{"entity": "researcher", "timestamp": "2026-09-24T01:05:27.730Z", "family": "Moroz", "given": "Yurii S", "initials": "YS", "orcid": "0000-0001-6073-002X", "affiliations": ["Enamine Ltd, Kyiv, Ukraine.", "Taras Shevchenko National University of Kyiv, Kyiv, Ukraine.", "Chemspace LLC, Kyiv, Ukraine."], "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/researcher/85e5c6a40d854426b96476233f59ccfa.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/researcher/85e5c6a40d854426b96476233f59ccfa"}}, "publications": [{"entity": "publication", "iuid": "76e5f848ccc041ac9b4fa821b20ba8b0", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/76e5f848ccc041ac9b4fa821b20ba8b0.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/76e5f848ccc041ac9b4fa821b20ba8b0"}}, "title": "Ultra-large virtual screening unveils potent agonists of the neuromodulatory orphan receptor GPR139.", "authors": [{"family": "Cabeza de Vaca", "given": "Israel", "initials": "I", "orcid": "0000-0002-6208-1091", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/defa085f944942239696861994f25e79.json"}}, {"family": "Trapkov", "given": "Boris", "initials": "B", "orcid": "0000-0003-1245-888X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/1aff7885ecf14656b053ddfd6d94b17a.json"}}, {"family": "Shen", "given": "Ling", "initials": "L"}, {"family": "Vo", "given": "Duy Duc", "initials": "DD"}, {"family": "Zhang", "given": "Xiaoqun", "initials": "X", "orcid": "0000-0002-9461-8682", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/4395a11b24bf40308b6d3a8467763517.json"}}, {"family": "Yang", "given": "Yunting", "initials": "Y"}, {"family": "Pezeshki", "given": "Mitra", "initials": "M", "orcid": "0009-0001-0155-7463", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/5d5cade660844b84980e852280aabedb.json"}}, {"family": "Zhang", "given": "Xuehan", "initials": "X"}, {"family": "B\u00e4llgren", "given": "Frida", "initials": "F"}, {"family": "Saleh", "given": "Aljona", "initials": "A"}, {"family": "Tarnovskiy", "given": "Andrii V", "initials": "AV"}, {"family": "Radchenko", "given": "Dmytro S", "initials": "DS", "orcid": "0000-0001-5444-7754", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/5a8f8993ce024259aa09cfae9a745a20.json"}}, {"family": "Moroz", "given": "Yurii S", "initials": "YS", "orcid": "0000-0001-6073-002X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/85e5c6a40d854426b96476233f59ccfa.json"}}, {"family": "Br\u00e4uner-Osborne", "given": "Hans", "initials": "H"}, {"family": "Svenningsson", "given": "Per", "initials": "P", "orcid": "0000-0001-6727-3802", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b01bbacfa24e4b9794734bf1121d1c38.json"}}, {"family": "Kihlberg", "given": "Jan", "initials": "J", "orcid": "0000-0002-4205-6040", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/7edb4dfa7c4b4d6c8c4cf0282a9c9a1a.json"}}, {"family": "Liu", "given": "Zhi-Jie", "initials": "ZJ", "orcid": "0000-0001-7279-2893", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/3ab058d718354e5b96adef9dca906de2.json"}}, {"family": "Hauser", "given": "Alexander Sebastian", "initials": "AS", "orcid": "0000-0003-1098-6419", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b8ac3dae8d9543cfabc166986ce35847.json"}}, {"family": "Carlsson", "given": "Jens", "initials": "J", "orcid": "0000-0003-4623-2977", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/792c1cd4aca248dc94b967115ffa82df.json"}}], "type": "journal article", "published": "2025-12-09", "journal": {"title": "Nat Commun", "issn": "2041-1723", "volume": "17", "issue": "1", "pages": "129", "issn-l": "2041-1723"}, "abstract": "The orphan G protein-coupled receptor (GPCR) GPR139 attracts interest as a target for neuropsychiatric disorders. Whereas the physiological functions of GPR139 remain elusive, a high-resolution receptor structure is now available. To assess whether structural information enables ligand discovery, we computationally dock 235 million compounds to the GPR139 binding site. Of 68 top-ranked compounds evaluated experimentally, five are full agonists with potencies ranging from 160 nM to 3.6 \u00b5M. Structure-guided optimization identifies one of the most potent GPR139 agonists, and a cryo-EM structure of the receptor-ligand complex confirms the predicted binding mode. Functional characterization provides insights into GPR139 signalling, and one agonist elicits behavioural effects in mice. We also explore the potential to replace experimental structure determination with the deep-learning method AlphaFold3, revealing a limited capability of artificial intelligence to model receptor-ligand interactions for understudied GPCRs. The results demonstrate how high-resolution GPCR structures combined with large-library docking can accelerate drug discovery.", "doi": "10.1038/s41467-025-66845-y", "pmid": "41365886", "labels": {"SciLifeLab Fellow": "", "Jens Carlsson": ""}, "xrefs": [{"db": "pmc", "key": "PMC12775434"}, {"db": "pii", "key": "10.1038/s41467-025-66845-y"}], "notes": [], "created": "2026-09-23T09:12:16.102Z", "modified": "2026-09-23T09:12:16.377Z"}, {"entity": "publication", "iuid": "9f52d4026e054c489cc4c94a5de91017", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/9f52d4026e054c489cc4c94a5de91017.