Molecular Modeling and Simulation

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Summary: Gateway to molecular simulation
Review: "Molecular Modeling and Simulation: An Interdisciplinary Guide" is an excellent entry point to this subject. It is suitable as a reference for research on methods for molecular modeling, and as a textbook. For example, I have used it both as a reference for the development of new computational methods and as a textbook on an introductory graduate/advanced undergraduate seminar on computational biology. The introductory material is superb, introducing experimental and theoretical developments in understanding proteins (chapters 1-4) and nucleic acids (chapters 5,6). This material is particularly useful to computer scientists, mathematicians, or physicists who want to understand the problems addressed by biomolecular simulations, such as protein folding. The material is up to date, clearly presented, and beautifully illustrated with simulation results. In our course, students gave presentations on each one of these chapters, and all found the material accessible, and the references therein valuable to expand on details.

The most original material of this book is the discussion of computational methods for biomolecular simulation. After an excellent introduction in chapter 7, the book covers force fields (the description of the interacting forces in a biomolecule) in chapter 8, fast n-body solvers for electrostatic computation in chapter 9, optimization methods in chapter 10, and Monte Carlo (chapter 11) and molecular dynamics (chapters 12,13). The author has made notable contributions in these areas, and presents an advanced body of knowledge in a precise and consistent manner. An added benefit is that she frequently accompanies the mathematical descriptions by simulation results using the methods, and gives substantial references that allow the reader to assess the importance of the techniques discussed. As an instructor, I presented introductory material that is assumed in the book, to make it easier for the students to grasp the relevance of the more advanced material. There is also a final chapter on computer-assisted drug design, which is interesting, but somewhat unrelated to the rest of the material, since it focuses on techniques more statistical in nature.

Finally, the homework and sample syllabus provided as appendices in the book make the concepts accessible and relevant. In summary, this should be the book of choice for anyone desiring to go in depth into biomolecular modeling. Given the rapid advance of the field, I hope already for subsequent editions!

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Summary: Outstanding introduction
Review: ... not only to molecular modeling, but to some of the subtleties of DNA and protein behavior and geometry, too.

This book's focus is generally on interactions with large molecules, DNA and proteins, although it does discuss small molecules (drugs, a few dozen to a few hundred atoms) too. That means that it skips most of the quantum mechanical modeling of more advanced computational chemistry texts.

Nothing is lost, because Schlick covers her chosen topic (molecular modeling and dynamics) in such detail. She starts with a very clear discussion of the structure of large biomolecules, with emphasis on the features that need quantitative description for modeling. That covers protein structure at ever level. It also covers DNA/RNA structure in the best detail I've ever seen. The double-helix is the just the starting point. There are alternative helix forms, non-standard binding between nucleotides, and asymmetries caused by nucleotide composition. The next chapters describe the geometric model and, briefly, the forces acting between atoms.

The second half of the book gets down to the nuts and bolts of modeling. This includes numerical techniques, minimization, sampling and Monte Carlo techniques, and the start of dynamics. Schlick attacks some of the nasty points of the calculations, such as modeling of forces that act on very different time scales. As with the simpler material, the development is clear, descriptive, and free of pointless theorems. The meticulous reader should come away able to implement most or all of the techniques described. The level of presentation is consistent and approachable. I think freshman physics should be enough preparation for most students to get most of the value out of the discussion.

The book is written with clarity as a top priority. The glossary is in the front, making sure that the reader knows it's a first-class part of the text. After that, every chapter starts with a list of the mathematical symbols and variables used and a one-line description of each. These are small things, but they increase the book's readability immensely. The illustrations are generally informative enough. On the whole, though, they don't seem quite up to the level of the textual and mathematical presentations.

I needed a crash course in the mathematical techniques used for describing molecular structure and behavior. I should have read this book first - its clarity and thoroughness would have saved me a lot of time. After this one, I can now go back and reread the more complex texts with more hops of understanding. Do yourself a favor and read this one first.

