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Computer-Aided Molecular Design: Theory and Applications PDF

517 Pages·1996·24.77 MB·English
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Computer-Aided Molecular Design: Theory and Applications This Page Intentionally Left Blank Computer-Aided Molecular Design: Theory and Applications Jean-Pierre Doucet Institut de Topologie et de Dynamique de Systems Universit~ de Paris 7-Denis Diderot 1 rue Guy de la Brosse 75005 Paris France Jacques Weber D6partemeut de Chimie Physique Universit~ de Gen~ve 30 quai Ernest-Ansermet 1211 Gen~ve 4 Suisse Academic Press Harcourt Brace & Company, Publishers London San Diego New York Boston Sydney Tokyo Toronto ACADEMIC PRESS LIMITED 24-28 Oval Road LONDON NW1 7DX U.S. Edition Published by ACADEMIC PRESS INC. San Diego, CA 92101 This book is printed on acid free paper Copyright (cid:14)9 1996 ACADEMIC PRESS LIMITED Second Printing 1997 All rights reserved No part of this book may be reproduced or transmitted in any form or by any means, electronic or mechanical including photocopying, recording, or any information storage and retrieval system without permission in writing from the publisher. A catalogue record for this book is available from the British Library ISBN 0-12-221285-1 Typeset by Phoenix Photosetting, Chatham, Kent UK Printed and bound in Great Britain by Hartnolls Limited, Bodmin, Cornwall Contents Preface vii Acknowledgements ix Introduction xvii 1 Computer graphics: an introduction 1 1.1 Display and input devices 2 1.2 Elementary graphics primitives 9 1.3 Geometrical transformations 17 2 Computer graphics: towards realistic images 23 2.1 Representation of 3D objects 24 2.2 Viewing, windowing and clipping 31 2.3 Segments 37 2.4 Hidden lines and surfaces removal 38 2.5 Rendering 49 3 Displaying molecular shapes 59 3.1 Representation of structural shapes 61 3.2 Representation of property shapes 70 3.3 Concluding remarks: symbolic pictorial primitives 78 4 Access to experimental geometrical parameters 81 4.1 Crystals and X-ray diffraction 82 4.2 Neutron scattering and miscellaneous techniques 89 4.3 NMR: a source of geometrical data in solution 92 4.4 The Cambridge Structural Database 103 4.5 The Brookhaven Protein Data Bank 118 4.6 Databases of calculated structures 120 5 Empirical force field methods and molecular mechanics 124 5.1 The force field 127 5.2 Steric energy and derived information: strain energy and heat of formation 139 5.3 Search for the preferred geometry and energy minimization 140 5.4 Molecular mechanics: scope, limitations and evolution 144 5.5 Some applications 151 5.6 Trends and prospects 165 6 Monte Carlo and molecular dynamics simulations 171 6.1 Monte Carlo simulations 172 6.2 Molecular dynamics simulations 183 Exploring the conformational space: distance geometry and model builders 197 7.1 Distance geometry 2O0 7.2 Exploring the conformational space 206 7.3 Model builders 220 vi CONTENTS 8 Molecular surfaces and volumes 239 8.1 Definition of molecular volumes 240 8.2 Analytical evaluations of surfaces or volumes 243 8.3 Numerical methods 247 8.4 Boolean operations and molecular comparisons 256 8.5 Towards quantitative relationships 257 8.6 Concluding remarks: roughness and fractal surfaces 261 Key features of quantum chemistry methods used in CAMD 266 9.1 The time-independent Schr6dinger equation 269 9.2 Hartree-Fock and Roothaan equations: AB initio methods 273 9.3 Semi-empirical methods 282 9.4 Density functional methods 293 10 Derivation and visualization of molecular properties 301 10.1 Molecular orbitals 301 10.2 Electron densities 308 10.3 Electrostatic properties 311 10.4 Reactivity indices 319 11 Molecular similarity 328 11.1 Geometrical comparisons: molecular superimposition 332 11.2 Common substructure searches 340 11.3 Similarity between structural shapes 352 12 Drug receptor interactions: receptor mapping and pharmacophore approach 363 12.1 The pharmacophore hypothesis 364 12.2 Active conformations of a drug: feasible binding modes of a ligand molecule at the receptor site 367 13 Modelling proteins 405 13.1 Structural analysis 408 13.2 Representation 411 13.3 Determination of geometrical data: 2D NMR in protein structural analysis 415 13.4 Computer building 426 13.5 Knowledge-based prediction: model building