Literature DB >> 19708826

QSAR of cytochrome inhibitors.

Kunal Roy1, Partha Pratim Roy.   

Abstract

Cytochrome P450 (CYP450) enzymes are predominantly involved in the Phase I metabolism of xenobiotics. Metabolic inhibition and induction can give rise to clinically important drug-drug interactions. Metabolic stability is a prerequisite for sustaining the therapeutically relevant concentrations, and very often drug candidates are sacrificed due to poor metabolic profiles. Computational tools such as quantitative structure-activity relationships are widely used to study different metabolic end points successfully to accelerate the drug discovery process. There are a lot of computational studies on clinically important CYPs already reported in recent years. But other clinically significant families are to yet be explored computationally. Powerfulness of quantitative structure-activity relationship will drive computational chemists to develop new potent and selective inhibitors of different classes of CYPs for the treatment of different diseases with least drug-drug interactions. Furthermore, there is a need to enhance the accuracy, interpretability and confidence in the computational models in accelerating the drug discovery pathways.

Entities:  

Mesh:

Substances:

Year:  2009        PMID: 19708826     DOI: 10.1517/17425250903158940

Source DB:  PubMed          Journal:  Expert Opin Drug Metab Toxicol        ISSN: 1742-5255            Impact factor:   4.481


  9 in total

1.  Understanding the determinants of selectivity in drug metabolism through modeling of dextromethorphan oxidation by cytochrome P450.

Authors:  Julianna Oláh; Adrian J Mulholland; Jeremy N Harvey
Journal:  Proc Natl Acad Sci U S A       Date:  2011-03-28       Impact factor: 11.205

2.  Predictive models for cytochrome p450 isozymes based on quantitative high throughput screening data.

Authors:  Hongmao Sun; Henrike Veith; Menghang Xia; Christopher P Austin; Ruili Huang
Journal:  J Chem Inf Model       Date:  2011-09-26       Impact factor: 4.956

3.  Prediction of Cytochrome P450 Profiles of Environmental Chemicals with QSAR Models Built from Drug-like Molecules.

Authors:  Hongmao Sun; Henrike Veith; Menghang Xia; Christopher P Austin; Raymond R Tice; Ruili Huang
Journal:  Mol Inform       Date:  2012-10-11       Impact factor: 3.353

Review 4.  Computational prediction of metabolism: sites, products, SAR, P450 enzyme dynamics, and mechanisms.

Authors:  Johannes Kirchmair; Mark J Williamson; Jonathan D Tyzack; Lu Tan; Peter J Bond; Andreas Bender; Robert C Glen
Journal:  J Chem Inf Model       Date:  2012-02-17       Impact factor: 4.956

5.  Use of In Vitro and Predictive In Silico Models to Study the Inhibition of Cytochrome P4503A by Stilbenes.

Authors:  Loai Basheer; Keren Schultz; Merav Fichman; Zohar Kerem
Journal:  PLoS One       Date:  2015-10-20       Impact factor: 3.240

Review 6.  Interactions between CYP3A4 and Dietary Polyphenols.

Authors:  Loai Basheer; Zohar Kerem
Journal:  Oxid Med Cell Longev       Date:  2015-06-09       Impact factor: 6.543

7.  Inhibition of cytochrome P450 3A by acetoxylated analogues of resveratrol in in vitro and in silico models.

Authors:  Loai Basheer; Keren Schultz; Zohar Kerem
Journal:  Sci Rep       Date:  2016-08-17       Impact factor: 4.379

Review 8.  Insights on cytochrome p450 enzymes and inhibitors obtained through QSAR studies.

Authors:  Jayalakshmi Sridhar; Jiawang Liu; Maryam Foroozesh; Cheryl L Klein Stevens
Journal:  Molecules       Date:  2012-08-03       Impact factor: 4.411

9.  Large-scale evaluation of cytochrome P450 2C9 mediated drug interaction potential with machine learning-based consensus modeling.

Authors:  Anita Rácz; György M Keserű
Journal:  J Comput Aided Mol Des       Date:  2020-03-27       Impact factor: 3.686

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.