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For: Finkelmann AR, Goldmann D, Schneider G, Göller AH. MetScore: Site of Metabolism Prediction Beyond Cytochrome P450 Enzymes. ChemMedChem 2018;13:2281-2289. [PMID: 30184341 DOI: 10.1002/cmdc.201800309] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2018] [Revised: 08/31/2018] [Indexed: 12/20/2022]
Number Cited by Other Article(s)
1
Ree N, Wollschläger JM, Göller AH, Jensen JH. Atom-based machine learning for estimating nucleophilicity and electrophilicity with applications to retrosynthesis and chemical stability. Chem Sci 2025;16:5676-5687. [PMID: 40041802 PMCID: PMC11875096 DOI: 10.1039/d4sc07297a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2024] [Accepted: 02/23/2025] [Indexed: 03/28/2025]  Open
2
Liu Z, Lin Y, He Q, Dai L, Tan Q, Jin B, Lee PW, Zhang X, Zhang L. Atom-Driven and Knowledge-Based Hydrolysis Metabolite Assessment for Environmental Organic Chemicals. Molecules 2025;30:234. [PMID: 39860105 PMCID: PMC11767695 DOI: 10.3390/molecules30020234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2024] [Revised: 01/03/2025] [Accepted: 01/07/2025] [Indexed: 01/27/2025]  Open
3
Vyas SK, Das A, Suryanarayana Murty U, Dixit VA. Sulfotransferase-mediated phase II drug metabolism prediction of substrates and sites using accessibility and reactivity-based algorithms. Mol Inform 2024;43:e202400008. [PMID: 39110066 DOI: 10.1002/minf.202400008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 05/18/2024] [Accepted: 06/24/2024] [Indexed: 10/16/2024]
4
Mao W, Zhou T, Zhang F, Qian M, Xie J, Li Z, Shu Y, Li Y, Xu H. Pan-cancer single-cell landscape of drug-metabolizing enzyme genes. Pharmacogenet Genomics 2024;34:217-225. [PMID: 38814173 DOI: 10.1097/fpc.0000000000000538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/31/2024]
5
Borup RM, Ree N, Jensen JH. pKalculator: A pK a predictor for C-H bonds. Beilstein J Org Chem 2024;20:1614-1622. [PMID: 39076289 PMCID: PMC11285060 DOI: 10.3762/bjoc.20.144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 07/02/2024] [Indexed: 07/31/2024]  Open
6
King-Smith E, Faber FA, Reilly U, Sinitskiy AV, Yang Q, Liu B, Hyek D, Lee AA. Predictive Minisci late stage functionalization with transfer learning. Nat Commun 2024;15:426. [PMID: 38225239 PMCID: PMC10789750 DOI: 10.1038/s41467-023-42145-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 10/01/2023] [Indexed: 01/17/2024]  Open
7
Smith AME, Lanevskij K, Sazonovas A, Harris J. Impact of Established and Emerging Software Tools on the Metabolite Identification Landscape. FRONTIERS IN TOXICOLOGY 2022;4:932445. [PMID: 35800176 PMCID: PMC9253584 DOI: 10.3389/ftox.2022.932445] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 05/30/2022] [Indexed: 11/25/2022]  Open
8
Ertl P, Gerebtzoff G, Lewis RA, Muenkler H, Schneider N, Sirockin F, Stiefl N, Tosco P. Chemical reactivity prediction: current methods and different application areas. Mol Inform 2021;41:e2100277. [PMID: 34964302 DOI: 10.1002/minf.202100277] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 12/28/2021] [Indexed: 11/10/2022]
9
Muller C, Rabal O, Diaz Gonzalez C. Artificial Intelligence, Machine Learning, and Deep Learning in Real-Life Drug Design Cases. METHODS IN MOLECULAR BIOLOGY (CLIFTON, N.J.) 2021;2390:383-407. [PMID: 34731478 DOI: 10.1007/978-1-0716-1787-8_16] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
10
Machine Learning Applied to the Modeling of Pharmacological and ADMET Endpoints. Methods Mol Biol 2021. [PMID: 34731464 DOI: 10.1007/978-1-0716-1787-8_2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2023]
11
