Part 1 book “Burger’s medicinal chemistry and drug discovery” has contents: History of quantitative structure- actmty relationships, recent trends in quantitatrve structure - actmty relationships, molecular, - advances in force field approaches,… and other contents. modeling in drug design, drug -target binding forces,… and other contents.
MEDICINAL CHEMISTRY AND DRUG DISCOVERY Sixth Edition Volume 1: Drug Discovery Edited by Donald J.Abraham Department of Medicinal Chemistry School of Pharmacy - r- m Vir iversity Burger's Medicinal Chemistry and Drug Discovery is available Online in full color at www.mrw.interscience.wiley.com/bmcdd A John Wiley and Sons, Inc., Publication BURGER MEMORIAL EDITION laboratories, brought to market [Parnate, which is the brand name for tranylcypromine, a monoamine oxidase (MAO) inhibitor] Dr Burger was a visiting Professor at the University of Hawaii and lectured throughout the world He founded the Journal of Medicinal Chemistry, Medicinal Chemistry Research, and published the first major reference work "Medicinal Chemistry" in two volumes in 1951 His last published work, a book, was written at age 90 (Understanding Medications: What the Label Doesn't Tell You, June 1995) Dr Burger received the Louis Pasteur Medal of the Pasteur Institute and the Amer, ican Chemical Society Smissman Award Dr Burger played the violin and loved classical music He was married for 65 years to Frances Page Burger, a genteel Virginia lady who always had a smile and an open house for the Professor's graduate students and postdoctoral fellows The Sixth Edition of Burger's Medicinal Chemistry and Drug Discovery is being designated as a Memorial Edition Professor Alfred Burger was born in Vienna, Austria on September 6, 1905 and died on December 30, 2000 Dr Burger received his Ph.D from the University of Vienna in 1928 and joined the Drug Addiction Laboratory in the Department of Chemistry at the University of Virginia in 1929 During his early years at UVA, he synthesized fragments of the morphine molecule in an attempt to find the analgesic pharmacophore He joined the UVA chemistry faculty in 1938 and served the department until his retirement in 1970 The chemistry department at UVA became the major academic training ground for medicinal chemists because of Professor Burger Dr Burger's research focused on analgesics, antidepressants, and chemotherapeutic agents He is one of the few academicians to have a drug, designed and synthesized in his vii PREFACE The Editors, Editorial Board Members, and John Wiley and Sons have worked for three and a half years to update the fifth edition of Burger's Medicinal Chemistry and Drug Discovery The sixth edition has several new and unique features For the first time, there will be an online version of this major reference work The online version will permit updating and easy access For the first time, all volumes are structured entirely according to content and published simultaneously Our intention was to provide a spectrum of fields that would provide new or experienced medicinal chemists, biologists, pharmacologists and molecular biologists entry to their subjects of interest as well as provide a current and global perspective of drug design, and drug development Our hope was to make this edition of Burger the most comprehensive and useful published to date To accomplish this goal, we expanded the content from 69 chapters (5 volumes) by approximately 50% (to over 100 chapters in volumes) We are greatly in debt to the authors and editorial board members participating in this revision of the major reference work in our field Several new subject areas have emerged since the fifth edition appeared Proteomics, genomics, bioinformatics, combinatorial chemistry, high-throughput screening, blood substitutes, allosteric effectors as potential drugs, COX inhibitors, the statins, and high-throughput pharmacology are only a few In addition to the new areas, we have filled in gaps in the fifth edition by including topics that were not covered In the sixth edition, we devote an entire subsection of Volume to cancer research; we have also reviewed the major published Medicinal Chemistry and Pharmacology texts to ensure that we did not omit any major therapeutic classes of drugs An editorial board was constituted for the first time to also review and suggest topics for inclusion Their help was greatly appreciated The newest innovation in this series will be the publication of an academic, "textbook-like" version titled, "Burger's Fundamentals of Medicinal Chemistry." The academic text is to be published about a year after this reference work appears It will also appear with soft cover Appropriate and key information will be extracted from the major reference There are numerous colleagues, friends, and associates to thank for their assistance First and foremost is Assistant