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22 of 22 found the following review helpful:
 A great book for begginers.May 17, 1999
By saras@servidor.unam.mx
This book covers many interesting topics in molecular simulation, both Monte Carlo and M.D. It focuses on understanding the main ideas rather than giving long codes. It's a good place to start, but it also covers some ideas not found in many other books. When I try to extend my molecular dynamics program I always check what Frenkel and Smit have to say about it.
33 of 36 found the following review helpful:
 A nice disappointmentAug 30, 2001
By Jose R. Valverde Carrillo
"jrvalverde"
The title of the book is overly ambitious and falls short on its promises. The book is a good introduction to Molecular Mechanics (MM), Molecular Dynamics (MD) and Monte Carlo (MC) methods, with detailed descriptions of the methods used and FORTRAN (pseudo)code, covering from the basics to some middle-level and some advanced algorithms.
But it does NOT cover all the fields of Molecular Modelling, just the three mentioned (MM, MD and MC), there's no coverage of quantum mechanics methods, nor QSAR or other technologies. And, while it described the algorithms, I can't think of it going all the way through up to building applications. For this, Rapaport's makes a better job, and for a general intro to Molecular Modelling, Grant & Richards' Computational Chemistry is more comprehensive (albeit at a more superficial level). Nor does it provide much detail on the methods used in modelling biological macromolecules, an increasing application field for the methods discussed in the book.
All in all, this book fails to satisfy its cover title, it won't introduce to the whole field (just the areas of MM, MD and MC) nor does it go up to application level. But it IS a REAL GOOD introduction to the subjects covered and their basic algorithms,
with sample code, detailed descriptions and plenty of references to specialized articles, texts and resources.
20 of 21 found the following review helpful:
Perfect for New Grad StudentsNov 24, 2002
By Owen Hehmeyer
This book is how I bootstrapped my way into being a molecular simulationist. Anyone who can program in some language can get started writing simple routines for the basic MD and MC simulations.I do Monte Carlo simulations at Princeton, and found this book to be the most helpful available for getting my research started. It is my most common reference, and is used extensively in writing background information for various research documents. However, after you have written your first few codes, you will pass the level of this book and need to move on. I use it less now than I did my first year. Every student in my group (Panagiotopoulos) has this book I think. And like me, they started with it, but moved on.
8 of 9 found the following review helpful:
Excellent text for beginners in simulationNov 19, 2004
By Kanishk Rastogi
"Freelenser"
Its an excellent book for those who are just beginners in MC & MD simulations. everything is very clearly explained with lot of examples and some related unsolved problems. the text explores this topic indetails with advanced chapters in later sections. Good for anybody int hsi field be it in materials science, physics or related fields.
3 of 4 found the following review helpful:
 Totally misses the mark, waste of timeJun 08, 2010
By Omega
While the book is a legitimate effort to codify the study of molecular mechanics, etc...I found it to be obtuse and wholly frustrating. I often write programs to solve problems in chemistry and biology, and the underlying tenets that serve me well are ignored in this book. The book has a huge discussion about what other people have done to write Monte Carlo algorithms, for example. But they fail to emphasize the algorithmic nature of the computer program, instead aiming to teach graduate students how to reproduce code that other people have already written. Monte Carlo: works on everything, but good for little if you don't already know the answer.
A good program makes the right assumptions about the problem, and this book fails to communicate this essential balance at the core of molecular modeling: treatment of complexity vs. exhaustiveness of sampling. There is a huge discussion of thermostats, etc. It is like trying to have a friendly debate with a friend who can't let go of the details to agree that the whole discussion is focused on the wrong topic. We write programs to solve problems algorithmically....the focus should be the algorithms, not the programs.
Unfortunately, I can't recommend a good alternative textbook. Rather, there is a wealth of information in journal articles and in the source code of several excellent open source projects. A reader/student would be well-served to identify those articles/projects that are personally most interesting, and study these rather than read this textbook.
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