A method of incorporating rate constants as kinetic constraints in molecular dynamics simulations

• DOI: 10.1073/pnas.2012423118
• Publication Date: 2020-12-29T17:40:19Z
• Authors: Z. Faidon Brotzakis; Michele Vendruscolo; Peter G. Bolhuis
• Keywords: Chemical Physics (physics.chem-ph); Statistical Mechanics (cond-mat.stat-mech); 500; FOS: Physical sciences; Computational Physics (physics.comp-ph); 540; 01 natural sciences; Biological Physics (physics.bio-ph); Physics - Chemical Physics; 0103 physical sciences; Physics - Biological Physics; Physics - Computational Physics; Condensed Matter - Statistical Mechanics

From the point of view statistical mechanics, a full characterization molecular system requires an accurate determination its possible states, their populations, and respective interconversion rates. Toward this goal, well-established methods increase accuracy dynamics simulations by incorporating experimental information about states using structural restraints populations thermodynamics restraints. However, it is still unclear how to include knowledge Here, we introduce method imposing known rate constants as constraints in simulations, which based on combination maximum-entropy maximum-caliber principles. Starting from existing ensemble trajectories, obtained either or enhanced trajectory sampling, provides minimally perturbed path distribution consistent with kinetic constraints, well modified free energy committor landscapes. We illustrate application series model systems, including all-atom protein folding. Our results show that combining approach enables transition reaction mechanisms, energies. anticipate will extend applicability studies biology assist development force fields reproduce thermodynamic observables. Furthermore, generally applicable wide range systems biology, physics, chemistry, material science.