الفهرس 
Chapter I : IntroductionOnly 14 pages are availabe for public view
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Abstract
Breast cancer resistance protein (BCRP; also known as ATP-binding cassette transporter G2, ABCG2) is a human ATP-binding cassette (ABC) that plays a paramount role in multidrug resistance (MDR) in cancer therapy. Until recently, the 3D structure of ABCG2 has not been resolved, which resulted in the limitation of developing potential ABCG2 inhibitors using structure-based drug discovery. In the current thesis, eMolecules, ChEMBL, and ChEBI databases, containing >25 million compounds, were virtually screened against the ABCG2 transporter in homodimer form. Performance of AutoDock4.2.6 software to predict inhibitor-ABCG2 binding mode and affinity were validated on the basis of available experimental data. The explored databases were filtered based on docking scores. The most potent hits with binding affinities higher than that of experimental bound ligand (MZ29) were then selected and subjected to molecular mechanics minimization, followed by binding energy calculation using molecular mechanics-generalized Born surface area (MM-GBSA) approach. Furthermore, molecular dynamics simulations for 50 ns, followed by MM-GBSA binding energy calculations, were performed for the promising compounds, unveiling eight potential inhibitors with binding affinities <−55.8 kcal/mol.
Besides, the binding affinities of 181 drug candidates in clinical-trial or investigational stages as ABCG2 inhibitors were inspected using in silico techniques. Based on available experimental data, the performance of AutoDock4.2.6 software was first validated to predict the inhibitor-ABCG2 binding mode and affinity. Combined molecular docking calculations and molecular dynamics (MD) simulations, followed by molecular mechanics-generalized Born surface area (MM-GBSA) binding energy calculations, were then performed to filter out the studied drug candidates. from the estimated docking scores and MM-GBSA binding energies, six auspicious drug candidates —namely, pibrentasvir, venetoclax, ledipasvir, avatrombopag, cobicistat, and revefenacin— exhibited auspicious binding energies with value <−70.0 kcal/mol. Interestingly, pibrentasvir, venetoclax, and ledipasvir were observed to show even higher binding affinities with the ABCG2 transporter with binding energies of <−80.0 kcal/mol over long MD simulations of 100 ns.
In the search for unprecedented chemical compounds that inhibit this ABCG2 transporter, an in silico screening was conducted on the NPACT database containing 1574 natural product compounds. The performance of AutoDock Vina software was initially assessed to portend the binding mode and affinity of the ABCG2-inhibitor complex according to obtainable experimental data. ABCG2-inhibitor binding affinities from the virtual screening were estimated on the basis of molecular docking and molecular minimization (MM) calculations with a co-crystalized inhibitor, BWQ acting as a reference inhibitor. Molecular dynamics (MD) simulations pursued by molecular mechanics-generalized Born surface area (MM-GBSA) binding energy calculations were then applied for compounds with MM-GBSA//MM binding energies lower than BWQ (calc. −60.5 kcal/mol). Compounds NPACT00968 and NPACT01545 demonstrated auspicious inhibitory activities in accordance with binding affinities (ΔGbinding) that were one and half times compared to that of BWQ (−100.4, −94.7, and −62.9 kcal/mol, respectively).
Structural and energetic analyses unveiled outstanding stability for the investigated compounds when bound with the ABCG2 transporter over the MD simulation time. In silico calculations hold promise for the identified compounds as drug candidates of ABCG2 transporter and emphasize that further in vitro and in vivo experiments are guaranteed. All calculations were performed using High-Performance Computer (HPC) located at CompChem Lab, Minia University, and supported by the Science and Technology Development Fund, STDF, Egypt, Grant No.5480 &7972.