{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T09:34:13Z","timestamp":1787045653649,"version":"build-2736575974"},"reference-count":54,"publisher":"American Chemical Society (ACS)","issue":"7","license":[{"start":{"date-parts":[[2023,3,8]],"date-time":"2023-03-08T00:00:00Z","timestamp":1678233600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,3,8]],"date-time":"2023-03-08T00:00:00Z","timestamp":1678233600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2023,3,8]],"date-time":"2023-03-08T00:00:00Z","timestamp":1678233600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-045"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,4,10]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>AlphaFold2 and RoseTTAfold impress with their high accuracy in protein structure prediction. However, for structure-based virtual screenings, not only the overall structure but especially the binding sites need to be accurately predicted. In this work, the docking performance for 66 targets with known ligands but without experimental structures available in the protein data bank was elucidated. The results suggest that using an experimental surrogate\u2013ligand complex is often superior over homology models, and only at low sequence identity to the closest homologue AlphaFold2 structures show an equal performance. The generally high fluctuation of receiver operating characteristic area under the curve values obtained for different homology models suggests that multiple combinations of docking programs and homology models should be tested prior to prospective virtual screenings, and in some cases post-processing of crude models might be necessary.<\/jats:p>","DOI":"10.1021\/acs.jcim.2c01400","type":"journal-article","created":{"date-parts":[[2023,3,8]],"date-time":"2023-03-08T10:59:24Z","timestamp":1678273164000},"page":"2218-2225","source":"Crossref","is-referenced-by-count":17,"title":["Hic Sunt Dracones:\nMolecular Docking in Uncharted\nTerritories with Structures from AlphaFold2 and RoseTTAfold"],"prefix":"10.1021","volume":"63","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9976-7639","authenticated-orcid":true,"given":"Christian","family":"Kersten","sequence":"first","affiliation":[{"name":"Johannes Gutenberg-University Mainz , , Staudingerweg 5 , ,","place":["Mainz, Germany, 55128"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Steven","family":"Clower","sequence":"additional","affiliation":[{"name":"Johannes Gutenberg-University Mainz , , Staudingerweg 5 , ,","place":["Mainz, Germany, 55128"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fabian","family":"Barthels","sequence":"additional","affiliation":[{"name":"Johannes Gutenberg-University Mainz , , Staudingerweg 5 , ,","place":["Mainz, Germany, 55128"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"316","published-online":{"date-parts":[[2023,3,8]]},"reference":[{"key":"2026081804442778500_cit1","doi-asserted-by":"publisher","first-page":"1607","DOI":"10.1002\/prot.26237","article-title":"Critical Assessment\nof Methods of Protein Structure Prediction (CASP)\ue5f8Round XIV","volume":"89","author":"Kryshtafovych","year":"2021","journal-title":"Proteins: Struct., Funct., Bioinf."},{"key":"2026081804442778500_cit2","doi-asserted-by":"publisher","first-page":"583","DOI":"10.1038\/s41586-021-03819-2","article-title":"Highly Accurate Protein\nStructure Prediction with AlphaFold","volume":"596","author":"Jumper","year":"2021","journal-title":"Nature"},{"key":"2026081804442778500_cit3","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1038\/s41592-021-01362-6","article-title":"Protein Structure Predictions\nto Atomic Accuracy with\nAlphaFold","volume":"19","author":"Jumper","year":"2022","journal-title":"Nat. Methods"},{"key":"2026081804442778500_cit4","doi-asserted-by":"publisher","first-page":"604","DOI":"10.1038\/s41586-020-03051-4","article-title":"Mastering Atari, Go,\nChess and Shogi by Planning with a Learned