Atomistic simulations: an introduction

In this manual we describe ORAC , a program for the molecular dynamics (MD) simulation of atomistic models of complex molecular systems. In atomistic models the coordinates of all atomic nuclei including hydrogen are treated explicitly and interactions between distant atoms are represented by a pairwise additive dispersive-repulsive potential and a Coulomb contribution due to the atomic charges. Furthermore, nearby atoms interact through special two body, three body and four body functions representing the valence bonds, bending and torsional interaction energies surfaces.

The validity of such an approach as well as the reliability of the various potential models proposed in the literature [3,4,5,6] is not the object of the present book. For reading on this topic, we refer to the extensive and ever growing literature [4,7,8,9]. Here, we want only to stress the general concept that atomistic simulations usually have more predictive power than simplified models, but are also very expensive with respect to the latter from a computational standpoint. This predictive power stems from the fact that, in principle, simulations at the atomistic level do not introduce any uncontrolled approximation besides the obvious assumptions inherent in the definition of the potential model and do not assume any a priori knowledge of the system, except of course its chemical composition and topology. Therefore, the failure in predicting specific properties of the system for an atomistic simulation is due only to the inadequacy of the adopted interaction potential. We may define this statement as the brute force postulate. In practice, however, in order to reduce the computational burden, severe and essentially uncontrolled approximations such as neglect of long range interactions, suppression of degrees of freedom, dubious thermostatting or constant pressure schemes are often undertaken. These approximations, however, lessen the predictive power of the atomistic approach and incorrect results may follow due to the inadequacy in the potential model, baseless approximations or combinations of the two. Also, due to their cost, the predictive capability of atomistic level simulations might often only be on paper, since in practice only a very limited phase space region can be accessed in an affordable way, thereby providing only biased and unreliable statistics for determining the macroscopic and microscopic behavior of the system. It is therefore of paramount importance in atomistic simulations to use computational techniques that do not introduced uncontrolled approximations and at the same time are efficient in the sampling of the complex and rugged conformational space of biological systems. Regarding this last issue, many progresses has been done recently by devising new both non-Boltzmann and Boltzmann techniques for extended sampling of complex systems. Chapter 6 and Chapter 7 are devoted to these aspects of atomistic molecular simulations.