Optimization of protein force-field parameters with the Protein Data Bank

TL;DR

This paper introduces a new method to optimize protein force-field parameters by minimizing atomic forces on protein structures from the Protein Data Bank, leading to more accurate folding simulations.

Contribution

The paper presents a novel force-field optimization technique using PDB structures, improving the accuracy of protein folding simulations.

Findings

Optimized force-field parameters yielded structures closer to experimental data.

The method improved the accuracy of folding simulations for α-helical and β-hairpin peptides.

Optimized parameters enhanced the predictive power of the AMBER force field.

Abstract

We propose a novel method to optimize existing force-field parameters for protein systems. The method consists of minimizing the summation of the square of the force acting on each atom in the proteins with the structures from the Protein Data Bank. We performed this optimization to the partial-charge and torsion-energy parameters of the AMBER parm96 force field, using 100 molecules from the Protein Data Bank. We then performed folding simulations of $\alpha$-helical and $\beta$-hairpin peptides. The optimized force-field parameters gave structures more similar to the experimental implications than the original AMBER force field.