Browse Books

Reviewer: Dik Kettenis

According to the preface, the intended audience for this book is interdisciplinary: beginning graduate students in medical schools, and students in all scientific departments, including biology, chemistry, physics, mathematics, and computer science. As a textbook, this book was written with the intention of providing a framework for teachers, rather than a rigid guide, with material to be supplemented or substituted as appropriate for the audience. As a reference book, scientists who are interested in learning about biomolecular modeling may view the book as a broad introduction to this new field. Three parts of the book, though it is not formally structured that way. The first part, chapters 1 to 6, provides an overview of biomolecular structure. This part presents a historical perspective of biomolecular modeling, outlining current progress in experimental techniques, computational challenges, and the practical applications of this enterprise, and presenting a review of the basic elements of protein structure, and of basic and advanced elements of nucleic acids, such as the structure of DNA and RNA. Chapters 7 to 9, the second part of the book, present molecular mechanics and force field terms, and focuses on non-bonded energy terms such as cutoff techniques and Ewald and multipole schemes. The third part, chapters 10 to 14, is about dynamic simulations; it discusses optimization methods for multivariate functions, introduces Monte Carlo techniques, and describes the algorithmic challenges in biomolecular dynamics simulations. This part also presents numerical integration algorithms, and outlines the techniques used in chemical design, such as the design of new drugs. Four appendices are included, one of which contains 15 homework assignments. There are also two Web sites associated with the book. The first includes information available in the book, as well as the text of the homework assignments in PDF format and the data and programs necessary to complete them. On the second Web site, the outline of a course that the author taught in 1999 is presented. This site includes, among other things, instructions on how to use the required software. The author expects that readers have a good grounding in basic biochemistry, chemical physics, statistical and quantum mechanics, numerical methods, and programming techniques. Since readers will rarely have such a background, the author offers some tutorials on both biological and mathematical topics. I feel that the balance of these is not completely right. To give one example, conditional convergence of series is explained in a footnote, whereas I could not find a definition for fast Fourier transform (FFT). Furthermore, the author assumes that the reader already knows what a tensor is. The index is far from complete: important key words like fast Fourier transform, Legendre polynomial, Fourier series, Coulomb potential, and Particle-mesh Ewald method are not listed. There are many boxes in the text that explain topics in more detail, or that indicate the impact of the discipline in real life venues such as healthcare; these boxes make reading this book a pleasure. Another nice feature of the book is the way each chapter starts with a list of symbols and their definitions. The text has 1,006 references. The references are numbered, and referred to by number. The entries in the reference list, however, are not sorted in alphabetical order. For reading as a text, this is acceptable, however, for a scientist working in the field, this might be cumbersome. On the book’s Web site, there is a list of references that is sorted in alphabetical order. In addition to references to books and papers, there are many pointers to relevant Web sites. The author is aware of the limitations of the text, as the following citation from the preface indicates: “By construction, this book is very broad in scope and thus no subjects are covered in great depth. References to the literature are only representative. The material presented is necessary selective, unbalanced in parts, and reflects some of my areas of interest and expertise. This text should thus be viewed as an attempt to introduce the discipline of molecular modeling to students and to scientists from disparate fields, and should be taken together with other related texts, such as those listed in Appendix C, and the representative references cited.” This book is a goldmine of information about this rapidly developing subject. However, because of the many reference to outside sources, certain parts of the text can be rather dry. The book is therefore better suited as text for a scientist who is interested in learning about biomolecular modeling than as text for students. All in all, however, this book is a valuable contribution for newcomers to this fascinating discipline. The author has a clear writing style. The typography of the book is good, and the 147 full-color illustrations are impressive. Online Computing Reviews Service