Identification of high affinity bioactive Salbutamol conformer directed against mutated (Thr164Ile) beta 2 adrenergic receptor.

Salbutamol forms an important and widely administered ß2 agonist prescribed in the symptomatic treatment of bronchial asthma. Unfortunately, a subset of patients show refractoriness to it owing to ADRB2 gene variant (rs 1800888). The variant substitutes Thr to Ile at the position 164 in the ß2 adrenergic receptor leading to sub-optimal binding of agonists. The present study aims to associate the Salbutamol response with the variant and select the bioactive conformer of Sabutamol with optimal binding affinity against mutated receptor by in silico approaches. To assess bronchodilator response spirometry was performed before and 15 min after Salbutamol (200 mcg) inhalation. Responders to Salbutamol were categorized if percentage reversibility was greater than or equal to 12%, while those showing FEV1 reversibility less than 12% were classified as non-responders. Among the 344 subjects screened, 238 were responders and 106 were non-responders. The frequency of mutant allele "T" was significantly higher in case of non-responders (p < 0.05). In silico process involved generation of Salbutamol conformer ensembles supported by systematic search algorithm. 4369 conformers were generated of which only 1882 were considered bioactive conformers (threshold RMSD≤1 in reference to normalized structure of salbutamol). All the bioactive conformers were evaluated for the binding affinity against (Thr164 Ile) receptor through MolDock aided docking algorithm. One of the bioactive conformer (P.E. = -57.0038, RMSD = 0.6) demonstrated 1.54 folds greater affinity than the normal Salbutamol in the mutated receptor. The conformer identified in the present study may be put to pharmacodynamic and pharmacokinetic studies in future ahead.

Molecular docking approaches in identification of High affinity inhibitors of Human SMO receptor.

Inappropriate activation of the Hh signaling pathway has been implicated in the development of several types of cancers including prostate, lung, pancreas, breast, brain and skin. Present study identified the binding affinities of eight established inhibitors viz., Cyclopamine, Saridegib, Itraconazole, LDE-225, TAK-441, BMS-833923 (XL139), PF-04449913 and Vismodegib targeting SMO receptor - a candidate protein involved in hedgehog pathway and sought to identify the best amongst the established inhibitors through by molecular docking. Exelxis® BMS 833923 (XL 139) demonstrated superior binding affinity aided by MolDock scoring docking algorithm. Further BMS 833923 (XL 139) was evaluated for pharmacophoric features which revealed appreciable ligand receptor interactions.