Molecular modeling is the science and art of studying molecular structure and function through model building and computation. The model building can be as simple as plastic templates or metal rods, or as sophisticated as interactive, animated color stereo-graphics and laser-made wooden sculptures. The computations encompass ab initio and semi-empirical quantum mechanics, empirical (molecular) mechanics, visualization, homology modeling, docking, molecular dynamics (MD), Monte Carlo, free energy and solvation methods, enhanced sampling and pathway methods, principal component analysis (PCA), structure/activity relationships (SAR), chemical/biochemical information and databases and many other established procedures and method.
The questions being addressed by computational approaches today are as intriguing and as complex as the biological systems themselves. They range from understanding the equilibrium structure of a small biopolymer subunit to the energetics of hydrogen-bond formation in proteins and nucleic acids, binding aﬃnities of ligands/drugs to their target, complex kinetics of protein folding and the complex functioning of a supramolecular aggregate. Indeed, given many experimental triumphs, modeling approaches are needed to pursue many fundamental questions concerning the biological motions and functions of complex systems like ion channels, signaling receptors, membrane transporters, ribosomes, nucleosomes and non-coding RNAs. Modeling can provide a way to systematically explore structural/dynamical/thermodynamic patterns, and test and develop hypotheses to help understand and extend basic laws that govern molecular structure, ﬂexibility and function.
With improved modeling algorithms, better force ﬁelds, faster computers and experimental advances (e.g. single-molecule techniques and high-speed X-rays), modeling and simulation have expanded in both quality and scope. Problems and approaches that were insurmountable a few years ago are now possible.
Yet, a ﬁeld’s maturity also implies that some current users may not be familiar with caveats and inherent approximations that ﬁeld pioneers clearly recognized. Indeed, the readily available programs for simulation and visualization make usage much more facile but possibly also easier to abuse. Moreover, advanced programs and simulation methods like MD and folding are far from generally applicable automated procedures ; their application relies on user expertise as well as biological intuition [Schlick, 2011].