{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T03:45:08Z","timestamp":1791863108091,"version":"4.3.4"},"reference-count":41,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Journal of Molecular Graphics and Modelling"],"published-print":{"date-parts":[[2026,12]]},"DOI":"10.1016\/j.jmgm.2026.109568","type":"journal-article","created":{"date-parts":[[2026,9,12]],"date-time":"2026-09-12T15:16:56Z","timestamp":1789226216000},"page":"109568","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Accelerating HDAC8 inhibitor discovery through deep learning, cheminformatics, docking, and molecular dynamics simulations"],"prefix":"10.1016","volume":"149","author":[{"given":"Mohsen","family":"Sargolzaei","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hossein","family":"Nikoofard","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"3","key":"10.1016\/j.jmgm.2026.109568_bib1","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1038\/nm.2305","article-title":"Cancer epigenetics reaches mainstream oncology","volume":"17","author":"Rodr\u00edguez-Paredes","year":"2011","journal-title":"Nat. Med."},{"issue":"21","key":"10.1016\/j.jmgm.2026.109568_bib2","first-page":"1838","article-title":"HDAC8 inhibitors: advances and perspectives","volume":"18","author":"Zhang","year":"2018","journal-title":"Curr. Top. Med. Chem."},{"issue":"9","key":"10.1016\/j.jmgm.2026.109568_bib3","first-page":"795","article-title":"HDAC8 as an emerging target in drug discovery with selective inhibitors: focus on cancer treatment","volume":"15","author":"Rajaram","year":"2023","journal-title":"Future Med. Chem."},{"issue":"1","key":"10.1016\/j.jmgm.2026.109568_bib4","first-page":"105","article-title":"A review on molecular docking on HDAC isoforms: novel tool for designing selective inhibitors","volume":"16","author":"Drakontaeidi","year":"2023","journal-title":"Pharmaceuticals"},{"issue":"2","key":"10.1016\/j.jmgm.2026.109568_bib5","first-page":"26","article-title":"Development of a potent and selective HDAC8 inhibitor","volume":"9","author":"Ingham","year":"2016","journal-title":"Pharmaceuticals"},{"key":"10.1016\/j.jmgm.2026.109568_bib6","article-title":"Recent developments of HDAC inhibitors: emerging indications and novel molecules","volume":"171","author":"Bondarev","year":"2021","journal-title":"Pharmacol. Res."},{"issue":"5","key":"10.1016\/j.jmgm.2026.109568_bib7","doi-asserted-by":"crossref","DOI":"10.1093\/bioinformatics\/btae304","article-title":"Molecular property prediction based on graph structure learning","volume":"40","author":"Zhao","year":"2024","journal-title":"Bioinformatics"},{"issue":"8","key":"10.1016\/j.jmgm.2026.109568_bib8","doi-asserted-by":"crossref","DOI":"10.1016\/j.jpha.2025.101338","article-title":"Discovery of selective HDAC6 inhibitors driven by artificial intelligence and molecular dynamics simulation approaches","volume":"15","author":"Liu","year":"2025","journal-title":"J. Pharm. Anal."},{"key":"10.1016\/j.jmgm.2026.109568_bib9","doi-asserted-by":"crossref","DOI":"10.3389\/fbioe.2022.946329","article-title":"MLP-based regression prediction model for compound bioactivity","volume":"10","author":"Qin","year":"2022","journal-title":"Front. Bioeng. Biotechnol."},{"issue":"16","key":"10.1016\/j.jmgm.2026.109568_bib10","first-page":"11625","article-title":"Artificial intelligence in drug discovery","volume":"63","author":"Jim\u00e9nez-Luna","year":"2020","journal-title":"J. Med. Chem."},{"key":"10.1016\/j.jmgm.2026.109568_bib11","doi-asserted-by":"crossref","DOI":"10.1016\/j.bmcl.2024.129810","article-title":"Replacement of the hydroxamic acid group in the selective HDAC8 inhibitor PCI-34051","volume":"108","author":"Long","year":"2024","journal-title":"Bioorg. Med. Chem. Lett."},{"issue":"8","key":"10.1016\/j.jmgm.2026.109568_bib12","first-page":"1508","article-title":"HDAC8-Selective inhibition by PCI-34051 enhances synergistic anticancer effects with other drugs","volume":"21","author":"Kim","year":"2022","journal-title":"Mol. Cancer Therapeut."},{"issue":"1","key":"10.1016\/j.jmgm.2026.109568_bib13","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1109\/TNNLS.2020.2978386","article-title":"A comprehensive survey on graph neural networks","volume":"32","author":"Wu","year":"2021","journal-title":"IEEE Transact. Neural Networks Learn. Syst."