Optimization of protein force-field parameters with the Protein Data Bank
classification
❄️ cond-mat.stat-mech
q-bio.BM
keywords
proteinparametersbankdataforceforce-fieldamberfield
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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.
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