Enhancing Sidechain Rotamer Sampling Using Non-Equilibrium Candidate Monte Carlo

<div>Molecular simulations are a valuable tool for studying biomolecular motions and thermodynamics. However, such motions can be slow compared to simulation timescales, yet critical. Specifically, adequate sampling of sidechain motions in protein binding pockets proves crucial for obtaining accurate estimates of ligand binding free energies from molecular simulations. The timescale of sidechain rotamer flips can range from a few ps to several hundred ns or longer, particularly in crowded environments like the interior of proteins. Here, we apply a mixed non-equilibrium candidate Monte Carlo (NCMC)/molecular dynamics (MD) method to enhance sampling of sidechain rotamers. The NCMC portion of our method applies a switching protocol wherein the steric and electrostatic interactions between target sidechain atoms and the surrounding environment are cycled off and then back on during the course of a move proposal. Between NCMC move proposals, simulation of the system continues via traditional molecular dynamics. Here, we first validate this approach on a simple, solvated valine-alanine dipeptide system and then apply it to a well-studied model ligand binding site in T4 lysozyme L99A. We compute the rate of rotamer transitions for a valine sidechain using our approach and compare it to that of traditional molecular dynamics simulations. Here, we show that our NCMC/MD method substantially enhances sidechain sampling, especially in systems where the torsional barrier to rotation is high (>10 kcal/mol). These barriers can be intrinsic torsional barriers or steric barriers imposed by the environment.</div><div>Overall, this may provide a promising strategy to selectively improve sidechain sampling in molecular simulations.</div>

Enhancing Sidechain Rotamer Sampling Using Non-Equilibrium Candidate Monte Carlo

10.26434/chemrxiv.7184876.v2 ◽

2019 ◽

Author(s):

Kalistyn H. Burley ◽

Samuel C. Gill ◽

Nathan M. Lim ◽

David Mobley

Keyword(s):

Molecular Dynamics ◽

Monte Carlo ◽

Ligand Binding ◽

Electrostatic Interactions ◽

Molecular Simulations ◽

Adequate Sampling ◽

Binding Pockets ◽

Sidechain Rotamers ◽

Dynamics Simulations ◽

<div>Molecular simulations are a valuable tool for studying biomolecular motions and thermodynamics. However, such motions can be slow compared to simulation timescales, yet critical. Specifically, adequate sampling of sidechain motions in protein binding pockets proves crucial for obtaining accurate estimates of ligand binding free energies from molecular simulations. The timescale of sidechain rotamer flips can range from a few ps to several hundred ns or longer, particularly in crowded environments like the interior of proteins. Here, we apply a mixed non-equilibrium candidate Monte Carlo (NCMC)/molecular dynamics (MD) method to enhance sampling of sidechain rotamers. The NCMC portion of our method applies a switching protocol wherein the steric and electrostatic interactions between target sidechain atoms and the surrounding environment are cycled off and then back on during the course of a move proposal. Between NCMC move proposals, simulation of the system continues via traditional molecular dynamics. Here, we first validate this approach on a simple, solvated valine-alanine dipeptide system and then apply it to a well-studied model ligand binding site in T4 lysozyme L99A. We compute the rate of rotamer transitions for a valine sidechain using our approach and compare it to that of traditional molecular dynamics simulations. Here, we show that our NCMC/MD method substantially enhances sidechain sampling, especially in systems where the torsional barrier to rotation is high (>10 kcal/mol). These barriers can be intrinsic torsional barriers or steric barriers imposed by the environment.</div><div>Overall, this may provide a promising strategy to selectively improve sidechain sampling in molecular simulations.</div>

A Study of Permeation of n-Butane through ZSM-5 Membrane by Using Monte Carlo and Equilibrium/Non-Equilibrium Molecular Dynamics Simulations.

JOURNAL OF CHEMICAL ENGINEERING OF JAPAN ◽

10.1252/jcej.36.313 ◽

2003 ◽

Vol 36 (3) ◽

pp. 313-321 ◽

Cited By ~ 5

Author(s):

Shin-ichi Furukawa ◽

Tomoshige Nitta

Keyword(s):

Molecular Dynamics ◽

Monte Carlo ◽

Non Equilibrium Molecular Dynamics ◽

Dynamics Simulations ◽

Fragment Pose Prediction Using Non-Equilibrium Candidate Monte Carlo and Molecular Dynamics Simulations

10.26434/chemrxiv.10032218 ◽

2019 ◽

Author(s):

Nathan M. Lim ◽

Meghan Osato ◽

Gregory L. Warren ◽

David L. Mobley

Keyword(s):

