Computational Chemistry: Reviews of Current Trends. Volume 5 Edited by Jerzy Leszczynski (Jackson State University). World Scientific: Singapore, New Jersey, London, Hong Kong. 2000. x + 326 pp. $68.00. 981-02-4371-5.
Computational Chemistry: Reviews of Current Trends. Volume 5 Edited by Jerzy Leszczynski (Jackson State University). World Scientific: Singapore, New Jersey, London, Hong Kong. 2000. x + 326 pp. $68.00. 981-02-4371-5.
复制标题
计算化学：当前趋势的评论。
DOI：
10.1021/ja015203h
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发表时间：
2001
影响因子：
15
通讯作者：
J. Stanton
中科院分区：
文献类型：
--
作者：
J. Stanton
Becker（特拉维夫大学）、Alexander D. MacKerell, Jr.（马里兰大学）、Benoıt Roux（康奈尔大学）和 Masakatsu Watanabe（Wavefunction, Inc.）。 Marcel Dekker：纽约和巴塞尔。 2001.xii+ 512 页，195.00 美元。国际标准书号：0-8247-0455-X。 1977 年，McCammon、Gelin 和 Karplus 发表了第一个蛋白质分子动力学模拟。这一事件距离 Rahman 发表第一个液体分子动力学模拟仅 13 年。对液体进行这种详细程度的分子模拟的能力有助于创建真实的液态物理学。在生物分子中，情况更为复杂。额外的复杂性源于对生物分子功能很重要的广泛时间尺度，以及生物分子内部运动的不同自由度的数量。标准统计力学分析在蛋白质分子动力学模拟中的应用虽然有用且重要，但仅提供了对有限范围的蛋白质现象的见解。在过去的几十年中，生物分子计算研究的适用范围已被一群工作者扩展，他们基本上创建了一个可能被称为计算物理生物化学的新领域。该领域的基础在于计算机科学（数值分析）、统计力学和物理化学。除了分子动力学之外，重要的发展还包括布朗动力学、智能蒙特卡罗、精确的静电计算、改进的原子力场、生物分子的隐式溶剂模型、分析实验数据的新工具、自动化分子建模软件以及这些技术从溶剂化环境中的蛋白质和核酸扩展到膜领域。所有这些发展，以互补的方式应用，将为计算物理生物化学的未来进步提供基础。计算生物化学和生物物理学的目的是提供这些理论和计算技术的权威介绍。每一章均由一位作者提供，他是计算物理生物化学中重要组成技术或理论体系的主要贡献者。显然，每个贡献者都被要求提供全面和平衡的背景，并且不要过度反思自己的贡献。结果是一本非凡的书。对于一本多人合着的书来说，风格非常一致。对于一本由有竞争力的人撰写的书来说，这本书即使不是完全平衡，也是非常平衡的。无论如何，对作者自己作品的任何强调都不会太过极端，以至于妨碍细心的读者获得平衡观点的能力。很明显，尽管本书的主题取得了快速进展，但本书的目的是在未来几年内发挥作用。通过选择该领域真正基础的主题以及将每个主题扎根于相关的统计力学（可以在应用领域中增长但不能从根本上改变）来增强其寿命。在我看来，这个目标将会实现。我当然希望它能在未来几年成为我办公桌上的有用参考。事实上，我不会把这本书借给我实验室的人，而是会为实验室公共区域购买第二本，以供其他人参考。通常，参考文献是 1999 年最新的。当然，几年后它们将变得明显不那么最新。幸运的是，如果人们有一个相当新的起点，现在互联网上有一些很好的工具可以使主题参考书目保持最新状态……
Becker (Tel Aviv University), Alexander D. MacKerell, Jr.(University of Maryland), Benoıt Roux (Cornell University), and Masakatsu Watanabe (Wavefunction, Inc.). Marcel Dekker: New York and Basel. 2001. xii+ 512 pp. $195.00. ISBN: 0-8247-0455-X. The first molecular dynamics simulation of a protein was published by McCammon, Gelin, and Karplus in 1977. This event followed by just 13 years the publication by Rahman of the first molecular dynamics simulation of a liquid. The ability to do molecular simulations at this level of detail on liquids was instrumental in creating a true physics of the liquid state. In biomolecules, the situation has been more complicated. The additional complexity has arisen from the wide range of time scales that are important in biomolecular function, combined with the number of different degrees of freedom for the internal motions of biomolecules. The application of standard statistical mechanical analysis to molecular dynamics simulations of proteins, although useful and important, provides insights into only a severely limited range of protein phenomena.In the last couple of decades, the domain of applicability of computational studies of biomolecules has been extended by a community of workers who have essentially created a new field that might be called computational physical biochemistry. The foundations of this field reside in computer science (numerical analysis), statistical mechanics, and physical chemistry. Important developments, in addition to molecular dynamics, include Brownian dynamics, smart Monte Carlo, precise electrostatics calculations, improved atomic force fields, implicit solvent models for biomolecules, new tools for analyzing experimental data, automated molecular modeling software, and extension of these techniques from proteins and nucleic acids in solvated environments to the domain of membranes. All of these developments, applied in complementary fashion, will provide the basis for future advances in computational physical biochemistry. The aim of Computational Biochemistry and Biophysics is to provide an authoritative presentation of these theories and computational techniques. Each chapter is provided by an author who has been a major contributor to an important component technique or body of theory in computational physical biochemistry. It is clear that each contributor was asked to provide a thorough and balanced background and not to unduly reflect on his or her own contribution. The result is a remarkable book. For a multiauthored book, the style is remarkably consistent. For a book by authors who are competitive people, the book is remarkably, if not completely, balanced. In any case, any emphasis there is on an author’s own work is not so extreme that it pre-empts a careful reader’s ability to achieve a balanced view. It is clear that this book is designed to be useful for years to come, despite the rapid progress in its subject. Its longevity is enhanced by a choice of topics that are truly fundamental to the field and by grounding each topic in the relevant statistical mechanics, which can grow in application domain but cannot fundamentally change. In my judgment, this goal will be achieved. I certainly expect it to be a useful reference on my desk for years to come. Indeed, I will not lend my copy of the book to people in my lab, but will instead purchase a second copy for the lab commons area for reference by others. The literature references are up-to-date to 1999, as a rule. Naturally, they will become significantly less up-to-date in a few years. Fortunately, there are now good tools on the Internet to keep topical bibliographies up-to-date if one has a reasonably recent starting point …