ArticleJournal of computer-aided molecular design2004
Docking and scoring of metallo-beta-lactamases inhibitors.
Article in Journal of computer-aided molecular design, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 31 citations in OpenAlex.
- Prioritizing Small Sets of Molecules for Synthesis through in-silico Tools: A Comparison of Common Ranking Methods.ChemMedChem · 2023Article
- Discovery of novel new Delhi metallo-β-lactamases-1 inhibitors by multistep virtual screening.PloS one · 2015Article
- Biapenem inactivation by B2 metallo β-lactamases: energy landscape of the hydrolysis reaction.PloS one · 2013Article
- Docking and scoring with ICM: the benchmarking results and strategies for improvement.Journal of computer-aided molecular design · 2012Article
- Docking of sialic acid analogues against influenza A hemagglutinin: a correlational study between experimentally measured and computationally estimated affinities.Journal of molecular modeling · 2010Article
- Evolving carbapenemases: can medicinal chemists advance one step ahead of the coming storm?Journal of medicinal chemistry · 2010Article
- Antimalarial drugs inhibit human 5-HT(3) and GABA(A) but not GABA(C) receptors.British journal of pharmacology · 2008Article
- The antimalarial drugs quinine, chloroquine and mefloquine are antagonists at 5-HT3 receptors.British journal of pharmacology · 2007Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The performance of the AutoDock, GOLD and FlexX docking programs was evaluated for docking of dicarboxylic acid inhibitors into metallo-beta-lactamases (MBLs). GOLD provided the best overall performance, with RMSDs between experimental and docked structures of 1.8-2.6 A and a good correlation between the experimentally determined MBL-inhibitor affinities and the GOLD scores. GOLD was selected for a test including a broad spectrum of inhibitors for which experimental MBL-inhibitor binding affinities are available. This study revealed that (1) for most compound classes (dicarboxylic acids, tetrazoles, sulfonylhydrazones, and peptide-like compounds) there is a good correlation between the experimentally determined MBL-inhibitor affinities and the GOLD scores, (2) the correlation only holds within a given class, that is, scores of compounds from different classes cannot be directly compared, (3) for some compound classes (e.g. small sulphur compounds) there is no direct correlation between the experimentally determined MBL-inhibitor affinities and the GOLD scores. Using partial least squares methods, a model with R2 = 0.82 and Q2 = 0.78 for the training set was obtained based on the GOLD score and descriptors associated with binding of the IMP-1 inhibitors to the enzyme. The external Q2 for the test set is 0.73. This final model for prediction of IMP-1 MBL-inhibitor affinity handled all known classes of MBL-inhibitors, except small sulphur 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.