ArticleJournal of computer-aided molecular design2010
Improved docking, screening and selectivity prediction for small molecule nuclear receptor modulators using conformational ensembles.
Article in Journal of computer-aided molecular design, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
25 citing papers in PubMed, 62 citations in OpenAlex.
- Benchmarking reverse docking through AlphaFold2 human proteome.Protein science : a publication of the Protein Society · 2024Article
- Worth the Weight: Sub-Pocket EXplorer (SubPEx), a Weighted Ensemble Method to Enhance Binding-Pocket Conformational Sampling.Journal of chemical theory and computation · 2023Article
- Worth the weight: Sub-Pocket EXplorer (SubPEx), a weighted-ensemble method to enhance binding-pocket conformational sampling.bioRxiv : the preprint server for biology · 2023Article
- Article
- Review ofFrontiers in endocrinology · 2022Review
- Recent trends in artificial intelligence-driven identification and development of anti-neurodegenerative therapeutic agents.Molecular diversity · 2021Article
- An Integrative in silico Drug Repurposing Approach for Identification of Potential Inhibitors of SARS-CoV-2 Main Protease.Molecular informatics · 2021Article
- ALADDIN: Docking Approach Augmented by Machine Learning for Protein Structure Selection Yields Superior Virtual Screening Performance.Molecular informatics · 2020Article
- In Silico Predictions of Endocrine Disruptors Properties.Endocrinology · 2019Review
- Endocrine Disruption at the Androgen Receptor: Employing Molecular Dynamics and Docking for Improved Virtual Screening and Toxicity Prediction.International journal of molecular sciences · 2018Article
- Empirical Scoring Functions for Structure-Based Virtual Screening: Applications, Critical Aspects, and Challenges.Frontiers in pharmacology · 2018Review
- Metal-free O-H/C-H difunctionalization of phenols byChemical science · 2017Article
- Enhancing Virtual Screening Performance of Protein Kinases with Molecular Dynamics Simulations.Journal of chemical information and modeling · 2016Article
- Mapping functional group free energy patterns at protein occluded sites: nuclear receptors and G-protein coupled receptors.Journal of chemical information and modeling · 2015Article
- In silico identification and pharmacological evaluation of novel endocrine disrupting chemicals that act via the ligand-binding domain of the estrogen receptor α.Toxicological sciences : an official journal of the Society of Toxicology · 2014Article
- Receptor-ligand molecular docking.Biophysical reviews · 2014Review
- Docking to multiple pockets or ligand fields for screening, activity prediction and scaffold hopping.Future medicinal chemistry · 2014Article
- Designing Endocrine Disruption Out of the Next Generation of Chemicals.Green chemistry : an international journal and green chemistry resource : GC · 2013Article
- Conformational dynamics of CYP3A4 demonstrate the important role of Arg212 coupled with the opening of ingress, egress and solvent channels to dehydrogenation of 4-hydroxy-tamoxifen.Biochimica et biophysica acta · 2012Article
- Metformin interacts with AMPK through binding to γ subunit.Molecular and cellular biochemistry · 2012Article
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 1 country.
Funding
Abstract
Nuclear receptors (NRs) are ligand dependent transcriptional factors and play a key role in reproduction, development, and homeostasis of organism. NRs are potential targets for treatment of cancer and other diseases such as inflammatory diseases, and diabetes. In this study, we present a comprehensive library of pocket conformational ensembles of thirteen human nuclear receptors (NRs), and test the ability of these ensembles to recognize their ligands in virtual screening, as well as predict their binding geometry, functional type, and relative binding affinity. 157 known NR modulators and 66 structures were used as a benchmark. Our pocket ensemble library correctly predicted the ligand binding poses in 94% of the cases. The models were also highly selective for the active ligands in virtual screening, with the areas under the ROC curves ranging from 82 to a remarkable 99%. Using the computationally determined receptor-specific binding energy offsets, we showed that the ensembles can be used for predicting selectivity profiles of NR ligands. Our results evaluate and demonstrate the advantages of using receptor ensembles for compound docking, screening, and profiling.
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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.