Literature DB >> 20882991

Prediction of michael-type acceptor reactivity toward glutathione.

Johannes A H Schwöbel1, Dominik Wondrousch, Yana K Koleva, Judith C Madden, Mark T D Cronin, Gerrit Schüürmann.   

Abstract

A model has been developed to predict the kinetic rate constants (k(GSH)) of α,β-unsaturated Michael acceptor compounds for their reaction with glutathione (GSH). The model uses the local charge-limited electrophilicity index ω(q) [Wondrousch, D., et al. (2010) J. Phys. Chem. Lett. 1, 1605-1610] at the β-carbon atom as a descriptor of reactivity, a descriptor for resonance stabilization of the transition state, and one for steric hindrance at the reaction sites involved. Overall, the Michael addition model performs well (r² = 0.91; rms = 0.34). It includes various classes of compounds with double and triple bonds, linear and cyclic systems, and compounds with and without substituents in the α-position. Comparison of experimental and predicted rate constants demonstrates even better performance of the model for individual classes of compounds (e.g., for aldehydes, r² = 0.97 and rms = 0.15; for ketones, r² = 0.95 and rms = 0.35). The model also allows for the prediction of the RC₅₀ values from the Schultz chemoassay, the accuracy being close to the interlaboratory experimental error. Furthermore, k(GSH) and associated RC₅₀ values can be predicted in cases where experimental measurements are not possible or restricted, for example, because of low solubility or high volatility. The model has the potential to provide information to assist in the assessment and categorization of toxicants and in the application of integrated testing strategies.

Entities:  

Mesh:

Substances:

Year:  2010        PMID: 20882991     DOI: 10.1021/tx100172x

Source DB:  PubMed          Journal:  Chem Res Toxicol        ISSN: 0893-228X            Impact factor:   3.739


  27 in total

1.  Pyrrolidine catalyzed reactions of cyclopentadiene with α,β-unsaturated carbonyl compounds: 1,2- versus 1,4-additions.

Authors:  Necdet Coskun; Meliha Çetin; Scott Gronert; Jingxiang Ma; Ihsan Erden
Journal:  Tetrahedron       Date:  2015-05-06       Impact factor: 2.457

2.  Deep Learning to Predict the Formation of Quinone Species in Drug Metabolism.

Authors:  Tyler B Hughes; S Joshua Swamidass
Journal:  Chem Res Toxicol       Date:  2017-02-02       Impact factor: 3.739

Review 3.  Application of the Hard and Soft, Acids and Bases (HSAB) theory to toxicant--target interactions.

Authors:  Richard M Lopachin; Terrence Gavin; Anthony Decaprio; David S Barber
Journal:  Chem Res Toxicol       Date:  2011-11-16       Impact factor: 3.739

Review 4.  Role of reactive metabolites in the circulation in extrahepatic toxicity.

Authors:  Roy M Irving; Adnan A Elfarra
Journal:  Expert Opin Drug Metab Toxicol       Date:  2012-06-11       Impact factor: 4.481

5.  Determining Cysteines Available for Covalent Inhibition Across the Human Kinome.

Authors:  Zheng Zhao; Qingsong Liu; Spencer Bliven; Lei Xie; Philip E Bourne
Journal:  J Med Chem       Date:  2017-04-04       Impact factor: 7.446

6.  Covalent Modifiers: A Chemical Perspective on the Reactivity of α,β-Unsaturated Carbonyls with Thiols via Hetero-Michael Addition Reactions.

Authors:  Paul A Jackson; John C Widen; Daniel A Harki; Kay M Brummond
Journal:  J Med Chem       Date:  2016-12-20       Impact factor: 7.446

7.  Automated computational screening of the thiol reactivity of substituted alkenes.

Authors:  Jennifer M Smith; Christopher N Rowley
Journal:  J Comput Aided Mol Des       Date:  2015-07-10       Impact factor: 3.686

8.  The generation of 4-hydroxynonenal, an electrophilic lipid peroxidation end product, in rabbit cornea organ cultures treated with UVB light and nitrogen mustard.

Authors:  Ruijin Zheng; Iris Po; Vladimir Mishin; Adrienne T Black; Diane E Heck; Debra L Laskin; Patrick J Sinko; Donald R Gerecke; Marion K Gordon; Jeffrey D Laskin
Journal:  Toxicol Appl Pharmacol       Date:  2013-07-09       Impact factor: 4.219

9.  Synthesis of piperlogs and analysis of their effects on cells.

Authors:  Zarko V Boskovic; Mahmud M Hussain; Drew J Adams; Mingji Dai; Stuart L Schreiber
Journal:  Tetrahedron       Date:  2013-09-09       Impact factor: 2.457

10.  The Metabolic Rainbow: Deep Learning Phase I Metabolism in Five Colors.

Authors:  Na Le Dang; Matthew K Matlock; Tyler B Hughes; S Joshua Swamidass
Journal:  J Chem Inf Model       Date:  2020-02-24       Impact factor: 4.956

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.