Pharmacophore modeling, 3D-QSAR, docking study and ADME prediction of acyl 1,3,4-thiadiazole amides and sulfonamides as antitubulin agents

Abstract

Pharmacophore modeling, molecular docking, and in silico ADME studies have been carried out to determine the binding mode and drug likeliness profile of acyl 1,3,4-thiadiazole amides and sulfonamides as antitubulin agents. A four point pharmacophore model (AAHR.11) was generated using 63 compounds with IC50 values ranging from 3.16 to 505.76 μM. A statistically significant 3D-QSAR model was generated from the pharmacophore hypothesis. The model had a high correlation coefficient (R2 = 0.8925), cross validation coefficient (Q2 = 0.8204) and F value (44.3) at 6 component PLS factor. The results of external validation indicated that the generated QSAR model possessed a high predictive power (R2 = 0.83). The generated model also passed Tropsha’s test for predictive ability and Y-Randomisation test. The Domain of Applicability (APD) of the model was also successfully defined to ascertain that a given estimation can be considered reliable. Further, the restrictivity of the model was checked with inactive compounds by enrichment studies using the decoy test. In order to evaluate the effectiveness of the docking protocol, co-crystallized ligand was extracted from the ligand binding domain of the protein and was re-docked into the same position. The conformer obtained on re-docking and the co-crystallized ligand were superimposed and the RMSD between the two was found to be 0.853 Å. ADME predictions were also performed for these compounds. Outcomes of the present study have been first utilized to get insight into the molecular feature that promotes bioactivity, and then within screening procedure, have been exploited for the estimation of novel potential antitubulin compounds prior to their synthesis and biological tests.