Editor Dr John Andrako, Professor emeritus, Virginia Commonwealth University, School of Pharmacy John and I met almost every Tuesday for over three years to map out and execute the game plan for the sixth edition His contribution to the sixth edition cannot be understated Ms Susanne Steitz, Editorial Program Coordinator at Wiley, tirelessly and meticulously kept us on schedule Her contribution was also key in helping encourage authors to return manuscripts and revisions so we could publish the entire set at once I would also like to especially thank colleagues who attended the QSAR Gordon Conference in 1999 for very helpful suggestions, especially Roy Vaz, John Mason, Yvonne Martin, John Block, and Hugo Preface Kubinyi The editors are greatly indebted to Professor Peter Ruenitz for preparing a template chapter as a guide for all authors My secretary, Michelle Craighead, deserves special thanks for helping contact authors and reading the several thousand e-mails generated during the project I also thank the computer center at Virginia Commonwealth University for suspending rules on storage and e-mail so that we might safely store all the versions of the author's manuscri~tswhere t not they could be backed up daily ~ r $and least, I want to thank each and every author, some of whom tackled two chapters Their contributions have ~rovidedour-field with a sound foundation of information to build for the future We thank the many reviewers of manuscripts whose critiques have greatly enhanced the presentation and content for the sixth edition Special thanks to Professors Richard Glennon, William Soine, Richard Westkaemper, Umesh Desai, Glen Kellogg, Brad Windle, Lemont Kier, Malgorzata A Dukat, Martin Safo, Jason Rife, Kevin Reynolds, and John Andrako in our Department of Medicinal Chemistry, School of Pharmacy, Virginia Commonwealth University for suggestions and special assistance in reviewing manuscripts and text Graduate student Derek Cashman took able charge of our web site, http:l/www.burgersmedchem.com, another first for this reference work I would especially like to thank my dean, Victor Yanchick, and Virginia Commonwealth University for their support and encouragement Finally, I thank my wife Nancy who understood the magnitude of this project and provided insight on how to set up our home office as well as provide John Andrako and me lunchtime menus where we often dreamed of getting chapters completed in all areas we selected To everyone involved, many, many thanks DONALD J ABRAHAM Midlothian, Virginia Dr Alfred Burger Pholtograph of Professor Burger followed by his comments to the American Chemical Society 26th Medicinal Che,mistry Symposium on June 14, 1998 This was his last public appearance a t a meeting of medicinal cheimists As general chair of the 1998 ACS Medicinal Chemistry Symposium, the editor invited Professor Burger to open the meeting He was concerned that the young chemists would not know who he was and he might have an attack due to his battle with Parkinson's disease These fears never were realized and his com.ments to the more than five hundred attendees drew a sustained standing ovation The Professor was 93, and it was Mrs Burger's 91st birthday Opening Remarks ACS 26th Medicinal Chemistry Symposium June 14, 1998 Alfred Burger University of Virginia It has been 46 years since the third Medicinal Chemistry Symposium met at the University of Virginia in Charlottesville in 1952 Today, the Virginia Commonwealth University welcomes you and joins all of you in looking forward to an exciting program So many aspects of medicinal chemistry have changed in that half century that most of the new data to be presented this week would have been unexpected and unbelievable had they been mentioned in 1952 The upsurge in biochemical understandings of drug transport and drug action has made rational drug design a reality in many therapeutic areas and has made medicinal chemistry an independent science We have our own journal, the best in the world, whose articles comprise all the innovations of medicinal researches And if you look at the announcements of job opportunities in the pharmaceutical industry as they appear in Chemical & Engineering News, you will find in every issue more openings in medicinal chemistry than in other fields of chemistry Thus, we can feel the excitement of being part of this medicinal tidal wave, which has also been fed by the expansion of the needed research training provided by increasing numbers of universities The ultimate beneficiary of scientific advances in discovering new and better therapeutic agents and understanding their modes of action is the patient Physicians now can safely look forward to new methods of treatment of hitherto untreatable conditions To the medicinal scientist all this has increased the pride of belonging to a profession which can offer predictable