Computational search for nature-derived dual-action inhibitors of HIV-1 reverse transcriptase and integrase: a potential strategy to mitigate drug resistance progression
- Authors: Mwiinga, Luyando
- Date: 2024-10-11
- Subjects: Uncatalogued
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/463930 , vital:76458
- Description: Human immunodeficiency virus Type 1 (HIV-1) is a devastating viral infection affecting millions worldwide and presents significant challenges in treatment and management. In 2022, approximately 39 million people were living with HIV with Sub-Saharan Africa having two thirds of these infections. Devastatingly, there were approximately 300 000 HIV/AIDS related deaths in Sub-Saharan Africa alone in 2022 alone. Antiretroviral therapy (ART) which is fundamental for HIV treatment, comprises of a combination of drugs such as nucleoside reverse transcriptase inhibitors (NRTIs), non-nucleoside reverse transcriptase inhibitors (NNRTs), protease inhibitors (PIs) and integrase strand transfer inhibitors (INSTIs). However, although 28.7 million people out of the estimated 38.4 million people living with HIV in 2021 were receiving ART, the emergence of drug-resistant strains further complicates treatment efforts, highlighting the need for novel therapeutic approaches. This study aimed to address the challenges raised by drug resistance and significant side effects by identifying potential dual inhibitors against HIV-1 Reverse Transcriptase (RT) and Integrase (IN) using in silico techniques. RT RNase H and IN were chosen as targets for their shared dependency on Mg2+ ions within their active sites, which are crucial for catalytic activity. The selection of dual inhibitors was motivated by the fact that the virus would need to replicate at two points simultaneously to develop resistance, making it less likely. The objectives of this study included the creation of a natural derivative compound library using RDKit with the aid of SciFinder, utilizing (-)-epigallocatechin-3-O-gallate (EGCG), because of its dual inhibitory effects against RT and IN, as indicated by a study conducted by Sanna et al. 2019. The natural derivatives were chosen to take advantage of their chemical diversity and to explore potential novel therapeutic options for combating HIV drug resistance. The compound library created comprised of 125 203 compounds. Then docking studies were conducted to assess proteinligand binding. After the correlation of the RT and IN docking studies, 288 compounds were filtered to have potential dual inhibitory activity. Then quantitative estimation of druggability (QED) analysis identified three compounds with superior properties compared to EGCG and FDAapproved drug raltegravir (RAL). Molecular docking simulations revealed interactions between the inhibitors and the key active site residues of RT and IN, along with the chelation of at least one 3 Mg2+, suggesting the potential for enzymatic disruption. Furthermore, molecular dynamic (MD) simulations were then conducted to assess protein-ligand system behavior, through RMSD and RMSF analysis. The RMSD analysis uncovered instability in the IN-Sci30703 complex, leading to its exclusion as a potential dual action inhibitor. RMSF analysis for IN showed that all the inhibitors had the ability to limit the flexibility of the catalytic loop which is essential for catalytic activity. Therefore, further in vitro studies are required to evaluate the effectiveness of the remaining two EGCG derivatives (Sci33211 and Sci48919) in inhibiting RT and IN through the chelation of at least one Mg2+ ion to determine if they have superior dual inhibitory effects compared to EGCG. This study adds to the ongoing efforts to develop effective strategies against HIV-1 drug resistance and emphasizes the importance of continued research in this field. , Thesis (MSc) -- Faculty of Science, Biochemistry, Microbiology & Bioinformatics, 2024
- Full Text:
Search for acrylonitrile-based inhibitors of SAR-Cov-19 main and papain-like proteases through covalent docking and high-throughput virtual screening
- Authors: Ntantiso, Yamkela
- Date: 2024-10-11
- Subjects: Uncatalogued
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/463941 , vital:76459
- Description: The sudden outbreak of SARS-CoV-2 formerly known as the 2019 novel coronavirus (2019-nCoV) quickly turned into a pandemic of coronavirus disease 2019 (COVID-19), the scale of which has never been seen before. High infection rates and mortality from COVID-19 placed pressure on global health services, and this has been to the detriment of the global economy. However, treatment options for COVID-19 are still very limited; hence, it is now as important as ever that researchers explore searching for new compounds with pharmacokinetic properties that inhibit the two COVID proteases - the main protease (Mpro) and the papain-like protease (PLpro). The main protease is a cysteine protease; as such, it is susceptible to permanent inhibition by reactive species (warheads) that may covalently bind to cysteine residues. One such class of compounds is acrylonitriles, in which the reactive acrylonitrile is reactive towards cysteine through a Michael addition reaction. The resulting covalent interaction is permanent and inactivates the cysteine residue and hence the protease within the context of the COVID-19 life-cycle. In this context, this study seeks to utilize computational-based approaches to identify acrylonitrile-based inhibitors of coronavirus drug targets. To do this, the ZINC database has been screened for compounds containing acrylonitrile functionality, due to its known nature as a warhead that binds to cysteine residues. Pharmacokinetic properties are computed to evaluate the viability of identified inhibitors, and covalent and non-covalent molecular docking approaches to the Mpro enzyme crystal structure have also been used to assess the identified systems. To gather more information and evaluate the most promising systems, a subset of the most promising compounds have been subjected to molecular dynamics simulation (for both covalently bound and non-covalently bound systems). , Thesis (MSc) -- Faculty of Science, Biochemistry, Microbiology & Bioinformatics, 2024
- Full Text: