Substructured molecular dynamics using multibody dynamics algorithms

Abstract

This paper presents results obtained from simulating several biomolecular and bulk materials using multibody dynamics algorithms. The systems studied include bulk water, alkane chains, alanine dipeptide and carboxyl terminal fragments of calmodulin, ribosomal protein, and rhodopsin. The atomistic representations of these systems include several thousand degrees of freedom and the results of nano-second long simulations of several of these systems are presented. The stability and validity of the simulations are studied through conservation of energy, thermodynamics properties and conformational analysis. In these simulations, a speed up of an order of magnitude is realized for conservative error bounds with a fixed time step integration scheme. A discussion is presented on the open-source software developed to facilitate future research using multibody dynamics with molecular dynamics.

Coarse-Grained Structural Modeling of Molecular Motors Using Multibody Dynamics

“…To explore the large conformational changes associated with molecular motor movement, we have taken advantage of multibody dynamics methods originally developed for the simulation of macroscopic systems of interconnected rigid bodies and used for analysis of vehicle dynamics,33 robotic mechanisms,28 and human movement biomechanics 8. Multibody dynamics methods have also been used to speed up molecular dynamics simulations while reproducing the thermodynamic properties and detailed conformational dynamics of molecular systems 4,24. In contrast with other applications, the multibody dynamics employed here are not intended to directly simulate the dynamic behavior of molecular motors.…”

The small mass assumption applied to the multibody dynamics of motor proteins

“…This allows inclusion of an infinite number of particles and also eliminates high frequency vibrations. Several techniques have been proposed for achieving this grouping (Chun et al, 2000;Chirikjian, 2004, 2005;Schwieters and Clore, 2007;Mukherjee et al, 2008) yielding a coarse grain model expressed in terms of a few generalized coordinates. The less stiff connections between sets of particles, those between the heads and necks, are modeled as joints that allow freedom of movement.…”

“…Several works reduce simulation run times by cleverly adapting or restructuring the numerical integration procedure (Jain et al, 1993;Watanabe and Karplus, 1993;Chun et al, 2000;Mukherjee et al, 2008;Medyanik and Liu, 2008) or the computational architecture (Alam et al, 2008) to efficiently calculate the model. A different approach is to isolate the dynamics of the larger time scales so that a larger time step can be used.…”

“…This approach includes modal analysis retaining only low frequency modes (Schuyler and Chirikjian, 2005), the method of multiple scales (MMS) retaining only low order perturbations (Nayfeh, 1973;Pavliotis and Stuart, 2005;Coe et al, 2007), and the small mass assumption which omits the mass terms altogether (Mateos, 2004;Chen and Kim, 2004;Ciudad et al, 2006). The literature addressing molecular dynamic simulation is too vast to cover here, so the reader is referred to Chun et al (2000), Schuyler and Chirikjian (2004) and Mukherjee et al (2008).…”

Molecular dynamics simulation of simple polymer chain formation using divide and conquer algorithm based on the augmented Lagrangian method

“…Different methods that fall into this category has been summarized here. 4,5 On the other hand, there exists a large variety of low-order formulations for multibody dynamics simulation designed both for sequential and parallel computations. The examples of O(n) (n: number of bodies) recursive sequential algorithms for analysis of treelike and closed-loop topologies can be found in various references.…”