ReviewJournal of chemical theory and computation2023
Perspectives on Ligand/Protein Binding Kinetics Simulations: Force Fields, Machine Learning, Sampling, and User-Friendliness.
Review in Journal of chemical theory and computation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Article
- Review
- Molecular Dynamics Simulations Demonstrate Reduced Antibiotic Affinity to Mirror Bacterial Targets.Computational and structural biotechnology journal · 2026Article
- Piperine: From Green Extraction to Clinical Translation-A Review.Drug design, development and therapy · 2026Review
- Computational and experimental design of L-amino acid-based alternatives to ketorolac.Scientific reports · 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
- Prediction of enzyme inhibition (ICJournal of molecular modeling · 2025Article
- Investigating the unbinding mechanisms and kinetics of MmpL3 inhibitors: A computational study.Protein science : a publication of the Protein Society · 2025Article
- Functional dynamics of G protein-coupled receptors reveal new routes for drug discovery.Nature reviews. Drug discovery · 2025Review
- Detection of Putative Ligand Dissociation Pathways in Proteins Using Site-Identification by Ligand Competitive Saturation.Journal of chemical information and modeling · 2025Article
- Pathway Specific Unbinding Free Energy Profiles of Ritonavir Dissociation from HIV-1 Protease.Biochemistry · 2025Article
- Host-Guest Binding Free Energies à la Carte: An Automated OneOPES Protocol.Journal of chemical theory and computation · 2024Article
- Computational screening of the effects of mutations on protein-protein off-rates and dissociation mechanisms by τRAMD.Communications biology · 2024Article
- The Open Force Field Initiative: Open Software and Open Science for Molecular Modeling.The journal of physical chemistry. B · 2024Article
- Mechanism of Ligand Binding to Theophylline RNA Aptamer.Journal of chemical information and modeling · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Computational techniques applied to drug discovery have gained considerable popularity for their ability to filter potentially active drugs from inactive ones, reducing the time scale and costs of preclinical investigations. The main focus of these studies has historically been the search for compounds endowed with high affinity for a specific molecular target to ensure the formation of stable and long-lasting complexes. Recent evidence has also correlated the in vivo drug efficacy with its binding kinetics, thus opening new fascinating scenarios for ligand/protein binding kinetic simulations in drug discovery. The present article examines the state of the art in the field, providing a brief summary of the most popular and advanced ligand/protein binding kinetics techniques and evaluating their current limitations and the potential solutions to reach more accurate kinetic models. Particular emphasis is put on the need for a paradigm change in the present methodologies toward ligand and protein parametrization, the force field problem, characterization of the transition states, the sampling issue, and algorithms' performance, user-friendliness, and data openness.
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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.