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Summary: A truly insightful book, a perfect companion for research
Review: As a computational scientist with expertise in statistical mechanics and high performance computing, I was looking for a textbook that teaches biology for physicists. I found the book on Molecular Modeling and Simulation by Tamar Schlick to do just that and more. I find myself using this textbook on a regular basis to aid my research in computational biology. Moreover, I find the information and litrature this book offers to be complete, and the language very exciting to read. I definitely recommend this book to any one doing computational science from undergraduates to postdoctoral associates and research scientists.

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Summary: Beautifully written!
Review: As a person with no expertise in molecular modeling who wanted to learn about this field, this book is right on! I find the author's lively text to be as well-written and clear as any science textbook I have ever read. I especially enjoyed the first two chapters for their historical perspective and their practical illustrations of applications of genetics in the world today. These chapters can be understood by non-scientists, whereas the rest of the book is clearly designed for graduate students in any one of the science disciplines.

The interesting information sprinkled throughout the book, including the boxes and figures, help keep the reader stimulated and yearning for greater knowledge of this exciting field. The color graphics also complement the book nicely. Although the subject covered in the book is extremely broad, the author managed to convey the perspectives of multiple scientific disciplines (e.g., biology, chemistry, computer science, math) very well. The combination of breadth and depth in a readable style is remarkable.

Overall, I highly recommend this book to readers interested in the area.

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Summary: A long expected book in molecular modeling is finally here
Review: I highly recommend Professor T. Schlick's book. It is beautifully written with many examples and great illustrations. The book is truly interdisciplinary; it covers, in good depth, both the biological and mathematical aspects of computational structural biology. Most chapters start with an amenable introduction and finish with "hands-on" recommendations and future challenges. I was particularly pleased with the level of detail in each chapter (in particular those that show the reader the advantages and pitfalls of the different methods presented). My colleague Mariel Vazquez and I used this book in the design and preparation of our "Special topics in Mathematics" course at the UC Berkeley Mathematics Department during the Spring of 2003.

This upper-level undergraduate/lower-level graduate course was centered on mathematical and computational models of the three dimensional structure of DNA, and DNA topology. We found Professor T. Schlick's book very useful in our class preparation. In particular we covered chapter 5 (DNA structure) completely, sections 3 and 4 from chapter 7 (basic principles and formulation of atomic interactions in molecular mechanics), and several sections or subsections from chapters 8 and 9 (force terms used in molecular dynamics simulations). We also covered most of the material in chapter 10 (Multivariate Minimization), and gave a brief introduction to chapter 11 (Monte-Carlo techniques) and chapter 12 (Molecular Dynamics algorithms).

Chapter 5 starts with a very amenable and brief introduction that relates DNA with other biological processes and describes some of the challenges in studying DNA structure. It continues describing the basic building blocks of DNA. The author wisely spends some time defining the nomenclature for each of the atoms, angles and bonds that form these basic blocks. The following sections teach the reader what parameters are relevant for describing a DNA double helix and how they characterize the A, B and Z- forms of DNA. Illustrations in this chapter are particularly helpful.

Although our course's approach to DNA supercoiling was different that the one in the book I found particularly useful some illustrations in chapter 6 and movies (to be found in her webpage) that Prof. Schlick's group has developed over the years. In brief, chapter 6 is a study of more complex structures and behavior of DNA (such as structural role of the DNA sequence, DNA-protein interactions, and higher order organization of DNA -i.e. DNA supercoiling and histone-DNA interactions). This chapter can be a good source for short research projects (e.g. final projects).

Chapters 7, 8 and 9 describe the basic concepts in molecular mechanics. From sections 7.3 and 7.4 I found of interest how the author addresses the problem of the system size (i.e. number of interacting molecules) and some of the details that the author gives for modeling the geometry of atomic interactions. At the end of the chapter (section 7.4.3) interested readers can find some of the limitations of current approaches. Chapters 8 and 9 describe in depth the force fields and how to implement them. Chapter 9 also illustrates with clarity how to implement periodic boundary conditions and the advantages of using different lattice models.

Chapter 10 describes a number of familiar methods for energy minimization (i.e. steepest descent, conjugate gradient, etc....). We used sections 10.1 to 10.4 and section 10.5.2 (conjugate gradient). I found the Hessian patterns shown in figures 10.4 and 10.5 and the minimization trajectories shown in 10.10 very pedagogical. As in previous chapters the author finishes with practical recommendations and future challenges.

