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

Authors

Jose Isagani B. Janairo, De La Salle University, Manila
Gerardo C. Janairo, De La Salle University, Manila
Frumencio F. Co, De La Salle University, Manila
Derrick Ethelbhert C. Yu, De La Salle University, Manila

College

College of Science

Department/Unit

Physics

Document Type

Article

Source Title

Orbital

Volume

3

Issue

1

First Page

15

Last Page

23

Publication Date

2011

Abstract

The activity of a selected class of DPP4 inhibitors was preliminary assessed using chemical descriptors derived AM1 optimized geometries. Using multiple linear regression model, it was found that ΔE⁰ , LUMO energy, area, molecular weight and ΔH⁰ are the significant descriptors that can adequately assess the binding affinity of the compounds. The derived multiple linear regression (MLR) model was validated using rigorous statistical analysis. The preliminary model suggests that bulky and electrophilic inhibitors are desired.

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Recommended Citation

Janairo, J. B., Janairo, G. C., Co, F. F., & Yu, D. C. (2011). Assessing the binding affinity of a selected class of DPP4 inhibitors using chemical descriptor-based multiple linear regression. Orbital, 3 (1), 15-23. Retrieved from https://animorepository.dlsu.edu.ph/faculty_research/6604

Disciplines

Biochemistry, Biophysics, and Structural Biology

Keywords

CD26 antigen—Inhibitors

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