Part I Molecular Modeling -- Introduction to Molecular Dynamics: Theory and Applications in Biomolecular Modeling -- The Many Faces of Structure-Based Potentials: From Protein Folding Landscapes to Structural Characterization of Complex Biomolecules -- Discrete Molecular Dynamics Simulation of Biomolecules -- Small Molecule Docking from Theoretical Structural Models -- Homology Modeling: Generating Structural Models to Understand Protein Function and Mechanism -- Quantum Mechanical Insights into Biological Processes at the Electronic Level -- Part II Modeling Macromolecular Assemblies -- Multiscale Modeling of Virus Structure, Assembly and Dynamics -- Mechanisms and Kinetics of Amyloid Aggregation Investigated by a Phenomenological Coarse-Grained Model -- The Structure of Intrinsically Disordered Peptides Implicated in Amyloid Diseases: Insights from Fully Atomistic Simulations -- Part III Modeling Cells and Cellular Pathways -- Computer Simulations of Mechano-Chemical Networks: Choreographing Actin Dynamics in Cell Motility -- Computational and Modeling Strategies for Cell Motility -- Theoretical Analysis of Molecular Transport Across Membrane Channels and Nanopores -- Part IV Modeling Evolution -- Modeling Protein Evolution -- Modeling Structural and Genomic Constraints in the Evolution of Proteins -- Modeling Proteins at the Interface of Structure, Evolution, and Population Genetics.

Computational modeling is emerging as a powerful new approach for studying and manipulating biological systems. Many diverse methods have been developed to model, visualize, and rationally alter these systems at various length scales, from atomic resolution to the level of cellular pathways. Processes taking place at larger time and length scales, such as molecular evolution, have also greatly benefited from new breeds of computational approaches. Computational Modeling of Biological Systems: From Molecules to Pathways provides an overview of established computational methods for the modeling of biologically and medically relevant systems. It is suitable for researchers and professionals working in the fields of biophysics, computational biology, systems biology, and molecular medicine.