THEORETICAL MODELLING FOR INVESTIGATING SOME ACTIVE COMPOUNDS AS POTENT INHIBITORS AGAINST LUNG CANCER: A MULTI-LINEAR REGRESSION APPROACH

A Quantitative Structure Activity Relationship (QSAR) study has been attempted on ciprofloxacin derivatives as potent anti-lung cancer. QSAR models were derived with the aid of multi-linear regression (MLR) approach using topological, molecular shape, electronic and structural descriptors. The predi...

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Bibliographic Details
Main Authors: Shola Elijah Adeniji, Momohjimoh Idris Ovaku, Tukur Saidu, Ahanonu Saviour Ugochukwu, Gideon Shallangwa, Adamu Uzairu
Format: Article
Language:English
Published: Universidade Federal de Viçosa (UFV) 2019-03-01
Series:The Journal of Engineering and Exact Sciences
Subjects:
Online Access:https://periodicos.ufv.br/ojs/jcec/article/view/2509
Description
Summary:A Quantitative Structure Activity Relationship (QSAR) study has been attempted on ciprofloxacin derivatives as potent anti-lung cancer. QSAR models were derived with the aid of multi-linear regression (MLR) approach using topological, molecular shape, electronic and structural descriptors. The predictive ability of the QSAR models generated  were validated and the best model selected has squared correlation coefficient (R2) of 0.954801, adjusted squared correlation coefficient (Radj) of 0.939265, Leave one out (LOO) cross validation coefficient () value of 0.907523. The external validation set used for confirming the predictive power of the model has its R2pred of 0.8387. The QSAR models point out that AATSC2m, VR3_Dzp and BIC2 are the important descriptors effectively describing the bioactivity of these compounds.
ISSN:2527-1075