ArticleFrontiers in chemistry2018
An Efficient Implementation of the Nwat-MMGBSA Method to Rescore Docking Results in Medium-Throughput Virtual Screenings.
Article in Frontiers in chemistry, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
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- Screening of potent STAT3-SH2 domain inhibitors from JAK/STAT compound library through molecular dynamics simulation.Molecular diversity · 2023Article
- Identifying potential ligand molecules EGFR mediated TNBC targeting the kinase domain-identification of customized drugs throughResearch in pharmaceutical sciences · 2023Article
- ChemFlow─From 2D Chemical Libraries to Protein-Ligand Binding Free Energies.Journal of chemical information and modeling · 2023Article
- Assessing How Residual Errors of Scoring Functions Correlate to Ligand Structural Features.International journal of molecular sciences · 2022Article
- PLAS-5k: Dataset of Protein-Ligand Affinities from Molecular Dynamics for Machine Learning Applications.Scientific data · 2022Article
- Potential COVID-19 Therapies from Computational Repurposing of Drugs and Natural Products against the SARS-CoV-2 Helicase.International journal of molecular sciences · 2022Article
- ReliableJournal of chemical information and modeling · 2022Article
- Phytochemical Characterization, Functional Nutrition, and Anti-Diabetic Potentials ofBioinformatics and biology insights · 2022Article
- Molecular docking studies, molecular dynamics and ADME/tox reveal therapeutic potentials of STOCK1N-69160 against papain-like protease of SARS-CoV-2.Molecular diversity · 2021Article
Corrections and comments
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4 authors.
Funding
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Abstract
Nwat-MMGBSA is a variant of MM-PB/GBSA based on the inclusion of a number of explicit water molecules that are the closest to the ligand in each frame of a molecular dynamics trajectory. This method demonstrated improved correlations between calculated and experimental binding energies in both protein-protein interactions and ligand-receptor complexes, in comparison to the standard MM-GBSA. A protocol optimization, aimed to maximize efficacy and efficiency, is discussed here considering penicillopepsin, HIV1-protease, and BCL-XL as test cases. Calculations were performed in triplicates on both classic HPC environments and on standard workstations equipped by a GPU card, evidencing no statistical differences in the results. No relevant differences in correlation to experiments were also observed when performing Nwat-MMGBSA calculations on 4 or 1 ns long trajectories. A fully automatic workflow for structure-based virtual screening, performing from library set-up to docking and Nwat-MMGBSA rescoring, has then been developed. The protocol has been tested against no rescoring or standard MM-GBSA rescoring within a retrospective virtual screening of inhibitors of AmpC β-lactamase and of the Rac1-Tiam1 protein-protein interaction. In both cases, Nwat-MMGBSA rescoring provided a statistically significant increase in the ROC AUCs of between 20 and 30%, compared to docking scoring or to standard MM-GBSA rescoring.
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