PreMetabo: An in silico phase I and II drug metabolism prediction platform.

Abstract:

:This study aimed to develop a drug metabolism prediction platform using knowledge-based prediction models. Site of Metabolism (SOM) prediction models for four cytochrome P450 (CYP) subtypes were developed along with uridine 5'-diphosphoglucuronosyltransferase (UGT) and sulfotransferase (SULT) substrate classification models. The SOM substrate for a certain CYP was determined using the sum of the activation energy required for the reaction at the reaction site of the substrate and the binding energy of the substrate to the CYP enzyme. Activation energy was calculated using the EaMEAD model and binding energy was calculated by docking simulation. Phase II prediction models were developed to predict whether a molecule is the substrate of a certain phase II conjugate protein, i.e., UGT or SULT. Using SOM prediction models, the predictability of the major metabolite in the top-3 was obtained as 72.5-84.5% for four CYPs, respectively. For internal validation, the accuracy of the UGT and SULT substrate classification model was obtained as 93.94% and 80.68%, respectively. Additionally, for external validation, the accuracy of the UGT substrate classification model was obtained as 81% in the case of 11 FDA-approved drugs. PreMetabo is implemented in a web environment and is available at https://premetabo.bmdrc.kr/.

authors

Hwang S,Shin HK,Shin SE,Seo M,Jeon HN,Yim DE,Kim DH,No KT

doi

10.1016/j.dmpk.2020.05.007

subject

Has Abstract

pub_date

2020-08-01 00:00:00

pages

361-367

issue

4

eissn

1347-4367

issn

1880-0920

pii

S1347-4367(20)30369-4

journal_volume

35

pub_type

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