Accurate and efficient constrained molecular dynamics of polymers through Newton’s method and special purpose code

Abstract

AbstractIn molecular dynamics simulations we can often increase the time step by imposing constraints on internal degrees of freedom, such as bond lengths and bond angles. This allows us to extend the length of the time interval and therefore the range of physical phenomena that we can afford to simulate. In this article we analyse the impact of the accuracy of the constraint solver. We present ILVES-PC, an algorithm for imposing constraints on proteins accurately and efficiently.ILVES-PC solves the same system of differential algebraic equations as the celebrated SHAKE algorithm, but uses Newton’s method for solving the nonlinear constraint equations. It solves the necessary linear systems of equations using a specialised linear solver that utilises the molecular structure. ILVES-PC can rapidly solve the nonlinear constraint equations to nearly the limit of machine precision. This eliminates the spurious forces introduced to simulations through the very common use of inaccurate approximations. The run-time of ILVES-PC is proportional to the number of constraints.We have integrated ILVES-PC into GROMACS and simulated proteins of different sizes. Compared with SHAKE, we have achieved speedups of up to 4.9× in single-threaded executions and up to 76× in shared-memory multi-threaded executions. Moreover, we find that ILVES-PC is more accurate than the P-LINCS algorithm. Our work is a proof-of-concept of the utility of software designed specifically for the simulation of polymers.Author summaryMolecular dynamics simulates the time evolution of molecular systems. It has become a tool of extraordinary importance for e.g. understanding biological processes and designing drugs and catalysts. This article presents an algorithm for computing the forces needed to impose constraints in molecular dynamics, i.e., the constraint forces; moreover, it analyses the effect of the accuracy of the constraint solver. Presently, it is customary to calculate the constraint forces with a relative error that that is not tiny. This is due to the high computational cost associated with the available software. Accurate calculations are possible, but they are very time-consuming. The algorithm that we present solves this problem: it computes the constraint forces accurately and efficiently. Our work will improve the accuracy and reliability of molecular dynamics simulations beyond the present state-of-the-art. The results that we present are also a proof-of-concept that special-purpose code can increase the performance of software for the simulation of polymers. The algorithm is implemented into a popular molecular simulation package, and is now available for the research community.