Crystal Structure ◽

Molecular Dynamics ◽

Monte Carlo ◽

Ligand Binding ◽

Md Simulations ◽

Binding Mode ◽

Protein Crystal ◽

Pose Prediction ◽

Binding Modes ◽

<div>Part of early stage drug discovery involves determining how molecules may bind to the target protein. Through understanding where and how molecules bind, chemists can begin to build ideas on how to design improvements to increase binding affinities. In this retrospective study, we compare how computational approaches like docking, molecular dynamics (MD) simulations, and a non-equilibrium candidate Monte Carlo (NCMC) based method (NCMC+MD) perform in predicting binding modes for a set of 12 fragment-like molecules which bind to soluble epoxide hydrolase. We evaluate each method's effectiveness in identifying the dominant binding mode and finding any additional binding modes (if any). Then, we compare our predicted binding modes to experimentally obtained X-ray crystal structures.</div><div>We dock each of the 12 small molecules into the apo-protein crystal structure and then run simulations up to 1 microsecond each. Small and fragment-like molecules likely have smaller energy barriers separating different binding modes by virtue of relatively fewer and weaker interactions relative to drug-like molecules, and thus likely undergo more rapid binding mode transitions. We expect, thus, to see more rapid transitions betweeen binding modes in our study. </div><div><br></div><div>Following this, we build Markov State Models (MSM) to define our stable ligand binding modes. We investigate if adequate sampling of ligand binding modes and transitions between them can occur at the microsecond timescale using traditional MD or a hybrid NCMC+MD simulation approach. Our findings suggest that even with small fragment-like molecules, we fail to sample all the crystallographic binding modes using microsecond MD simulations, but using NCMC+MD we have better success in sampling the crystal structure while obtaining the correct populations.</div>

Fragment Pose Prediction Using Non-Equilibrium Candidate Monte Carlo and Molecular Dynamics Simulations

10.26434/chemrxiv.10032218.v2 ◽

2019 ◽

Author(s):

Nathan M. Lim ◽

Meghan Osato ◽

Gregory L. Warren ◽

David L. Mobley

Keyword(s):

Crystal Structure ◽

Molecular Dynamics ◽

Monte Carlo ◽

Ligand Binding ◽

Md Simulations ◽

Binding Mode ◽

Protein Crystal ◽

Pose Prediction ◽

Binding Modes ◽

<div>Part of early stage drug discovery involves determining how molecules may bind to the target protein. Through understanding where and how molecules bind, chemists can begin to build ideas on how to design improvements to increase binding affinities. In this retrospective study, we compare how computational approaches like docking, molecular dynamics (MD) simulations, and a non-equilibrium candidate Monte Carlo (NCMC) based method (NCMC+MD) perform in predicting binding modes for a set of 12 fragment-like molecules which bind to soluble epoxide hydrolase. We evaluate each method's effectiveness in identifying the dominant binding mode and finding any additional binding modes (if any). Then, we compare our predicted binding modes to experimentally obtained X-ray crystal structures.</div><div>We dock each of the 12 small molecules into the apo-protein crystal structure and then run simulations up to 1 microsecond each. Small and fragment-like molecules likely have smaller energy barriers separating different binding modes by virtue of relatively fewer and weaker interactions relative to drug-like molecules, and thus likely undergo more rapid binding mode transitions. We expect, thus, to see more rapid transitions betweeen binding modes in our study. </div><div><br></div><div>Following this, we build Markov State Models (MSM) to define our stable ligand binding modes. We investigate if adequate sampling of ligand binding modes and transitions between them can occur at the microsecond timescale using traditional MD or a hybrid NCMC+MD simulation approach. Our findings suggest that even with small fragment-like molecules, we fail to sample all the crystallographic binding modes using microsecond MD simulations, but using NCMC+MD we have better success in sampling the crystal structure while obtaining the correct populations.</div>

Fragment Pose Prediction Using Non-equilibrium Candidate Monte Carlo and Molecular Dynamics Simulations

Journal of Chemical Theory and Computation ◽

10.1021/acs.jctc.9b01096 ◽

2020 ◽

Vol 16 (4) ◽

pp. 2778-2794 ◽

Cited By ~ 3

Author(s):

Nathan M. Lim ◽

Meghan Osato ◽

Gregory L. Warren ◽

David L. Mobley

Keyword(s):

Molecular Dynamics ◽

Monte Carlo ◽

Pose Prediction ◽

Dynamics Simulations ◽

Handling Electrostatic Interactions in Molecular Simulations: A Systematic Study

Collection of Czechoslovak Chemical Communications ◽

10.1135/cccc20080481 ◽

2008 ◽

Vol 73 (4) ◽

pp. 481-506 ◽

Cited By ~ 11

Author(s):

