{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"bioRxiv"}],"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T12:03:38Z","timestamp":1775045018387,"version":"3.50.1"},"posted":{"date-parts":[[2026,3,29]]},"group-title":"Pharmacology and Toxicology","reference-count":23,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2026,3,29]],"date-time":"2026-03-29T00:00:00Z","timestamp":1774742400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.biorxiv.org\/about\/FAQ#license"}],"funder":[{"DOI":"10.13039\/100000062","name":"National Institute of Diabetes and Digestive and Kidney Diseases","doi-asserted-by":"crossref","award":["R01DK137299"],"award-info":[{"award-number":["R01DK137299"]}],"id":[{"id":"10.13039\/100000062","id-type":"DOI","asserted-by":"crossref"}]},{"name":"AIRC","award":["IG 2021\u2013ID 25865"],"award-info":[{"award-number":["IG 2021\u2013ID 25865"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,3,29]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:p>\n                  Targeting protein-protein interactions (PPIs) with small molecules is historically challenging due to shallow, solvent-exposed interfaces that lack classical binding pockets. Furthermore, employing traditional structure-based virtual screening (SBVS) across ultra-large chemical spaces to find novel chemotypes imposes prohibitive computational bottlenecks. Here, we report the first prospective, real-world application of the PyRMD2Dock platform, an AI-enforced SBVS workflow that integrates machine learning and standard docking available within the PyRMD Studio suite. To target the structurally demanding immune receptor CD28, a chemically diverse subset of 2.4 million molecules from the Enamine REAL Diversity Space was docked into a cleft adjacent to the canonical ligand interface. These data were used to train 672 classification models, and the optimized model rapidly screened the remaining \u223c46 million compounds. Following interaction filtering and clustering, 232 highly prioritized ligands were identified. Experimental validation of 150 purchased candidates yielded a remarkable hit rate, identifying multiple direct CD28 binders. Lead compounds\n                  <jats:bold>100<\/jats:bold>\n                  and\n                  <jats:bold>104<\/jats:bold>\n                  exhibited submicromolar affinity (K\n                  <jats:sub>d<\/jats:sub>\n                  = 343.8 nM and 407.1 nM, respectively), potent CD28-CD80 disruption, and functional blockade in cellular reporter assays. Furthermore, these compounds successfully reduced cytokine secretion in primary human tumor-PBMC and epithelial tissue co-culture models. This study validates PyRMD2Dock as a highly scalable, effective protocol for mining massive chemical libraries to discover small-molecule modulators of challenging immune receptor interfaces.\n                <\/jats:p>","DOI":"10.64898\/2026.03.26.714621","type":"posted-content","created":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T04:00:13Z","timestamp":1774843213000},"source":"Crossref","is-referenced-by-count":0,"title":["AI-Enforced Ultra-Large Virtual Screening Discovers Potent CD28 Binders"],"prefix":"10.64898","author":[{"given":"Saurabh","family":"Upadhyaya","sequence":"first","affiliation":[{"name":"Department of Radiology, Molecular Imaging Innovations Institute (MI3), Weill Cornell Medicine, New York, NY 10065, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michele","family":"Roggia","sequence":"additional","affiliation":[{"name":"DiSTABiF, University of Campania Luigi Vanvitelli, 81100 Caserta, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shaoren","family":"Yuan","sequence":"additional","affiliation":[{"name":"Department of Radiology, Molecular Imaging Innovations Institute (MI3), Weill Cornell Medicine, New York, NY 10065, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sandro","family":"Cosconati","sequence":"additional","affiliation":[{"name":"DiSTABiF, University of Campania Luigi Vanvitelli, 81100 Caserta, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Moustafa T.","family":"Gabr","sequence":"additional","affiliation":[{"name":"Department of Radiology, Molecular Imaging Innovations Institute (MI3), Weill Cornell Medicine, New York, NY 10065, 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