Molecular Modeling and Simulation
by Tamar Schlick
A Long Expected Book In Molecular Modeling Is Finally Here
This book evolved from an interdisciplinary graduate course entitled
Molecular Modeling developed at New York University. Its primary goal is
to stimulate excitement for molecular modeling research while introducing
readers to the wide range of biomolecular problems being solved by
computational techniques and to those computational tools. The book is
intended for beginning graduate students in medical schools and scientific
fields such as biology, chemistry, physics, mathematics, and computer
science. Other scientists who wish to enter, or become familiar, with the
field of biomolecular modeling and simulation may also benefit from the
broad coverage of problems and approaches. The book surveys three
broad areas: biomolecular structure and modeling: current problems and
state of computations; molecular mechanics: force field origin,
composition, and evaluation techniques; and simulation methods:
geometry optimization, Monte Carlo, and molecular dynamics approaches.
Appendices featuring homework assignments, reading lists, and other

information useful for teaching molecular modeling complement the
material in the main text. Extensive use of world wide web resources is
encouraged, and additional course and text information may be found on a
supplementary website. Some praise for Tamar Schlicks Molecular
Modeling and Simulation: An Interdisciplinary Guide:||The interdisciplinary
structural biology community has waited long for a book of this kind which
provides an excellent introduction to molecular modeling.|-Harold A.
Scheraga, Cornell University||A uniquely valuable introduction to the
modeling of biomolecular structure and dynamics. A rigorous and up-to-
date treatment of the foundations, enlivened by engaging anecdotes and
historical notes.|-J. Andrew McCammon, Howard Hughes Medical Institute,
University of California at San Diego||I am often asked by physicists,
mathematicians and engineers to recommend a book that would be useful
to get them started in computational molecular biology. I am also often
approached by my colleagues in computational biology to recommend a
solid textbook for a graduate course in the area. Tamar Schlick has written
the book that I will be recommending to both groups. Tamar has done an
amazing job in writing a book that is both suitably accessible for beginners,
and suitably rigorous for experts.|-J.J. Collins, Boston University FROM
THE REVIEWS: BIOTECH INTERNATIONAL [BTI]: . . . The text
emphasises that the field is changing very rapidly and that it is full of
exciting discoveries. Many of these findings have lead to medical and
technological breakthroughs. This book stimulates this excitement, while
still providing students many computational details . . . It should appeal to
beginning graduate students in medical schools, and in many scientific
departments such as biology, chemistry, physics, mathematics, and
computer science.
Personal Review: Molecular Modeling and Simulation by Tamar
Schlick
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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