Multiscale Estimation of Binding Kinetics Using Brownian Dynamics, Molecular Dynamics and
Markov State Models
Department of Chemistry and Biochemistry, UC San Diego
The kinetic rate constants of binding were estimated for four biochemically relevant
molecular systems by a method that combines Brownian dynamics simulations with more
accurate molecular dynamics simulations using a Markov state model.
The rate constants found using this method were in good agreement with experimentally and
theoretically obtained values. We predicted the association rate of a small charged
molecule toward both a charged and an uncharged sphere and verified the estimated value
with well-established theory. We also calculated the kon rate constant for
superoxide dismutase with its natural substrate O2- in a repeat of a
previous experiment using similar methods but with a number of important improvements.
We also calculated the kon for a new system: the N-terminal domain of Troponin C
with its natural substrate Ca2+. The kon calculated for both systems closely resemble experimentally obtained values. This multiscale approach is computationally cheaper and more parallelizable compared to other methods of similar accuracy. We anticipate that this methodology will be useful for predicting kinetic rate constants and for understanding the process of binding between a small molecule and a protein receptor.