Filibuvir

Microtubules are among the critical targets for chemotherapeutic agents to fight against cancer because of their crucial role in mitosis. Microtubule inhibitors block cell cycle progression and result in apoptosis, they can frequently disrupt microtubule/tubulin dynamics by binding to the α‐tubulin receptor. To this end, we have developed compounds against α‐tubulin receptor using several tools of computational chemistry: 3D‐QSAR, Molecular Docking, Molecular Dynamics Simulation, and ADMET prediction. The significant findings incorporated two reliable models: CoMFA (Q2=0.75; R2=0.89) and CoMSIA (Q2=0.57; R2=0.78). Molecular Docking was generated and validated using Molecular Dynamics simulation to investigate the binding mode between the most active compound and the α‐tubulin receptor. The results of the MD simulation demonstrated stability over a 100 ns period. Four compounds (C1, C2, C3, and C4) were developed based on the contour maps, and their activities were predicted. Additionally, Molecular Docking was executed to elucidate the interaction and affinity between the novel compounds and the α‐tubulin receptor. C1 exhibited high affinity and essential interactions and was subjected to MD simulation studies. The results of the MD simulation revealed that the modifications made to enhance the anticancer activity did not impact stability. Finally, ADMET analysis was utilized to examine drug‐likeness.

To the best of our knowledge, the current study could be considered the first comprehensive one based on the application of molecular docking on the non-nucleoside thumb and palm inhibitors to nonstructural NS5B protein for the detailed evaluation of their binding patterns in the corresponding binding regions in the protein. Non-nucleoside thumb and palm inhibitors were docked into the thumb and palm sites of the nonstructural NS5B protein which is the RNA-dependent RNA polymerase, respectively. Two docking programs, AutoDock 4.2 and AutoDock Vina were employed for the docking of thumb inhibitors (filibuvir and lomibuvir) and palm inhibitors (dasabuvir and nesbuvir) into the respective binding region. The preliminary analysis of the docking performance demonstrated that AutoDock Vina was suitable for the docking of large flexible molecules as deduced from the alignment of docking conformations in all cases. Based on the docking calculation, the interaction pattern analysis was carried out for all the inhibitors which were found to reside in the respective binding region. Before the interaction pattern analysis, the best docking pose was selected based on the high binding affinity value. The interaction pattern analysis of the inhibitors revealed that hydrogen bonding and hydrophobic contacts with amino acid residues of the respective binding region were the leading force in the stabilization of these inhibitors besides other interactions. The interaction pattern analysis based on the docking calculation was also realized to be the meaningful approach to figuring out the relative stability of the protein-ligand complex formed after the inhibitor binding which eventually led to assessing the inhibitory potential of these inhibitors and could also be helpful for the future inhibitor design.