Sign in
BiophysicsbioRxiv

Use of multiple picosecond high-mass molecular dynamics simulations to predict crystallographic B-factors of folded globular proteins

Yuan-Ping Pang

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 [A]2 for C and 7.3 {+/-} 0.9-9.6 {+/-} 0.2 [A]2 for C{gamma}, when the sampling was done, for each of these proteins, over 20 distinct, independent, and 50-picosecond high-mass molecular dynamics simulations using 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 to a priori prediction of crystallographic B-factors of a folded globular protein.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISRiga '17Ribeiro '25Wall '17Klyshko '23Pang '16Ribeiro '23
63% semantic matchBiophysics
Anthony Riga, Jasmin Rivera, David A. Snyder·bioRxiv·Dec 28, 2017