Ab Initio Nucleic Acid Folding Simulations Using a Physics-Based Atomistic Free Energy Model

TL;DR

This paper introduces a physics-based, all-atom simulation model for nucleic acid folding that captures key molecular forces and employs advanced algorithms to efficiently predict DNA structure formation from first principles.

Contribution

It presents a novel ab initio folding simulation method for nucleic acids using a detailed atomistic model and analytical theories for solvent effects, improving computational efficiency.

Findings

Successfully simulated DNA folding from scratch

Achieved efficient Monte Carlo sampling for nucleic acids

Benchmark results demonstrate model's accuracy and advantages

Abstract

Performing full-resolution atomistic simulations of nucleic acid folding has remained a challenge for biomolecular modeling. Understanding how nucleic acids fold and how they transition between different folded structures as they unfold and refold has important implications for biology. This paper reports a theoretical model and computer simulation of the ab initio folding of DNA inverted repeat sequences. The formulation is based on an all-atom conformational model of the sugar-phosphate backbone via chain closure, and it incorporates three major molecular-level driving forces - base stacking, counterion-induced backbone self-interactions and base pairing - via separate analytical theories designed to capture and reproduce the effects of the solvent without requiring explicit water and ions in the simulation. To accelerate computational throughput, a mixed numerical/analytical algorithm for the calculation of the backbone conformational volume is incorporated into the Monte Carlo simulation, and special stochastic sampling techniques were employed to achieve the computational efficiency needed to fold nucleic acids from scratch. This paper describes implementation details, benchmark results and the advantages and technical challenges with this approach.