Model","volume":"588","author":"Schrittwieser","year":"2020","journal-title":"Nature"},{"key":"2026081804442778500_cit5","doi-asserted-by":"publisher","first-page":"350","DOI":"10.1038\/s41586-019-1724-z","article-title":"Grandmaster\nLevel in\nStarCraft II Using Multi-Agent Reinforcement Learning","volume":"575","author":"Vinyals","year":"2019","journal-title":"Nature"},{"key":"2026081804442778500_cit6","doi-asserted-by":"publisher","first-page":"871","DOI":"10.1126\/science.abj8754","article-title":"Accurate Prediction\nof Protein Structures and Interactions Using a Three-Track Neural\nNetwork","volume":"373","author":"Baek","year":"2021","journal-title":"Science"},{"key":"2026081804442778500_cit7","doi-asserted-by":"publisher","DOI":"10.1101\/2022.07.20.500902","article-title":"Evolutionary-Scale Prediction of Atomic Level Protein Structure with\na Language Model","author":"Lin","year":"2022","journal-title":"bioRxiv"},{"key":"2026081804442778500_cit8","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1038\/d41586-022-03539-1","article-title":"AlphaFold\u2019s\nNew Rival? Meta AI Predicts Shape of 600 Million Proteins","volume":"611","author":"Callaway","year":"2022","journal-title":"Nature"},{"key":"2026081804442778500_cit9","doi-asserted-by":"publisher","first-page":"679","DOI":"10.1038\/s41592-022-01488-1","article-title":"ColabFold: Making Protein Folding Accessible to All","volume":"19","author":"Mirdita","year":"2022","journal-title":"Nat. Methods"},{"key":"2026081804442778500_cit10","doi-asserted-by":"publisher","first-page":"D439","DOI":"10.1093\/nar\/gkab1061","article-title":"AlphaFold Protein Structure Database:\nMassively Expanding the Structural Coverage of Protein-Sequence Space\nwith High-Accuracy Models","volume":"50","author":"Varadi","year":"2022","journal-title":"Nucleic Acids Res."},{"key":"2026081804442778500_cit11","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1038\/d41586-022-00997-5","article-title":"What\u2019s\nnext for AlphaFold and the AI Protein-Folding Revolution","volume":"604","author":"Callaway","year":"2022","journal-title":"Nature"},{"key":"2026081804442778500_cit12","doi-asserted-by":"publisher","first-page":"823","DOI":"10.2174\/1389203722666211122092605","article-title":"Solving Protein\nStructure with AI: Viva AlphaFold and\nCo.!","volume":"22","author":"Obermayer","year":"2021","journal-title":"Curr. Protein Pept. Sci."},{"key":"2026081804442778500_cit13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.15252\/embr.202154046","article-title":"AI Revolutions in\nBiology","volume":"22","author":"Perrakis","year":"2021","journal-title":"EMBO\nRep."},{"key":"2026081804442778500_cit14","doi-asserted-by":"publisher","first-page":"73","DOI":"10.2144\/btn-2022-0007","article-title":"Has DeepMind\u2019s\nAlphaFold Solved the Protein Folding Problem?","volume":"72","author":"Al-Janabi","year":"2022","journal-title":"Biotechniques"},{"key":"2026081804442778500_cit15","doi-asserted-by":"publisher","first-page":"487","DOI":"10.1038\/d41586-021-02265-4","article-title":"Protein-Structure\nPrediction Revolutionized","volume":"596","author":"AlQuraishi","year":"2021","journal-title":"Nature"},{"key":"2026081804442778500_cit16","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3389\/frai.2022.875587","article-title":"An Overview of Alphafold\u2019s\nBreakthrough","volume":"5","author":"Marcu","year":"2022","journal-title":"Front. Artif. Intell."},{"key":"2026081804442778500_cit17","doi-asserted-by":"publisher","first-page":"3142","DOI":"10.1021\/acs.jcim.2c00026","article-title":"AI-Based Protein Structure Prediction\nin Drug Discovery:\nImpacts and Challenges","volume":"62","author":"Schauperl","year":"2022","journal-title":"J. Chem. Inf. Model."