AN INTRODUCTION TO COMPUTATIONAL BIOCHEMISTRY AN INTRODUCTION TO COMPUTATIONAL BIOCHEMISTRY C. Stan Tsai, Ph.D. Department of Chemistry and Institute of Biochemistry Carleton University Ottawa, Ontario, Canada A JOHN WILEY & SONS, INC., PUBLICATION This book is printed on acid-free paper. - Copyright  2002 by Wiley-Liss, Inc., New York. All rights reserved. Published simultaneously in Canada. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, 222 Rosewood Drive, Danvers, MA 01923, (978) 750-8400, fax (978) 750-4744. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 605 Third Avenue, New York, NY 10158-0012, (212) 850-6011, fax (212) 850-6008, E-Mail: PERMREQWILEY.COM. For ordering and customer service information please call 1-800-CALL-WILEY. Library of Congress Cataloging-in-Publication Data: Tsai, C. Stan. An introduction to computational biochemistry / C. Stan Tsai. p. cm. Includes bibliographical references and index. ISBN 0-471-40120-X (pbk. : alk. paper) 1. Biochemistry Data processing. 2. Biochemistry Computer simulation. 3. Biochemistry Mathematics. I. Title. QP517.M3 T733 2002 572.0285 dc21 2001057366 Printed in the United States of America. 10987654321 a CONTENTS Preface . . . . . . . . . . . ix 1 INTRODUCTION 1 1.1. Biochemistry: Studies of Life at the Molecular Level . . . 1 1.2. Computer Science and Computational Sciences . 5 1.3. Computational Biochemistry: Application of Computer Technology to Biochemistry 6 References . . . . . 9 2 BIOCHEMICAL DATA: ANALYSIS AND MANAGEMENT 11 2.1. Statistical Analysis of Biochemical Data . . . . . . 11 2.2. Biochemical Data Analysis with Spreadsheet Application 20 2.3. Biochemical Data Management with Database Program 28 2.4. Workshops . 31 References . . . . . 40 3 BIOCHEMICAL EXPLORATION: INTERNET RESOURCES 41 3.1. Introduction to Internet . 41 3.2. Internet Resources of Biochemical Interest . . . . . 46 3.3. Database Retrieval 48 3.4. Workshops . 52 References . . . . . 52 4 MOLECULAR GRAPHICS: VISUALIZATION OF BIOMOLECULES 53 4.1. Introduction to Computer Graphics . . . . . . . . . 53 4.2. Representation of Molecular Structures . . . . . . . 56 4.3. Drawing and Display of Molecular Structures . . 60 4.4. Workshops . 69 References . . . . . 70 v 5 BIOCHEMICAL COMPOUNDS: STRUCTURE AND ANALYSIS 73 5.1. Survey of Biomolecules . 73 5.2. Characterization of Biomolecular Structures . . . 80 5.3. Fitting and Search of Biomolecular Data and Information 87 5.4. Workshops . 98 References . . . . . 103 6 DYNAMIC BIOCHEMISTRY: BIOMOLECULAR INTERACTIONS 107 6.1. Biomacromolecule—Ligand Interactions . . . . . . . 107 6.2. Receptor Biochemistry and Signal Transduction 111 6.3. Fitting of Binding Data and Search for Receptor Databases . . . 113 6.4. Workshops . 119 References . . . . . 121 7 DYNAMIC BIOCHEMISTRY: ENZYME KINETICS 123 7.1. Characterization of Enzymes . . . 123 7.2. Kinetics of Enzymatic Reactions 126 7.3. Search and Analysis of Enzyme Data . . . . . . . . . 133 7.4. Workshops . 140 References . . . . . 144 8 DYNAMIC BIOCHEMISTRY: METABOLIC SIMULATION 147 8.1. Introduction to Metabolism 147 8.2. Metabolic Control Analysis 152 8.3. Metabolic Databases and Simulation . . . . . . . . . 153 8.4. Workshops . 160 References . . . . . 162 9 GENOMICS: NUCLEOTIDE SEQUENCES AND RECOMBINANT DNA 165 9.1. Genome, DNA Sequence, and Transmission of Genetic Information 165 9.2. Recombinant DNA Technology . 169 9.3. Nucleotide Sequence Analysis . . 171 9.4. Workshops . 179 References . . . . . 181 vi CONTENTS 10 GENOMICS: GENE IDENTIFICATION 183 10.1. Genome Information and Features . . . . . . . . . 183 10.2. Approaches to Gene Identification . . . . . . . . . . 185 10.3. Gene Identification with Internet Resources . . . 188 10.4. Workshops 204 References . . . . . 207 11 PROTEOMICS: PROTEIN SEQUENCE ANALYSIS 209 11.1. Protein Sequence: Information and Features . . 209 11.2. Database Search and Sequence Alignment . . . . 213 11.3. Proteomic Analysis Using Internet Resources: Sequence and Alignment 221 11.4. Workshops 228 References . . . . . 230 12 PROTEOMICS: PREDICTION OF PROTEIN STRUCTURES 233 12.1. Prediction of Protein Secondary Structures from Sequences . . 