Gaussian Accelerated Molecular Dynamics (GaMD)

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.



Wang J, Arantes P, Bhattarai A, Hsu R, Pawnikar S, Huang Y-M, Palermo G* and Miao Y* (2021) Gaussian accelerated molecular dynamics: principles and applications. WIREs Computational Molecular Science: e1521. (Abstract | PDF)
Advanced Science News: A “time-accelerated computational microscope” provides biologists with powerful insights

Miao, Y.*, Feher V. and McCammon JA (2015) Gaussian Accelerated Molecular Dynamics: Unconstrained Enhanced Sampling and Free Energy Calculation. J Chemical Theory and Computation, 11(8): 3584-3595. (Abstract | PDF)

Pang, Y.T.#, Y. Miao#,*, Y. Wang* and J. A. McCammon* (2017) Gaussian accelerated molecular dynamics in NAMD, J Chemical Theory and Computation, 13(1): 9-19. (Abstract | PDF)

Y. Miao and J. A. McCammon (2017), Gaussian Accelerated Molecular Dynamics: Theory, Implementation and Applications. David Dixon (editor), Annual Reports in Computational Chemistry, DOI: 10.1016/bs.arcc.2017.06.005. (Abstract | PDF)


Ligand Gaussian Accelerated Molecular Dynamics (LiGaMD)

Based on GaMD, a new algorithm called ligand GaMD or “LiGaMD” has been developed to simulate ligand binding and unbinding. It works by selectively boosting the ligand non-bonded interaction potential energy. Another boost potential could be applied to the remaining potential energy of the entire system in a dual-boost algorithm (LiGaMD_Dual) to facilitate ligand binding. LiGaMD has been demonstrated on host-guest and protein-ligand binding model systems. Repetitive guest binding and unbinding in the β-cyclodextrin host were observed in hundreds-of-nanosecond LiGaMD simulations. The calculated binding free energies of guest molecules with sufficient sampling agreed excellently with experimental data (< 1.0 kcal/mol error). In comparison with previous microsecond-timescale conventional molecular dynamics simulations, accelerations of ligand kinetic rate constants in LiGaMD simulations were properly estimated using Kramers' rate theory. Furthermore, LiGaMD allowed us to capture repetitive dissociation and binding of the benzamidine inhibitor in trypsin within 1 μs simulations. The calculated ligand binding free energy and kinetic rate constants compared well with the experimental data. Therefore, LiGaMD provides a promising approach for characterizing ligand binding thermodynamics and kinetics simultaneously.



Miao, Y.; A. Bhattarai; and J. Wang, Ligand Gaussian accelerated molecular dynamics (LiGaMD): Characterization of ligand binding thermodynamics and kinetics. bioRxiv, 2020.

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