Open AccessIn Silico Docking of Rhodanine Derivatives and 3D-QSAR Study to Identify Potent Prostate Cancer Inhibitors
Author(s) -
Koffi Alexis Respect Kouassi,
Adenidji Ganiyou,
Diomande Gbe Gondo Didier,
Anoubilé Benié,
Nahossé Ziao
Publication year - 2022
Publication title -
computational chemistry
Language(s) - English
Resource type - Journals
eISSN - 2332-5984
pISSN - 2332-5968
DOI - 10.4236/cc.2022.102002
Subject(s) - pharmacophore , rhodanine , quantitative structure–activity relationship , adme , virtual screening , in silico , chemistry , prostate cancer , computational biology , combinatorial chemistry , stereochemistry , cancer , biochemistry , biology , in vitro , genetics , gene