233 12.2. Protein Folding Problems and Functional Sites 236 12.3. Proteomic Analysis Using Internet Resources: Structure and Function . . . . . . . . . . . . 243 12.4. Workshops 264 References . . . . . 266 13 PHYLOGENETIC ANALYSIS 269 13.1. Elements of Phylogeny . 269 13.2. Methods of Phylogenetic Analysis . . . . . . . . . . 271 13.3. Application of Sequence Analyses in Phylogenetic Inference . . 275 13.4. Workshops 280 References . . . . . 284 14 MOLECULAR MODELING: MOLECULAR MECHANICS 285 14.1. Introduction to Molecular Modeling . . . . . . . . 285 14.2. Energy Minimization, Dynamics Simulation, and Conformational Search . 287 14.3. Computational Application of Molecular Modeling Packages . 296 14.4. Workshops 311 References . . . . . 313 15 MOLECULAR MODELING: PROTEIN MODELING 315 15.1. Structure Similarity and Overlap 315 15.2. Structure Prediction and Molecular Docking . . 319 CONTENTS vii 15.3. Applications of Protein Modeling . . . . . . . . . . 322 15.4. Workshops 337 References . . . . . 340 APPENDIX 343 1. List of Software Programs 343 2. List of World Wide Web Servers . 345 3. Abbreviations 353 INDEX 357 viii CONTENTS PREFACE Since the arrival of information technology, biochemistry has evolved from an interdisciplinary role to becoming a core program for a new generation of interdis- ciplinary courses such as bioinformatics and computational biochemistry. A demand exists for an introductory text presenting a unified approach for the combined subjects that meets the need of undergraduate science and biomedical students. This textbook is the introductory courseware at an entry level to teach students biochemical principles as well as the skill of using application programs for acquisition, analysis, and management of biochemical data with microcomputers. The book is written for end users, not for programmers. The objective is to raise the students’ awareness of the applicability of microcomputers in biochemistry and to increase their interest in the subject matter. The target audiences are undergraduate chemistry, biochemistry, biomedical sciences, molecular biology, and biotechnology students or new graduate students of the above-mentioned fields. Every field of computational sciences including computational biochemistry is evolving at such a rate that any book can seem obsolete if it has to discuss the technology. For this reason, this text focuses on a conceptual and introductory description of computational biochemistry. The book is neither a collection of presentations of important computational software packages in biochemistry nor the exaltation of some specific programs described in more detail than others. The author has focused on the description of specific software programs that have been used in his classroom. This does not mean that these programs are superior to others. Rather, this text merely attempts to introduce the undergraduate students in biochemistry, molecular biology, biotechnology, or chemistry to the realm of computer methods in biochemical teaching and research. The methods are not alternatives to the current methodologies, but are complementary. This text is not intended as a technical handbook. In an area where the speed of change and growth is unusually high, a book in print cannot be either compre- hensive or entirely current. This book is conceived as a textbook for students who have taken biochemistry and are familiar with the general topics. However, the book aims to reinforce subject matter by first reviewing the fundamental concepts of biochemistry briefly. These are followed by overviews on computational approaches to solve biochemical problems of general and special topics. This book delves into practical solutions to biochemical problems with software programs and interactive bioinformatics found on the World Wide Web. After the introduction in Chapter 1, the concept of biochemical data analysis and management is described in Chapter 2. The interactions between biochemists and computers are ix the topics of Chapter 3 (Internet resources) and Chapter 4 (computer graphics). Computational applications in structural biochemistry are described in Chapter 5 (biochemical compounds) and then in Chapters 14 and 15 (molecular modeling). Dynamic biochemistry is treated in Chapter 6 (biomolecular interactions), Chapter 7 (enzyme kinetics), and Chapter 8 (metabolic simulation). Information biochemistry that overlaps bioinformatics and utilizes the Internet resources extensively is dis- cussed in Chapters 9 and 10 (genomics), Chapters 11 and 12 (proteomics), and Chapter 13 (phylogenetic analysis). I would like to thank all the authors who elucidate sequences and 3D structures of nucleic acids as well as proteins, and they kindly place such valuable information in the public domain. The contributions of all the authors who develop algorithms for free access on the Web sites and who provide highly useful software programs for free distribution are gratefully acknowledged. I thank them for granting me the permissions to reproduce their web pages, online and e-mail returns. I am grateful to Drs. Athel Cornish-Bowden (Leonora), Tom Hall (BioEdit), Petr Kuzmic (DynaFit), and Pedro Mendes (Gepasi) for the consents to use their software programs. The effort of all the developers and managers of the many outstanding Web sites are most appreciated. The development of this text would not have been possible without the contribution and generosity of these investigators, authors, and developers. I am thankful to Dr. D. R. Wiles for reading parts of this manuscript. It is my pleasure to state that the writing of this text has been a family effort. My wife, Alice, has been most instrumental in helping me complete this text by introducing and continuously coaching me on the wonderful world of microcomputers. My son, Willis, and my daughter, Ellie, have assisted me in various stages of this endeavor. The credit for the realization of this textbook goes to Luna Han, Editor, and Danielle Lacourciere, Associate Managing Editor, of John Wiley & Sons. This book is dedicated to Alice. C. Stan Tsai Ottawa, Ontario, Canada x PREFACE 1 INTRODUCTION The use of microcomputers will certainly become an integral part of the biochemistry curriculum. Computational biochemistry is the new interdisciplinary subject that applies computer technology to solve biochemical problems and to manage and analyze biochemical information. 1.1. BIOCHEMISTRY: STUDIES OF LIFE AT THE MOLECULAR LEVEL All the living organisms share many common attributes, such as the capability to extract energy from nutrients, the power to respond to changes in their environ- ments, and the ability to grow, to differentiate, and to reproduce. Biochemistry is the study of life at the molecular level (Garrett and Grisham, 1999; Mathews and van Holde, 1996; Voet and Voet, 1995; Stryer, 1995; Zubay, 1998). It investigates the phenomena of life by using physical and chemical methods dealing with (a) the structures of biological compounds (biomolecules), (b) biomolecular transformations and functions, (c) changes accompanying these transformations, (d) their control mechanisms, and (e) impacts arising from these activities. The distinct feature of biochemistry is that it uses the principles and language of one science, chemistry, to explain the other science, biology at the molecular level. Biochemistry can be divided into three principal areas: (1) Structural biochemistry focuses on the structural chemistry of the components of living matter and the relationship between chemical structure and biological function. (2) Dynamic bio- chemistry deals with the totality of chemical reactions known as metabolic processes that occur in living systems and their regulations. (3) Information biochemistry is 1 An Introduction to Computational Biochemistry. C. Stan Tsai Copyright ¶ 2002 by Wiley-Liss, Inc. ISBN: 0-471-40120-X [...]