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Journals / Turkish Journal of Chemistry / 2018 / Cilt: 42 - Sayı: 6

4D-QSAR analysis and pharmacophore modeling for alkynylphenoxyacetic acids as CRTh2 (DP2) receptor antagonists

Semiha KÖPRÜ
Emin SARIPINAR
Pages
1577–1597
Publication Date
2022-11-01
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

For the best model the r 2training , r 2test , q 2, q 2ext1 , q 2ext2 , and q 2ext3 values were found to be0.8580, 0.8571, 0.8105, 0.8282, 0.8145, and 0.8475, respectively.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, we performed the pharmacophore modeling and 4D-QSAR research of alkynylphenoxyaceticacid analogues as CRTh2 receptor opponent agents by utilizing the electron conformational genetic algorithm method.Quantum chemical calculations and conformational analyses of the compounds were carried out at HF/6-31G* level.Then electron conformational matrices of congruity were prepared for each conformer of each compound, which arerepresented by electronic and structural properties.
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Key Findings & Data:The compounds in the dataset were randomly segregated for training (61 compounds) andtest sets (25 compounds) for statistical analysis.
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Conclusion & Impact:For the best model the r 2training , r 2test , q 2, q 2ext1 , q 2ext2 , and q 2ext3 values were found to be0.8580, 0.8571, 0.8105, 0.8282, 0.8145, and 0.8475, respectively.
🔬Design:Lab & Field Experiment
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

In this study, we performed the pharmacophore modeling and 4D-QSAR research of alkynylphenoxyaceticacid analogues as CRTh2 receptor opponent agents by utilizing the electron conformational genetic algorithm method.Quantum chemical calculations and conformational analyses of the compounds were carried out at HF/6-31G* level.Then electron conformational matrices of congruity were prepared for each conformer of each compound, which arerepresented by electronic and structural properties. As a result of the comparison of the matrices that are called electronconformational submatrices of activity, the pharmacophoric group of the compounds responsible for the activity wasfound at the determined tolerance intervals. The genetic algorithm and nonlinear least squares regression methods wereapplied to estimate the conjectural activity and investigate the most reliable molecular identifiers as feature selectionfrom a large parameter pool. The compounds in the dataset were randomly segregated for training (61 compounds) andtest sets (25 compounds) for statistical analysis. Validation of the 4D-QSAR model was appraised by the leave-one-outcross-validation technique. For the best model the r 2training , r 2test , q 2, q 2ext1 , q 2ext2 , and q 2ext3 values were found to be0.8580, 0.8571, 0.8105, 0.8282, 0.8145, and 0.8475, respectively.

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Cite This Article

KÖPRÜ, S., SARIPINAR, E. (2022). 4D-QSAR analysis and pharmacophore modeling for alkynylphenoxyacetic acids as CRTh2 (DP2) receptor antagonists. Turkish Journal of Chemistry, Cilt: 42 - Sayı: 6, 1577–1597. https://ajindex.com/articles/601823

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