},{"issue":"8","key":"10.1016\/j.jmgm.2026.109568_bib14","doi-asserted-by":"crossref","first-page":"595","DOI":"10.1007\/s10822-016-9938-8","article-title":"Molecular graph convolutions: moving beyond fingerprints","volume":"30","author":"Kearnes","year":"2016","journal-title":"J. Comput. Aided Mol. Des."},{"key":"10.1016\/j.jmgm.2026.109568_bib15","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1186\/s13321-025-00963-z","article-title":"Fifteen years of ChEMBL and its role in cheminformatics and drug discovery","volume":"17","author":"Zdrazil","year":"2025","journal-title":"J. Cheminf."},{"issue":"5","key":"10.1016\/j.jmgm.2026.109568_bib16","first-page":"759","article-title":"The importance of being earnest: validation is the absolute essential for successful application and interpretation of QSPR models","volume":"50","author":"Tropsha","year":"2010","journal-title":"J. Chem. Inf. Model."},{"issue":"7","key":"10.1016\/j.jmgm.2026.109568_bib17","doi-asserted-by":"crossref","first-page":"1189","DOI":"10.1021\/ci100176x","article-title":"Trust, but verify: on the importance of chemical structure curation in cheminformatics and QSAR modeling research","volume":"50","author":"Fourches","year":"2010","journal-title":"J. Chem. Inf. Model."},{"key":"10.1016\/j.jmgm.2026.109568_bib18","author":"Landrum"},{"issue":"5","key":"10.1016\/j.jmgm.2026.109568_bib19","doi-asserted-by":"crossref","first-page":"694","DOI":"10.1002\/qsar.200610151","article-title":"Principles of QSAR models validation: internal and external","volume":"26","author":"Gramatica","year":"2007","journal-title":"QSAR Comb. Sci."},{"issue":"4","key":"10.1016\/j.jmgm.2026.109568_bib20","doi-asserted-by":"crossref","first-page":"783","DOI":"10.1021\/ci400084k","article-title":"Time-split cross-validation as a method for estimating the goodness of prospective prediction","volume":"53","author":"Sheridan","year":"2013","journal-title":"J. Chem. Inf. Model."},{"issue":"1\u20133","key":"10.1016\/j.jmgm.2026.109568_bib21","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/S0169-409X(00)00129-0","article-title":"Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings","volume":"46","author":"Lipinski","year":"2001","journal-title":"Adv. Drug Deliv. Rev."},{"issue":"12","key":"10.1016\/j.jmgm.2026.109568_bib22","doi-asserted-by":"crossref","first-page":"2615","DOI":"10.1021\/jm020017n","article-title":"Molecular properties that influence the oral bioavailability of drug candidates","volume":"45","author":"Veber","year":"2002","journal-title":"J. Med. Chem."},{"issue":"5","key":"10.1016\/j.jmgm.2026.109568_bib23","doi-asserted-by":"crossref","first-page":"742","DOI":"10.1021\/ci100050t","article-title":"Extended-connectivity fingerprints","volume":"50","author":"Rogers","year":"2010","journal-title":"J. Chem. Inf. Model."},{"key":"10.1016\/j.jmgm.2026.109568_bib24","series-title":"Deep Learning","author":"Goodfellow","year":"2016"},{"issue":"1","key":"10.1016\/j.jmgm.2026.109568_bib25","first-page":"1929","article-title":"Dropout: a simple way to prevent neural networks from overfitting","volume":"15","author":"Srivastava","year":"2014","journal-title":"J. Mach. Learn. Res."},{"key":"10.1016\/j.jmgm.2026.109568_bib26","first-page":"448","article-title":"Batch normalization: accelerating deep network training by reducing internal covariate shift","author":"Ioffe","year":"2015","journal-title":"Proc. 32nd Int. Conf. Mach. Learn."},{"issue":"4","key":"10.1016\/j.jmgm.2026.109568_bib27","article-title":"SELFIES: a robust representation for machine learning of molecules","volume":"1","author":"Krenn","year":"2020","journal-title":"Mach. Learn. Sci. Technol."},{"issue":"21","key":"10.1016\/j.jmgm.2026.109568_bib28","doi-asserted-by":"crossref","first-page":"6752","DOI":"10.1021\/jm901241e","article-title":"Escape from flatland: increasing saturation as an approach to improving clinical success","volume":"52","author":"Lovering","year":"2009","journal-title":"J. Med. Chem."},{"issue":"12","key":"10.1016\/j.jmgm.2026.109568_bib29","doi-asserted-by":"crossref","first-page":"2562","DOI":"10.1021\/acs.jcim.5b00654","article-title":"Better informed distance geometry: using what we know to improve conformation generation","volume":"55","author":"Riniker","year":"2015","journal-title":"J. Chem. Inf. Model."