Molecular Design Based on Receptor-Independent Pharmacophore: Application to Estrogen Receptor Ligands

Abstract

Estrogens, a group of steroid hormones, act primarily by regulating gene expression after binding with estrogen receptor (ER), a nuclear ligand-activated transcription factor, translocates to the nucleus after dimer formation, enhances the gene transcription. Estrogen Receptor Modulators (ERMs) have selective agonist and antagonist effects to different tissues, and the purpose of research on ERMs is to identify new potent and less toxic drug molecules. The present study has been focused on finding the structural requirements of ER ligand, using receptor-independent pharmacophore space modeling studies that can explore 3D structural features and configurations, responsible for the biological activity of structurally diverse compounds. The studies show (R‫,549.0؍‬ RMSD‫,681.2؍‬ D Dcost‫)453.776؍‬ the importance of hydrogen bond acceptors in the aromatic rings and a planner hydrophobic region in the molecular architecture along with critical geometrical distance between features are effectively crucial for binding with ER.

Identification of structural requirements of estrogen receptor modulators using pharmacoinformatics techniques for application to estrogen therapy

“…. Additionally, the variance ratio (F) with degree of freedom (df) and explained variance (EV) for 2D-QSAR study were also considered, while different cost factors (Islam et al 2008) were used for space modeling study. In order to evaluate the predictive power of the model, R 2 pred (correlation coefficient), s p (error of prediction) and modified correlation coefficient (r 2 m(test) ) of the test set were also determined in both studies.…”

Poly(<small>DL</small>-lactide-<i>co</i>-glycolic acid) Nanoparticle Design and Payload Prediction: A Molecular Descriptor Based Study

“…The final reduced model was cross validated in each case and similar findings were reported elsewhere. 42,60,61) Descriptor inter-correlations were cross checked and the final MLR equations were developed accommodating only the non-correlated descriptors. The best linear QSPR models for drug loading in PLGA in three different descriptor platform were depicted in Table 3.…”

Pharmacophore-Based Virtual Screening and Structural Modification of Novel Benzamide Derivatives as HBV Capsid Assembly Modulators

“…Based Screening Pharmacophore modeling makes use of compound collections to generate structural patterns present in active compounds. [16][17][18][19] Pharmacophore-based virtual screening relies on molecular simulation technology, which is fast, versatile, and easy to operate. Additionally, the tandem approach is performed to obtain hits efficiently by combining structure-based virtual screening with ligand-based pharmacophore screening.…”