Open AccessInsilco study on the toxicity of anti-cancer compounds tested against MOLT-4 and p388 cell lines using GA-MLR technique
Author(s) -
David Ebuka Arthur,
Adamu Uzairu,
Paul Andrew Mamza,
Stephen Eyije Abechi,
Gideon Adamu Shallangwa
Publication year - 2016
Publication title -
beni-seuf university journal of basic and applied sciences /beni-suef university journal of basic and applied sciences
Language(s) - English
Resource type - Journals
eISSN - 2314-8543
pISSN - 2314-8535
DOI - 10.1016/j.bjbas.2016.11.003
Subject(s) - robustness (evolution) , toxicity , isopropyl , quantitative structure–activity relationship , computational biology , chemistry , stereochemistry , biology , biochemistry , organic chemistry , gene
The research entails the development of two models that can be used to predict the toxicity of compounds suspected of having anti-leukemia activity, the two models, one for MOLT-4 and the other for P388 cell lines, were developed by carefully selecting 5 descriptors in each case from a pool of 4900 molecular descriptors using GA-MLR method. The ability of the models to predict chemicals that were not used in the preparation set was evaluated by validating the models internally [Q2CV MOLT-4 = 0.644 and Q2CV (P388) = 0.641] and externally [R2pred (P388) = 0.662 and R2pred (MOLT-4) = 0.679], other criteria such as r2m, R2p, k and k′ were also determined and were found to support R2pred results of the models. The effects of every descriptor in the model were dictated by calculating their individual mean effect to (pLC50) the toxicities of the compounds. SpMax7_Bhm (1.697) and RDF145u (−4.300) influenced the models the most, while in MOLT-4 the descriptors with the least effect was n-isopropyl (0.0343) and for P388 is 1.162. The models were further validated by subjecting them to y-randomization which finally confirmed the robustness of the models developed