ArticleJournal of chemical theory and computation2020
Ligand Gaussian Accelerated Molecular Dynamics (LiGaMD): Characterization of Ligand Binding Thermodynamics and Kinetics.
Article in Journal of chemical theory and computation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 92 papers.
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Who cites it
92 citing papers in PubMed, 184 citations in OpenAlex.
- ModBindProceedings of the National Academy of Sciences of the United States of America · 2026Article
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- Boosting Drug Discovery: Expanding the Applicability of Fragment Dissolved Molecular Dynamics to Accelerate Binding Mode Elucidation.Journal of chemical information and modeling · 2025Article
- More Sophisticated Is Not Always Better: A Comparison of Similarity Measures for Unsupervised Learning of Pathways in Biomolecular Simulations.The journal of physical chemistry. B · 2025Article
- A conserved mechanism of LRRC8 channel inhibition by two structurally distinct drugs.Communications biology · 2025Article
- In Silico discovery of novel androgen receptor inhibitors for prostate cancer therapy using virtual screening, molecular docking, and molecular dynamics simulations.Scientific reports · 2025Article
- Recent Developments in Amber Biomolecular Simulations.Journal of chemical information and modeling · 2025Article
- Symmetric Ligand Binding Pathways and Dual-State Bottleneck in [NiFe] Hydrogenases from Unbiased Molecular Dynamics.The journal of physical chemistry letters · 2025Article
- Residence time in drug discovery: current insights and future perspectives.Pharmacological reports : PR · 2025Review
- Article
- Deep learning-based dipeptidyl peptidase IV inhibitor screening, experimental validation, and GaMD/LiGaMD analysis.BMC biology · 2025Article
- Dissecting Large-Scale Structural Transitions in Membrane Transporters Using Advanced Simulation Technologies.The journal of physical chemistry. B · 2025Review
- Harnessing AlphaFold to reveal hERG channel conformational state secrets.bioRxiv : the preprint server for biology · 2025Article
- Diverse toxins exhibit a common binding mode to the nicotinic acetylcholine receptors.Biophysical journal · 2025Article
- Mechanistic Perspective on C-N and C-S Bond Construction Catalyzed by Cytochrome P450 Enzymes.ACS bio & med chem Au · 2025Review
- ModBind, a Rapid Simulation-Based Predictor of Ligand Binding and Off-Rates.Journal of chemical information and modeling · 2025Article
- Design, optimization, and ADMET evaluation of S11a-0000168202: A promising LIMK1 inhibitor for gastric cancer treatment.PloS one · 2025Article
32 more citing papers are in PubMed but not listed here.
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Calculations of ligand binding free energies and kinetic rates are important for drug design. However, such tasks have proven challenging in computational chemistry and biophysics. To address this challenge, we have developed a new computational method, ligand Gaussian accelerated molecular dynamics (LiGaMD), which selectively boosts the ligand nonbonded interaction potential energy based on the Gaussian accelerated molecular dynamics (GaMD) enhanced sampling technique. 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_Dual simulations. The calculated guest binding free energies agreed excellently with experimental data with <1.0 kcal/mol errors. Compared with converged microsecond-time scale conventional molecular dynamics simulations, the sampling errors of LiGaMD_Dual simulations were also <1.0 kcal/mol. 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. In summary, LiGaMD provides a powerful enhanced sampling approach for characterizing ligand binding thermodynamics and kinetics simultaneously, which is expected to facilitate computer-aided drug design.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.