Computational Modeling And Simulations Of Biomolecular Systems

This textbook originated from the course 'Simulation, Modeling, and Computations in Biophysics' that I have taught at the University of Chicago since 2011. The students typically came from a wide range of backgrounds, including biology, physics, chemistry, biochemistry, and mathematics, and the course was intentionally adapted for senior undergraduate students and graduate students. This is not a highly technical book dedicated to specialists. The objective is to provide a broad survey from the physical description of a complex molecular system at the most fundamental level, to the type of phenomenological models commonly used to represent the function of large biological macromolecular machines.The key conceptual elements serving as building blocks in the formulation of different levels of approximations are introduced along the way, aiming to clarify as much as possible how they are interrelated. The only assumption is a basic familiarity with simple mathematics (calculus and integrals, ordinary differential equations, matrix linear algebra, and Fourier-Laplace transforms).

The third volume in the series on Computer Simulation of Biomolecular Systems continues with the format introduced in the first volume [1] and elaborated in the second volume [2]. The primary emphasis is on the methodological aspects of simulations, although there are some chapters that present the results obtained for specific systems of biological interest. The focus of this volume has changed somewhat since there are several chapters devoted to structure-based ligand design, which had only a single chapter in the second volume. It seems useful to set the stage for this volume by quoting from my preface to Volume 2 [2]. "The long-range 'goal of molecular approaches to biology is to describe living systems in terms of chemistry and physics. Over the last fifty years great progress has been made in applying the equations representing the underlying physical laws to chemical problems involv ing the structures and reactions of small molecules. Corresponding studies of mesoscopic systems have been undertaken much more recently. Molecular dynamics simulations, which are the primary focus of this volume, represent the most important theoretical approach to macromolecules of biological interest." ...

Computational modeling is emerging as a powerful new approach to study and manipulate biological systems. Multiple methods have been developed to model, visualize, and rationally alter systems at various length scales, starting from molecular modeling and design at atomic resolution to cellular pathways modeling and analysis. Higher time and length scale processes, such as molecular evolution, have also greatly benefited from new breeds of computational approaches. This book provides an overview of the established computational methods used for modeling biologically and medically relevant systems.

A practice-oriented survey of techniques for computational modeling and simulation suitable for a broad range of biological problems. There are many excellent computational biology resources now available for learning about methods that have been developed to address specific biological systems, but comparatively little attention has been paid to training aspiring computational biologists to handle new and unanticipated problems. This text is intended to fill that gap by teaching students how to reason about developing formal mathematical models of biological systems that are amenable to computational analysis. It collects in one place a selection of broadly useful models, algorithms, and theoretical analysis tools normally found scattered among many other disciplines. It thereby gives the aspiring student a bag of tricks that will serve him or her well in modeling problems drawn from numerous subfields of biology. These techniques are taught from the perspective of what the practitioner needs to know to use them effectively, supplemented with references for further reading on more advanced use of each method covered. The text, which grew out of a class taught at Carnegie Mellon University, covers models for optimization, simulation and sampling, and parameter tuning. These topics provide a general framework for learning how to formulate mathematical models of biological systems, what techniques are available to work with these models, and how to fit the models to particular systems. Their application is illustrated by many examples drawn from a variety of biological disciplines and several extended case studies that show how the methods described have been applied to real problems in biology.

The chemical and biological sciences face unprecedented opportunities in the 21st century. A confluence of factors from parallel universes - advances in experimental techniques in biomolecular structure determination, progress in theoretical modeling and simulation for large biological systems, and breakthroughs in computer technology - has opened new avenues of opportunity as never before. Now, experimental data can be interpreted and further analysed by modeling, and predictions from any approach can be tested and advanced through companion methodologies and technologies. This two volume set describes innovations in biomolecular modeling and simulation, in both the algorithmic and application fronts. With contributions from experts in the field, the books describe progress and innovation in areas including: simulation algorithms for dynamics and enhanced configurational sampling, force field development, implicit solvation models, coarse-grained models, quantum-mechanical simulations, protein folding, DNA polymerase mechanisms, nucleic acid complexes and simulations, RNA structure analysis and design and other important topics in structural biology modeling. The books are aimed at graduate students and experts in structural biology and chemistry and the emphasis is on reporting innovative new approaches rather than providing comprehensive reviews on each subject.

This two volume set describes innovations in biomolecular modeling and simulation, in both the algorithmic and application fronts.