},{"key":"2026081804442778500_cit18","doi-asserted-by":"publisher","first-page":"2742","DOI":"10.1093\/bioinformatics\/btac202","article-title":"Impact of Protein Conformational Diversity on AlphaFold\nPredictions","volume":"38","author":"Saldano","year":"2022","journal-title":"Bioinformatics"},{"key":"2026081804442778500_cit19","doi-asserted-by":"publisher","first-page":"725","DOI":"10.1038\/d41573-021-00161-0","article-title":"What Does\nAlphaFold Mean for Drug Discovery?","volume":"20","author":"Mullard","year":"2021","journal-title":"Nat. Rev.\nDrug Discovery"},{"key":"2026081804442778500_cit20","doi-asserted-by":"publisher","first-page":"D930","DOI":"10.1093\/nar\/gky1075","article-title":"ChEMBL:\nTowards\nDirect Deposition of Bioassay Data","volume":"47","author":"Mendez","year":"2019","journal-title":"Nucleic\nAcids Res."},{"key":"2026081804442778500_cit21","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1093\/nar\/28.1.235","article-title":"The Protein Data Bank","volume":"28","author":"Berman","year":"2000","journal-title":"Nucleic\nAcids Res."},{"key":"2026081804442778500_cit22","doi-asserted-by":"publisher","first-page":"D482","DOI":"10.1093\/nar\/gky1114","article-title":"SIFTS: Updated\nStructure Integration\nwith Function, Taxonomy and Sequences Resource Allows 40-Fold Increase\nin Coverage of Structure-Based Annotations for Proteins","volume":"47","author":"Dana","year":"2019","journal-title":"Nucleic Acids Res."},{"key":"2026081804442778500_cit23","doi-asserted-by":"publisher","first-page":"D480","DOI":"10.1093\/nar\/gkaa1100","article-title":"UniProt: The Universal\nProtein Knowledgebase in 2021","volume":"49","author":"Bateman","year":"2021","journal-title":"Nucleic Acids\nRes."},{"key":"2026081804442778500_cit24","doi-asserted-by":"publisher","first-page":"403","DOI":"10.1016\/S0022-2836(05)80360-2","article-title":"Basic Local\nAlignment Search Tool","volume":"215","author":"Altschul","year":"1990","journal-title":"J. Mol. Biol."},{"key":"2026081804442778500_cit25","doi-asserted-by":"publisher","first-page":"251","DOI":"10.1023\/A:1008130001697","article-title":"Property\nDistribution of Drug-Related Chemical Databases","volume":"14","author":"Oprea","year":"2000","journal-title":"J. Comput.-Aided Mol. Des."},{"key":"2026081804442778500_cit26","doi-asserted-by":"publisher","first-page":"481","DOI":"10.1038\/513481a","article-title":"Chemistry: Chemical\nCon Artists Foil Drug Discovery","volume":"513","author":"Baell","year":"2014","journal-title":"Nature"},{"key":"2026081804442778500_cit27","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1016\/j.addr.2012.09.019","article-title":"Experimental and\nComputational Approaches to Estimate Solubility and Permeability in\nDrug Discovery and Development Settings","volume":"64","author":"Lipinski","year":"2012","journal-title":"Adv.\nDrug Delivery Rev."},{"key":"2026081804442778500_cit28","doi-asserted-by":"publisher","first-page":"6582","DOI":"10.1021\/jm300687e","article-title":"Directory of Useful\nDecoys, Enhanced (DUD-E): Better Ligands and Decoys for Better Benchmarking","volume":"55","author":"Mysinger","year":"2012","journal-title":"J. Med. Chem."},{"key":"2026081804442778500_cit29","doi-asserted-by":"publisher","first-page":"W296","DOI":"10.1093\/nar\/gky427","article-title":"SWISS-MODEL: Homology\nModelling of Protein Structures and Complexes","volume":"46","author":"Waterhouse","year":"2018","journal-title":"Nucleic Acids Res."},{"key":"2026081804442778500_cit30","doi-asserted-by":"publisher","first-page":"2041","DOI":"10.1021\/ci100241y","article-title":"Analyzing the Topology\nof Active Sites: On the Prediction of Pockets and Subpockets","volume":"50","author":"Volkamer","year":"2010","journal-title":"J. Chem. Inf. Model."},{"key":"2026081804442778500_cit31","doi-asserted-by":"publisher","first-page":"360","DOI":"10.1021\/ci200454v","article-title":"Combining\nGlobal and Local Measures for Structure-Based Druggability Predictions","volume":"52","author":"Volkamer","year":"2012","journal-title":"J. Chem. Inf. Model."