We left chapter 11 (Monte Carlo methods) for last in the course and discussed chapter 12 (molecular dynamics) first. As in previous chapters the author gives a very nice introduction (section 12.1 and 12.2) and covers the basics on simulation protocols in sections 12.3 and 12.4. Section 12.4 describes the basic integration algorithms such as leap-frog, verlet, etc... Figure 12.3 was revealing for the students as it compares the time scales in biological systems.

Chapter 11 (Monte-Carlo methods) provides a very comprehensive introduction to Monte-Carlo methods. We found particularly useful some of the subsections of random number generation and the treatment of Importance sampling and Markov chains in section 11.5.

As mentioned earlier we were particularly delighted with the amount of details given in each topic. For example chapters 7 and 8 provide all the formalism needed for the problems of molecular mechanics. In section 8.4 (bond angle potential) the author highlights the differences (both formally and by figures-see figure 8.4) between different formulations of the problem (see also figure 8.6). In Chapter 10 the author describes minimization algorithms in detail and shows some of the patterns that one observes in the Hessian associated to minimization functions of biological structures (see figs. 10.4, 10.5 and 10.11). She also makes very detailed comparisons between the different minimization methods (see figs 10. 2, 10.10). In chapter 12 she compares the different methods and initial conditions for the algorithms discussed (figs 12.3, 12.4, 12.6).

Overall we found that Prof. T. Schlick's book is very adequate for a broad spectrum of levels and very accessible to both graduate and undergraduate students interested in mathematical modeling and computational biology. It is also very well organized facilitating the option of selecting parts of the material for the classroom or for use in one's research.

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Summary: Never short of something exciting
Review: It contains many many exiting problems and stimulate to go through the world of art of biology and mathematics. This book can guide the way where to go when you lost in the world of biomathematics, specifically molecular modeling. It looks like a well-organized dictionary with analysis. So it is good for a beginner and also deep-thinker in computational biology field.

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Summary: Making a biological molecule alive in silico and on screen
Review: Molecular modeling is now an important area of biochemistry. It is amazing, however, to see that the practicing scientists in this field are mainly the descendents of a very few pioneers in the field. Therefore, it is wonderful to see the present book, written by an applied mathematician turned computational biochemist, which provides a rather fresh perspective on things and ways in this growing field. Clearly and rightly, the author emphasizes the interdisciplinary nature of the subject.

In addition, pedagogically, the author had in mind readers without the traditional background in chemistry. The book covers various important topics in modern simulations, and even tells you a little bit about how people getting macromolecular structures and other relevant data in a laboratory: from crystallography to nuclear magnetic resonance, from sequencing to microarray.

Finally but not the least, the author was able to keep the entire book at a fairly high level of excitement, and the reading is enjoyable.

The introductory historical perspective is brief but informative - and you get to know who's who in the founding period of the trade.

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Summary: A clearly written book as an intro. to molecular modeling
Review: The book is well organized. It is concise and easy enough for students to follow while it covers enough material. I still refer to this book at times and it is very helpful.

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Summary: Very useful textbook for graduate students
Review: The book of "Molecular Modeling and Simulation: An Interdisciplinary Guide" introduces basic knowledge for protein and nucleic acid structures and a wide range of computational techniques to simulate these macromolecules. It is very useful for chemistry graduate students to learn about this new exciting field of biomolecular modeling. I was expecting such books many years ago when I was a graduate student in Physical Chemistry. Now I am very glad to have one in hand. I would like to recommend this book to the graduate students in Chemistry, Biology, Physics, and Mathematics who are stepping into the molecular modeling and simulation field.

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Summary: Excellent book for both students and researchers
Review: This book covers state-of-arts technologies used in today's hot field: molecular modeling. The book is easy to understand and it is suitable for graduate students in both theoretic majors and experimental majors. The homeworks in the book are practical for students to learn basic molecular modeling computer skills very fast.

Dr. Schlick is an expert in this field and her group has published tons of molecular modeling research papers. Her expertise also makes this book valuable for computational scientific researchers. I highly recommend it.