... procedure language such as FORTRAN and C enables a programmer to communicate with many different machines in the same language, and it is easier to comprehend than machine language The programmer prepares a procedure language program, and the computer compiles it into a sequence of machine language instructions To solve a problem, a computer must be given a clear set of instructions and the data to be operated... Different Environments Kluwer Academic, Boston, MA Zubay, G L (1998) Biochemistry, 4th edition W C Brown, Chicago An Introduction to Computational Biochemistry C Stan Tsai Copyright 2002 by Wiley-Liss, Inc ISBN: 0-4 7 1-4 0120-X 2 BIOCHEMICAL DATA: ANALYSIS AND MANAGEMENT This chapter is aimed at introducing the concepts of biostatistics and informatics Statistical analysis that evaluates the reliability... (Excel) and database (Access) software packages to analyze and organize biochemical data are described 2.1 STATISTICAL ANALYSIS OF BIOCHEMICAL DATA Many investigations in biochemistry are quantitative Thus, some objective methods are necessary to aid the investigators in presenting and analyzing research data (Fry, 1993) Statistics refers to the analysis and interpretation of data with a view toward... of substance 14 BIOCHEMICAL DATA: ANALYSIS AND MANAGEMENT that can be detected The specificity is the ability to detect only the test substance It is important to appreciate that specificity is often linked to sensitivity It is possible to reduce the sensitivity of a method with the result that interference effects become less significant and the method is more specific 2.1.2 Analysis of Variance, ANOVA... It has become uncommon for ANOVA with more than two factors to be analyzed on a computer, owing to considerations of time, ease, and accuracy It will presume that established computer programs will be used to perform the necessary mathematical manipulation of ANOVA 16 BIOCHEMICAL DATA: ANALYSIS AND MANAGEMENT TABLE 2.1 Single Factor ANOVA Calculations Source of Variation  Total [X 9 X] GH Group (i.e.,... variables The computational procedures required for most multiple regression and correlation analyses are difficult, and demand computer capability to perform the necessary operation A computer program for multiple regression and correlation analysis will typically include an analysis of variance (ANOVA) of the regression (Table 2.3) 20 BIOCHEMICAL DATA: ANALYSIS AND MANAGEMENT TABLE 2.3 ANOVA Calculations... Practical Guide for Biochemists and Molecular Biologists Cambridge University Press, New York Waterman, M S (1995) Introduction to Computational Biology: Maps, Sequences and Genomes Chapman and Hall, New York Watson, J D., Gilman, M., Witkowski, J., and Zoller, M (1992) Recombinant DNA, 2nd edition, W H Freeman, New York Wilson, S., and Diercksen, G H F (1997) Problem Solving in Computational Molecular Science:... eukaryotic and prokaryotic, differ in several respects but most fundamentally in that a eukaryotic cell has a nucleus and a 4 INTRODUCTION prokaryotic cell has no nucleus Two prokaryotic groups are the eubacteria and the archaebacteria (archaea) Archaea, which include thermoacidophiles (heat- and acid-tolerant bacteria), halophiles (salt-tolerant bacteria), and methanogens (bacteria that generate methane),... biomolecules enables biochemists not only to predict and refine three-dimensional structures but also to correlate structures with their properties and functions The field has matured from the management and analysis of sequence data, albeit still the most important areas, into other areas of biochemistry This text is an attempt to capture that spirit by introducing computational biochemistry from the biochemists’... the mean and standard deviation, type Mean: in B1 and S.D: in C1, select B2 and C2, and enter the formulas :average(range) and :stdev(range) The calculated Mean and Standard Deviation are placed in the cells B2 and C2, respectively 2.2.2 Statistical Functions Statistical functions are selected from two menus within Excel The first approach is through the Function Wizard Click the Function Wizard, f to . AN INTRODUCTION TO COMPUTATIONAL BIOCHEMISTRY AN INTRODUCTION TO COMPUTATIONAL BIOCHEMISTRY C. Stan Tsai, Ph.D. Department of Chemistry and Institute of Biochemistry Carleton University Ottawa,. 1-8 00-CALL-WILEY. Library of Congress Cataloging-in-Publication Data: Tsai, C. Stan. An introduction to computational biochemistry / C. Stan Tsai. p. cm. Includes bibliographical references and. goes to Luna Han, Editor, and Danielle Lacourciere, Associate Managing Editor, of John Wiley & Sons. This book is dedicated to Alice. C. Stan Tsai Ottawa, Ontario, Canada x PREFACE 1 INTRODUCTION The