Table Of Content3D 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
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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
