction Force FieldRMSD root mean square deviationROCS Rapid Overlay of Chemical StructuresROSDAL Representation of Organic Structure Descriptions Arranged

LinearlyRNA ribonucleic acidSAR structure–activity relationshipSBDD structure-based drug designSCR structurally conserved regionSDS synthesis design systemsSCOP Structural Classification of ProteinsSECS Simulation and Evaluation of Chemical SynthesisSESAM Search for Starting MaterialsSIBFA Sum of Interactions Between Fragments Ab Initio ComputedSIE Solvated Interaction EnergySLN SYBYL Line NotationSMILES Simplified Molecular Input Line Entry SpecificationSMoG Small Molecule GrowthSP standard precisionSST Starting Material Selection StrategiesSUA structural unit analysisSVL Scientific Vector LanguageSYBYL the Greek word for oracle names a force field and software

from TriposSYNGEN Synthesis GenerationTPSA topological polar surface areaUBCFF Urey–Bradley Consistent Force FieldUFF Universal Force FieldVALIDATE a docking scoring function

SYMBOLS AND ACRONYMS USED IN THIS BOOK xxvii

VR variable regionWLN Wiswesser Line NotationWODCA Workbench for the Organization of Data for Chemical

ApplicationsXP extra precisionYETI a force field

xxviii SYMBOLS AND ACRONYMS USED IN THIS BOOK