{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,24]],"date-time":"2026-07-24T17:25:39Z","timestamp":1784913939564,"version":"3.55.0"},"reference-count":38,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2024,8,22]],"date-time":"2024-08-22T00:00:00Z","timestamp":1724284800000},"content-version":"vor","delay-in-days":28,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82150208"],"award-info":[{"award-number":["82150208"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["8242510018"],"award-info":[{"award-number":["8242510018"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82173690"],"award-info":[{"award-number":["82173690"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,7,25]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>During the drug discovery and design process, the acid\u2013base dissociation constant (pKa) of a molecule is critically emphasized due to its crucial role in influencing the ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties and biological activity. However, the experimental determination of pKa values is often laborious and complex. Moreover, existing prediction methods exhibit limitations in both the quantity and quality of the training data, as well as in their capacity to handle the complex structural and physicochemical properties of compounds, consequently impeding accuracy and generalization. Therefore, developing a method that can quickly and accurately predict molecular pKa values will to some extent help the structural modification of molecules, and thus assist the development process of new drugs. In this study, we developed a cutting-edge pKa prediction model named GR-pKa (Graph Retention pKa), leveraging a message-passing neural network and employing a multi-fidelity learning strategy to accurately predict molecular pKa values. The GR-pKa model incorporates five quantum mechanical properties related to molecular thermodynamics and dynamics as key features to characterize molecules. Notably, we originally introduced the novel retention mechanism into the message-passing phase, which significantly improves the model\u2019s ability to capture and update molecular information. Our GR-pKa model outperforms several state-of-the-art models in predicting macro-pKa values, achieving impressive results with a low mean absolute error of 0.490 and root mean square error of 0.588, and a high R2 of 0.937 on the SAMPL7 dataset.<\/jats:p>","DOI":"10.1093\/bib\/bbae408","type":"journal-article","created":{"date-parts":[[2024,8,22]],"date-time":"2024-08-22T23:14:09Z","timestamp":1724368449000},"source":"Crossref","is-referenced-by-count":11,"title":["GR-p<i>K<\/i>a: a message-passing neural network with retention mechanism for p<i>K<\/i>a prediction"],"prefix":"10.1093","volume":"25","author":[{"given":"Runyu","family":"Miao","sequence":"first","affiliation":[{"name":"Shanghai Key Laboratory of New Drug Design , School of Pharmacy, , No. 130, Meilong Road, Xuhui District, Shanghai, 200237 , China"},{"name":"East China University of Science and Technology , School of Pharmacy, , No. 130, Meilong Road, Xuhui District, Shanghai, 200237 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Danlin","family":"Liu","sequence":"additional","affiliation":[{"name":"Innovation Center for AI and Drug Discovery , School of Pharmacy, , No. 3663, Zhongshan North Road, Putuo District, Shanghai, 200062 , China"},{"name":"East China Normal University , School of Pharmacy, , No. 3663, Zhongshan North Road, Putuo District, Shanghai, 200062 , China"},{"name":"School of Computer Science and Technology, East China Normal University , No. 3663, Zhongshan North Road, Putuo District, Shanghai, 200062 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liyun","family":"Mao","sequence":"additional","affiliation":[{"name":"Shanghai Key Laboratory of New Drug Design , School of Pharmacy, , No. 130, Meilong Road, Xuhui District, Shanghai, 200237 , China"},{"name":"East China University of Science and Technology , School of Pharmacy, , No. 130, Meilong Road, Xuhui District, Shanghai, 200237 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xingyu","family":"Chen","sequence":"additional","affiliation":[{"name":"Shanghai Key Laboratory of New Drug Design , School of Pharmacy, , No. 130, Meilong Road, Xuhui District, Shanghai, 200237 , China"},{"name":"East China University of Science and Technology , School of Pharmacy, , No. 130, Meilong Road, Xuhui District, Shanghai, 200237 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Leihao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Shanghai Key Laboratory of New Drug Design , School of Pharmacy, , No. 130, Meilong Road, Xuhui District, Shanghai, 200237 , China"},{"name":"East China University of Science and Technology , School of Pharmacy, , No. 130, Meilong Road, Xuhui District, Shanghai, 200237 