Optimal charge-shaping functions for the particle–particle—particle–mesh (P3M) method for computing electrostatic interactions in molecular simulations

2000 ◽  
Vol 113 (23) ◽  
pp. 10464-10476 ◽  
Author(s):  
Philippe H. Hünenberger
Keyword(s):  
Electrostatic Interactions ◽  
Molecular Simulations

Lattice‐sum methods for calculating electrostatic interactions in molecular simulations

1995 ◽  
Vol 103 (8) ◽  
pp. 3014-3021 ◽  
Author(s):  
Brock A. Luty ◽  
Ilario G. Tironi ◽  
Wilfred F. van Gunsteren
Keyword(s):  
Electrostatic Interactions ◽  
Molecular Simulations ◽  
Lattice Sum

scholarly journals Enhancing Sidechain Rotamer Sampling Using Non-Equilibrium Candidate Monte Carlo

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 ◽  
Non Equilibrium

<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>

scholarly journals Enhancing Sidechain Rotamer Sampling Using Non-Equilibrium Candidate Monte Carlo

2018 ◽  
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 ◽  
Non Equilibrium

<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>

scholarly journals Enhancing Sidechain Rotamer Sampling Using Non-Equilibrium Candidate Monte Carlo

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 ◽  
Non Equilibrium

<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>

scholarly journals Correction Terms for Calculating Binding Free Energy Using Rates from Nonequilibrium Simulations

2020 ◽  
Author(s):  
Robert Hall ◽  
Tom Dixon ◽  
Alex Dickson
Keyword(s):  
Free Energy ◽  
Electrostatic Interactions ◽  
Binding Free Energy ◽  
Molecular Simulations ◽  
Binding Kinetics ◽  
Drug Candidate ◽  
Free Energies ◽  
Unbound States ◽  
Correction Terms ◽  
Binding Free Energies

<div>The free energy of a process is the fundamental quantity that determines its spontaneity or propensity at a given temperature. Binding free energy of a drug candidate to its biomolecular target is used as an objective quantity in drug design. Binding kinetics -- rates of association (k<sub>on</sub>) and dissociation (k<sub>off</sub>) -- have also demonstrated utility for their ability to predict efficacy and in some cases have been shown to be more predictive than the binding free energy alone. Although challenging, some methods exist to calculate binding kinetics from molecular simulations. While the kinetics of the binding process are related to the free energy by the log of their ratio, it is not straightforward to account for common, practical details pertaining to the calculation of rates in molecular simulations, such as the finite simulation volume or the particular definition of the ``bound" and ``unbound" states. Here we derive a set of correction terms that can be applied to calculations of binding free energies using rates observed in simulations. One term accounts for the particular definitions of the bound and unbound states. The second term accounts for residual electrostatic interactions that might still be present between the molecules, which is especially useful if one or both of the molecules carry an explicit charge. The third term accounts for the volume of the unbound state in the simulation box, which is useful to keep the simulated volume as small as possible during rate calculations. We apply these correction terms to revisit the calculation of binding free energies from rate constants for a host-guest system that was part of a blind prediction challenge, where significant deviations were observed between free energies calculated with rate ratios and those calculated from alchemical perturbation. The correction terms combine to significantly decrease the error with respect to computational benchmarks, from 3.4 to 0.76 kcal/mol.</div>

scholarly journals Correction Terms for Calculating Binding Free Energy Using Rates from Nonequilibrium Simulations

2020 ◽  
Author(s):  
Robert Hall ◽  
Tom Dixon ◽  
Alex Dickson
Keyword(s):  
Free Energy ◽  
Electrostatic Interactions ◽  
Binding Free Energy ◽  
Molecular Simulations ◽  
Binding Kinetics ◽  
Drug Candidate ◽  
Free Energies ◽  
Unbound States ◽  
Correction Terms ◽  
Binding Free Energies

<div>The free energy of a process is the fundamental quantity that determines its spontaneity or propensity at a given temperature. Binding free energy of a drug candidate to its biomolecular target is used as an objective quantity in drug design. Binding kinetics -- rates of association (k<sub>on</sub>) and dissociation (k<sub>off</sub>) -- have also demonstrated utility for their ability to predict efficacy and in some cases have been shown to be more predictive than the binding free energy alone. Although challenging, some methods exist to calculate binding kinetics from molecular simulations. While the kinetics of the binding process are related to the free energy by the log of their ratio, it is not straightforward to account for common, practical details pertaining to the calculation of rates in molecular simulations, such as the finite simulation volume or the particular definition of the ``bound" and ``unbound" states. Here we derive a set of correction terms that can be applied to calculations of binding free energies using rates observed in simulations. One term accounts for the particular definitions of the bound and unbound states. The second term accounts for residual electrostatic interactions that might still be present between the molecules, which is especially useful if one or both of the molecules carry an explicit charge. The third term accounts for the volume of the unbound state in the simulation box, which is useful to keep the simulated volume as small as possible during rate calculations. We apply these correction terms to revisit the calculation of binding free energies from rate constants for a host-guest system that was part of a blind prediction challenge, where significant deviations were observed between free energies calculated with rate ratios and those calculated from alchemical perturbation. The correction terms combine to significantly decrease the error with respect to computational benchmarks, from 3.4 to 0.76 kcal/mol.</div>

Sign in / Sign up

Export Citation Format

Share Document