TY - JOUR
T1 - Combining Virtual Reality Visualization with Ensemble Molecular Dynamics to Study Complex Protein Conformational Changes
AU - Juárez-jiménez, Jordi
AU - Tew, Philip
AU - O′connor, Michael
AU - Llabrés, Salomé
AU - Sage, Rebecca
AU - Glowacki, David
AU - Michel, Julien
PY - 2020/11/12
Y1 - 2020/11/12
N2 - Molecular dynamics (MD) simulations are increasingly used to elucidate relationships between protein structure, dynamics, and their biological function. Currently, it is extremely challenging to perform MD simulations of large-scale structural rearrangements in proteins that occur on millisecond timescales or beyond, as this requires very significant computational resources, or the use of cumbersome “collective variable” enhanced sampling protocols. Here, we describe a framework that combines ensemble MD simulations and virtual reality visualization (eMD-VR) to enable users to interactively generate realistic descriptions of large amplitude, millisecond timescale protein conformational changes in proteins. Detailed tests demonstrate that eMD-VR substantially decreases the computational cost of folding simulations of a WW domain, without the need to define collective variables a priori. We further show that eMD-VR generated pathways can be combined with Markov state models to describe the thermodynamics and kinetics of large-scale loop motions in the enzyme cyclophilin A. Our results suggest eMD-VR is a powerful tool for exploring protein energy landscapes in bioengineering efforts.
AB - Molecular dynamics (MD) simulations are increasingly used to elucidate relationships between protein structure, dynamics, and their biological function. Currently, it is extremely challenging to perform MD simulations of large-scale structural rearrangements in proteins that occur on millisecond timescales or beyond, as this requires very significant computational resources, or the use of cumbersome “collective variable” enhanced sampling protocols. Here, we describe a framework that combines ensemble MD simulations and virtual reality visualization (eMD-VR) to enable users to interactively generate realistic descriptions of large amplitude, millisecond timescale protein conformational changes in proteins. Detailed tests demonstrate that eMD-VR substantially decreases the computational cost of folding simulations of a WW domain, without the need to define collective variables a priori. We further show that eMD-VR generated pathways can be combined with Markov state models to describe the thermodynamics and kinetics of large-scale loop motions in the enzyme cyclophilin A. Our results suggest eMD-VR is a powerful tool for exploring protein energy landscapes in bioengineering efforts.
U2 - 10.1021/acs.jcim.0c00221
DO - 10.1021/acs.jcim.0c00221
M3 - Article
SN - 1549-9596
JO - Journal of Chemical Information and Modeling
JF - Journal of Chemical Information and Modeling
ER -