},{"key":"2026081804442778500_cit32","doi-asserted-by":"publisher","first-page":"572","DOI":"10.1021\/ci100031x","article-title":"Conformer Generation with OMEGA:\nAlgorithm and Validation\nUsing High Quality Structures from the Protein Databank and Cambridge\nStructural Database","volume":"50","author":"Hawkins","year":"2010","journal-title":"J. Chem. Inf. Model."},{"key":"2026081804442778500_cit33","doi-asserted-by":"publisher","first-page":"470","DOI":"10.1006\/jmbi.1996.0477","article-title":"A Fast Flexible Docking\nMethod Using an Incremental Construction Algorithm","volume":"261","author":"Rarey","year":"1996","journal-title":"J. Mol. Biol."},{"key":"2026081804442778500_cit34","doi-asserted-by":"publisher","first-page":"578","DOI":"10.1021\/ci100436p","article-title":"FRED Pose\nPrediction and Virtual Screening Accuracy","volume":"51","author":"McGann","year":"2011","journal-title":"J.\nChem. Inf. Model."},{"key":"2026081804442778500_cit35","doi-asserted-by":"publisher","first-page":"897","DOI":"10.1007\/s10822-012-9584-8","article-title":"FRED and HYBRID\nDocking Performance on Standardized Datasets","volume":"26","author":"McGann","year":"2012","journal-title":"J. Comput.-Aided Mol. Des."},{"key":"2026081804442778500_cit36","doi-asserted-by":"publisher","first-page":"1561","DOI":"10.1021\/ci100214a","article-title":"Rapid Context-Dependent\nLigand Desolvation in Molecular\nDocking","volume":"50","author":"Mysinger","year":"2010","journal-title":"J. Chem. Inf. Model."},{"key":"2026081804442778500_cit37","doi-asserted-by":"publisher","first-page":"4799","DOI":"10.1038\/s41596-021-00597-z","article-title":"A Practical Guide to Large-Scale\nDocking","volume":"16","author":"Bender","year":"2021","journal-title":"Nat. Protoc."},{"key":"2026081804442778500_cit38","doi-asserted-by":"publisher","first-page":"755","DOI":"10.2174\/156802609789207091","article-title":"Docking Screens: Right for the Right\nReasons?","volume":"9","author":"Kolb","year":"2009","journal-title":"Curr. Top. Med. Chem."},{"key":"2026081804442778500_cit39","doi-asserted-by":"publisher","first-page":"2489","DOI":"10.1021\/acs.jmedchem.0c02227","article-title":"Decision\nMaking\nin Structure-Based Drug Discovery: Visual Inspection of Docking Results","volume":"64","author":"Fischer","year":"2021","journal-title":"J. Med. Chem."},{"key":"2026081804442778500_cit40","doi-asserted-by":"publisher","first-page":"5712","DOI":"10.1021\/jm9006966","article-title":"Automated Docking Screens: A Feasibility\nStudy","volume":"52","author":"Irwin","year":"2009","journal-title":"J. Med. Chem."},{"key":"2026081804442778500_cit41","doi-asserted-by":"publisher","first-page":"1326","DOI":"10.1016\/j.str.2019.05.012","article-title":"Continuous Evaluation of Ligand Protein Predictions:\nA Weekly Community Challenge for Drug Docking","volume":"27","author":"Wagner","year":"2019","journal-title":"Structure"},{"key":"2026081804442778500_cit42","doi-asserted-by":"publisher","first-page":"727","DOI":"10.1038\/nrd892","article-title":"The Druggable Genome","volume":"1","author":"Hopkins","year":"2002","journal-title":"Nat. Rev.\nDrug Discovery"},{"key":"2026081804442778500_cit43","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41598-019-41594-3","article-title":"Exponential Consensus\nRanking Improves the Outcome in Docking and Receptor Ensemble Docking","volume":"9","author":"Palacio-Rodri\u0301guez","year":"2019","journal-title":"Sci. Rep."},{"key":"2026081804442778500_cit44","doi-asserted-by":"publisher","first-page":"105920","DOI":"10.1016\/j.isci.2022.105920","article-title":"How Good Are AlphaFold Models for\nDocking-Based Virtual Screening","volume":"26","author":"Scardino","year":"2023","journal-title":"iScience"},{"key":"2026081804442778500_cit45","doi-asserted-by":"publisher","first-page":"2046","DOI":"10.1021\/acs.jcim.8b00941","article-title":"Accelerating Lead Identification\nby High Throughput Virtual Screening: Prospective Case Studies from\nthe Pharmaceutical Industry","volume":"59","author":"Damm-Ganamet","year":"2019","journal-title":"J. Chem. Inf. Model."