In-Silico Mining of the Toxins Database (T3DB) towards Hunting Prospective Candidates as ABCB1 Inhibitors: Integrated Molecular Docking and Lipid Bilayer-Enhanced Molecular Dynamics Study.

Abstract

Multidrug resistance (MDR) is one of the most problematic issues in chemotherapeutic carcinoma therapy. The ABCB1 transporter, a drug efflux pump overexpressed in cancer cells, has been thoroughly investigated for its association with MDR. Thus, discovering ABCB1 inhibitors can reverse the MDR in cancer cells. In the current work, a molecular docking technique was utilized for hunting the most prospective ABCB1 inhibitors from the Toxin and Toxin-Target Database (T3DB). Based on the docking computations, the most promising T3DB compounds complexed with the ABCB1 transporter were subjected to molecular dynamics (MD) simulations over 100 ns. Utilizing the MM-GBSA approach, the corresponding binding affinities were computed. Compared to ZQU (calc. -49.8 kcal/mol), Emamectin B1a (T3D1043), Emamectin B1b (T3D1044), Vincristine (T3D4016), Vinblastine (T3D4017), and Vindesine (T3D2479) complexed with ABCB1 transporter demonstrated outstanding binding affinities with ΔGbinding values of -93.0, -92.6, -93.8, -92.2, and -90.8 kcal/mol, respectively. The structural and energetic investigations confirmed the constancy of the identified T3DB compounds complexed with the ABCB1 transporter during the 100 ns MD course. To mimic the physiological conditions, MD simulations were conducted for those identified inhibitors complexed with ABCB1 transporter in the presence of a POPC membrane. These findings revealed that Emamectin B1a, Emamectin B1b, Vincristine, Vinblastine, and Vindesine are promising ABCB1 inhibitors that can reverse the MDR. Therefore, subjecting those compounds to further in-vitro and in-vivo investigations is worthwhile.