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3D-QSAR study of benzotriazol-1-yl carboxamide scaffold as monoacylglycerol lipase inhibitors.

Afzal O, Kumar S, Kumar R, Jaggi M, Bawa S - J Pharm Bioallied Sci (2014)

Bottom Line: A 3D-QSAR study on benztriazol-1-yl carboxamide derivatives as monoacylglycerol lipase (MAGL) inhibitors was successfully performed by means of pharmacophore mapping using PHASE 3.5 module of Schrφdinger-9.4.The 3D-QSAR obtained from APRRR-105 hypothesis was found to be statistically good with r(2) = 0.9228 and q(2) = 0.871, taking PLS factor 4.Thus, it can be assumed that the present QSAR analysis is enough to demonstrate MAGL inhibition with the help of APRRR-105 hypothesis and will be helpful in designing novel and potent MAGL inhibitors.

View Article: PubMed Central - PubMed

Affiliation: Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Hamdard University, New Delhi, India.

ABSTRACT

Purpose: The purpose of this study is to build up the 3D pharmacophore of Monoacylglycerol lipase (MAGL) inhibitor and to provide the basis to design the novel and potent MAGL inhibitors.

Material and method: A 3D-QSAR study on benztriazol-1-yl carboxamide derivatives as monoacylglycerol lipase (MAGL) inhibitors was successfully performed by means of pharmacophore mapping using PHASE 3.5 module of Schrφdinger-9.4.

Result: The 3D-QSAR obtained from APRRR-105 hypothesis was found to be statistically good with r(2) = 0.9228 and q(2) = 0.871, taking PLS factor 4. The statistical significance of the model was also confirmed by a high value of Fisher's ratio of 82.8 and a very low value of root-mean-square error (RMSE) 0.2564. Another parameter which signifies the model predictivity is Pearson R. Its value of 0.9512 showed that the correlation between predicted and observed activities for the test set compounds is excellent.

Conclusion: The study suggested that one H-bond acceptor, one positive center, and proper positioning of hydrophobic groups near the distal aromatic ring C are the crucial determinants for MAGL inhibition. Thus, it can be assumed that the present QSAR analysis is enough to demonstrate MAGL inhibition with the help of APRRR-105 hypothesis and will be helpful in designing novel and potent MAGL inhibitors.

No MeSH data available.


Fitness graph between observed activities versus PHASEpredicted activity for training and test set compounds
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Figure 4: Fitness graph between observed activities versus PHASEpredicted activity for training and test set compounds

Mentions: The reliability of the present 3D-QSAR analysis can be justified by the fact that all statistical measures are significant to any level. The model showed 99% variance exhibited by benztriazol-1-yl carboxamides, which is near to one and signified a very close agreement of fitting points on the regression line for the observed and PHASE-predicted activity. The fitness graph is shown in Figure 4 and the observed and PHASE-predicted activity data are summarized in Table 4. Validity of the model can be expressed by internal predictivity (q2 = 0.871) which is obtained by leave-one out (LOO). The q2 obtained by LOO method is a more reliable and robust statistical parameter than r2 because it is obtained by external validation method of dividing the dataset into training and test set. The large value of F (82.8) indicates a statistically significant regression model, which is supported by the small value of the variance ratio (P), an indication of a high degree of confidence. Further small values of standard deviation of the regression (0.2969) and root-mean-square error (RMSE; 0.2564) make an obvious implication that the data used for model generation are best for the QSAR analysis. Apart from the above-mentioned features, PLS factor also confirms the reliability of the model. In this study, the number of PLS factor was taken as 4, and for each increment, it gives one equation and there should be stepwise improvement each time the model generated. In addition to the above parameters, it is interesting to note that active ligands are closely fitted to the regression line and inactive ligands are scattered [Figure 5]. Figure 3 shows the 3D-pharmacophore regions around compounds. For the selected pharmacophore, blue and red cubes represent favorable and unfavorable regions, respectively. Molecular substitutions that increase the number of blue cubes will definitely lead to increased binding affinity of the molecules toward MAGL inhibition, while molecular substitutions that increase the number of red cubes will lead to decreased activity.


