Assessing the binding affinity of a selected class of DPP4 inhibitors using chemical descriptor-based multiple linear regression

Orbital: The Electronic Journal of Chemistry

Gerardo Janairo¹  Derrick Ethelbhert Yu²  Frumencio Co³  Jose Isagani Janairo⁴ 

[1] Chemistry Department, De La Salle University and Materials Science and Nanotechnology Unit, Center for NaturalSciences and Environmental Research (CENSER), De La Salle University, 2401 Taft Avenue, Manila, Philippines.bChemistry Department, De La Salle University.;Chemistry Department, De La Salle University, 2401 Taft Avenue, Manila, Philippines.Materials Science and Nanotechnology Unit, Center for NaturalSciences and Environmental Research (CENSER), De La Salle University, 2401 Taft Avenue, Manila, Philippines;Mathematics Department, De La Salle University, 2401 Taft Avenue, Manila, Philippines;Physics Department, De La Salle University and Materials Science and Nanotechnology Unit, Center for NaturalSciences and Environmental Research (CENSER), De La Salle University, 2401 Taft Avenue, Manila, Philippines.bChemistry Department, De La Salle University;

关键词: dpp4 inhibitors;    am1;    chemical descriptors;    multiple linear regression;   

DOI  :  10.17807/orbital.v3i1.206

来源: DOAJ

【 摘 要 】

The activity of a selected class of DPP4 inhibitors was preliminarilyassessed using chemical descriptors derived AM1 optimized geometries. Usingmultiple linear regression model, it was found that ?E0, LUMO energy, area,molecular weight and ?H0 are the significant descriptors that can adequatelyassess the binding affinity of the compounds. The derived multiple linear regression(MLR) model was validated using rigorous statistical analysis. The preliminarymodel suggests that bulky and electrophilic inhibitors are desired.

【 授权许可】

Unknown