from homology 431 13.6 Evaluating similarity 447 Subject index 463 Author index 475 Colour plate section between pages 236 to 237 Preface The originality of this book is to train undergraduates, who have grown up during the computer revolution, in the core parts of those computer tools intended to help chemists, with graphics assistance, in handling molecular representations. The goal is complex, as there is an important synergy in the creative design of molecules or properties between the fundamental theories of chemistry and their computational extensions. This duality, felt constantly through the last thirty years, has led to immense progress thanks to major developments in both chemical informatics and computational chemistry. The authors, well known actors in this transformation of chemistry, have identified in a single book the foundations of the modelling and design successes in chemistry. Their aim is to teach some crucial components both in the computer field and in theoretical chemistry, often closely linked in CAMD. The two authors, who have participated in the deployment of CAMD, have identified and selected, with talent and efficiency, its fundamental elements. Their teaching is clear with alternate explanations and applications. The task was not simple, as these elements are shadowed by the progress of the information revolution and the rapid advances of molecular modelling. The synergy of these actions often obscures the identification of those basic components essential for an up to date course. Thus, Computer Aided Molecular Design (CAMD) is identified as a mature discipline. The theoretical and practical aspects of its potential and of its basic tenets are described. Applications are chosen to underline the power of various CAMD strategies. There are many reasons for such a course at the undergraduate level. Students are usually familiar with the information revolution, and they know that the rapid evolution of science and technology makes it imperative to acquire generalized training enabling them to deal with many changes in their active life. They are sensitive to the radical changes around them in communication fields, and they are aware that equivalent transformations and mutations are taking place in science and technology. These affect our vision of science but also modify our working methods both in our chosen field of activity and in the methods we use. A brief sample enumeration of such trends helps to justify special training such as CAMD. Let us cite, for instance: the dramatic improvement expected in data and information sharing; CAMD collaboration (online or offlinr between researchers and engineers separated by physical distance; the increase use of visual tools and methods for viewing, animating, interacting with CAMD mechanisms; the development of heuristic design through intelligent agents endowed with browsing capabilities. For chemists to take advantage of all this, it is essential to point out that viii PREFACE chemistry is based on numerous concepts conferring more or less precise 2D or 3D shapes on 'invisible' molecules. The imaginary world of chemistry is thus geometrical, shape oriented and thereby open to graphics. Molecular species lead to either property maps or volumes incorporating all information derived from the molecular paradigm. Graphics presentations are used to handle the conceptual nature of bonds, the conformational flexibility of entities and chemical transformations. This knowledge will be necessary for the future chemist if he is to make free use of modern tools. J. P. Doucet and J. Weber have woven together the powerful tools of classification and correlation that help conduct similarity searches. Here the basic blocks are those derived from fragmentation or topological procedures. They are used to build adequate working 'spaces of states' suited to correlation searches. Molecular similarity is presented in a drug design application to illustrate the complexity involved in the search of a 'lead' drug and the difficulties encountered in estimating the embedding of a drug on a biological receptor. The book maintains its homogeneity on structural design, but its authors successfully tackle CAMD tools and applications in bioinformatics. In short, this book presents an excellent package of complementary ideas and tools and should greatly help students to master their use of molecular software. Instead of blindly applying programs, their knowledge of CAMD will give them the freedom required in creative molecular design research. Finally, this work should be kept by them as a long term classical reference volume. Jacques-Emile Dubois Professor, ITODYS, University Paris 7. (President of CODATA} Acknowledgements The following have kindly granted permission to reprint the illustrations cited. Scheme on pp. 20-21 From W.M. Newman and R.F. Sproull Principles of Interactive Computer Graphics. 