الفهرس 
Chapter I : IntroductionOnly 14 pages are availabe for public view
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Abstract
The coronavirus pandemic has affected more than 150 million people, while over 3.25 million people have died from the coronavirus disease 2019 (COVID-19). As there are no established therapies for COVID-19 treatment, drugs that inhibit viral replication are a promising target; specifically, the main protease (Mpro) that process CoV-encoded polyproteins serves as an Achilles heel for assembly of replication-transcription machinery as well as down-stream viral replication. In the current thesis, the DrugBank database which contains 10,036 approved and investigational drugs was explored deeply for potential drugs that target SARS-CoV-2 main protease (Mpro). Filtration process of the database was conducted using three levels of accuracy for molecular docking calculations. The top 35 drugs with docking scores <−11.0 kcal/mol were then subjected to 10 ns molecular dynamics (MD) simulations followed by molecular mechanics-generalized Born surface area (MM-GBSA) binding energy calculations. The results showed that DB02388 and Cobicistat (DB09065) exhibited potential binding affinities towards Mpro over 100 ns MD simulations, with binding energy values of −49.7 and −46.6 kcal/mol, respectively.
Besides, in silico drug discovery approaches have been utilized to identify potential natural products (NPs) as Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) main protease (Mpro) inhibitors. The MolPort database that contains over 100,000 NPs was screened and filtered using molecular docking techniques. Based on calculated docking scores, the top 5,000 NPs/natural-like products (NLPs) were selected and subjected to molecular dynamics (MD) simulations followed by molecular mechanics–generalized Born surface area (MM-GBSA) binding energy calculations. Combined 50 ns MD simulations and MM-GBSA calculations revealed nine potent NLPs with binding affinities (ΔGbinding) <−48.0 kcal/mol. Interestingly, among the identified NLPs, four bis([1,3]dioxolo)pyran-5-carboxamide derivatives showed ΔGbinding <−56.0 kcal/mol, forming essential short hydrogen bonds with HIS163 and GLY143 amino acids via dioxolane oxygen atoms.
Recently, several repositioned drugs have been subjected to clinical investigations as anti-COVID-19 drugs. Therefore, in silico drug discovery tools were utilized to evaluate the binding affinities and features of eighteen anti-COVID-19 drug candidates against SARS-CoV 2 main protease (Mpro). Molecular docking calculations using AutoDock Vina showed considerable binding affinities of the investigated drugs with docking scores ranging from −5.3 to −8.3 kcal/mol, with higher binding affinities for HIV drugs compared to the other antiviral drugs. Molecular dynamics (MD) simulations were performed for the predicted drug-Mpro complexes for 50 ns, followed by binding energy calculations utilizing molecular mechanics-generalized Born surface area (MM-GBSA) approach. MM-GBSA calculations demonstrated promising binding affinities of TMC-310911 and ritonavir towards SARS-CoV-2 Mpro, with binding energy values of −52.8 and −49.4 kcal/mol, respectively. Surpass potentialities of TMC-310911 and ritonavir are returned to their capabilities of forming multiple hydrogen bonds with the proximal amino acids inside Mpro’s binding site.
Flavonoids, especially rutin, have attracted considerable interest as a prospective SARS-CoV-2 main protease (Mpro) inhibitor. For this reason, a database containing 2017 flavone analogs was prepared and screened against SARS-CoV-2 Mpro using the molecular docking technique. According to the results, 371 flavone analogs exhibited good potency towards Mpro with docking scores less than −9.0 kcal/mol. Molecular dynamics (MD) simulations, followed by molecular mechanics-generalized Born surface area (MM-GBSA) binding energy calculations, were performed for the top potent analogs in complex with Mpro. Compared to rutin, PubChem-129-716-607 and PubChem-885-071-27 showed better binding affinities against SARS-CoV-2 Mpro over 150 ns MD course with ΔGbinding values of −69.0 and −68.1 kcal/mol, respectively.
Besides, two hundred and twenty-seven terpene natural products isolated from the biodiverse Red-Sea ecosystem were screened for inhibitor activity against the SARS-CoV-2 main protease (Mpro) using molecular docking and molecular dynamics (MD) simulations combined with molecular mechanics-generalized Born surface area binding energy calculations. On the basis of in silico analyses, six terpenes demonstrated high potency as Mpro inhibitors with ΔGbinding ≤−40.0 kcal/mol. The stability and binding affinity of the most potent metabolite, erylosides B, were compared to the human immunodeficiency virus protease inhibitor, lopinavir. Erylosides B showed greater binding affinity towards SARS-CoV-2 Mpro than lopinavir over 100 ns with ΔGbinding values of −51.9 vs. −33.6 kcal/mol, respectively.
In the search for potential antiviral drugs that target Mpro, a series of cembranoid diterpenes from the biologically active soft-coral genus Sarcophyton have been examined as SARS-CoV-2 Mpro inhibitors. Over 360 metabolites from the genus were screened using molecular docking calculations. Promising diterpenes were further characterized by molecular dynamics (MD) simulations based on molecular mechanics-generalized Born surface area (MM-GBSA) binding energy calculations. According to in silico calculations, five cembranoid diterpenes manifested adequate binding affinities as Mpro inhibitors with ΔGbinding <−33.0 kcal/mol. Binding energy and structural analyses of the most potent Sarcophyton inhibitor, bislatumlide A (340), was compared to darunavir, an HIV protease inhibitor that has been recently subjected to clinical-trial as an anti-COVID-19 drug. In silico analysis indicates that 340 has a higher binding affinity against Mpro than darunavir with ΔGbinding values of −43.8 and −34.8 kcal/mol, respectively throughout 100 ns MD simulations.
A further in silico attempt was conducted to identify potential Mpro inhibitors from toxins source. Toxin and Toxin-Target Database (T3DB) was virtually screened for inhibitor activity towards the SARS-CoV-2 Mpro utilizing molecular docking calculations. Promising toxins were subsequently characterized using a combination of molecular dynamics (MD) simulations and molecular mechanics-generalized Born surface area (MM-GBSA) binding energy estimations. According to the MM-GBSA binding energies over 200 ns MD simulations, three toxins –namely philanthotoxin (T3D2489), azaspiracid (T3D2672), and taziprinone (T3D2378)– demonstrated higher binding affinities against SARS-CoV-2 Mpro than the co-crystalized inhibitor XF7 throughout 200 ns with MM-GBSA binding energies of −58.9, −55.9, −50.1, and −43.7 kcal/mol, respectively.
Structural and energetic analyses demonstrated the high stability of the identified inhibitors inside the SARS-CoV-2 Mpro’s active site over the MD simulation time. The oral bioavailabilities of probable SARS-CoV-2 Mpro inhibitors were underpinned using drug-likeness parameters. The findings of the presented studies are expected to provide a valuable contribution to the field of computer-aided discovery of anti-COVID-19 drug candidates. 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.