SOMP: web server for in silico prediction of sites of metabolism for drug-like compounds | Zendy

Anastasia V. Rudik | Zendy; Alexander V. Dmitriev | Zendy; Alexey A. Lagunin | Zendy; Dmitry Filimonov | Zendy; Vladimir Poroikov | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

SOMP: web server for in silico prediction of sites of metabolism for drug-like compounds

Author(s) -

Anastasia V. Rudik,

Alexander V. Dmitriev,

Alexey A. Lagunin,

Dmitry Filimonov,

Vladimir Poroikov

Publication year - 2015

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btv087

Subject(s) - in silico , computer science , web server , drug , drug metabolism , web site , computational biology , chemistry , world wide web , pharmacology , the internet , biology , biochemistry , gene

A new freely available web server site of metabolism predictor to predict the sites of metabolism (SOM) based on the structural formula of chemicals has been developed. It is based on the analyses of 'structure-SOM' relationships using a Bayesian approach and labelled multilevel neighbourhoods of atoms descriptors to represent the structures of over 1000 metabolized xenobiotics. The server allows predicting SOMs that are catalysed by 1A2, 2C9, 2C19, 2D6 and 3A4 isoforms of cytochrome P450 and enzymes of the UDP-glucuronosyltransferase family. The average invariant accuracy of prediction that was calculated for the training sets (using leave-one-out cross-validation) and evaluation sets is 0.9 and 0.95, respectively.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research