A simple, rapid and precise reverse phase liquid chromatographic (RP-HPLC) method was developed and subsequently validated for simultaneous estimation of Ambroxol hydrochloride and Fexofenadine hydrochloride in bulk drug and in a synthetic mixture. The method is based on High Performance Liquid Chromatography (HPLC) on a reversed -phase column, Hypersil ODS C18 (Hypersil ODS 250 x 4.6 mm, 5, Make: Thermo Scientific) prepacked column. The separation was carried out using a mobile phase containing a buffer and acetonitrile (56:44 v/v), was pumped at a flow rate of 0.8 mL/min, column temperature at 35º C using UVdetection at 225 nm. Both the drugs were well resolved on the stationary phase and the retention times were around 2.424 minute for Ambroxol hydrochloride and 3.753 minute for Fexofenadine hydrochloride. The method was validated and shown to be linear for both the drugs. The correlation coefficients for Ambroxol hydrochloride and Fexofenadine hydrochloride are 0.9994 and 0.9992 respectively.

Background: Cancer is the most common malignancy in men and women globally. The tyrosine kinases and serine/threonine kinases are essential to cell mediators for extra & intra-cellular signal transduction processes and play a key role in cell proliferation, differentiation, migration, metabolism, and programmed cell deaths. In this context, kinases are considered as a potential drug target for cancer therapy. Methods: In the present study, a two-dimensional (2D) quantitative structure-activity relationship (2D-QSAR) was performed to analyze anticancer activities of 28 quinazolinyl-arylurea (QZA) derivatives based on the liver (BEL-7402), stomach (MGC-803), and colon (HCC-827) cancer cell lines using multiple linear regression (MLR) analysis. It was accomplished by using 2D-QSAR analysis on the available IC50 data of 28 molecules based on theoretical molecular descriptors to develop predictive models that correlate structural features of QZA derivatives to their anticancer activities. A suitable set of molecular descriptors such as constitutional, topological, geometrical, electrostatic, and quantum-chemical descriptors were calculated to represent the structural features of compounds. The genetic algorithm (GA) method was used to identify the important molecular descriptors to build the QSAR models and used to predict the anti-cancer activities. Results and Discussion: The obtained 2D-QSAR models were vigorously validated using various statistical metrics using leave-one-out (LOO) and external test set prediction approaches. The best predictive models by MLR gave highly significant square of correlation coefficient (R2train) values of 0.799, 0.815, and 0.779 for the training set and the correlation coefficients (R2test) were obtained 0.885, 0.929, and 0.774 for the test set for the liver, stomach, and colon cancer cell lines. The models also demonstrated good predictive power confirmed by the high value of cross-validated correlation coefficient Q2 value of 0.663, 0.717, and 0.671 for three different cancer cell lines. Importantly, the model's quality was judged as well based on mean absolute error (MAE) criteria and the results were consistent with proposed limits by Golbraikh and Tropsha. Conclusion: The QSAR results of the study indicated that the proposed models were robust and free from chance correlation. This study indicated that maxHBint7, SpMax8_Bhm, and ETA_Beta_ns_d have positively contributed descriptors for anti-cancer activity in the liver, stomach, and colon cancer cell lines and a detailed mechanistic interpretation of each model revealed important structural features that were responsible for favorable or unfavorable for anti-cancer activity. The predictive ability of the proposed models was good and may be useful for developing more potent quinazolinyl-arylurea compounds as anti-cancer agents.

Pyridine-based ring systems are heterocycle-structured subunits that are being abundantly employed in drug design, primarily because of their tremendous effect on pharmacological activity, which has resulted in the discovery of various broad-spectrum medicinal compounds. Pyridine derivatives are employed to treat multiple medical illnesses, including prostate cancer, AIDS, tuberculosis, angina, ulcer, arthritis, urinary tract analgesic, Alzheimer’s disease, and cardiovascular diseases. This chapter emphasized the currently available synthetic pyridine derivatives, including nimodipine, ciclopirox, efonidipine, nifedipine, milrinone, and amrinone, effects on cardiac ionic channels and their mechanisms of action for the cure. Pyridine derivatives regulate several voltage-gated ion channel behaviors, including sodium (Nav), calcium (Cav), and potassium (Kv) channels, and are set as a therapeutic approach. Particularly, calcium-channel blockers are the most common action of medicines with a dihydropyridine ring and are often used to treat hypertension and heart-related problems. Finally, this chapter gives the prospects of highly potent bioactive molecules to emphasize the advantages of using pyridine and dihydropyridine in drug design. This chapter discusses pyridine derivatives acting on cardiac ionic channels to combat CVS diseases. The book chapter describes the importance of pyridine derivatives as a novel class of medications for treating cardiovascular disorders.

HER2 positive breast cancer is most common malignancy in women globally. Aberrant behavior of HER2 kinase protein is a hallmark of tumorigenesis, and as a result it has been considered as an emerging potential drug target for breast cancer therapy. In the present investigation a series of N-substituted rhodanine derivatives (33 compounds) were subjected to 2D-QSAR studies with the aid of genetic algorithm (GA) method to identify the essential structural features that responsible for cytotoxic activity. Based on the results, the cytotoxic activity of N-substituted rhodanine derivatives can be successfully explained in terms of twodimensional (ATSC7v), and three-dimensional (geomRadius and RDF45i) descriptors. The obtained model was vigorously validated and passed all validation metrics (R2train = 0.913, R2adj = 0.899, Q2LOO = 0.870, R2test = 0.848). Importantly, the model quality was good based on mean absolute error (MAE) criteria and the results were consistent with proposed limits by Golbraikh and Tropsha. Molecular docking study of the active compounds (ligands 4, 16, and 27) revealed the formation of hydrogen and hydrophobic interactions within the active site of HER2 protein. Keywords: HER2 proteins, breast cancer, cytotoxic agents, rhodanine, molecular docking, 2DQSAR.