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/9f52d4026e054c489cc4c94a5de91017"}}, "title": "Rapid traversal of vast chemical space using machine learning-guided docking screens.", "authors": [{"family": "Luttens", "given": "Andreas", "initials": "A", "orcid": "0000-0003-2915-7901", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/d2944edc47eb4b639f1c61ae7b94b60a.json"}}, {"family": "Cabeza de Vaca", "given": "Israel", "initials": "I"}, {"family": "Sparring", "given": "Leonard", "initials": "L"}, {"family": "Brea", "given": "Jos\u00e9", "initials": "J"}, {"family": "Mart\u00ednez", "given": "Ant\u00f3n Leandro", "initials": "AL", "orcid": "0000-0002-1595-3459", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/ccf0b72b679f424cac5adb240ed16b7a.json"}}, {"family": "Kahlous", "given": "Nour Aldin", "initials": "NA", "orcid": "0000-0002-7744-1491", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/ed14cfbd31384338928150f4a97aee16.json"}}, {"family": "Radchenko", "given": "Dmytro S", "initials": "DS", "orcid": "0000-0001-5444-7754", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/5a8f8993ce024259aa09cfae9a745a20.json"}}, {"family": "Moroz", "given": "Yurii S", "initials": "YS", "orcid": "0000-0001-6073-002X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/85e5c6a40d854426b96476233f59ccfa.json"}}, {"family": "Loza", "given": "Mar\u00eda Isabel", "initials": "MI", "orcid": "0000-0003-4730-0863", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/177c0793b32b44f2b46cdf286da0d3f3.json"}}, {"family": "Norinder", "given": "Ulf", "initials": "U", "orcid": "0000-0003-3107-331X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/da36a1cdadab4126b4e2527721ac2710.json"}}, {"family": "Carlsson", "given": "Jens", "initials": "J", "orcid": "0000-0003-4623-2977", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/792c1cd4aca248dc94b967115ffa82df.json"}}], "type": "journal article", "published": "2025-04-00", "journal": {"title": "Nat Comput Sci", "issn": "2662-8457", "volume": "5", "issue": "4", "pages": "301-312", "issn-l": null}, "abstract": "The accelerating growth of make-on-demand chemical libraries provides unprecedented opportunities to identify starting points for drug discovery with virtual screening. However, these multi-billion-scale libraries are challenging to screen, even for the fastest structure-based docking methods. Here we explore a strategy that combines machine learning and molecular docking to enable rapid virtual screening of databases containing billions of compounds. In our workflow, a classification algorithm is trained to identify top-scoring compounds based on molecular docking of 1 million compounds to the target protein. The conformal prediction framework is then used to make selections from the multi-billion-scale library, reducing the number of compounds to be scored by docking. The CatBoost classifier showed an optimal balance between speed and accuracy and was used to adapt the workflow for screens of ultralarge libraries. Application to a library of 3.5 billion compounds demonstrated that our protocol can reduce the computational cost of structure-based virtual screening by more than 1,000-fold. Experimental testing of predictions identified ligands of G protein-coupled receptors and demonstrated that our approach enables discovery of compounds with multi-target activity tailored for therapeutic effect.", "doi": "10.1038/s43588-025-00777-x", "pmid": "40082701", "labels": {"SciLifeLab Fellow": "", "Jens Carlsson": "", "Andreas Luttens": "", "DDLS Fellow": ""}, "xrefs": [{"db": "pmc", "key": "PMC12021657"}, {"db": "pii", "key": "10.1038/s43588-025-00777-x"}, {"db": "Protein", "key": "7CMV, 8GNE, 6CM4, 4EIY, 6DPT, 6XUE,"}], "notes": [], "created": "2026-09-23T08:32:11.684Z", "modified": "2026-09-23T08:32:12.183Z"}, {"entity": "publication", "iuid": "584e5a83218d4ee481f1071ddaa2c952", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/584e5a83218d4ee481f1071ddaa2c952.