3D-QSAR study of benzotriazol-1-yl carboxamide scaffold as monoacylglycerol lipase inhibitors.

Afzal O, Kumar S, Kumar R, Jaggi M, Bawa S - J Pharm Bioallied Sci (2014)

Fitness graph between observed activities versus PHASEpredicted activity for training and test set compounds
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4231386&req=5

Figure 4: Fitness graph between observed activities versus PHASEpredicted activity for training and test set compounds
Mentions: The reliability of the present 3D-QSAR analysis can be justified by the fact that all statistical measures are significant to any level. The model showed 99% variance exhibited by benztriazol-1-yl carboxamides, which is near to one and signified a very close agreement of fitting points on the regression line for the observed and PHASE-predicted activity. The fitness graph is shown in Figure 4 and the observed and PHASE-predicted activity data are summarized in Table 4. Validity of the model can be expressed by internal predictivity (q2 = 0.871) which is obtained by leave-one out (LOO). The q2 obtained by LOO method is a more reliable and robust statistical parameter than r2 because it is obtained by external validation method of dividing the dataset into training and test set. The large value of F (82.8) indicates a statistically significant regression model, which is supported by the small value of the variance ratio (P), an indication of a high degree of confidence. Further small values of standard deviation of the regression (0.2969) and root-mean-square error (RMSE; 0.2564) make an obvious implication that the data used for model generation are best for the QSAR analysis. Apart from the above-mentioned features, PLS factor also confirms the reliability of the model. In this study, the number of PLS factor was taken as 4, and for each increment, it gives one equation and there should be stepwise improvement each time the model generated. In addition to the above parameters, it is interesting to note that active ligands are closely fitted to the regression line and inactive ligands are scattered [Figure 5]. Figure 3 shows the 3D-pharmacophore regions around compounds. For the selected pharmacophore, blue and red cubes represent favorable and unfavorable regions, respectively. Molecular substitutions that increase the number of blue cubes will definitely lead to increased binding affinity of the molecules toward MAGL inhibition, while molecular substitutions that increase the number of red cubes will lead to decreased activity.

Bottom Line: A 3D-QSAR study on benztriazol-1-yl carboxamide derivatives as monoacylglycerol lipase (MAGL) inhibitors was successfully performed by means of pharmacophore mapping using PHASE 3.5 module of Schrφdinger-9.4.The 3D-QSAR obtained from APRRR-105 hypothesis was found to be statistically good with r(2) = 0.9228 and q(2) = 0.871, taking PLS factor 4.Thus, it can be assumed that the present QSAR analysis is enough to demonstrate MAGL inhibition with the help of APRRR-105 hypothesis and will be helpful in designing novel and potent MAGL inhibitors.

View Article: PubMed Central - PubMed

Affiliation: Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Hamdard University, New Delhi, India.

ABSTRACT

Purpose: The purpose of this study is to build up the 3D pharmacophore of Monoacylglycerol lipase (MAGL) inhibitor and to provide the basis to design the novel and potent MAGL inhibitors.

Material and method: A 3D-QSAR study on benztriazol-1-yl carboxamide derivatives as monoacylglycerol lipase (MAGL) inhibitors was successfully performed by means of pharmacophore mapping using PHASE 3.5 module of Schrφdinger-9.4.

Result: The 3D-QSAR obtained from APRRR-105 hypothesis was found to be statistically good with r(2) = 0.9228 and q(2) = 0.871, taking PLS factor 4. The statistical significance of the model was also confirmed by a high value of Fisher's ratio of 82.8 and a very low value of root-mean-square error (RMSE) 0.2564. Another parameter which signifies the model predictivity is Pearson R. Its value of 0.9512 showed that the correlation between predicted and observed activities for the test set compounds is excellent.

Conclusion: The study suggested that one H-bond acceptor, one positive center, and proper positioning of hydrophobic groups near the distal aromatic ring C are the crucial determinants for MAGL inhibition. Thus, it can be assumed that the present QSAR analysis is enough to demonstrate MAGL inhibition with the help of APRRR-105 hypothesis and will be helpful in designing novel and potent MAGL inhibitors.

No MeSH data available.