207 related articles for article (PubMed ID: 32786543)
1. GLORYx: Prediction of the Metabolites Resulting from Phase 1 and Phase 2 Biotransformations of Xenobiotics.
de Bruyn Kops C; Šícho M; Mazzolari A; Kirchmair J
Chem Res Toxicol; 2021 Feb; 34(2):286-299. PubMed ID: 32786543
[TBL] [Abstract][Full Text] [Related]
2. GLORY: Generator of the Structures of Likely Cytochrome P450 Metabolites Based on Predicted Sites of Metabolism.
de Bruyn Kops C; Stork C; Šícho M; Kochev N; Svozil D; Jeliazkova N; Kirchmair J
Front Chem; 2019; 7():402. PubMed ID: 31249827
[TBL] [Abstract][Full Text] [Related]
3. FAME 2: Simple and Effective Machine Learning Model of Cytochrome P450 Regioselectivity.
Šícho M; de Bruyn Kops C; Stork C; Svozil D; Kirchmair J
J Chem Inf Model; 2017 Aug; 57(8):1832-1846. PubMed ID: 28782945
[TBL] [Abstract][Full Text] [Related]
4. [Xenobiotic toxicity prediction combined with xenobiotic metabolism prediction in the human body].
Rudik AV; Dmitriev AV; Lagunin AA; Ivanov SM; Filimonov DA; Poroikov VV
Biomed Khim; 2019 Feb; 65(2):114-122. PubMed ID: 30950816
[TBL] [Abstract][Full Text] [Related]
5. Computational prediction of the metabolites of agrochemicals formed in rats.
Scholz VA; Stork C; Frericks M; Kirchmair J
Sci Total Environ; 2023 Oct; 895():165039. PubMed ID: 37355108
[TBL] [Abstract][Full Text] [Related]
6. Site of metabolism prediction for six biotransformations mediated by cytochromes P450.
Zheng M; Luo X; Shen Q; Wang Y; Du Y; Zhu W; Jiang H
Bioinformatics; 2009 May; 25(10):1251-8. PubMed ID: 19286831
[TBL] [Abstract][Full Text] [Related]
7. NERDD: a web portal providing access to in silico tools for drug discovery.
Stork C; Embruch G; Šícho M; de Bruyn Kops C; Chen Y; Svozil D; Kirchmair J
Bioinformatics; 2020 Feb; 36(4):1291-1292. PubMed ID: 32077475
[TBL] [Abstract][Full Text] [Related]
8. BioTransformer 3.0-a web server for accurately predicting metabolic transformation products.
Wishart DS; Tian S; Allen D; Oler E; Peters H; Lui VW; Gautam V; Djoumbou-Feunang Y; Greiner R; Metz TO
Nucleic Acids Res; 2022 Jul; 50(W1):W115-W123. PubMed ID: 35536252
[TBL] [Abstract][Full Text] [Related]
9. MetaTox: Web Application for Predicting Structure and Toxicity of Xenobiotics' Metabolites.
Rudik AV; Bezhentsev VM; Dmitriev AV; Druzhilovskiy DS; Lagunin AA; Filimonov DA; Poroikov VV
J Chem Inf Model; 2017 Apr; 57(4):638-642. PubMed ID: 28345905
[TBL] [Abstract][Full Text] [Related]
10. Development of a computational tool to rival experts in the prediction of sites of metabolism of xenobiotics by p450s.
Campagna-Slater V; Pottel J; Therrien E; Cantin LD; Moitessier N
J Chem Inf Model; 2012 Sep; 52(9):2471-83. PubMed ID: 22916680
[TBL] [Abstract][Full Text] [Related]
11. GutBug: A Tool for Prediction of Human Gut Bacteria Mediated Biotransformation of Biotic and Xenobiotic Molecules Using Machine Learning.
Malwe AS; Srivastava GN; Sharma VK
J Mol Biol; 2023 Jul; 435(14):168056. PubMed ID: 37356904
[TBL] [Abstract][Full Text] [Related]
12. SOMP: web server for in silico prediction of sites of metabolism for drug-like compounds.
Rudik A; Dmitriev A; Lagunin A; Filimonov D; Poroikov V
Bioinformatics; 2015 Jun; 31(12):2046-8. PubMed ID: 25777527
[TBL] [Abstract][Full Text] [Related]
13. Novel Electrotopological Atomic Descriptors for the Prediction of Xenobiotic Cytochrome P450 Reactions.
Kaitoh K; Kotera M; Funatsu K
Mol Inform; 2019 Oct; 38(10):e1900010. PubMed ID: 31187601
[TBL] [Abstract][Full Text] [Related]
14. BioTransformer: a comprehensive computational tool for small molecule metabolism prediction and metabolite identification.
Djoumbou-Feunang Y; Fiamoncini J; Gil-de-la-Fuente A; Greiner R; Manach C; Wishart DS
J Cheminform; 2019 Jan; 11(1):2. PubMed ID: 30612223
[TBL] [Abstract][Full Text] [Related]
15. CyProduct: A Software Tool for Accurately Predicting the Byproducts of Human Cytochrome P450 Metabolism.
Tian S; Cao X; Greiner R; Li C; Guo A; Wishart DS
J Chem Inf Model; 2021 Jun; 61(6):3128-3140. PubMed ID: 34038112
[No Abstract] [Full Text] [Related]
16. HGMMX: Host Gut Microbiota Metabolism Xenobiotics Database.
Kolodnitsky AS; Ionov NS; Rudik AV; Filimonov DA; Poroikov VV
J Chem Inf Model; 2023 Nov; 63(21):6463-6468. PubMed ID: 37871298
[TBL] [Abstract][Full Text] [Related]
17. Hit Dexter 2.0: Machine-Learning Models for the Prediction of Frequent Hitters.
Stork C; Chen Y; Šícho M; Kirchmair J
J Chem Inf Model; 2019 Mar; 59(3):1030-1043. PubMed ID: 30624935
[TBL] [Abstract][Full Text] [Related]
18. SyGMa: combining expert knowledge and empirical scoring in the prediction of metabolites.
Ridder L; Wagener M
ChemMedChem; 2008 May; 3(5):821-32. PubMed ID: 18311745
[TBL] [Abstract][Full Text] [Related]
19. FAME 3: Predicting the Sites of Metabolism in Synthetic Compounds and Natural Products for Phase 1 and Phase 2 Metabolic Enzymes.
Šícho M; Stork C; Mazzolari A; de Bruyn Kops C; Pedretti A; Testa B; Vistoli G; Svozil D; Kirchmair J
J Chem Inf Model; 2019 Aug; 59(8):3400-3412. PubMed ID: 31361490
[TBL] [Abstract][Full Text] [Related]
20. An in vitro approach to detect metabolite toxicity due to CYP3A4-dependent bioactivation of xenobiotics.
Vignati L; Turlizzi E; Monaci S; Grossi P; Kanter Rd; Monshouwer M
Toxicology; 2005 Dec; 216(2-3):154-67. PubMed ID: 16169652
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
