Role of water and steric constraints in the kinetics of cavity–ligand unbinding

Abstract

A key factor influencing a drug's efficacy is its residence time in the binding pocket of the host protein. Using atomistic computer simulation to predict this residence time and the associated dissociation process is a desirable but extremely difficult task due to the long timescales involved. This gets further complicated by the presence of biophysical factors such as steric and solvation effects. In this work, we perform molecular dynamics (MD) simulations of the unbinding of a popular prototypical hydrophobic cavity-ligand system using a metadynamics-based approach that allows direct assessment of kinetic pathways and parameters. When constrained to move in an axial manner, the unbinding time is found to be on the order of 4,000 s. In accordance with previous studies, we find that the cavity must pass through a region of sharp wetting transition manifested by sudden and high fluctuations in solvent density. When we remove the steric constraints on ligand, the unbinding happens predominantly by an alternate pathway, where the unbinding becomes 20 times faster, and the sharp wetting transition instead becomes continuous. We validate the unbinding timescales from metadynamics through a Poisson analysis, and by comparison through detailed balance to binding timescale estimates from unbiased MD. This work demonstrates that enhanced sampling can be used to perform explicit solvent MD studies at timescales previously unattainable, to our knowledge, obtaining direct and reliable pictures of the underlying physiochemical factors including free energies and rate constants.ligand unbinding | kinetics | enhanced sampling | dewetting transition T he unbinding of ligands from host substrates is a phenomenon widely occurring across biological and chemical sciences. It is of great interest to be able to understand the thermodynamics and kinetics of such processes, especially how they are influenced by solvent and steric effects. An accurate estimate of unbinding kinetics is in fact of crucial importance for drug discovery paradigms (1, 2). However, despite the advent of massively parallel computer resources, it has not been so easy to simulate the dynamics of ligand unbinding and calculate associated rate constants. The complications are mainly twofold. First, as has been seen in studies of model systems (3-10), various proteins (11-13), HIV (14), and actual anticancer drugs (15-17), the solvent often manifests itself at the molecular scale. Whereas coarse-grained models can be fit to explicit solvent molecular dynamics (MD) simulations (3), predictive power can be attained only by performing all-atom MD. Second, performing all-atom MD for unbinding of such systems is however plagued by the timescale problem. MD is restricted to integration timesteps of a few femtoseconds, which can be partially mitigated by multiple timestep MD algorithms (18). However, it is not yet routinely feasible to go into the millisecond regime and beyond for any system with more than a few thousand atoms.In this paper we consider a popular prototy...

Overcoming time scale and finite size limitations to compute nucleation rates from small scale well tempered metadynamics simulations

“…When this is the case, the whole transition time distribution can be recovered from a set of WTmetaD simulations. This approach has been applied to several problems, thus allowing the computation of rates of activated processes such as DNA unfolding 16 , and protein-ligand unbinding [17][18][19] .…”

Stochastic level-set variational implicit-solvent approach to solute-solvent interfacial fluctuations

“…1,3,13,59,[75][76][77] Assuming a Gaussian statistics, Lum-Chandler-Weeks 78 include such fluctuations in a continuum solvent theory for hydrophobic interactions. 23 In this theory, the solvent density is decomposed into a macroscopic part, which is governed by a van der Waals functional of gradient-squared term and a double-well potential for the solute-solvent interfacial structure, and a microscopic part, which describes the solvent fluctuations; cf.…”

Kramers turnover: From energy diffusion to spatial diffusion using metadynamics

“…While many of these enhanced sampling methods concern a) Electronic mail: pt2399@columbia.edu recovering the underlying free energy landscape, some are designed to calculate the actual rate of barrier crossing. [9][10][11][12][13][14] In this short communication, we consider one such recently proposed method, the so-called "infrequent metadynamics" approach, 14,15 which has recently been applied successfully to obtain rate constants in a variety of complex molecular systems, 16,17 and is briefly summarized in Sec. II.…”

“…It tends to become less reliable as the coupling constant is made very low and the system enters the deeply underdamped regime. Thankfully, most biomolecular systems, which are the target systems for the method, 16,17 involve large numbers of solvent atoms executing rapid thermal motions where one expects the moderate to high friction regime to be applicable. As we find in this work, the infrequent metadynamics approach is indeed reliable in this regime.…”