Potential drug candidates as P-glycoprotein inhibitors to reverse multidrug resistance in cancer: an in silico drug discovery study.

The failure of chemotherapy in the treatment of carcinoma is mainly due to the development of multidrug resistance (MDR), which is largely caused by the overexpression of P-glycoprotein (P-gp/ABCB1/MDR1). Until recently, the 3D structure of the P-gp transporter has not been experimentally resolved, which restricted the discovery of prospective P-gp inhibitors utilizing in silico techniques. In this study, the binding energies of 512 drug candidates in clinical or investigational stages were assessed as potential P-gp inhibitors employing in silico methods. On the basis of the available experimental data, the performance of the AutoDock4.2.6 software to predict the drug-P-gp binding mode was initially validated. Molecular docking and molecular dynamics (MD) simulations combined with molecular mechanics-generalized Born surface area (MM-GBSA) binding energy computations were subsequently conducted to screen the investigated drug candidates. Based on the current results, five promising drug candidates, namely valspodar, dactinomycin, elbasvir, temsirolimus, and sirolimus, showed promising binding energies against P-gp transporter with ΔGbinding values of -126.7, -112.1, -111.9, -102.9, and -101.4 kcal/mol, respectively. The post-MD analyses revealed the energetical and structural stabilities of the identified drug candidates in complex with the P-gp transporter. Furthermore, in order to mimic the physiological conditions, the potent drugs complexed with the P-gp were subjected to 100 ns MD simulations in an explicit membrane-water environment. The pharmacokinetic properties of the identified drugs were predicted and demonstrated good ADMET characteristics. Overall, these results indicated that valspodar, dactinomycin, elbasvir, temsirolimus, and sirolimus hold promise as prospective P-gp inhibitors and warrant further invitro/invivo investigations.