الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
Cancer disease represents a major cause of death and a significant hindrance to an increase in the average lifespan globally in the twenty-first century. Additionally, the primary bottleneck in cancer therapy and patient mortality rates is the development of resistance to chemotherapy and radiotherapy. These facts eloquently highlight the urgent need for potent and specific inhibitors against the most critical cancer targets. In the current thesis, several in-silico approaches were utilized to explore novel and potential inhibitors towards therapeutic targets involving ABCB1 transporter, SIRT2, NRP1, and BRD4-BD1 proteins for treating cancer disease.
ABCB1 transporter is one of the most critical targets for conquering the MDR phenomena. In the presented thesis, in-silico drug screening techniques were executed for the sake of identifying potential NPs from the NPASS database that will be able to inhibit the ABCB1 transporter. MD simulations were conducted based on the expected docking scores and the NPASS-ABCB1 binding energies were calculated. MM-GBSA binding energies throughout MD simulations over 100 ns demonstrated that NPC104372, NPC475164, NPC2313, NPC197736, and NPC477344 displayed auspicious binding affinities against the ABCB1 transporter with ΔGbinding of −111.4, −108.7, −108.5, −107.7, and –106.0 kcal/mol, respectively.
Additionally, in-silico techniques were used for screening the SuperNatural II database to identify potential inhibitors to the ABCB1 transporter. Based on the docking scores, the most promising natural compounds with docking scores ≤ –11.0 kcal/mol were subjected to MD simulations, followed by MM-GBSA binding energy computations. According to the MM-GBSA results, UMHSN00009999 and UMHSN00097206 showed superior binding energies with average ΔGbinding values of –68.3 and –64.1 kcal/mol over 100 ns MD simulations, respectively, compared to the co-crystallized ZQU inhibitor (calc. –49.8 kcal/mol). The structural and energetical analyses confirmed inhibitor stability over the 100 ns MD simulation. According to pharmacokinetic properties, UMHSN000099999 and UMHSN00097206 demonstrated good oral bioavailability. In addition, transporter MD simulations executed in a POPC environment revealed no significant change in inhibitor binding affinities.
As well, 512 drug candidates in clinical-trial and investigational stages were scrutinized as potential P-gp inhibitors. Combined molecular docking and molecular dynamics simulations were conducted in the absence and presence of the POPC membrane, pursued by MM-GBSA binding energies. Valspodar, dactinomycin, elbasvir, temsirolimus, and sirolimus exhibited favourable binding affinities with ΔGbinding < −100.0 kcal/mol within the binding pocket of the P-gp transporter. Finally, the energetical and structural analyses during the 100 ns MD simulations confirmed the great steadiness of five promising drug candidates. The current findings bring valspodar, dactinomycin, elbasvir, temsirolimus, and sirolimus to light as potential drug candidates for inhibiting the P-gp transporter.
P-gp inhibitors with no toxicity profiles have not been clinically discovered until recently, making it urgent to identify effective P-gp inhibitors with no toxicity. For this purpose, the SuperDRUG2 database was mined for hunting effective inhibitors using molecular docking computations and molecular dynamics (MD) simulations. Interestingly, angiotensin amide (SD003508), terlipressin (SD002603), argipressin (SD002535), and lanreotide (SD001365) displayed considerable binding affinities towards P-gp transporter over 100 ns MD simulations with binding energies (ΔGbinding) of –155.9, –138.6, –123.8, and –120.3 kcal/mol, respectively, compared to tariquidar (calc. –72.0 kcal/mol). The structural and energetic analyses of the identified drug candidates and tariquidar complexed with the P-gp transporter over the 100 ns MD simulations were inspected and demonstrated their stabilities within the P-gp transporter. Furthermore, acceptable ADMET characteristics were noticed.
