3D QSAR in Drug Design: Ligand-Protein Interactions and Molecular Similarity PDF
Preview 3D QSAR in Drug Design: Ligand-Protein Interactions and Molecular Similarity
3D QSAR in Drug Design Ligand-ProteinInteractionsand Molecular Similarity QSAR =Three-Dimensional Quantitative Structure Activity Relationships VOLUME 2 Thetitles published inthisseriesare listed attheendofthis volume. 3D QSAR in Drug Design Volume 2 Ligand-Protein Interactions and Molecular Similarity Editedby Hugo Kubinyi ZHF/G,A30, BASF AG, D-67056 Ludwigshafen, Germany Gerd Folkers ETH-Zürich, Department Pharmazie, Winterthurer Strasse 190,CH-8057 Zürich, Switzerland Yvonne C. Martin AbbottLaboratories,PharmaceuticalProductsDivision, 100AbbottParkRd., AbbottPark,IL60064-3500,USA KLUWER ACADEMIC PUBLISHERS New York/Boston/Dordrecht / London / Moscow eBookISBN: 0-306-46857-3 Print ISBN: 0-792-34790-0 ©2002 Kluwer Academic Publishers New York, Boston, Dordrecht, London, Moscow Print ©1998 Kluwer AcademicPublishers London All rights reserved No part of this eBook may be reproduced or transmitted in any form or by any means, electronic, mechanical, recording, or otherwise, without written consent from the Publisher Created in the United States of America Visit Kluwer Online at: http://kluweronline.com and Kluwer's eBookstore at: http://ebooks.kluweronline.com Contents Preface vii Part I. Ligand–Protein Interactions Progress in Force-Field Calculations of Molecular Interaction Fields and 3 Intermolecular Interactions Tommy Liljefors Comparative Binding Energy Analysis 19 Rebecca C. Wade, Angel R. Ortiz and Federico Gigo Receptor-Based Prediction ofBinding Affinities 35 Tudor I. OpreaandGirlandR. Marshall A Priori Prediction ofLigand Affinity by Energy Minimization 63 M. KatharineHolloway Rapid Estimation ofRelative Binding Affinities ofEnzyme Inhibitors 85 M. Rami Reddy,Velarkad N. Viswanadhan andM. D. Erion Binding Affinities and Non-Bonded Interaction Energies 99 RonaldM.A. Knegtel andPeter D.J. Grootenhuis Molecular Mechanics Calculations on Protein-Ligand Complexes 115 IreneT. WeberandRobertW.Harrison PartII. QuantumMechanicalModelsandMolecularDynamics Simulations Some Biological Applications of Semiempirical MO Theory 131 BerndBeckandTimothy Clark Density-Functional Theory and Molecular Dynamics: A New Perspective for 161 Simulations of Biological Systems WandaAndreoni Density-functional Theory Investigations of Enzyme-substrate Interactions 169 Paolo CarloniandFrankAlber V Contents Molecular Dynamics Simulations: A Tool for Drug Design 181 DidierRognan Part III. Pharmacophore Modelling and Molecular Similarity Bioisosterism and MolecularDiversity 213 Robert D. Clark, Allan M. Ferguson and Richard D. Cramer Similarity and Dissimilarity: A Medicinal Chemist’s View 225 Hugo Kubinyi Pharmacophore Modelling: Methods, Experimental Verification and 253 Applications Arup K. Ghose and John J. Wendoloski The Use of Self-organizing Neural Networks in Drug Design 273 Soheila Anzali, Johann Gasteiger, Ulrike Holzgrabe, Jaroslaw Polanski, Jens Sadowski, Andreas Teckentrup and Markus Wugener Calculation of Structural Similarity by the Alignment of Molecular 301 Electrostatic Potentials David A. Thorner, David J. Wild, Peter Willett and P. Matthew Wright Explicit Calculation of3D Molecular Similarity 321 Andrew C. Good and W. Graham Richards Novel Software Tools for Chemical Diversity 339 Robert S. Pearlman and K.M. Smith New 3D Molecular Descriptors: The WHIM Theory and QSAR Applications 355 Roberto Todeschini and Paola Gramatica EVA: A Novel Theoretical Descriptor for QSARStudies 381 Trevor W. Heritage, Allan M. Ferguson, David B. Turner and Peter Willett AuthorIndex 399 SubjectIndex 401 vi Preface Significant progress has been made in the study of three-dimensional quantitative structure-activity relationships (3D QSAR) since the first publication by Richard Cramer in 1988 and the first volume in the series. 3D QSAR in Drug Design. Theory, Methods and Applications, published in 1993. The aim of that early book was to contribute to the understanding and the further application of CoMFA and related approaches and to facilitatethe appropriate use ofthese methods. Sincethen, hundreds ofpapershave appeared using the quickly developing techniques of both 3D QSAR and computational sciences to study a broad variety of biological problems. Again the editor(s) felt that the time had come to solicit reviews onpublished and new viewpoints to document the state of the art of 3D QSAR in its broadest definition and to provide visions of where new techniques will emerge or new applica- tions maybe found. The intention is notonly to highlightnew ideasbutalso to show the shortcomings, inaccuracies, and abuses of the methods. We hope this book will enable others to separate trivial from visionary approaches and me-too methodology from inno- vative techniques. These concerns guided our choice ofcontributors. To ourdelight, our call for papers elicited a great many manuscripts. These articles are collected in two boundvolumes, whichareeachpublished simultaneously intworelatedseries: theyform Volumes 2 and 3 ofthe 3D QSAR in Drug Design series which correspond to volumes 9-11 and 12-14, respectively, in Perspectives in Drug Discovery and Design. Indeed, the field is growing sorapidlythatwesolicited additional chapters even astheearlychapters werebeingfinished. Ultimatelyit will be the scientific communitywhowill decide ifthe collectivebiasesoftheeditorshavefurthereddevelopmentinthefield. The challenge of the quantitative prediction ofthe biological potency of a new mole- cule has not yet been met. However, in the four years since the publication ofthe first volume, there have been major advances in our understanding of ligand-receptor inter- action s, molecular similarity , pharmacophore s, and macromolecular structures. Although currently we are well prepared computationally to describe ligand-receptor interactions, the thorny problem lies in