Abstract
In this study, we performed the pharmacophore modeling and 4D-QSAR research of alkynylphenoxyacetic acid 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 are represented by electronic and structural properties. As a result of the comparison of the matrices that are called electron conformational submatrices of activity, the pharmacophoric group of the compounds responsible for the activity was found at the determined tolerance intervals. The genetic algorithm and nonlinear least squares regression methods were applied to estimate the conjectural activity and investigate the most reliable molecular identifiers as feature selection from a large parameter pool. The compounds in the dataset were randomly segregated for training (61 compounds) and test sets (25 compounds) for statistical analysis. Validation of the 4D-QSAR model was appraised by the leave-one-out cross-validation technique. For the best model the r$^{2}_{training}$, r$^{2}_{test}$, q$^{2}$, q$^{2}_{ext1}$, q$^{2}_{ext2}$, and q$^{2}_{ext3}$ values were found to be 0.8580, 0.8571, 0.8105, 0.8282, 0.8145, and 0.8475, respectively.
Highlights
The CRTh2 receptor, which is an arachidonic acid metabolite and is released from mast cells, seems to act as a central negotiator for the treatment of asthma and other inflammatory illnesses. 1,2 Allergic diseases and inflammation are commonly related to immunoglobulin E (IgE) production and mast cell activation.[3]
A dataset containing 86 compounds consisting of CRTh2 receptor antagonist derivatives was used in the 4DQSAR study
In this 4D-Quantitative structure-activity relationships (QSARs) study using the electron conformational-genetic algorithm (EC-GA) method within the scope, the EC method and genetic algorithm optimization technique were used together and ligand-based computer-aided drug design was done at the same time
Summary
The CRTh2 receptor ( known as DP2), which is an arachidonic acid metabolite and is released from mast cells, seems to act as a central negotiator for the treatment of asthma and other inflammatory illnesses. 1,2 Allergic diseases and inflammation are commonly related to immunoglobulin E (IgE) production and mast cell activation.[3]. 4−6 PGD2 exerts its biological responses by means of two high affinity G protein-coupled receptors, the DP1 receptor and a chemoattractant receptor-homologous molecule represented classically by T-helper 2 cells (CRTh2) receptor. 11 Quantitative structure-activity relationships (QSARs) are an important part of modern drug design and medicinal chemistry and are used to detect the correlation between the biological activity of a set of molecules and molecular descriptors by means of a statistical or mathematical tool. 12−16 In a QSAR study, molecules are characterized by the presence of molecular descriptors that contain physicochemical and structural features. The selection of potential molecular descriptors from a set of biologically active conformers is the most important step in QSAR model generation to understand the nature of molecular features prior to actual QSAR model building. The selection of potential molecular descriptors from a set of biologically active conformers is the most important step in QSAR model generation to understand the nature of molecular features prior to actual QSAR model building. 17,18
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