SEEKR: Simulation Enabled Estimation of Kinetic Rates, A Computational Tool to Estimate Molecular Kinetics and Its Application to Trypsin–Benzamidine Binding

Abstract

We present the Simulation Enabled Estimation of Kinetic Rates (SEEKR) package, a suite of open-source scripts and tools designed to enable researchers to perform multi-scale computation of the kinetics of molecular binding, unbinding, and transport using a combination of molecular dynamics, Brownian dynamics, and milestoning theory. To demonstrate its utility, we compute the kon, koff, and ΔGbind for the protein trypsin with its noncovalent binder, benzamidine, and examine the kinetics and other results generated in the context of the new software, and compare our findings to previous studies performed on the same system. We compute a kon estimate of 2.1±0.3•107 M−1s−1, a koff estimate of 83±14 s−1, and a ΔGbind of −7.4±0.2 kcal•mol−1, all of which compare closely to the experimentally measured values of 2.9•107 M−1s−1, 600±300 s−1, and −6.7 kcal•mol−1, respectively.

Steered molecular dynamics simulations for uncovering the molecular mechanisms of drug dissociation and for drug screening: A test on the focal adhesion kinase

“…One begins with a large force because it takes less computer time to perform these simulations. Discard the compounds that come out first as they are more likely to have shorter residence times. Perform steered molecular dynamics simulations on the remaining compounds with a smaller force. Discard the compounds that come out sooner. Repeat steps 2 through 4 until a desired number of compounds with the longest residence times are found. If worthwhile, use a more rigorous method—such as weighted‐ensemble, Markov state model, or milestoning—to confirm findings, to gain finer details into the dissociation mechanisms, and to obtain quantitative estimates of dissociation rates. After screening by the fast steered molecular dynamics simulation method, using these more expensive methods to study a small number of compounds becomes easier.…”

“…For example, my collaborators and I have invested several hundred CPU‐years on simulating two of the compounds in this paper but still have not obtained quantitative dissociation constants yet. Other expensive methods based on running unbiased molecular dynamics simulations that have been applied to study drug‐binding kinetics include the weighted ensemble method and the mile‐stoning approach …”

A Multiscale Simulation Approach to Modeling Drug–Protein Binding Kinetics

“…[1][2][3] In computer-aided drug discovery (CADD) the main emphasis has so far been placed on predicting the most likely binding pose (usually by docking and other fast but approximate methods) 4 and determining relative binding affinity 5,6 . In contrast, only recently, it has been possible to predict the pathways for binding/unbinding events and their associated free energy profiles through more refined computational methods 1,[7][8][9][10][11] . However, it is increasingly recognized that protein-ligand binding kinetics are crucial for understanding the efficacy and toxicity of lead compounds.…”

MSM/RD: Coupling Markov state models of molecular kinetics with reaction-diffusion simulations

“…In related work, [41,42] have coupled MD with a diffusion scheme. The work [43] further incorporates milestoning theory [44] to compute the local kinetic information in terms of transitions between milestones via short MD runs. In contrast with their work, we do not employ direct MD simulations at the "small" scale, but represent the small scale by an MSM as this allows us to operate on roughly the same timesteps for the small and the large scales.…”