Accelerating the 3D-RISM theory of molecular solvation with treecode summation and cut-offs

TL;DR

This paper introduces treecode summation and cut-offs to significantly accelerate 3D-RISM calculations of molecular solvation, enabling efficient analysis of large biomolecular systems like microtubules.

Contribution

The authors developed and implemented treecode summation and analytical cut-offs to speed up 3D-RISM computations, achieving a fourfold reduction in time for large protein systems.

Findings

Computation time for tubulin reduced by a factor of 4.

Parallel scaling of the new methods is nearly linear.

Successful calculation of solvation thermodynamics for a 1.2 million atom microtubule.

Abstract

The 3D reference interaction site model (3D-RISM) of molecular solvation is a powerful tool for computing the equilibrium thermodynamics and density distributions of solvents, such as water and co-ions, around solute molecules. However, 3D-RISM solutions can be expensive to calculate, especially for proteins and other large molecules where calculating the potential energy between solute and solvent requires more than half the computation time. To address this problem, we have developed and implemented treecode summation for long-range interactions and analytically corrected cut-offs for short-range interactions to accelerate the potential energy and long-range asymptotics calculations in non-periodic 3D-RISM in the AmberTools molecular modeling suite. For the largest single protein considered in this work, tubulin, the total computation time was reduced by a factor of 4. In addition, parallel calculations with these new methods scale almost linearly and the iterative solver remains the largest impediment to parallel scaling. To demonstrate the utility of our approach for large systems, we used 3D-RISM to calculate the solvation thermodynamics and density distribution of 7-ring microtubule, consisting of 910 tubulin dimers, over 1.2 million atoms.