Identification of Essential 2D and 3D Chemical Features for Discovery of the Novel Tubulin Polymerization Inhibitors.

BACKGROUND: Tubulin polymerization inhibitors interfere with microtubule assembly and their functions lead to mitotic arrest, therefore they are attractive target for design and development of novel anticancer compounds. OBJECTIVE: The proposed novel and effective structures following the use of three-dimensionalquantitative structure activity relationship (3D-QSAR) pharmacophore based virtual screening clearly demonstrate the high efficiency of this method in modern drug discovery. METHODS: Combined computational approach was applied to extract the essential 2D and 3D features requirements for higher activity as well as identify new anti-tubulin agents. RESULTS: The best quantitative pharmacophore model, Hypo1, exhibited good correlation of 0.943 (RMSD=1.019) and excellent predictive power in the training set compounds. Generated model AHHHR, was well mapped to colchicine site and three-dimensional spatial arrangement of their features were in good agreement with the vital interactions in the active site. Total prediction accuracy (0.92 for training set and 0.86 for test set), enrichment factor (4.2 for training set and 4.5 for test set) and the area under the ROC curve (0.86 for training set and 0.94 for the test set), the developed model using Extended Class FingerPrints of maximum diameter 4 (ECFP_4) was chosen as the best model. CONCLUSION: Developed computational platform provided a better understanding of requirement features for colchicine site inhibitors and we believe the results of this study might be useful for the rational design and optimization of new inhibitors.

Gp41 inhibitory activity prediction of theaflavin derivatives using ligand/structure-based virtual screening approaches.

Gp41 and its conserved hydrophobic groove on the NHR region is one of the attractive targets in the design of HIV-1 entry inhibitory agents. This hydrophobic pocket is very critical for the progression of HIV and host cell fusion. In this study different ligand-based (structure similarity search) and structure-based (molecular docking and molecular dynamic simulation) methods were performed in a virtual screening procedure to select the best compounds with the most probable HIV-1 gp41 inhibitory activities. In silico pharmacokinetics and ADMET (absorption, distribution, metabolism, excretion and toxicity) properties filtration also was considered to choose the compounds with best drug-like properties. The results of molecular docking and molecular dynamic simulations of the final selected compounds showed suitable stabilities of their complexes with gp41. The final selected hits could have better pharmacokinetics properties than the template compound, theaflavin digallate (TF3), a naturally-originated potent gp41 inhibitor.