2e, 1979. McGraw-Hill Inc. Ed, Copyright 1979 McGraw-Hill, reproduced with permission of McGraw-Hill Inc. Figure 2.2 Reproduced from K. Kronlof and M. Tamminen The Visual Computer. 1:1985;24-36. Copyright Springer Verlag 1985. By permission of Springer Verlag Gmbh & Co. A Viewing Pipeline for Discrete Solid Modeling, p. 25. Figure 2.5 Adapted from W.M. Newman and R.F. Sproull Principles of Interactive Computer Graphics. 2e, 1979. McGraw-Hill Inc. Ed, Copyright 1979 McGraw-Hill, reproduced with permission of McGraw-Hill Inc. Figure 2.6 Adapted from W.M. Newman and R.F. Sproull Principles of Interactive Computer Graphics. 2e, 1979. McGraw-Hill Inc. Ed, Copyright 1979 McGraw-Hill, reproduced with permission of McGraw-Hill Inc. Figure 2.7 Adapted from W.M. Newman and R.F. Sproull Principles of Interactive Computer Graphics. 2e, 1979. McGraw-Hill Inc. Ed, Copyright 1979 McGraw-Hill, reproduced with permission of McGraw-Hill Inc. Figure 2.8 Adapted from W.M. Newman and R.F. Sproull Principles of Interactive Computer Graphics. 2e, 1979. McGraw-Hill Inc. Ed, Copyright 1979 McGraw-Hill, reproduced with permission of McGraw-Hill Inc. Figure 2.11 Reproduced from G. Wyvill and T.L. Kunii The Visual Computer. 1:1985;3-14. Copyright Springer Verlag 1985. By permission of Springer Verlag Gmbh & Co. A Functional Model for Constructive Solid Geometry, p. 3. Figure 2.22 Reproduced from D.F. Rogers Mathematical Elements for Computer Graphics. French Translation by J.J. Lecoeur, 1988. McGraw-Hill Inc. Ed, Copyright 1938 McGraw-Hill Inc. reproduced with permission of McGraw-Hill Inc. Figure 2.26 Adapted from W.M. Newman and R.F. Sproull Principles of Interactive Computer Graphics. 2e, 1979. McGraw-Hill Inc. Ed, Copyright 1979 McGraw-Hill, reproduced with permission of McGraw-Hill Inc. Figure 2.31 Reproduced from D.F. Rogers Mathematical Elements for Computer Graphics. French Translation by J.J. Lecoeur, 1988. McGraw-Hill Inc. Ed, Copyright 1988 McGraw-Hill Inc. reproduced with permission of McGraw-Hill Inc. Figure 2.34 Adapted from W.M. Newman and R.F. Sproull Principles of Interactive Computer Graphics. 2e, 1979. McGraw-Hill Inc. Ed, Copyright 1979 McGraw-Hill, reproduced with permission of McGraw-Hill Inc. Figure 2.35 Adapted from W.M. Newman and R.F. Sproull Principles of Interactive Computer Graphics. 2e, 1979. McGraw-Hill Inc. Ed, Copyright 1979 McGraw-Hill, reproduced with permission of McGraw-Hill Inc. Figure 2.36 Adapted from W.M. Newman and R.F. Sproull Principles of Interactive Computer Graphics. 2e, 1979. McGraw-Hill Inc. Ed, Copyright 1979 McGraw-Hill, reproduced with permission of McGraw-Hill Inc. Figure 3.2 Reprinted with permission from G.M. Smith and P. Gund J. Chem. Inf. Comput. Sci. 18:1978;207-210. Copyright 1978 American Chemical Society, and Computer-Generated Space-Filling Molecular Models, p. 208. Figure 3.5 From L.H. Pearl J. Molecular Graphics. 6:1988;109-111, and Calculating CPK images on a UNIX workstation, p. 110. Figure 3.7 From D.S. Goodsell, I. Saira Mian and A.J. Olson J. Molecular Graphics. 7:1989;41-44, and Rendering Volumetric data in Molecular Systems, p. 43. Figure 3.9 From M. GwiUiam and N. Max J. Molecular Graphics. 7:1989;54-59, and Atoms with Shadows- an Area-based Algorithm for Cast Shadows on Space-filling Molecular Models, p. 56.

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The computer-aided design of novel molecular systems has undoubtedly reached the stage of a mature discipline offering a broad range of tools available to virtually any chemist. However, there are few books coveringmost of these techniques in a single volume and using a language which may generally
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