The Toxin and Toxin-Target Database (T3DB) database was also virtually screened against the ABCB1 binding pocket to discover novel inhibitors. The T3DB database was initially docked within the ABCB1 binding pocket using AutoDock4.2.6 software. MD simulations were executed subsequently based on the evaluated docking scores. The MM-GBSA binding energy estimations of the T3DB-ABCB1 complexes followed these simulations. According to the results, Emamectin B1a (T3D1043), Emamectin B1b (T3D1044), Vincristine (T3D4016), Vinblastine (T3D4017), and Vindesine (T3D2479) exhibited promising binding affinities against the ABCB1 transporter over the 100 ns MD simulations with ΔGbinding of –93.0, –92.6, –93.8, –92.2, and –90.8 kcal/mol, compared to ZQU inhibitor (calc. –49.8 kcal/mol).
In a slew of studies, sirtuin 2 (SIRT2) has been linked to cancer pathogenesis. As a result, SIRT2 inhibition stands out as a possible intervention strategy in the long-running fight against cancer. Hence, in-silico based techniques were performed to identify potential natural products from the Natural Products Atlas (NPAtlas) database that might inhibit the activity of the SIRT2 protein. Based on the molecular docking, molecular dynamics, and MM-GBSA binding affinity results, NPA009578, NPA006805, and NPA001884 were identified as prospective SIRT2 inhibitors. According to the estimated binding affinities over 200 ns MD simulations, NPA009578, NPA006805, and NPA001884 demonstrated better binding affinities compared to the co-crystallized SirReal2 with ΔGbinding values of –59.9, –57.4, –53.5, and –49.7 kcal/mol, respectively. The energetical and structural inspections throughout 200 ns MD simulations indicated great stabilization for the identified NPAtlas compounds complexed with SIRT2 protein. Besides, the identified NPAtlas compounds manifested convenient drug-like features and oral bioavailability.
Neuropilin-1 (NRP1) is a transmembrane glycoprotein receptor that signals different members of the vascular endothelial growth factor (VEGF) family. The receptor is a potential inhibitor site for cancer therapy. In this consequence, the NPASS database containing over 35,000 natural products was virtually screened against the NRP1 protein for identifying potent inhibitors as anticancer drug candidates. The computed MM-GBSA binding energy over a MD course of 200 ns demonstrated superior binding affinity of kamolonol (NPC146388) compared to the HRG/Arg-1 ligand with NRP1, demonstrating ΔGbinding values of –34.5 and –32.0 kcal/mol, respectively. During 200 ns MD simulations, energetic and structural analyses indicated perfect constancy for the kamolonol. Furthermore, kamolonol elucidated favourable physiochemical and pharmacokinetic properties compared to HRG/Arg-1.
The bromodomain-containing protein 4 (BRD4) has generally been recognized to be a promising target for treating cancer disease. Among BRD4 domains, the first bromodomain (BD1) is a key therapeutic target. Consequently, the SuperDRUG2 database, containing > 4,600 active pharmaceutical ingredients, was virtually screened against the binding site of the BRD4-BD1 protein using molecular docking and molecular dynamic (MD) simulations. The binding free energies of the investigated inhibitors were then evaluated using the MM-GBSA approach. Only three inhibitors exhibited lower docking scores than the co-crystallized R6S inhibitor (calc. −9.9 kcal/mol) within the BRD4-BD1 active site. Interestingly, over the conducted 200 ns MD simulations, the pyronaridine (SD003509) demonstrated binding affinity with ∆Gbinding value of –42.7 kcal/mol against the BRD4-BD1 which was lower than that of the co-crystallized R6S inhibitor (calc. –41.5 kcal/mol). Furthermore, energetical and structural analyses revealed the high stability of the identified inhibitor in complex with the BRD4-BD1 protein during a simulation course of 200 ns. It is worth mentioning that the Evdw and Eele considerably contributed to pyronaridine- and R6S-BRD4-BD1 binding affinities. Additionally, the ADMET properties of pyronaridine were promising.
These results will represent a cornerstone in the drug discovery of novel and potent inhibitors for cancer treatment and will make a significant contribution to the field of computer-aided drug discovery. The High-Performance Computer (HPC) located at CompChem Lab, Chemistry Department, Faculty of Science, Minia University and supported by the Science and Technology Development Fund, STDF, Egypt, Grant No.5480 &7972 was utilized for all computations.