},{"key":"2026081804442778500_cit46","doi-asserted-by":"publisher","first-page":"1528","DOI":"10.2174\/156802611795860951","article-title":"Homology Models in Docking and High-Throughput Docking","volume":"11","author":"N.\nCavasotto","year":"2011","journal-title":"Curr. Top. Med. Chem."},{"key":"2026081804442778500_cit47","doi-asserted-by":"publisher","first-page":"2127","DOI":"10.1021\/ci400729j","article-title":"Ensemble-Based Docking Using Biased\nMolecular Dynamics","volume":"54","author":"Campbell","year":"2014","journal-title":"J. Chem. Inf. Model."},{"key":"2026081804442778500_cit48","doi-asserted-by":"publisher","first-page":"575","DOI":"10.1038\/nchem.1954","article-title":"Incorporation of\nProtein Flexibility and Conformational Energy Penalties in Docking\nScreens to Improve Ligand Discovery","volume":"6","author":"Fischer","year":"2014","journal-title":"Nat. Chem."},{"key":"2026081804442778500_cit49","doi-asserted-by":"publisher","first-page":"6781","DOI":"10.1021\/acs.jmedchem.7b00057","article-title":"The Roles of Water in the Protein Matrix: A Largely\nUntapped Resource for Drug Discovery","volume":"60","author":"Spyrakis","year":"2017","journal-title":"J. Med.\nChem."},{"key":"2026081804442778500_cit50","doi-asserted-by":"publisher","first-page":"581","DOI":"10.1021\/jm070759m","article-title":"Discovery of Novel Chemotypes to\na G-Protein-Coupled Receptor through Ligand-Steered Homology Modeling\nand Structure-Based Virtual Screening","volume":"51","author":"Cavasotto","year":"2008","journal-title":"J. Med.\nChem."},{"key":"2026081804442778500_cit51","doi-asserted-by":"publisher","first-page":"5806","DOI":"10.1021\/acs.jcim.2c00895","article-title":"Holo Protein Conformation\nGeneration from Apo Structures by Ligand Binding Site Refinement","volume":"62","author":"Zhang","year":"2022","journal-title":"J. Chem. Inf. Model."},{"key":"2026081804442778500_cit52","doi-asserted-by":"publisher","first-page":"1","DOI":"10.15252\/msb.202211081","article-title":"Benchmarking\nAlphaFold-Enabled Molecular Docking Predictions for Antibiotic Discovery","volume":"18","author":"Wong","year":"2022","journal-title":"Mol. Syst. Biol."},{"key":"2026081804442778500_cit53","doi-asserted-by":"publisher","first-page":"4351","DOI":"10.1021\/acs.jcim.2c00796","article-title":"Are Deep Learning\nStructural Models Sufficiently Accurate\nfor Free-Energy Calculations? Application of FEP+ to AlphaFold2-Predicted\nStructures","volume":"62","author":"Beuming","year":"2022","journal-title":"J. Chem. Inf. Model."},{"key":"2026081804442778500_cit54","doi-asserted-by":"publisher","first-page":"667","DOI":"10.1177\/1087057105281047","article-title":"Here Be\nDragons: Docking and Screening\nin an Uncharted Region of Chemical Space","volume":"10","author":"Brenk","year":"2005","journal-title":"J.\nBiomol. Screening"}],"container-title":["Journal of Chemical Information\nand Modeling"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/pubs.acs.org\/doi\/pdf\/10.1021\/acs.jcim.2c01400","content-type":"application\/pdf","content-version":"vor","intended-application":"unspecified"},{"URL":"https:\/\/pubs.acs.org\/jcisd8\/article-pdf\/63\/7\/2218\/8909365\/ci2c01400.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/pubs.acs.org\/jcisd8\/article-pdf\/63\/7\/2218\/8909365\/ci2c01400.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T09:23:42Z","timestamp":1787045022000},"score":1,"resource":{"primary":{"URL":"https:\/\/pubs.acs.org\/jcisd8\/article\/63\/7\/2218\/850334\/Hic-Sunt-Dracones-Molecular-Docking-in-Uncharted"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,8]]},"references-count":54,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2023,3,8]]},"published-print":{"date-parts":[[2023,4,10]]}},"URL":"https:\/\/doi.org\/10.1021\/acs.jcim.2c01400","relation":{},"ISSN":["1549-9596","1549-960X"],"issn-type":[{"value":"1549-9596","type":"print"},{"value":"1549-960X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,3,8]]}}}