QSAR Modelling of Peptidomimetic Derivatives towards HKU4-CoV 3CL<sup>pro</sup> Inhibitors against MERS-CoV
In this paper, we report the relationship between the anti-MERS-CoV activities of the HKU4 derived peptides for some peptidomimetic compounds and various descriptors using the quantitative structure activity relationships (QSAR) methods. The used descriptors were computed using ChemSketch, Marvin Sk...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-03-01
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| Series: | Chemistry |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2624-8549/3/1/29 |
| Summary: | In this paper, we report the relationship between the anti-MERS-CoV activities of the HKU4 derived peptides for some peptidomimetic compounds and various descriptors using the quantitative structure activity relationships (QSAR) methods. The used descriptors were computed using ChemSketch, Marvin Sketch and ChemOffice software. The principal components analysis (PCA) and the multiple linear regression (MLR) methods were used to propose a model with reliable predictive capacity. The original data set of 41 peptidomimetic derivatives was randomly divided into training and test sets of 34 and 7 compounds, respectively. The predictive ability of the best MLR model was assessed by determination coefficient R<sup>2</sup> = 0.691, cross-validation parameter Q<sup>2</sup><sub>cv</sub> = 0.528 and the external validation parameter R<sup>2</sup><sub>test</sub> = 0.794. |
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| ISSN: | 2624-8549 |