Identification of degradation impurity of TGR5 receptor agonist-ZY12201 by LC-MS technique during force degradation study.

Forced degradation study is a systemic characterization of degradation products of active pharmaceutical ingredient (API) at conditions which posses more harsh environment that accelerates degradation of API. Forced degradation and stability studies would be useful in selection of proper, packaging material and storage conditions of the API. These are also useful to demonstrate degradation pathways and degradation products of the API and further characterisation of the degradation products using mass spectrometry. TGR5 is a G protein-coupled receptor, activation of which promotes secretion of glucagon-like peptide-1 (GLP-1) and modulates insulin secretion. The potent and orally bioavailable TGR5 agonist, ZY12201, shows activation of TGR5 which increase secretion of GLP-1 and help in lowering blood glucose level in animal models. Hence it is necessary to establish and study degradation pathway and stability of API for better handling and regulatory approval. Force degradation studies of ZY12201 have shown presence of one oxidative impurity during oxidative degradation in HPLC analysis. The oxidized product is further characterized by LC-MS to elucidate structure of impurity and characterize its degradation pathway. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s42452-021-04660-y.

Synthesis, in vitro antitubercular activity and 3D-QSAR study of 1,4-dihydropyridines.

In continuation of our research program on new antitubercular agents, this article is a report of the synthesis of 97 various symmetrical, unsymmetrical, and N-substituted 1,4-dihydropyridines. The synthesized molecules were tested for their activity against M. tuberculosis H (37)Rv strain with rifampin as the standard drug. The percentage inhibition was found in the range 3-93%. In an effort to understand the relationship between structure and activity, 3D-QSAR studies were also carried out on a subset that is representative of the molecules synthesized. For the generation of the QSAR models, a training set of 35 diverse molecules representing the synthesized molecules was utilized. The molecules were aligned using the atom-fit technique. The CoMFA and CoMSIA models generated on the molecules aligned by the atom-fit method show a correlation coefficient (r (2)) of 0.98 and 0.95 with cross-validated r (2)(q (2)) of 0.56 and 0.62, respectively. The 3D-QSAR models were externally validated against a test set of 19 molecules (aligned previously with the training set) for which the predictive r(2)(r(r)(pred)) is recorded as 0.74 and 0.69 for the CoMFA and CoMSIA models, respectively. The models were checked for chance correlation through y-scrambling. The QSAR models revealed the importance of the conformational flexibility of the substituents in antitubercular activity.

Synthesis, screening for antitubercular activity and 3D-QSAR studies of substituted N-phenyl-6-methyl-2-oxo-4-phenyl-1,2,3,4-tetrahydro-pyrimidine-5-carboxamides.

Multi-drug resistance to commonly used antitubercular drugs has propelled the development of new structural classes of antitubercular agents. This paper reports the synthesis, evaluation and 3D-QSAR analysis of a set of substituted N-phenyl-6-methyl-2-oxo-4-phenyl-1,2,3,4-tetrahydropyrimidine-5-carboxamides as antitubercular agents. Substituted acetoacetanilides were reacted with various aromatic aldehydes and urea which yielded the tetrahydropyrimidine derivatives with a phenyl carbamoyl group at C5 position, and with various substitutions on the 4-phenyl and the N-phenyl aromatic rings. All compounds were screened for antitubercular activity against Mycobacterium tuberculosis H37Rv strain. The QSAR models were generated on a training set of 23 molecules. The molecules were aligned using the atom-fit and field-fit techniques. The CoMFA and CoMSIA models generated on the molecules aligned by the atom-fit method show a correlation coefficient (r2) of 0.98 and 0.95 with cross-validated r2(q2) of 0.68 and 0.58, respectively. The 3D-QSAR models were externally validated against a test set of 7 molecules for which the predictive r2 (r(pred)2) is recorded as 0.41 and 0.32 for the CoMFA and CoMSIA models, respectively. The CoMFA and CoMSIA contours helped to design some new molecules with improved activity.