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Title: Data-guided Multi-Map variables for ensemble refinement of molecular movies

Abstract

Driving molecular dynamics simulations with data-guided collective variables offer a promising strategy to recover thermodynamic information from structure-centric experiments. In this study, the three-dimensional electron density of a protein, as it would be determined by cryo-EM or x-ray crystallography, is used to achieve simultaneously free-energy costs of conformational transitions and refined atomic structures. Unlike previous density-driven molecular dynamics methodologies that determine only the best map-model fits, our work employs the recently developed Multi-Map methodology to monitor concerted movements within equilibrium, non-equilibrium, and enhanced sampling simulations. Construction of all-atom ensembles along the chosen values of the Multi-Map variable enables simultaneous estimation of average properties, as well as real-space refinement of the structures contributing to such averages. Using three proteins of increasing size, we demonstrate that biased simulation along the reaction coordinates derived from electron densities can capture conformational transitions between known intermediates. The simulated pathways appear reversible with minimal hysteresis and require only low-resolution density information to guide the transition. The induced transitions also produce estimates for free energy differences that can be directly compared to experimental observables and population distributions. The refined model quality is superior compared to those found in the Protein Data Bank. We find that the bestmore » quantitative agreement with experimental free-energy differences is obtained using medium resolution density information coupled to comparatively large structural transitions. Practical considerations for probing the transitions between multiple intermediate density states are also discussed.« less

Authors:
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [1]; ORCiD logo [3]; ORCiD logo [1]; ORCiD logo [4]; ORCiD logo [1]
  1. Arizona State Univ., Tempe, AZ (United States)
  2. Arizona State Univ., Tempe, AZ (United States); Purdue Univ., West Lafayette, IN (United States)
  3. National Institutes of Health (NIH), Bethesda, MD (United States)
  4. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)
Sponsoring Org.:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR); National Science Foundation (NSF); National Institutes of Health (NIH)
OSTI Identifier:
1735431
Grant/Contract Number:  
AC05-00OR22725; MCB-1942763; 2020298734; R01GM095583
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Chemical Physics
Additional Journal Information:
Journal Volume: 153; Journal Issue: 21; Journal ID: ISSN 0021-9606
Publisher:
American Institute of Physics (AIP)
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; steered molecular dynamics; molecular dynamics; x-ray crystallography; proteins; potential energy surfaces; covariance and correlation; free energy; cryogenic electron microscopy; real-space methods

Citation Formats

Vant, John W., Sarkar, Daipayan, Streitwieser, Ellen, Fiorin, Giacomo, Skeel, Robert, Vermaas, Josh V., and Singharoy, Abhishek. Data-guided Multi-Map variables for ensemble refinement of molecular movies. United States: N. p., 2020. Web. https://doi.org/10.1063/5.0022433.
Vant, John W., Sarkar, Daipayan, Streitwieser, Ellen, Fiorin, Giacomo, Skeel, Robert, Vermaas, Josh V., & Singharoy, Abhishek. Data-guided Multi-Map variables for ensemble refinement of molecular movies. United States. https://doi.org/10.1063/5.0022433
Vant, John W., Sarkar, Daipayan, Streitwieser, Ellen, Fiorin, Giacomo, Skeel, Robert, Vermaas, Josh V., and Singharoy, Abhishek. Tue . "Data-guided Multi-Map variables for ensemble refinement of molecular movies". United States. https://doi.org/10.1063/5.0022433.
@article{osti_1735431,
title = {Data-guided Multi-Map variables for ensemble refinement of molecular movies},
author = {Vant, John W. and Sarkar, Daipayan and Streitwieser, Ellen and Fiorin, Giacomo and Skeel, Robert and Vermaas, Josh V. and Singharoy, Abhishek},
abstractNote = {Driving molecular dynamics simulations with data-guided collective variables offer a promising strategy to recover thermodynamic information from structure-centric experiments. In this study, the three-dimensional electron density of a protein, as it would be determined by cryo-EM or x-ray crystallography, is used to achieve simultaneously free-energy costs of conformational transitions and refined atomic structures. Unlike previous density-driven molecular dynamics methodologies that determine only the best map-model fits, our work employs the recently developed Multi-Map methodology to monitor concerted movements within equilibrium, non-equilibrium, and enhanced sampling simulations. Construction of all-atom ensembles along the chosen values of the Multi-Map variable enables simultaneous estimation of average properties, as well as real-space refinement of the structures contributing to such averages. Using three proteins of increasing size, we demonstrate that biased simulation along the reaction coordinates derived from electron densities can capture conformational transitions between known intermediates. The simulated pathways appear reversible with minimal hysteresis and require only low-resolution density information to guide the transition. The induced transitions also produce estimates for free energy differences that can be directly compared to experimental observables and population distributions. The refined model quality is superior compared to those found in the Protein Data Bank. We find that the best quantitative agreement with experimental free-energy differences is obtained using medium resolution density information coupled to comparatively large structural transitions. Practical considerations for probing the transitions between multiple intermediate density states are also discussed.},
doi = {10.1063/5.0022433},
journal = {Journal of Chemical Physics},
number = 21,
volume = 153,
place = {United States},
year = {2020},
month = {12}
}

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