Matveieva M, Polishchuk P. Benchmarks for interpretation of QSAR models. J Cheminform 2021;13:41. [PMID: 34039411 PMCID: PMC8157407 DOI: 10.1186/s13321-021-00519-x] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Accepted: 05/15/2021] [Indexed: 01/06/2023]  Open
12
Abiri R, Atabaki N, Sanusi R, Malik S, Abiri R, Safa P, Shukor NAA, Abdul-Hamid H. New Insights into the Biological Properties of Eucalyptus-Derived Essential Oil: A Promising Green Anti-Cancer Drug. FOOD REVIEWS INTERNATIONAL 2021. [DOI: 10.1080/87559129.2021.1877300] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
13
Kim H, Kim E, Lee I, Bae B, Park M, Nam H. Artificial Intelligence in Drug Discovery: A Comprehensive Review of Data-driven and Machine Learning Approaches. BIOTECHNOL BIOPROC E 2021;25:895-930. [PMID: 33437151 PMCID: PMC7790479 DOI: 10.1007/s12257-020-0049-y] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Revised: 05/27/2020] [Accepted: 06/03/2020] [Indexed: 02/07/2023]
14
Göller AH, Kuhnke L, Montanari F, Bonin A, Schneckener S, Ter Laak A, Wichard J, Lobell M, Hillisch A. Bayer's in silico ADMET platform: a journey of machine learning over the past two decades. Drug Discov Today 2020;25:1702-1709. [PMID: 32652309 DOI: 10.1016/j.drudis.2020.07.001] [Citation(s) in RCA: 101] [Impact Index Per Article: 20.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 06/16/2020] [Accepted: 07/02/2020] [Indexed: 12/20/2022]
15
Göller AH. The art of atom descriptor design. DRUG DISCOVERY TODAY. TECHNOLOGIES 2020;32-33:37-43. [PMID: 33386093 DOI: 10.1016/j.ddtec.2020.06.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 06/19/2020] [Accepted: 06/19/2020] [Indexed: 02/03/2023]
16
Bauer CA, Schneider G, Göller AH. Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies. J Cheminform 2019;11:59. [PMID: 33430967 PMCID: PMC6737620 DOI: 10.1186/s13321-019-0381-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2019] [Accepted: 08/10/2019] [Indexed: 02/06/2023]  Open
17
Šícho M, Stork C, Mazzolari A, de Bruyn Kops C, Pedretti A, Testa B, Vistoli G, Svozil D, Kirchmair J. FAME 3: Predicting the Sites of Metabolism in Synthetic Compounds and Natural Products for Phase 1 and Phase 2 Metabolic Enzymes. J Chem Inf Model 2019;59:3400-3412. [PMID: 31361490 DOI: 10.1021/acs.jcim.9b00376] [Citation(s) in RCA: 62] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
18
Kaitoh K, Kotera M, Funatsu K. Novel Electrotopological Atomic Descriptors for the Prediction of Xenobiotic Cytochrome P450 Reactions. Mol Inform 2019;38:e1900010. [PMID: 31187601 DOI: 10.1002/minf.201900010] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2019] [Accepted: 04/28/2019] [Indexed: 01/06/2023]
19
Cronin MT, Madden JC, Yang C, Worth AP. Unlocking the potential of in silico chemical safety assessment - A report on a cross-sector symposium on current opportunities and future challenges. COMPUTATIONAL TOXICOLOGY (AMSTERDAM, NETHERLANDS) 2019;10:38-43. [PMID: 31218266 PMCID: PMC6559213 DOI: 10.1016/j.comtox.2018.12.006] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/15/2018] [Accepted: 12/17/2018] [Indexed: 12/21/2022]
20
Tyzack JD, Kirchmair J. Computational methods and tools to predict cytochrome P450 metabolism for drug discovery. Chem Biol Drug Des 2019;93:377-386. [PMID: 30471192 PMCID: PMC6590657 DOI: 10.1111/cbdd.13445] [Citation(s) in RCA: 110] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2018] [Revised: 11/05/2018] [Accepted: 11/11/2018] [Indexed: 01/08/2023]
21
Bauer CA, Schneider G, Göller AH. Gaussian Process Regression Models for the Prediction of Hydrogen Bond Acceptor Strengths. Mol Inform 2018;38:e1800115. [DOI: 10.1002/minf.201800115] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Accepted: 10/16/2018] [Indexed: 12/12/2022]
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