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An enhancement based on integrating protein\u2013ligand interaction with docking has previously been proposed, but its actual impact on improving screening outcomes has remained unclear. Here, we present a comprehensive assessment based on systematic benchmarking using a diverse set of class A G-protein-coupled receptors and different approaches to represent protein\u2013ligand, including dynamic patterns extracted from molecular dynamics simulations. Our results demonstrate that the combined approach overall improves the efficacy bias of selected ligands as compared to docking alone (ranking by scoring function). All tested variations prove broadly functional; however, the most sophisticated one\u2500incorporating simulation and a learning model\u2500emerges as the most robust alternative for a prospective setting. The analysis of two prospective cases, the design of both agonists and antagonists of CNR1 and the more challenging search for CXCR4 nonpeptidic agonist, reveals both great potential and inherent structural limitations, highlighting the need for an accurate and suitable three-dimensional structure.<\/jats:p>","DOI":"10.1021\/acs.jcim.6c02252","type":"journal-article","created":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T11:56:26Z","timestamp":1788436586000},"page":"12143-12162","source":"Crossref","is-referenced-by-count":0,"title":["Performances and Critical Limitations of Docking and\nProtein\u2013Ligand Interactions for Efficacy-Driven Virtual Screening\nTargeting Class A GPCRs"],"prefix":"10.1021","volume":"66","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2114-8683","authenticated-orcid":true,"given":"Luca","family":"Chiesa","sequence":"first","affiliation":[{"name":"Laboratoire d\u2019Innovation The\u0301rapeutique, UMR 7200 CNRS, Universite\u0301 de Strasbourg , ,","place":["Illkirch-Graffenstaden, France, 67400"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5434-0906","authenticated-orcid":true,"given":"Guillaume","family":"Bret","sequence":"additional","affiliation":[{"name":"Laboratoire d\u2019Innovation The\u0301rapeutique, UMR 7200 CNRS, Universite\u0301 de Strasbourg , ,","place":["Illkirch-Graffenstaden, France, 67400"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Se\u0301verine","family":"Schneider","sequence":"additional","affiliation":[{"name":"Laboratoire d\u2019Innovation The\u0301rapeutique, UMR 7200 CNRS, Universite\u0301 de Strasbourg , ,","place":["Illkirch-Graffenstaden, France, 67400"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8723-9502","authenticated-orcid":true,"given":"Martine","family":"Schmitt","sequence":"additional","affiliation":[{"name":"Laboratoire d\u2019Innovation The\u0301rapeutique, UMR 7200 CNRS, Universite\u0301 de Strasbourg , ,","place":["Illkirch-Graffenstaden, France, 67400"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4122-0929","authenticated-orcid":true,"given":"Fre\u0301de\u0301ric","family":"Bihel","sequence":"additional","affiliation":[{"name":"Laboratoire d\u2019Innovation The\u0301rapeutique, UMR 7200 CNRS, Universite\u0301 de Strasbourg , ,","place":["Illkirch-Graffenstaden, France, 67400"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Omolade","family":"Otun","sequence":"additional","affiliation":[{"name":"Institut de Ge\u0301nomique Fonctionnelle, Universite\u0301 de Montpellier, CNRS, INSERM , ,","place":["Montpellier, France, 34000"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mathias","family":"Lescuyer","sequence":"additional","affiliation":[{"name":"Institut de Ge\u0301nomique Fonctionnelle, Universite\u0301 de Montpellier, CNRS, INSERM , ,","place":["Montpellier, France, 34000"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thierry","family":"Durroux","sequence":"additional","affiliation":[{"name":"Institut de Ge\u0301nomique Fonctionnelle, Universite\u0301 de Montpellier, CNRS, INSERM , ,","place":["Montpellier, France, 34000"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9320-4840","authenticated-orcid":true,"given":"Esther","family":"Kellenberger","sequence":"additional","affiliation":[{"name":"Laboratoire d\u2019Innovation The\u0301rapeutique, UMR 7200 CNRS, Universite\u0301 de Strasbourg , ,","place":["Illkirch-Graffenstaden, France, 67400"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"316","published-online":{"date-parts":[[2026,9,1]]},"reference":[{"issue":"6","key":"2026092810070204700_cit1","doi-asserted-by":"publisher","first-page":"458","DOI":"10.1038\/s41573-025-01139-y","article-title":"GPCR Drug Discovery: New Agents,\nTargets and Indications","volume":"24","author":"Lorente","year":"2025","journal-title":"Nat. 