ArticleACS medicinal chemistry letters2022
Computational Prediction of the Binding Pose of Metal-Binding Pharmacophores.
Article in ACS medicinal chemistry letters, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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Who cites it
4 citing papers in PubMed.
- Zinc Affinity of Benzamide-Based Histone Deacetylase Inhibitors: A DFT Study.Molecules (Basel, Switzerland) · 2026Article
- An updated survey on the recent advancement of antimalarial molecules: synthetic methodologies and SAR studies.Molecular diversity · 2025Review
- Structural Studies of Inhibitors with Clinically Relevant Influenza Endonuclease Variants.Biochemistry · 2024Article
- Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Computational modeling of inhibitors for metalloenzymes in virtual drug development campaigns has proven challenging. To overcome this limitation, a technique for predicting the binding pose of metal-binding pharmacophores (MBPs) is presented. Using a combination of density functional theory (DFT) calculations and docking using a genetic algorithm, inhibitor binding was evaluated in silico and compared with inhibitor-enzyme cocrystal structures. The predicted binding poses were found to be consistent with the cocrystal structures. The computational strategy presented represents a useful tool for predicting metalloenzyme-MBP interactions.
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Registered trials
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