intellectual rewards Our symposium will be an integral part of these developments xii CONTENTS HISTORY OF QUANTITATIVE STRUCTURE-ACTMTY RELATIONSHIPS, DRUG-TARGET BINDING FORCES: ADVANCES IN FORCE FIELD APPROACHES, 169 C D Selassie Chemistry Department Pomona College Claremont, California Peter A Kollman University of California School of Pharmacy Department of Pharmaceutical Chemistry San Francisco, California RECENT TRENDS IN QUANTITATrVE STRUCTUREACTMTY RELATIONSHIPS, 49 David A Case The Scripps Research Institute Department of Molecular Biology La Jolla, California A Tropsha University of North Carolina Laboratory for Molecular Modeling School of Pharmacy Chapel Hill, North Carolina COMBINATORIAL LIBRARY DESIGN, MOLECULAR SIMILARITY, AND DIVERSITY APPLICATIONS,187 MOLECULAR, MODELING IN DRUG DESIGN, 77 Jonathan S Mason Pfizer Global Research & Development Sandwich, United Kingdom Garland R Marshall Washington University Center for Computational Biology St Louis, Missouri Stephen D Pickett GlmoSmithKline Research Stevenage, United Kingdom Denise D Beusen Tripos, Inc St Louis, Missouri xiii Contents xiv VIRTUAL SCREENING, 243 Ingo Muegge Istvan Enyedy Bayer Research Center West Haven, Connecticut DOCKING AND SCORING FUNCTIONS/VIRTUAL SCREENING, 281 Christoph Sotriffer Gerhard Klebe University of Marburg Department of Pharmaceutical Chemistry Marburg, Germany Martin Stahl Hans-Joachim Bohm Discovery Technologies F Hoffmann-La Roche AG Basel, Switzerland BIOINFORMATICS: ITS ROLE IN DRUG DISCOVERY, 333 David J ParrySmith ChiBio Informatics Cambridge, United Kingdom CHEMICAL INFORMATION COMPUTING SYSTEMS IN DRUG DISCOVERY, 357 Douglas R Henry MDL Information Systems, Inc San Leandro, California 10 STRUCTURE-BASED DRUG DESIGN, 417 Larry W Hardy Aurigene Discovery Technologies Lexington, Massachusetts Martin K Safo Virginia Commonwealth University Richmond, Virginia Donald J Abraham Virginia Commonwealth University Richmond, Virginia 11 X-RAY CRYSTALLOGRAPHY IN DRUG DISCOVERY, 471 Douglas A Livingston Sean G Buchanan Kevin L D'Amico Michael V Milburn Thomas S Peat J Michael Sauder Structural GenomiX San Diego, California 12 NMR AND DRUG DISCOVERY, 507 David J Craik Richard J Clark Institute for Molecular Bioscience Australian Research Council Special Research Centre for Functional and Applied Genomics University of Queensland Brisbane, Australia 13 MASS SPECTROMETRY AND DRUG DISCOVERY, 583 Richard B van Breemen Department of Medicinal Chemistry and Pharmacognosy University of Illinois at Chicago Chicago, Illinois 14 ELECTRON CRYOMICROSCOPY OF BIOLOGICAL MACROMOLECULES, 611 Richard Henderson Medical Research Council Laboratory of Molecular Biology Cambridge, United Kingdom Contents Timothy S Baker Purdue University Department of Biological Sciences West Lafayette, Indiana 15 PEPTIDOMIMETICS FOR DRUG DESIGN, 633 M Angels Estiarte Daniel H Rich School of Pharmacy-Department of Chemistry University of Wisconsin-Madison Madison, Wisconsin 16 ANALOG DESIGN, 687 Joseph G Cannon The University of Iowa Iowa City, Iowa 17 APPROACHES TO THE RATIONAL DESIGN OF ENZYME INHIBITORS, 715 Michael J McLeish George L Kenyon Department of Medicinal Chemistry University of Michigan Ann Arbor, Michigan 18 CHIRALITY AND BIOLOGICAL ACTIVITY, 781 Alistair G Draffan Graham R Evans James A Henshilwood Celltech R&D Ltd Granta Park, Great Abington, Cambridge, United Kingdom 19 STRUCTURAL CONCEPTS IN THE PREDICTION OF THE TOXICITY OF THERAPEUTICAL AGENTS, 827 Herbert S Rosenkranz Department of Biomedical Sciences Florida Atlantic University Boca Raton, Florida 20 NATURAL PRODUCTS AS LEADS FOR NEW PHARMACEUTICALS, 847 A D Buss MerLion Pharmaceuticals Singapore Science Park, Singapore B Cox Medicinal Chemistry Respiratory Diseases Therapeutic Area Novartis Pharma Research Centre Horsham, United Kingdom R D Waigh Department of Pharmaceutical Sciences University of Strathclyde Glasgow, Scotland INDEX, 901 402 Chemical Information Computing Systems in Drug Discovery CONVERTER A rapid 2D to 3D conversion network, it must then be "decompressed" by program marketed by Accelrys It uses a disreversing the steps in the compression protance geometry approach to modeling, which cess A chemical information example of comcovers a wider range of conformations than pression is the conversion of an MDL molfile other methods to a Chime string, which uses ZIP file comCORINA A rapid 2D to 3D conversion propression methods gram developed by the Gasteiger research Data Mart Typically, a one-dimensional group at the University of Erlangen It can data warehouse-collecting data from multihandle macrocyclic ring structures, which can ple sources, be problematic in other conversion programs loading (ECTL) the data, and then indexing it Chemists can access CORINA online (http:/I for analytical (OLAF') and data mining purwww2.chemie.uni-erlangen.de/software/ poses, to be used by a given group or departcorinatfree-struct.htm1) ment In chemistry, an example would be an Daemon From Unix, a program that runs inventory database, with structures, location, continually as a background process to perand purchasing information from many venform routine functions on demand or on a dors for use by synthetic chemists Like a data schedule In the context of a chemical data warehouse, a data mart often has a central fact warehouse, an example would be a registratable with each record containing tion program that periodically checks input into other dimension tables that contain reladatabases to see if there are any new structional data about the items in the fact table tures that need to be added to the warehouse The fact and dimension tables are connected If there are, the daemon extracts the strucin an organization called the star schema, tures from the source databases, transforms which is a common design for data marts and and "cleans" them if needed, and registers warehouses Data marts are often subsets of a them to the warehouse data warehouse Data Cartridge A popular term for userData Mining The extraction of previously customizable search "operators" that can be unknown predictive relationships from a large added to the SQL language of a relational dadata set or database Data mining makes use tabase system An example in chemical inforof descriptive unsupervised methods such as mation is the addition of a substructure search association and cluster analysis, as well as we(SSS) operator to integrate this type of search dictive supervised methods such as decision directly into a relational database search One trees, curve fitting, neural networks, and advantage of this approach is that the search Bayesian methods Data mining was once con"strategy" that the relational search program sidered "data snooping" and had a poor repuapplies can take the complexity of the custom tation The need to analyze huge volumes of operator into account (the "cost") when perdata and the success of these methods in marforming the various search operations keting and finance have prompted scientists Data Compression The process of transand statisticians to reconsider its use forming a large amount of data Data Warehouse A large relational datainto a smaller dataset, in such a way that rebase that collects data from multiple diverse versing the transformation results in no loss sources and organizes it for optimal analytical of information in the original data A simple searching and reporting (OLAF').A data wareexample of a compression operation is to rehouse is a superset of a data mart, containing place a string of blanks with a count plus a archival and unchanging data that is impornumber that designates the character to be tant to several groups of researchers (i.e., mulrepeated Compression programs include pertidimensional) Data that enters a data waresonal computer programs like PKZIP and house does not usually come from original WINZIP, and Unix utilities like gunzip Comsources (i.e., chemists, instruments, or aspression methods are often used before storsays) It usually comes from intermediate data ing data in a database and before transmitting sources and undergoes cleaning and transfordata over a network When the data is remation (ECTL) before registry into the data trieved from the database or received on the warehouse Typically, data is not deleted from A Glossary of Terms a data warehouse, because historical trends are important For this reason, the warehouse grows very large over a long period of time, and thus its organization and indexing are crucial considerations An example in chemistry would be a single database containing structures, models, reactions, and data, all cross-referenced, and used by chemists, biologists, and modelers Typically, each group would extract their own data mart from the warehouse, containing information relevant to their needs Data warehouses are often used in decision support systems (DSS) to provide data on which to base important corporate decisions Database Tier In a three-tier programming architecture, the database tier resides on a server computer with access to the databases and the programs that manage them Deduplication When registering into a chemical structure database, the process of finding whether the given structure already exists in the database This usually involves performing an exact match search with the given structure as the search query Note that the definition of exact match may vary with the database, and it may even be configurable For example, some databases may consider tautomers to be acceptable as exact matches, whereas others may require a more strict definition Dimension Tables In a data mart or warehouse, the dimension tables store non-redundant information about the entries in the fact table of the database For the