ArticleMolecules (Basel, Switzerland)2025
Quantitative Structure-Activity Relationship (QSAR) Modeling of Chiral CCR2 Antagonists with a Multidimensional Space of Novel Chirality Descriptors.
Article in Molecules (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The development of chirality descriptors for quantitative chirality structure-activity relationship (QCSAR) modeling has always attracted attention, owing to the importance of chiral molecules in pharmaceutical, agriculture, food, and fragrance industries, and environmental toxicology. The utility of a multidimensional space of novel relative chirality indices (RCIs) in the QCSAR modeling of twenty CCR2 antagonists is reported upon in this paper. The numerical characterization of chirality by the RCI approach gives a large pool of chirality descriptors with different degrees of mutual correlation (the correlation coefficient among the computed descriptors varied from 0.02 to 0.99). In the present study, the final data set contains 198 chirality descriptors for each of the twenty CCR2 antagonist molecules, providing a multidimensional space for modeling. The data reduction using principal component analysis resulted in the extraction of eight principal components (PCs). The linear regression using the principal component scores (PCSs) resulted in a three-predictor prediction model with good statistics: R
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