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhen","family":"Yuan","sequence":"additional","affiliation":[{"name":"Shanghai Key Laboratory of New Drug Design , School of Pharmacy, , No. 130, Meilong Road, Xuhui District, Shanghai, 200237 , China"},{"name":"East China University of Science and Technology , School of Pharmacy, , No. 130, Meilong Road, Xuhui District, Shanghai, 200237 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shanshan","family":"Shi","sequence":"additional","affiliation":[{"name":"Shanghai Key Laboratory of New Drug Design , School of Pharmacy, , No. 130, Meilong Road, Xuhui District, Shanghai, 200237 , China"},{"name":"East China University of Science and Technology , School of Pharmacy, , No. 130, Meilong Road, Xuhui District, Shanghai, 200237 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Honglin","family":"Li","sequence":"additional","affiliation":[{"name":"Shanghai Key Laboratory of New Drug Design , School of Pharmacy, , No. 130, Meilong Road, Xuhui District, Shanghai, 200237 , China"},{"name":"East China University of Science and Technology , School of Pharmacy, , No. 130, Meilong Road, Xuhui District, Shanghai, 200237 , China"},{"name":"Innovation Center for AI and Drug Discovery , School of Pharmacy, , No. 3663, Zhongshan North Road, Putuo District, Shanghai, 200062 , China"},{"name":"East China Normal University , School of Pharmacy, , No. 3663, Zhongshan North Road, Putuo District, Shanghai, 200062 , China"},{"name":"Lingang Laboratory , No. 319, Yueyang Road, Xuhui District, Shanghai , 200031, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4414-237X","authenticated-orcid":false,"given":"Shiliang","family":"Li","sequence":"additional","affiliation":[{"name":"Shanghai Key Laboratory of New Drug Design , School of Pharmacy, , No. 130, Meilong Road, Xuhui District, Shanghai, 200237 , China"},{"name":"East China University of Science and Technology , School of Pharmacy, , No. 130, Meilong Road, Xuhui District, Shanghai, 200237 , China"},{"name":"Innovation Center for AI and Drug Discovery , School of Pharmacy, , No. 3663, Zhongshan North Road, Putuo District, Shanghai, 200062 , China"},{"name":"East China Normal University , School of Pharmacy, , No. 3663, Zhongshan North Road, Putuo District, Shanghai, 200062 , China"},{"name":"Department of Pain management , HuaDong Hospital affiliated to Fudan University, No. 221, West Yan'an Road, Jing'an District, Shanghai, 200040, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2024,8,22]]},"reference":[{"key":"2024082219130300400_ref1","doi-asserted-by":"crossref","first-page":"19282","DOI":"10.1002\/anie.202008528","article-title":"Holistic prediction of the pK(a) in diverse solvents based on a machine-learning approach","volume":"59","author":"Yang","year":"2020","journal-title":"Angew Chem Int Ed Engl"},{"key":"2024082219130300400_ref2","doi-asserted-by":"crossref","first-page":"4706","DOI":"10.1021\/acs.jcim.9b00498","article-title":"Prediction of pKa using machine learning methods with rooted topological torsion fingerprints: application to aliphatic amines","volume":"59","author":"Lu","year":"2019","journal-title":"J Chem Inf Model"},{"key":"2024082219130300400_ref3","first-page":"1238","article-title":"Lead compound optimization strategy (3)--structure modification strategies for improving water solubility","volume":"49","author":"Li","year":"2014","journal-title":"Yao Xue Xue Bao= Acta Pharmaceutica Sinica"},{"key":"2024082219130300400_ref4","doi-asserted-by":"crossref","first-page":"9","DOI":"10.12688\/f1000research.22090.1","article-title":"Machine learning meets pK (a)","volume":"9","author":"Baltruschat","year":"2020","journal-title":"F1000Res"},{"key":"2024082219130300400_ref5","doi-asserted-by":"crossref","first-page":"3159","DOI":"10.1021\/acs.jcim.1c00075","article-title":"MolGpka: a web server for small molecule pKa prediction using a graph-convolutional neural network","volume":"61","author":"Pan","year":"2021","journal-title":"J Chem Inf Model"},{"key":"2024082219130300400_ref6","doi-asserted-by":"crossref","first-page":"792","DOI":"10.1093\/bioinformatics\/btab714","article-title":"Multi-instance learning of graph neural networks for aqueous pKa prediction","volume":"38","author":"Xiong","year":"2022","journal-title":"Bioinformatics"},{"key":"2024082219130300400_ref7","doi-asserted-by":"crossref","first-page":"2572","DOI":"10.1016\/j.apsb.2022.11.010","article-title":"MF-SuP-pK(a): multi-fidelity modeling with subgraph pooling mechanism for pK(a) prediction","volume":"13","author":"Wu","year":"2023","journal-title":"Acta Pharm Sin B"},{"key":"2024082219130300400_ref8","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1007\/s10822-020-00362-6","article-title":"Overview of the SAMPL6 pKa challenge: evaluating small molecule microscopic and macroscopic pKa predictions","volume":"35","author":"Isik","year":"2021","journal-title":"J 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