ArticleJournal of chemical information and modeling2019
Getting Docking into Shape Using Negative Image-Based Rescoring.
Article in Journal of chemical information and modeling, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Benchmarking Docking Protocols on Predicting Alternative Binding Modes.Journal of chemical information and modeling · 2026Article
- Intrinsically disordered regions in the NLRP family of receptors act as regulatory hubs for inflammasome condensation and activation.Frontiers in immunology · 2026Article
- Evaluation of Dexamethasone and Swimming Exercise as Complementary Interventions in a Rat Sciatic Nerve Injury Model.Antioxidants (Basel, Switzerland) · 2025Article
- SIRT5: a potential target for discovering bioactive natural products.Journal of natural medicines · 2025Review
- Building shape-focused pharmacophore models for effective docking screening.Journal of cheminformatics · 2024Article
- ChemFlow_py: a flexible toolkit for docking and rescoring.Journal of computer-aided molecular design · 2023Article
- Virtual Screening Strategy to Identify Retinoic Acid-Related Orphan Receptor γt Modulators.Molecules (Basel, Switzerland) · 2023Article
- Innovative, rapid, high-throughput method for drug repurposing in a pandemic-A case study of SARS-CoV-2 and COVID-19.Frontiers in pharmacology · 2023Article
- Ligand-Enhanced Negative Images Optimized for Docking Rescoring.International journal of molecular sciences · 2022Article
- Identification of bio-active food compounds as potential SARS-CoV-2 PLpro inhibitors-modulators via negative image-based screening and computational simulations.Computers in biology and medicine · 2022Article
- Optimization of Cavity-Based Negative Images to Boost Docking Enrichment in Virtual Screening.Journal of chemical information and modeling · 2022Article
- Sdfconf: A Novel, Flexible, and Robust Molecular Data Management Tool.Journal of chemical information and modeling · 2022Article
- DockStream: a docking wrapper to enhance de novo molecular design.Journal of cheminformatics · 2021Article
- Supercomputing Pipelines Search for Therapeutics Against COVID-19.Computing in science & engineering · 2021Article
- A Perspective: Active Role of Lipids in Neurotransmitter Dynamics.Molecular neurobiology · 2020Review
- Screening of Natural Products Targeting SARS-CoV-2-ACE2 Receptor Interface - A MixMD Based HTVS Pipeline.Frontiers in chemistry · 2020Article
- Detection of Binding Sites on SARS-CoV-2 Spike Protein Receptor-Binding Domain by Molecular Dynamics Simulations in Mixed Solvents.IEEE/ACM transactions on computational biology and bioinformaticsArticle
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The failure of default scoring functions to ensure virtual screening enrichment is a persistent problem for the molecular docking algorithms used in structure-based drug discovery. To remedy this problem, elaborate rescoring and postprocessing schemes have been developed with a varying degree of success, specificity, and cost. The negative image-based rescoring (R-NiB) has been shown to improve the flexible docking performance markedly with a variety of drug targets. The yield improvement is achieved by comparing the alternative docking poses against the negative image of the target protein's ligand-binding cavity. In other words, the shape and electrostatics of the binding pocket is directly used in the similarity comparison to rank the explicit docking poses. Here, the PANTHER/ShaEP-based R-NiB methodology is tested with six popular docking softwares, including GLIDE, PLANTS, GOLD, DOCK, AUTODOCK, and AUTODOCK VINA, using five validated benchmark sets. Overall, the results indicate that R-NiB outperforms the default docking scoring consistently and inexpensively, demonstrating that the methodology is ready for wide-scale virtual screening usage.
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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.