ReviewMethods in molecular biology (Clifton, N.J.)2021
Free Energy Calculations for Protein-Ligand Binding Prediction.
Review in Methods in molecular biology (Clifton, N.J.), 2021. 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.
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- The physics-AI dialogue in drug design.RSC medicinal chemistry · 2025Review
- Estimation of Absolute Binding Free Energies for Drugs That Bind Multiple Proteins.Journal of chemical information and modeling · 2025Article
- Multi-target therapeutic potential of Neem (In silico pharmacology · 2025Article
- Leveraging large language models to predict antibody biological activity against influenza A hemagglutinin.Computational and structural biotechnology journal · 2025Article
- 4-(1-Methylamino)ethylidene-1,5-disubstituted pyrrolidine-2,3-diones: synthesis, anti-inflammatory effect and in silico approaches.Beilstein journal of organic chemistry · 2025Article
- Searching for potential acetylcholinesterase inhibitors: a combined approach of multi-step similarity search, machine learning and molecular dynamics simulations.Royal Society open science · 2024Article
- Introducing the Automated Ligand Searcher.Journal of chemical information and modeling · 2023Article
- Screening and Biological Evaluation of Soluble Epoxide Hydrolase Inhibitors: Assessing the Role of Hydrophobicity in the Pharmacophore-Guided Search of Novel Hits.Journal of chemical information and modeling · 2023Article
- Lessons Learnt from COVID-19: Computational Strategies for Facing Present and Future Pandemics.International journal of molecular sciences · 2023Review
- Identification of natural inhibitor against L1 β-lactamase present in Stenotrophomonas maltophilia.Journal of molecular modeling · 2022Article
- A highly accurate metadynamics-based Dissociation Free Energy method to calculate protein-protein and protein-ligand binding potencies.Scientific reports · 2022Article
- CHARMM-GUI Free Energy Calculator for Practical Ligand Binding Free Energy Simulations with AMBER.Journal of chemical information and modeling · 2021Article
- A Computer-Driven Scaffold-Hopping Approach Generating New PTP1B Inhibitors from the Pyrrolo[1,2-a]quinoxaline Core.ChemMedChem · 2021Article
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3 authors.
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Abstract
Computational prediction of protein-ligand binding involves initial determination of the binding mode and subsequent evaluation of the strength of the protein-ligand interactions, which directly correlates with ligand binding affinities. As a consequence of increasing computer power, rigorous approaches to calculate protein-ligand binding affinities, such as free energy perturbation (FEP) methods, are becoming an essential part of the toolbox of computer-aided drug design. In this chapter, we provide a general overview of these methods and introduce the QFEP modules, which are open-source API workflows based on our molecular dynamics (MD) package Q. The module QligFEP allows estimation of relative binding affinities along ligand series, while QresFEP is a module to estimate binding affinity shifts caused by single-point mutations of the protein. We herein provide guidelines for the use of each of these modules based on data extracted from ligand-design projects. While these modules are stand-alone, the combined use of the two workflows in a drug-design project yields complementary perspectives of the ligand binding problem, providing two sides of the same coin. The selected case studies illustrate how to use QFEP to approach the two key questions associated with ligand binding prediction: identifying the most favorable binding mode from different alternatives and establishing structure-affinity relationships that allow the rational optimization of hit compounds.
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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.