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/584e5a83218d4ee481f1071ddaa2c952"}}, "title": "Virtual fragment screening for DNA repair inhibitors in vast chemical space.", "authors": [{"family": "Luttens", "given": "Andreas", "initials": "A", "orcid": "0000-0003-2915-7901", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/d2944edc47eb4b639f1c61ae7b94b60a.json"}}, {"family": "Vo", "given": "Duc Duy", "initials": "DD"}, {"family": "Scaletti", "given": "Emma R", "initials": "ER"}, {"family": "Wiita", "given": "Elis\u00e9e", "initials": "E"}, {"family": "Alml\u00f6f", "given": "Ingrid", "initials": "I"}, {"family": "Wallner", "given": "Olov", "initials": "O"}, {"family": "Davies", "given": "Jonathan", "initials": "J"}, {"family": "Ko\u0161enina", "given": "Sara", "initials": "S", "orcid": "0000-0001-7893-0249", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/04654f973aba4ecc9d8b45445741c38f.json"}}, {"family": "Meng", "given": "Liuzhen", "initials": "L"}, {"family": "Long", "given": "Maeve", "initials": "M"}, {"family": "Mortusewicz", "given": "Oliver", "initials": "O", "orcid": "0000-0002-4290-4994", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/6f546fe8f2c54824b942f7f88976e3bd.json"}}, {"family": "Masuyer", "given": "Geoffrey", "initials": "G", "orcid": "0000-0002-9527-2310", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c62ba219d3e34662aaa458dbd361cf31.json"}}, {"family": "Ballante", "given": "Flavio", "initials": "F", "orcid": "0000-0002-4831-3423", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8ce9aad230aa414886e3bf519937aad9.json"}}, {"family": "Michel", "given": "Maurice", "initials": "M"}, {"family": "Homan", "given": "Evert", "initials": "E"}, {"family": "Scobie", "given": "Martin", "initials": "M"}, {"family": "Kalder\u00e9n", "given": "Christina", "initials": "C"}, {"family": "Warpman Berglund", "given": "Ulrika", "initials": "U"}, {"family": "Tarnovskiy", "given": "Andrii V", "initials": "AV"}, {"family": "Radchenko", "given": "Dmytro S", "initials": "DS", "orcid": "0000-0001-5444-7754", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/5a8f8993ce024259aa09cfae9a745a20.json"}}, {"family": "Moroz", "given": "Yurii S", "initials": "YS", "orcid": "0000-0001-6073-002X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/85e5c6a40d854426b96476233f59ccfa.json"}}, {"family": "Kihlberg", "given": "Jan", "initials": "J", "orcid": "0000-0002-4205-6040", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/7edb4dfa7c4b4d6c8c4cf0282a9c9a1a.json"}}, {"family": "Stenmark", "given": "P\u00e5l", "initials": "P", "orcid": "0000-0003-4777-3417", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/9791bc0d7463417899d6953b5ca1bac3.json"}}, {"family": "Helleday", "given": "Thomas", "initials": "T"}, {"family": "Carlsson", "given": "Jens", "initials": "J", "orcid": "0000-0003-4623-2977", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/792c1cd4aca248dc94b967115ffa82df.json"}}], "type": "journal article", "published": "2025-02-18", "journal": {"title": "Nat Commun", "issn": "2041-1723", "volume": "16", "issue": "1", "pages": "1741", "issn-l": "2041-1723"}, "abstract": "Fragment-based screening can catalyze drug discovery by identifying novel scaffolds, but this approach is limited by the small chemical libraries studied by biophysical experiments and the challenging optimization process. To expand the explored chemical space, we employ structure-based docking to evaluate orders-of-magnitude larger libraries than those used in traditional fragment screening. We computationally dock a set of 14 million fragments to 8-oxoguanine DNA glycosylase (OGG1), a difficult drug target involved in cancer and inflammation, and evaluate 29 highly ranked compounds experimentally. Four of these bind to OGG1 and X-ray crystallography confirms the binding modes predicted by docking. Furthermore, we show how fragment elaboration using searches among billions of readily synthesizable compounds identifies submicromolar inhibitors with anti-inflammatory and anti-cancer effects in cells. Comparisons of virtual screening strategies to explore a chemical space of 1022 compounds illustrate that fragment-based design enables enumeration of all molecules relevant for inhibitor discovery. Virtual fragment screening is hence a highly efficient strategy for navigating the rapidly growing combinatorial libraries and can serve as a powerful tool to accelerate drug discovery efforts for challenging therapeutic targets.", "doi": "10.1038/s41467-025-56893-9", "pmid": "39966348", "labels": {"SciLifeLab Fellow": "", "Jens Carlsson": "", "Andreas Luttens": "", "DDLS Fellow": ""}, "xrefs": [{"db": "pmc", "key": "PMC11836371"}, {"db": "pii", "key": "10.1038/s41467-025-56893-9"}], "notes": [], "created": "2026-09-23T09:09:46.413Z", "modified": "2026-09-23T09:09:46.668Z"}]}