Assessing the binding affinity of a selected class of DPP4 inhibitors using chemical descriptor-based multiple linear regression
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 as...
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| Main Authors: | , , , |
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| Format: | text |
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Animo Repository
2011
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| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/6604 |
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| Institution: | De La Salle University |
| Summary: | 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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