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Inf Model"},{"issue":"7619","key":"2026092810070204700_cit24","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1038\/nature19112","article-title":"Structure-Based Discovery of Opioid\nAnalgesics with Reduced Side Effects","volume":"537","author":"Manglik","year":"2016","journal-title":"Nature"},{"issue":"6361","key":"2026092810070204700_cit25","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1126\/science.aan5468","article-title":"4 Dopamine Receptor High-Resolution\nStructures Enable the Discovery of Selective Agonists","volume":"358","author":"Wang","year":"2017","journal-title":"Science"},{"issue":"7","key":"2026092810070204700_cit26","doi-asserted-by":"publisher","first-page":"3070","DOI":"10.1021\/acs.jmedchem.7b00109","article-title":"Structure-Based\nDiscovery of New Antagonist and Biased Agonist Chemotypes for the\nKappa Opioid Receptor","volume":"60","author":"Zheng","year":"2017","journal-title":"J. Med. 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Model."},{"issue":"2","key":"2026092810070204700_cit30","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1038\/nrd722","article-title":"Efficacy at\nG-Protein-Coupled Receptors","volume":"1","author":"Kenakin","year":"2002","journal-title":"Nat. Rev. Drug\nDiscov"},{"issue":"5","key":"2026092810070204700_cit31","doi-asserted-by":"publisher","first-page":"561","DOI":"10.1002\/jcc.22893","article-title":"In Silico Screening for Agonists and Blockers of the \u03922 Adrenergic\nReceptor: Implications of Inactive and Activated State Structures","volume":"33","author":"Costanzi","year":"2012","journal-title":"J. Comput. Chem."},{"issue":"11","key":"2026092810070204700_cit32","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1009152","article-title":"Deciphering\nConformational Selectivity in the A2A Adenosine G Protein-Coupled\nReceptor by Free Energy Simulations","volume":"17","author":"Jespers","year":"2021","journal-title":"PLOS Computational\nBiol."},{"issue":"22","key":"2026092810070204700_cit33","doi-asserted-by":"publisher","first-page":"8414","DOI":"10.1021\/acs.jctc.3c00899","article-title":"Is the Functional Response\nof a Receptor Determined by the Thermodynamics of Ligand Binding?","volume":"19","author":"Vo\u0308gele","year":"2023","journal-title":"J. Chem. Theory Comput."},{"issue":"22","key":"2026092810070204700_cit34","doi-asserted-by":"publisher","DOI":"10.1002\/ange.202218959","article-title":"Design of Drug Efficacy\nGuided by Free Energy Simulations of the \u03b2 2 -Adrenoceptor","volume":"135","author":"Panel","year":"2023","journal-title":"Angew. 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Chem."},{"key":"2026092810070204700_cit42","doi-asserted-by":"publisher","first-page":"631","DOI":"10.1016\/j.ejmech.2018.10.060","article-title":"Structure-Based\nExploration and Pharmacological Evaluation of N-Substituted\nPiperidin-4-Yl-Methanamine CXCR4 Chemokine Receptor Antagonists","volume":"162","author":"Adlere","year":"2019","journal-title":"Eur. J. Med. Chem."},{"issue":"9","key":"2026092810070204700_cit43","doi-asserted-by":"publisher","first-page":"2235","DOI":"10.1021\/acs.jpclett.8b00633","article-title":"Agonists of G-Protein-Coupled Odorant Receptors Are\nPredicted from Chemical Features","volume":"9","author":"Bushdid","year":"2018","journal-title":"J. Phys. Chem.\nLett."},{"issue":"6","key":"2026092810070204700_cit44","doi-asserted-by":"publisher","first-page":"2675","DOI":"10.1021\/acs.jcim.1c00439","article-title":"Predictive Models to\nIdentify Small\nMolecule Activators and Inhibitors of Opioid Receptors","volume":"61","author":"Sakamuru","year":"2021","journal-title":"J. Chem. Inf. Model."},{"issue":"11","key":"2026092810070204700_cit45","doi-asserted-by":"publisher","first-page":"3248","DOI":"10.1021\/acs.jcim.2c01531","article-title":"Activity Models of\nKey GPCR Families in the Central\nNervous System: A Tool for Many Purposes","volume":"63","author":"El-Atawneh","year":"2023","journal-title":"J.\nChem. Inf. Model."},{"issue":"9","key":"2026092810070204700_cit46","doi-asserted-by":"publisher","first-page":"2561","DOI":"10.1093\/bioinformatics\/btac154","article-title":"DeepREAL: A Deep Learning\nPowered Multi-Scale Modeling Framework for Predicting out-of-Distribution\nLigand-Induced GPCR Activity","volume":"38","author":"Cai","year":"2022","journal-title":"Bioinformatics"},{"issue":"5","key":"2026092810070204700_cit47","doi-asserted-by":"publisher","DOI":"10.1002\/prp2.994","article-title":"Combined Docking and Machine Learning\nIdentify Key Molecular Determinants of Ligand Pharmacological Activity\non \u03922 Adrenoceptor","volume":"10","author":"Jime\u0301nez-Rose\u0301s","year":"2022","journal-title":"Pharmacol. Res. 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