Jiří Kolafa ◽

Filip Moučka ◽

Ivo Nezbeda

Keyword(s):

Molecular Dynamics ◽

Monte Carlo ◽

Long Range ◽

Electrostatic Interactions ◽

Short Range ◽

Ewald Summation ◽

Field Methods ◽

Reaction Field ◽

Lennard Jones ◽

Dynamics Simulations

Two qualitatively different models with strong long-range electrostatic interactions, Lennard-Jones diatomics with an embedded dipole moment and TIP4P/2005 water, are considered in extensive Monte Carlo and molecular dynamics simulations to systematically study the differences in results caused by different treatments of the long-range electrostatic interactions. In addition to the standard Ewald summation and reaction field methods, we consider also two variants of short-range approximations. Both thermodynamic and structural properties, and both homogeneous and inhomogeneous phases are considered. It is shown that the accuracy of the short-range approximations with carefully selected parameters may be sufficient for a number of applications; however, in some cases one can encounter accuracy limits or structural or other artifacts.

Fragment Pose Prediction Using Non-Equilibrium Candidate Monte Carlo and Molecular Dynamics Simulations

10.26434/chemrxiv.10032218.v1 ◽

2019 ◽

Author(s):

Nathan M. Lim ◽

Meghan Osato ◽

Gregory L. Warren ◽

David L. Mobley

Keyword(s):

Crystal Structure ◽

Molecular Dynamics ◽

Monte Carlo ◽

Ligand Binding ◽

Md Simulations ◽

Binding Mode ◽

Protein Crystal ◽

Pose Prediction ◽

Binding Modes ◽

<div>Part of early stage drug discovery involves determining how molecules may bind to the target protein. Through understanding where and how molecules bind, chemists can begin to build ideas on how to design improvements to increase binding affinities. In this retrospective study, we compare how computational approaches like docking, molecular dynamics (MD) simulations, and a non-equilibrium candidate Monte Carlo (NCMC) based method (NCMC+MD) perform in predicting binding modes for a set of 12 fragment-like molecules which bind to soluble epoxide hydrolase. We evaluate each method's effectiveness in identifying the dominant binding mode and finding any additional binding modes (if any). Then, we compare our predicted binding modes to experimentally obtained X-ray crystal structures.</div><div>We dock each of the 12 small molecules into the apo-protein crystal structure and then run simulations up to 1 microsecond each. Small and fragment-like molecules likely have smaller energy barriers separating different binding modes by virtue of relatively fewer and weaker interactions relative to drug-like molecules, and thus likely undergo more rapid binding mode transitions. We expect, thus, to see more rapid transitions betweeen binding modes in our study. </div><div><br></div><div>Following this, we build Markov State Models (MSM) to define our stable ligand binding modes. We investigate if adequate sampling of ligand binding modes and transitions between them can occur at the microsecond timescale using traditional MD or a hybrid NCMC+MD simulation approach. Our findings suggest that even with small fragment-like molecules, we fail to sample all the crystallographic binding modes using microsecond MD simulations, but using NCMC+MD we have better success in sampling the crystal structure while obtaining the correct populations.</div>

Exploring secondary interactions and the role of temperature in moisture-contaminated polymer networks through molecular simulations

Soft Matter ◽

10.1039/d0sm02009e ◽

2021 ◽

Vol 17 (10) ◽

pp. 2942-2956

Author(s):

Rishabh D. Guha ◽

Ogheneovo Idolor ◽

Katherine Berkowitz ◽

Melissa Pasquinelli ◽

Landon R. Grace

Keyword(s):

Molecular Dynamics ◽

Temperature Variation ◽

Polymer Networks ◽

Molecular Simulations ◽

Effect Of Temperature ◽

Secondary Interactions ◽

Dynamics Simulations ◽

Secondary Bonding

We investigated the effect of temperature variation on the secondary bonding interactions between absorbed moisture and epoxies with different morphologies using molecular dynamics simulations.

Mechanistic analysis of light-driven overcrowded alkene-based molecular motors by multiscale molecular simulations

Physical Chemistry Chemical Physics ◽

10.1039/d0cp06685k ◽

2021 ◽

Vol 23 (14) ◽

pp. 8525-8540

Author(s):

Mudong Feng ◽

Michael K. Gilson

Keyword(s):

Molecular Dynamics ◽

Excited State ◽

Ground State ◽

Molecular Motors ◽

Motor Performance ◽

Molecular Simulations ◽

Mechanistic Analysis ◽

Dynamics Simulations ◽

Shed Light

Ground-state and excited-state molecular dynamics simulations shed light on the rotation mechanism of small, light-driven molecular motors and predict motor performance. How fast can they rotate; how much torque and power can they generate?