chemical example of an inventory data mart, the fact table stores the various source database identifiers of each unique structure in the data mart A dimension table of molecular formulas would store the formula for the unique structure in the mart, rather than storing the same formula for each occurrence of that structure in the various source databases Drill-Down Accessing data with increasing amounts of detail When examining and browsing the results of a database search, a chemist can often request further information about a structure, even though that information was not included in the search The process of accessing further information, often stored in a hierarchical manner, is termed drill-down The opposite process, which aggregates data, is termed roll-up ECTL The process of Extracting, Cleaning, Transforming, and Loading data into a data mart or data warehouse The data in a mart or warehouse should be standardized, complete, unambiguous, etc Raw data from files, instruments, databases, the Internet, etc., must usually be preprocessed before it is "clean" enough to be used in decision making Structures present special problems because tautomers, isomers, salts, etc may all represent valid forms The use of chemical processing languages, which can search for substructures and make modifications of specific atoms and bonds, enables the enforcement of chemical business rules during the ECTL process Encryption The conversion of data in a readable or decipherable code into another, possibly undecipherable, code The most common encryption involves sensitive pieces of data like passwords and identification numbers In chemistry, it is sometimes necessary to encrypt larger pieces of information, such as chemical structures and the results of assays-at least during passage of such information over networks or the Internet Decryption of the information typically requires one or more keys, which are often built into the encryption and decryption software Enumeration The systematic substitution of all the Rgroup members in a generic structure, giving each possible specific structure the generic structure represents If some of the Rgroups are not converted in the process, it is termedpartial enumeration Equivalence Class In the canonicalization of structures that have some element of symmetry, certain atoms that are topologically equivalent may yield the same canonical number These atoms are considered to be in the same equivalence class The concept of equivalence class is used, for example, in the Daylight Chemical Information Systems handling of reactions, to examine equivalent atoms when mapping reactant and product atoms Exact Match Search One type of structure searching in which a query molecule is searched for in a database of structures To exactly match the query, the target structure must be topologically identical and not be a substructure or superstructure of the query 404 Chenmica1 Information Computing Systems in Drug Discovery Extended Stereochemistry A type of tetra- Filter A query or set of criteria designed to hedral or higher level stereochemistry that appears, for example, in allenes, where the stereochemical center is not a single atom but a system of atoms and bonds that can be conceptually collapsed to a single atom to yield a stereo center External Registry Number A unique "external" identifier assigned to a structure, reaction, 3D model, assay, etc The external registry number is usually unique across databases, and it can be used as a key to link data from one database or table to another Anv " given database may have its own "internal" identifiers that may not be unique across databases Fact Table A central table in a data warehouse whose rows each represent one unit of primary importance in the warehouse In a chemical warehouse, the rows of the fact table might correspond to unique structures in the database In a biology data warehouse, each row might correspond to a single experiment The fields in the fact table are mainly pointers to information stored in other tables, or they contain data that may be repeated in other tables but is stored in the fact table (i.e., denormalized) for rapid access The fact table connects to other "dimension" tables in the warehouse that contain specific information that is not duplicated Fastsearch Index Term used in MDL databases for a tree-structured index of all the structures in the database The nodes in the tree represent increasingly complex substructures or properties, where all the structures at or below a given node have in common The fastsearch index can be very large, but it makes possible very rapid substructure searching Field In database terminology a column of data in a table Fields are commonly selected in searches of the database, such as "SELECT MOLSTRUCTURE, MOLWEIGHT FROM MOLTABLE WHERE SSSWOLSTRUCTURE, 'query.mol')= 1AND MOLWEIGHT