title: Use of multiple picosecond high-mass molecular dynamics simulations to predict crystallographic B-factors of folded globular proteins.
abstract: Predicting crystallographic B-factors of a protein from a conventional molecular dynamics simulation is challenging, in part because the B-factors calculated through sampling the atomic positional fluctuations in a picosecond molecular dynamics simulation are unreliable, and the sampling of a longer simulation yields overly large root mean square deviations between calculated and experimental B-factors. This article reports improved B-factor prediction achieved by sampling the atomic positional fluctuations in multiple picosecond molecular dynamics simulations that use uniformly increased atomic masses by 100-fold to increase time resolution. Using the third immunoglobulin-binding domain of protein G, bovine pancreatic trypsin inhibitor, ubiquitin, and lysozyme as model systems, the B-factor root mean square deviations (mean ± standard error) of these proteins were 3.1 ± 0.2-9 ± 1 Å2for Cα and 7.3 ± 0.9-9.6 ± 0.2 Å2for Cγ, when the sampling was done for each of these proteins over 20 distinct, independent, and 50-picosecond high-mass molecular dynamics simulations with AMBER forcefield FF12MC or FF14SB. These results suggest that sampling the atomic positional fluctuations in multiple picosecond high-mass molecular dynamics simulations may be conducive toa prioriprediction of crystallographic B-factors of a folded globular protein.
authors.affiliation: Computer-Aided Molecular Design Laboratory, Mayo Clinic, Rochester, MN 55905, USA.
authors.forename: Yuan-Ping
authors.initials: YP
authors.lastname: Pang
keywords: Bioengineering; Bioinformatics; Biophysics; Biotechnology