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: HIV (Viruses) , Reverse transcriptase , Antiretroviral agents , RDKit , Drug resistance , Docking
- 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:
- Date Issued: 2024-10-11
- Authors: Mwiinga, Luyando
- Date: 2024-10-11
- Subjects: HIV (Viruses) , Reverse transcriptase , Antiretroviral agents , RDKit , Drug resistance , Docking
- 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:
- Date Issued: 2024-10-11
An in-silico investigation of Morita-Baylis-Hillman accessible heterocyclic analogues for applications as novel HIV-1 C protease inhibitors
- Authors: Sigauke, Lester Takunda
- Date: 2015
- Subjects: Protease inhibitors , Heterocyclic compounds , HIV (Viruses) , HIV infections , Drug resistance , Cheminformatics
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:4152 , http://hdl.handle.net/10962/d1017913
- Description: Cheminformatic approaches have been employed to optimize the bis-coumarin scaffold identified by Onywera et al. (2012) as a potential hit against the protease HIV-1 protein. The Open Babel library of commands was used to access functions that were incorporated into a markov chain recursive program that generated 17750 analogues of the bis-coumarin scaffold. The Morita-Baylis-Hillman accessible heterocycles were used to introduce structural diversity within the virtual library. In silico high through-put virtual screening using AutoDock Vina was used to rapidly screen the virtual library ligand set against 61 protease models built by Onywera et al. (2012). CheS-Mapper computed a principle component analysis of the compounds based on 13 selected chemical descriptors. The compounds were plotted against the principle component analysis within a 3 dimensional chemical space in order to inspect the diversity of the virtual library. The physicochemical properties and binding affinities were used to identify the top 3 performing ligands. ACPYPE was used to inspect the constitutional properties and eliminated virtual compounds that possessed open valences. Chromene based ligand 805 and ligand 6610 were selected as the lead candidates from the high-throughput virtual screening procedure we employed. Molecular dynamic simulations of the lead candidates performed for 5 ns allowed the stability of the ligand protein complexes with protease model 305152. The free energy of binding of the leads with protease model 305152 was computed over the first 50 ps of simulation using the molecular mechanics Poisson-Boltzmann method. Analysis structural features and energy profiles from molecular dynamic simulations of the protein–ligand complexes indicated that although ligand 805 had a weaker binding affinity in terms of docking, it outperformed ligand 6610 in terms of complex stability and free energy of binding. Medicinal chemistry approaches will be used to optimize the lead candidates before their analogues will be synthesized and assayed for in vivo protease activity.
- Full Text:
- Date Issued: 2015
- Authors: Sigauke, Lester Takunda
- Date: 2015
- Subjects: Protease inhibitors , Heterocyclic compounds , HIV (Viruses) , HIV infections , Drug resistance , Cheminformatics
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:4152 , http://hdl.handle.net/10962/d1017913
- Description: Cheminformatic approaches have been employed to optimize the bis-coumarin scaffold identified by Onywera et al. (2012) as a potential hit against the protease HIV-1 protein. The Open Babel library of commands was used to access functions that were incorporated into a markov chain recursive program that generated 17750 analogues of the bis-coumarin scaffold. The Morita-Baylis-Hillman accessible heterocycles were used to introduce structural diversity within the virtual library. In silico high through-put virtual screening using AutoDock Vina was used to rapidly screen the virtual library ligand set against 61 protease models built by Onywera et al. (2012). CheS-Mapper computed a principle component analysis of the compounds based on 13 selected chemical descriptors. The compounds were plotted against the principle component analysis within a 3 dimensional chemical space in order to inspect the diversity of the virtual library. The physicochemical properties and binding affinities were used to identify the top 3 performing ligands. ACPYPE was used to inspect the constitutional properties and eliminated virtual compounds that possessed open valences. Chromene based ligand 805 and ligand 6610 were selected as the lead candidates from the high-throughput virtual screening procedure we employed. Molecular dynamic simulations of the lead candidates performed for 5 ns allowed the stability of the ligand protein complexes with protease model 305152. The free energy of binding of the leads with protease model 305152 was computed over the first 50 ps of simulation using the molecular mechanics Poisson-Boltzmann method. Analysis structural features and energy profiles from molecular dynamic simulations of the protein–ligand complexes indicated that although ligand 805 had a weaker binding affinity in terms of docking, it outperformed ligand 6610 in terms of complex stability and free energy of binding. Medicinal chemistry approaches will be used to optimize the lead candidates before their analogues will be synthesized and assayed for in vivo protease activity.
- Full Text:
- Date Issued: 2015
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