Protein-peptide association kinetics beyond the seconds timescale from atomistic simulations

Abstract

Understanding and control of structures and rates involved in protein ligand binding are essential for drug design. Unfortunately, atomistic molecular dynamics (MD) simulations cannot directly sample the excessively long residence and rearrangement times of tightly binding complexes. Here we exploit the recently developed multi-ensemble Markov model framework to compute full protein-peptide kinetics of the oncoprotein fragment 25–109Mdm2 and the nano-molar inhibitor peptide PMI. Using this system, we report, for the first time, direct estimates of kinetics beyond the seconds timescale using simulations of an all-atom MD model, with high accuracy and precision. These results only require explicit simulations on the sub-milliseconds timescale and are tested against existing mutagenesis data and our own experimental measurements of the dissociation and association rates. The full kinetic model reveals an overall downhill but rugged binding funnel with multiple pathways. The overall strong binding arises from a variety of conformations with different hydrophobic contact surfaces that interconvert on the milliseconds timescale.

Exploring ligand binding pathways on proteins using hypersound–accelerated molecular dynamics

“…Although molecular dynamics (MD) simulations enable atomic-level observations, they are limited to several microseconds on standard high-performance computers and are thus normally applicable only to relatively fast processes (2). Recently, the kinetics of slower protein interaction processes were explored through long MD simulations spanning timescales of tens of microseconds to milliseconds (3)(4)(5), which were achieved through the development of special-purpose supercomputers for high-speed simulations (e.g., ANTON (6)) and/or algorithms to aggregate many short simulations (e.g., Markov state models (MSMs) (7)). Unfortunately, MD-specific supercomputers such as ANTON are accessible only to a limited number of researchers due to their high costs.…”

The mechanism of coupled folding-upon-binding of an intrinsically disordered protein

“…1 A central challenge in the study of IDPs is the characterization of the mechanisms by which they bind their physiological interaction partners: Mechanistic insight into the folding-upon-binding process of IDPs could ultimately enable a more predictive understanding of how their sequences, conformational propensities, and biophysical properties dictate their interactions and thus their biological activity. An increasing number of experimental, 2-6 theoretical, 7-11 and computational [12][13][14][15][16][17][18][19][20][21] studies have been used to predict or globally characterize molecular recognition in IDPs, but atomic-resolution details have only recently begun to emerge. [3][4][5] Atomistic molecular dynamics (MD) simulations are a promising approach for complementing experimental measurements of IDP folding-upon-binding.…”

Improved Modeling of Peptide-Protein Binding through Global Docking and Accelerated Molecular Dynamics Simulations

“…On the other hand, enhanced sampling MD methods have been developed to improve biomolecular simulations (Christen and van Gunsteren, 2008;Gao et al, 2008;Liwo et al, 2008;Dellago and Bolhuis, 2009;Abrams and Bussi, 2014;Spiwok et al, 2015;Miao and McCammon, 2016). Multi-ensemble Markov models (Paul et al, 2017), which combine cMD with Hamiltonian replica exchange enhanced sampling simulations, have been used to characterize peptide-protein binding and calculate kinetic rates of a nano-molar peptide inhibitor PMI to the MDM2 oncoprotein fragment (Paul et al, 2017). While cMD is able to simulate fast events such as peptide binding, enhanced sampling simulations can capture rare events such as peptide unbinding.…”