Gaussian accelerated molecular dynamics: Principles and applications

Abstract

Gaussian accelerated molecular dynamics (GaMD) is a robust computational method for simultaneous unconstrained enhanced sampling and free energy calculations of biomolecules. It works by adding a harmonic boost potential to smooth biomolecular potential energy surface and reduce energy barriers. GaMD greatly accelerates biomolecular simulations by orders of magnitude. Without the need to set predefined reaction coordinates or collective variables, GaMD provides unconstrained enhanced sampling and is advantageous for simulating complex biological processes. The GaMD boost potential exhibits a Gaussian distribution, thereby allowing for energetic reweighting via cumulant expansion to the second order (i.e., “Gaussian approximation”). This leads to accurate reconstruction of free energy landscapes of biomolecules. Hybrid schemes with other enhanced sampling methods, such as the replica‐exchange GaMD (rex‐GaMD) and replica‐exchange umbrella sampling GaMD (GaREUS), have also been introduced, further improving sampling and free energy calculations. Recently, new “selective GaMD” algorithms including the Ligand GaMD (LiGaMD) and Peptide GaMD (Pep‐GaMD) enabled microsecond simulations to capture repetitive dissociation and binding of small‐molecule ligands and highly flexible peptides. The simulations then allowed highly efficient quantitative characterization of the ligand/peptide binding thermodynamics and kinetics. Taken together, GaMD and its innovative variants are applicable to simulate a wide variety of biomolecular dynamics, including protein folding, conformational changes and allostery, ligand binding, peptide binding, protein–protein/nucleic acid/carbohydrate interactions, and carbohydrate/nucleic acid interactions. In this review, we present principles of the GaMD algorithms and recent applications in biomolecular simulations and drug design. This article is categorized under: Structure and Mechanism > Computational Biochemistry and Biophysics Molecular and Statistical Mechanics > Molecular Dynamics and Monte‐Carlo Methods Molecular and Statistical Mechanics > Free Energy Methods

Specific Engineered G Protein Coupling to Histamine Receptors Revealed from Cellular Assay Experiments and Accelerated Molecular Dynamics Simulations

“…Thus, enhanced sampling methods have been applied to improve the simulations of GPCR–G protein interactions [ 62 , 66 ]. Among these methods, Gaussian accelerated molecular dynamics (GaMD) is a robust method that allows for unconstrained enhanced sampling and free energy calculations of large biomolecules [ 67 , 68 , 69 , 70 ]. GaMD has been applied to successfully simulate protein folding [ 68 , 71 ], protein-ligand binding and unbinding [ 67 , 68 , 72 ], GPCR activation [ 72 ], and binding to a G protein mimetic nanobody [ 73 ].…”

Recognition of single-stranded nucleic acids by small-molecule splicing modulators

“…Then 40 ns GaMD equilibration after applying the boost potential was performed. All GaMD simulations were run at the ‘dual-boost’ level by setting the reference energy to the lower bound; i.e., E = V max ( 26 , 27 ). One boost potential is applied to the dihedral energetic term and another to the total potential energetic term.…”

“…Molecular dynamics (MD) has proven useful in simulations of the structural dynamics of nucleic acid ( 20 , 21 ), notably nucleic acid–ligand interactions ( 22–25 ). We performed all-atom simulations using a robust Gaussian accelerated MD (GaMD) ( 26 , 27 ) method to obtain new insights into the mechanism of risdiplam analogue binding to the target nucleic acids.…”

Cosolvent and Dynamic Effects in Binding Pocket Search by Docking Simulations

“…The computational methods developed for structure-based drug design fall into two main categories: de novo design methods construct new, tailored ligands, while docking methods select ligands complimentary to the target from the existing compound space. 37 Although different methodologies have been widely employed to investigate the binding of ligands to proteins, such as Monte Carlo techniques 38,39 and Gaussian accelerated molecular dynamics (MD), 40,41 the vast majority of theoretical drug design investigations rely on docking calculations due to their computational efficiency. Among the docking methods, virtual screening (VS) has emerged as a particularly successful technique.…”