Docking and QSAR Studies of New Imidazo [1,2-a] Quinoxaline Derivatives using Genetic Function Approximation (GFA) against Human Melanoma
Publication Date: 12/11/2020
Author(s): Emmanuel Israel Edache, Shafiu Saidu.
Volume/Issue: Volume 3 , Issue 3 (2020)
Abstract:
In this paper, to comprehend the chemical-biological interactions governing their activities toward antitumor activity, QSAR models of 31 derivatives of New imidazo [1, 2-a] quinoxaline derivatives with inhibitory tumor were developed. The quantitative structure-activity relationship (QSAR) model was built by using the genetic function algorithm (GFA) technique, and the best GFA model has SEE = 0.51748, R2 = 0.73038 cross-validated, R2adjusted = 0.63234, F = 7.44967 (DF: 4, 11), and Q2 = 0.51664 non-cross-validated. The predictive ability of the GFA model was further validated by a test set of 8 compounds, giving R2pred = 0.73038. Docking studies were used to discover the real conformations of chemicals in the active site, as well as the binding mode shape to the binding site in enzyme. Ligand with PubChem_CID number 44561182 has the least binding affinity with the enzyme. The information provided by the 2D-QSAR model and docking may lead to a better understanding of the structural requirements of 31 New imidazo [1, 2-a] quinoxaline derivatives and help to design potential anti-tumor molecules.
Keywords:
Tumor, Quinoxalinamine Derivatives, GFA-MLR, QSAR, Applicability Domain, Molecular Docking
