ArticlePloS one2019
The integration of pharmacophore-based 3D QSAR modeling and virtual screening in safety profiling: A case study to identify antagonistic activities against adenosine receptor, A2A, using 1,897 known drugs.
Article in PloS one, 2019. 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.
- 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
- General structure-activity relationship models for the inhibitors of Adenosine receptors: A machine learning approach.Molecular diversity · 2025Article
- Assessing the Inhibitory Potential of Natural Compounds for Targeting the CrtM Proteins in Methicillin-ResistantCurrent medicinal chemistry · 2025Article
- Inhibition of SARS-CoV-2 NSP-15 by Uridine-5'-Monophosphate Analogues Using QSAR Modelling, Molecular Dynamics Simulations, and Free Energy Landscape.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2024Article
- Using computer tools for the evaluation of biodegradability, toxicity, and activity on the AT1 receptor of degradation products identified in the removal of valsartan by using photo-electro-Fenton process.Environmental science and pollution research international · 2021Article
- Advances in Applying Computer-Aided Drug Design for Neurodegenerative Diseases.International journal of molecular sciences · 2021Review
- Generative chemistry: drug discovery with deep learning generative models.Journal of molecular modeling · 2021Review
- G protein-coupled receptors: structure- and function-based drug discovery.Signal transduction and targeted therapy · 2021Review
- 3D-QSAR-Based Pharmacophore Modeling, Virtual Screening, and Molecular Docking Studies for Identification of Tubulin Inhibitors with Potential Anticancer Activity.BioMed research international · 2021Article
- Covalent allosteric modulation: An emerging strategy for GPCRs drug discovery.European journal of medicinal chemistry · 2020Review
- A Taxicab geometry quantification system to evaluate the performance of in silico methods: a case study on adenosine receptors ligands.Journal of computer-aided molecular design · 2020Article
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Authors and funding
4 authors.
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Abstract
Safety pharmacology screening against a wide range of unintended vital targets using in vitro assays is crucial to understand off-target interactions with drug candidates. With the increasing demand for in vitro assays, ligand- and structure-based virtual screening approaches have been evaluated for potential utilization in safety profiling. Although ligand based approaches have been actively applied in retrospective analysis or prospectively within well-defined chemical space during the early discovery stage (i.e., HTS screening and lead optimization), virtual screening is rarely implemented in later stage of drug discovery (i.e., safety). Here we present a case study to evaluate ligand-based 3D QSAR models built based on in vitro antagonistic activity data against adenosine receptor 2A (A2A). The resulting models, obtained from 268 chemically diverse compounds, were used to test a set of 1,897 chemically distinct drugs, simulating the real-world challenge of safety screening when presented with novel chemistry and a limited training set. Due to the unique requirements of safety screening versus discovery screening, the limitations of 3D QSAR methods (i.e., chemotypes, dependence on large training set, and prone to false positives) are less critical than early discovery screen. We demonstrated that 3D QSAR modeling can be effectively applied in safety assessment prior to in vitro assays, even with chemotypes that are drastically different from training compounds. It is also worth noting that our model is able to adequately make the mechanistic distinction between agonists and antagonists, which is important to inform subsequent in vivo studies. Overall, we present an in-depth analysis of the appropriate utilization and interpretation of pharmacophore-based 3D QSAR models for safety screening.
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