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).

This book is the third volume in this highly successful series. Since the first volume in 1989 and the second in 1993, many exciting developments have occurred in the development of simulation techniques and their application to key biological problems such as protein folding, protein structure prediction and structure-based design, and in how, by combining experimental and theoretical approaches, very large biological systems can be studied at the molecular level. This series attempts to capture that progress. Volume 3 includes contributions that highlight developments in methodology which enable longer and more realistic simulations (e.g. multiple time steps and variable reduction techniques), a study of force fields for proteins and new force field development, a novel approach to the description of molecular shape and the use of molecular shape descriptors, the study of condensed phase chemical reactions, the use of electrostatic techniques in the study of protonation, equilibria and flexible docking studies, structure refinement using experimental data (X-ray, NMR, neutron, infrared) and theoretical methods (solvation models, normal mode analysis, MD simulations, MC lattice dynamics, and knowledge-based potentials). There are several chapters that show progress in the development of methodologies for the study of folding processes, binding affinities, and the prediction of ligand-protein complexes. The chapters, contributed by experienced researchers, many of whom are leaders in their field of study, are organised to cover developments in: simulation methodology the treatment of electrostatics protein structure refinement the combined experimental and theoretical approaches to the study of very large biological systems applications and methodology involved in the study of protein folding applications and methodology associated with structure-based design.

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.

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." ...

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 opening of the 21st century has been marked as a generation of biological science. Nowadays, the understanding of the sequence and structure of biomolecules is growing rapidly. And researchers from multiple disciplines, chemistry, physics and computational science in particular, are making significant contributions to modern biology and drug discovery. The state-of-the-art techniques of computational chemistry and molecular modeling can be applied to study a wide range of chemical and biological systems of interest. This enables us to study structural details at the atomic level and obtain chemical/biological information which is not available by experimental measurements. This dissertation project focused on modeling the recognition mechanisms of biomolecules and their conjugated ligands. Multiple computational techniques, such as molecular dynamics simulation, entropy and free energy calculation were applied. The model systems included signaling domains (FHA, BRCT and WW domain), kinase (p38 kinase) and HIV protease. The details of the dynamics, interactions and correlations of domain-phosphopeptide systems were discovered. The free energy calculation, mining minima algorithm, was performed to study detailed conformational changes of kinase-ligand systems and predict protein-ligand binding energies. In addition, the association process of protein and ligand, which requires large simulation time scales, was also investigated. This project studies the details of protein-peptide/ligand binding and provides clues for further structure-based biomolecule/drug design.

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

Chaired by K Wüthrich (Nobel Laureate in Chemistry, 2002) and co-chaired by B Weckhuysen, this by-invitation-only conference has gathered 39 participants — who are leaders in the field of computational modeling and its applications in Chemistry, Material Sciences and Biology. Highlights of the Conference Proceedings are short, prepared statements by all the participants and the records of lively discussions on the current and future perspectives in the field of computational modeling, from chemistry to materials to biology.