ArticleACS omega2023
MetaDOCK: A Combinatorial Molecular Docking Approach.
Article in ACS omega, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 38 citations in OpenAlex.
- DockM8: an all-in-one open-source platform for consensus virtual screening in drug design.Journal of cheminformatics · 2026Article
- Artificial intelligence and ultra-high performance computing methods and experiments for drug discovery: virtual screening, deep learning, molecular dynamics simulations, ADMET modelling, and experimental validation.Molecular biomedicine · 2026Review
- Drug Repurposing Uncovers New Chemical Scaffolds as Potent Urease Inhibitors: A Comprehensive Computational Study.International journal of molecular sciences · 2026Article
- Using transcriptomics and molecular docking to uncover the pharmacological targets and its associated biological mechanisms of paeoniflorigenone in treating bladder cancer.Discover oncology · 2026Article
- Contrastive learning-based drug screening model for GluN1/GluN3A inhibitors.Acta pharmacologica Sinica · 2025Article
- Integrating Hydrogen Exchange with Molecular Dynamics for Improved Ligand Binding Predictions.Journal of chemical information and modeling · 2025Article
- Determining the optimal antioxidant strategy: a comparative analysis of extraction methods inTurkish journal of biology = Turk biyoloji dergisi · 2025Article
- Revolutionizing Molecular Design for Innovative Therapeutic Applications through Artificial Intelligence.Molecules (Basel, Switzerland) · 2024Review
- Considerations Around Structure-Based Drug Discovery for KRAS Using DOCK.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Small Molecule Inhibitors against the Bacterial PathogenCurrent medicinal chemistry · 2024Review
- Mechanism of Taxanes in the Treatment of Lung Cancer Based on Network Pharmacology and Molecular Docking.Current issues in molecular biology · 2023Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Molecular docking plays a major role in academic and industrial drug screening and discovery processes. Despite the availability of numerous docking software packages, there is a lot of scope for improvement for the docking algorithms in terms of becoming more reliable to replicate the experimental binding results. Here, we propose a combinatorial or consensus docking approach where complementary powers of the existing methods are captured. We created a meta-docking protocol by combining the results of AutoDock4.2, LeDock, and rDOCK programs as these are freely available, easy to use, and suitable for large-scale analysis and produced better performance on benchmarking studies. Rigorous benchmarking analyses were undertaken to evaluate the scoring, posing, and screening capability of our approach. Further, the performance measures were compared against one standard state-of-the-art commercial docking software, GOLD, and one freely available software, PLANTS. Performances of MetaDOCK for scoring, posing, and screening the protein-ligand complexes were found to be quite superior compared to the reference programs. Exhaustive molecular dynamics simulation and molecular mechanics Poisson-Boltzmann and surface area-based free energy estimation also suggest better energetic stability of the docking solutions produced by our meta-approach. We believe that the MetaDOCK approach is a useful packaging of the freely available software and provides a better alternative to the scientific community who are unable to afford costly commercial packages.
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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.