QSAR

QSAR study has been carried out on the GPR119 agonistic activity of indole-based derivatives in terms of Dragon descriptors. The derived QSAR models have revealed that the atomic Sandersons electronegativities weighted and charge accounting descriptors ATS7e, GATS1e, GATS4e and GGI8, molecular mass weighted descriptors, MATS7m and BELm5, and atomic polarizabilities weighted descriptors ATS7p and BELp8, and molecular topology accounting feature Lovasz-Pelikan index (LP1) played a pivotal role in rationalization of GPR119 agonistic activity of titled compounds. Hydrophilic factor (Hy) and certain structural fragments, such as CHR2X (C-008), R--CX--X (C-008) and H attached to heteroatom (H-050) are also predominant to explain GPR119 agonistic actions of indole-based derivatives. PLS analysis has also corroborated the dominance of CP-MLR identified descriptors. Applicability domain analysis revealed that the suggested model matches the high quality parameters with good fitting power and the capability of assessing external data and all of the compounds was within the applicability domain of the proposed model and were evaluated correctly.

New Chemical Entities (NCEs) were designed using information from pharmacophore profile of known anticonvulsants. Binding affinities of designed NCEs were studied on gamma-aminobutyric acid (GABA-alpha) using docking studies. Two Dimensional (2D) Quantitative Structure–Activity Relationship (QSAR) studies were performed for correlating the chemical composition of triazolethione analogs and estimation of their anticonvulsant activity using Multiple Linear Regression (MLR) Analysis.  ADMET properties were also predicted. These four basic strategies (pharmacophore mapping, QSAR, docking & ADMET screening) were implemented to evaluate the performance of derivatives. Although predicted Ki through QSAR model showed significant mild activity for GABA. Conclusively compounds, 2, 6, 7, 8, 9, 10, 11, and 20 were observed to be most feasible to activate GABA for anticonvulsant activity.

Last three decades enormous work has been carried out on computational chemistry. The projects given for discovery of New Chemical Entities by these methods and gets a safe, potent drug molecule. However, the commercial output for the pharmaceutical company with these methodologies is negligible. Most of the drugs discovered in medicinal chemistry are accidentally. Thus synthesis of focused compound libraries and their pharmacological screening by efficient methods becomes powerful tool for drug discovery. But some additional points are required to move towards aryloxypropanolamines As 1-Aryloxy-3-(N4-substituted piperazinyl) propan-2 OLS (aryloxypropanolamines) shows β-adrenergic receptor antagonist activity (β-blockers), these chemical entities are applicable in management of various diseases due to their therapeutic effects. The main clinical indications of β-blockers are in the area of cardiovascular diseases, such as hypertension, angina pectoris, myocardial infarction and cardiac arrhythmias1-4. However, some β-blockers readily access the brain because of their lipophilicity and can influence some central nervous system functions. Therefore, Propranolol has been used for the treatment of anxiety syndromes, prophylaxis of migraine headaches, schizophrenia, alcohol withdrawals and tremors5-8. Looking at the biological profile of various aryloxypropanolamines (also Enciprazine) molecule, synthesis of various derivatives of Enciprazine having different aryloxy moiety and amine moiety (by taking different N- alkyl/aryl substituted piperazine) was planned to get safe, potent or new activity molecules.

Sulfones are known to possess various biological activities. Their great potential as bioactive compounds, combined with the easy method of synthesis, make this class a strong candidate for the production of medicines economically. This article deals with the synthesis of a series of ten diaryl sulfones, their antibacterial activity, individually, synergistic antibacterial activity with trimethoprim against E. coli and preliminary QSAR studies. The antibacterial activity was performed by agar diffusion method, against Gram positive and Gram negative bacteria. Few derivatives exhibited antibacterial activity comparable to or better than the standard, sulphamethoxazole, against Gram negative organisms (E. coli and S. dysentrae). Sulfones being folic acid inhibitors, their synergistic effect was checked with trimethoprim on E. coli. Most of the compounds exhibited synergistic effect with trimethoprim, which was better than the combination of trimethoprim and sulfamethoxazole (1:5). Quantitative structure activity relationships studies were performed by multiple linear regression analysis. The antibacterial activity of sulfones was found to correlate well with their dipole moment and ionization potential.

Spleen Tyrosine Kinase (SYK) is known to play vital role in many signal transduction pathways and hence is considered as a potent target for various disorders like inflammatory, cancer and many auto immune disorders. QSAR study of Napthyridines as SYK Kinase inhibitors was performed using accelrrys discovery studio client (DSV - Version 3.0) as the modelling tool. A total of 53 selected molecules were considered for the development of QSAR model. The study was performed using the most stable confirmer fitting best to SYK Kinase enzyme binding site. The study resulted in development of cross validated QSAR models using different set of descriptors.  Partial least square model of the data generated exhibited a very good linear relation between the training set of compounds with that of the reported activity as well as the test set of compounds with the predicted activity. The 4 statistical analysis performed revealed following observations; Training data set r2= 0.848, q2 (Cross validated r2) = 0.581 validated by internal validation with correlation of coefficient (r2) of 0.941 and cross validated r2 (q2) of 0.617 and external set of compounds with a predictive correlation of coefficient of 0.918.  A total of 11 descriptors pruned on the study explained the structural correlation of Napthyridines with SYK Kinase enzyme. The mode developed can be used to predict bio-efficacy of unknown molecules 7-methoxy-6-[3-morpholinopropoxy]-quinazoline as SYK Kinase inhibitors. The study calls for the development of the molecules predicted as bio efficacious in this model and a quantitative inhibitory analysis of SYK Kinase. Key words: Napthyridines, QSAR, SYK.

Epidermal Growth Factor Receptor (EGFR) is known to play vital role in many cellular signalling pathways and hence is considered as a potent target for cancer. Inhibition of this enzyme has been reported to be beneficial by various workers. QSAR study of Quinazolines as EGFR was performed using accelrys discovery studio client (DSV-Version 3.0) as the modelling tool. A total of 67 selected molecules were considered for the development of QSAR model. Partial least square model of the data generated exhibited a very good linear relation between the training set of compounds with that of the reported activity as well as the test set of compounds with the predicted activity. The 4 statistical analysis performed revealed following observations; Training data set r2= 0.701, q2 (Cross validated r2) = 0.616 validated by internal validation with correlation of coefficient (r2) of 0.848 and cross validated r2 (q2) of 0.573 and external set of compounds with a predictive correlation of coefficient of 0.900.  A total of 9 descripters pruned on the study explained the structural correlation of quinazolines with EGFR. The model developed can be used to predict bioefficacy of unknown molecules 4-[1,3-benzothiazol-2-yl]-N-[(1E)-(4-nitrophenyl)methylene]aniline as EGFR inhibitors. Further a hypothetical model to describe the interaction between the predicted molecules with EGFR is proposed and this hypothetical model explains the possibility of Met769 and Gln767 as the possible binding sites. The activity is observed in the preliminary cytotoxic activity (MTT assay). The study calls for the development of the molecules predicted as bio efficacious in this model and a quantitative inhibitory analysis of EGFR. Key word: EGFR, QSAR, r2, q2