Explicit models of motions to understand protein side-chain dynamics
arXiv:2204.05813 · doi:10.1103/PhysRevLett.129.203001
Abstract
Nuclear magnetic relaxation is widely used to probe protein dynamics. For decades, most analyses of relaxation in proteins have relied successfully on the model-free approach, forgoing mechanistic descriptions of motions. Model-free types of correlation functions cannot describe a large carbon-13 relaxation dataset in protein sidechains. Here, we use molecular dynamics simulations to design explicit models of motion and solve Fokker-Planck diffusion equations. These models of motion provide better agreement with relaxation data, mechanistic insight and a direct link to configuration entropy.
References in corpus (4)
- SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python
- emcee: The MCMC Hammer
- Theoretical and Computational Framework for the Analysis of the Relaxation Properties of Arbitrary Spin Systems. Application to High-Resolution Relaxometry
- Explicit models of motions to analyze NMR relaxation data in proteins