the complex physical chemistry of inter- molecular interactions. Structural biologists, whether experimental or theoretical in approach, continue to struggle with the field’s limited quantitative understanding of the enthalpic and entropic contributions to the overall free energy of binding of a ligand to a protein. With very few exceptions, we do not have experimental data on the thermo- dynamics of intermolecular interactions. The recent explosion of 3D protein structures helps us to refine our understanding of the geometry of ligand-protein complexes. However, as traditionally practiced, both crystallographic and NMR methods yield static pictures and relatively coarse results considering that an attraction between two non-bonded atoms may change to repulsion within a tenth of an Ångstrom. This is well below the typical accuracy of either method. Additionally, neither provides information about the energetics of the transfer of the ligand from solvent to the binding site. Preface With these challenges in mind, one aim ofthese volumes is to provide an overview of the current state of the quantitative description of ligand-receptorinteractions. To aid this understanding, quantum chemical methods, molecular dynamics simulations and the important aspects of molecular similarity of protein ligands are treated in detail in Volume 2. In the first part ‘Ligand-ProteinInteractions,’ seven chapters examine the problem from very different points of view. Rule- and group-contribution-based ap- proaches as well as force-field methods are included. The second part ‘Quantum Chemical Models and Molecular Dynamics Simulations’ highlights the recent ex- tensions of ab initio and semi-empirical quantum chemical methods to ligand-protein complexes. An additional chapter illustrates the advantages of molecular dynamics simulations for the understanding of such complexes. The third part ‘Pharmacophore Modelling and Molecular Similarity’ discusses bioisosterism. pharmacophores and molecular similarity, as related to both medicinal and computational chemistry. These chapters present new techniques, software tools and parameters for the quantitative description of molecular similarity. Volume 3 describes recent advances in Comparative Molecular Field Analysis and related methods. In the first part ‘3D QSAR Methodology. CoMFA and Related Approaches’, two overviews on the current state, scope and limitations, and recent progress in CoMFA and related techniques are given. The next four chapters describe improvements of the classical CoMFA approach as well as the CoMSIA method, an alternative to CoMFA. The last chapter of this part presents recent progress in Partial Least Squares (PLS) analysis. The part ‘Receptor Models and Other 3D QSAR Approaches’ describes 3D QSAR methods that are not directly related to CoMFA, i.e., Receptor Surface Models, Pseudo-receptor Modelling and Genetically Evolved Receptor Models. The last two chapters describe alignment-free 3D QSAR methods. The part ‘3D QSAR Applications’ completes Volume 3. It gives a comprehensive overview of recent applications but also of some problems in CoMFA studies. The first chapter should give a warning to all computational chemists. Its conclusion is that all investigations on the classic corticosteroid-binding globulin dataset suffer from serious errors in the chemical structures of several steroids, in the affinity data and/or in their results. Different authors made different mistakes and sometimes the structures used in the investigations are different from the published structures. Accordingly it is not poss- ible to make any exact comparison of the reported results! The next three chapters should be of great value to both 3D QSAR practitioners and to medicinal chemists, as they provide overviews on CoMFA applications in different fields, together with a detailed evaluation of many important CoMFA publications. Two chapters by Ki Kim and his comprehensive list of 1993-1997 CoMFA papers are a highly valuable source of information. These volumes are written not only for QSAR and modelling scientists. Because of their broad coverage of ligand binding, molecular similarity, and pharmacophore and receptor modelling, they will help synthetic chemists to design and optimize new leads, especially to a protein whose 3D structure is known. Medicinal chemists as well as agri- cultural chemists, toxicologists and environmental scientists will benefit from the de- scription of so many different approaches that are suited to correlating structure–activity Preface relationships in cases where the biological targets, or at least their 3D structures, are still unknown. This project would not have been realized without the ongoing enthusiasm of Mrs. Elizabeth Schram, founder and former owner of ESCOM Science Publishers, who initi- ated and strongly supported the idea of publishing further volumes on 3D QSAR in Drug Design. Special thanks belong also to Professor Robert Pearlman, University of Texas, Austin, Texas, who was involved in the first planning and gave additional support and input. Although during the preparation of the chapters Kluwer Academic Publishers acquired ESCOM, the project continued without any break or delay in the work. Thus, the Editors would also like to thank the new publisher, especially Ms. Maaike Oosting and Dr. John Martin, for their interest and open-mindedness, which helped to finish this project in time. Lastly, the Editors are grateful to all the authors. They made it possible for these volumes to be published only 16 months after the very first author was contacted. It is the authors’ diligence that has made these volumes as complete and timely as was Volume 1 onits publicationin 1993. Hugo Kubinyi, BASF AG, Ludwigshafen, Germany October 1997 Gerd Folkers,ETH Zürich, Switzerland Yvonne C. Martin, Abbott Laboratories, Abbott Park, IL, USA Part I Ligand–Protein Interactions
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