},{"key":"10.1016\/j.jmgm.2026.109568_bib30","series-title":"AMBER 2016","author":"Case","year":"2016"},{"issue":"8","key":"10.1016\/j.jmgm.2026.109568_bib31","doi-asserted-by":"crossref","first-page":"3696","DOI":"10.1021\/acs.jctc.5b00255","article-title":"ff14SB: improving the accuracy of protein side chain and backbone parameters from ff99SB","volume":"11","author":"Maier","year":"2015","journal-title":"J. Chem. Theory Comput."},{"issue":"9","key":"10.1016\/j.jmgm.2026.109568_bib32","doi-asserted-by":"crossref","first-page":"1157","DOI":"10.1002\/jcc.20035","article-title":"Development and testing of a general amber force field","volume":"25","author":"Wang","year":"2004","journal-title":"J. Comput. Chem."},{"issue":"11","key":"10.1016\/j.jmgm.2026.109568_bib33","doi-asserted-by":"crossref","first-page":"3315","DOI":"10.1021\/jm051197e","article-title":"MolDock: a new technique for high-accuracy molecular docking","volume":"49","author":"Thomsen","year":"2006","journal-title":"J. Med. Chem."},{"issue":"2","key":"10.1016\/j.jmgm.2026.109568_bib34","doi-asserted-by":"crossref","first-page":"926","DOI":"10.1063\/1.445869","article-title":"Comparison of simple potential functions for simulating liquid water","volume":"79","author":"Jorgensen","year":"1983","journal-title":"J. Chem. Phys."},{"issue":"3","key":"10.1016\/j.jmgm.2026.109568_bib35","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1016\/0021-9991(77)90098-5","article-title":"Numerical integration of the cartesian equations of motion of a system with constraints: molecular dynamics of n-alkanes","volume":"23","author":"Ryckaert","year":"1977","journal-title":"J. Comput. Phys."},{"issue":"12","key":"10.1016\/j.jmgm.2026.109568_bib36","doi-asserted-by":"crossref","first-page":"10089","DOI":"10.1063\/1.464397","article-title":"Particle mesh ewald: an n\u00b7log(N) method for ewald sums in large systems","volume":"98","author":"Darden","year":"1993","journal-title":"J. Chem. Phys."},{"issue":"6","key":"10.1016\/j.jmgm.2026.109568_bib37","doi-asserted-by":"crossref","first-page":"1409","DOI":"10.1080\/00268978800101881","article-title":"An analysis of the accuracy of langevin and molecular dynamics algorithms","volume":"65","author":"Pastor","year":"1988","journal-title":"Mol. Phys."},{"issue":"7","key":"10.1016\/j.jmgm.2026.109568_bib38","doi-asserted-by":"crossref","first-page":"3084","DOI":"10.1021\/ct400341p","article-title":"PTRAJ and CPPTRAJ: software for processing and analysis of molecular dynamics trajectory data","volume":"9","author":"Roe","year":"2013","journal-title":"J. Chem. Theory Comput."},{"issue":"3","key":"10.1016\/j.jmgm.2026.109568_bib39","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1109\/MCSE.2007.55","article-title":"Matplotlib: a 2D graphics environment","volume":"9","author":"Hunter","year":"2007","journal-title":"Comput. Sci. Eng."},{"issue":"60","key":"10.1016\/j.jmgm.2026.109568_bib40","doi-asserted-by":"crossref","first-page":"3021","DOI":"10.21105\/joss.03021","article-title":"Seaborn: statistical data visualization","volume":"6","author":"Waskom","year":"2021","journal-title":"J. Open Source Softw."},{"issue":"3","key":"10.1016\/j.jmgm.2026.109568_bib41","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1016\/S0169-409X(02)00003-0","article-title":"Prediction of 'drug-likeness'","volume":"54","author":"Walters","year":"2002","journal-title":"Adv. Drug Deliv. Rev."}],"container-title":["Journal of Molecular Graphics and Modelling"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1093326326002949?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1093326326002949?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T02:55:31Z","timestamp":1791860131000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1093326326002949"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,12]]},"references-count":41,"alternative-id":["S1093326326002949"],"URL":"https:\/\/doi.org\/10.1016\/j.jmgm.2026.109568","relation":{},"ISSN":["1093-3263"],"issn-type":[{"value":"1093-3263","type":"print"}],"subject":[],"published":{"date-parts":[[2026,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Accelerating HDAC8 inhibitor discovery through deep learning, cheminformatics, docking, and molecular dynamics simulations","name":"articletitle","label":"Article Title"},{"value":"Journal of Molecular Graphics and Modelling","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.jmgm.2026.109568","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"109568"}}