A large multiscale detailed modelling of aptamers as anticancer therapeutics
- Authors: Mokgopa, Kabelo Phuti
- Date: 2025-04-02
- Subjects: Aptamer , MicroRNA , Drug discovery , Python (Computer program language) , Molecular dynamics , Cheminformatics , Bioinformatics
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/479174 , vital:78267
- Description: Cancer remains a leading cause of death worldwide, characterized by uncontrolled cell growth and spread. The challenge of effectively treating cancer has spurred interest in novel therapeutic strategies that target specific biological or biochemical mechanisms involved in cancer progression. Although many enzymes have been labelled as inducers of cancer development, microRNAs (miRNAs) are also emerging as significant contributors to cancer progression. This is because miRNAs play a crucial role in regulating gene expression, while cancer develops and grows due to genetic mutations, variations, and alterations. Among these miRNAs, miRNA-10b is notable for its involvement in promoting cancer cell proliferation, migration, and metastasis across various cancers, including breast cancer, glioblastoma, and esophageal squamous cell carcinoma. For this reason, we propose inhibiting miRNA-10b using RNA aptamers as a novel and promising approach for developing new anti-cancer therapeutics. RNA aptamers are short, non-coded, synthetic, and single-stranded nucleic acid molecules capable of binding to a wide range of targets, including metal ions, chemical compounds, proteins, cells, and microorganisms. They are used for a range of applications due to their well-known specificity and selectivity, starting from drug delivery to diagnostics. In this project we aimed to design and discover novel RNA aptamers that can effectively inhibit miRNA-10b using advanced computational methods. However, major challenges were encountered due to the lack of databases or tools available to design and predict secondary and tertiary structures of RNA aptamers at a large scale. Furthermore, no tools were available to perform high throughput virtual screening of these aptamers against macromolecular targets at a large scale. Prompted by that, we developed the T_SELEX program, which encompasses the various algorithms and tools dedicated to designing RNA aptamer sequences, predicting their secondary and tertiary structures, and, lastly, virtually screening aptamers. These algorithms and advanced tools are designed to handle the complexities of aptamer selection and virtual screening. By employing virtual screening methods, the aptamer discovery process was streamlined, offering a cost-effective and efficient alternative to traditional SELEX techniques. Prior to the main purpose application, the T_SELEX program was tested by designing aptamers for targeting HIV-1 protease, and a few applications were also done to assess its aptamer design approach. The study explored RNA aptamer sequences, revealing important insights into nucleotide composition, sequence patterns, and their role in aptamer efficacy and design. Analysis of secondary and tertiary structure predictions showed that Minimum Free Energy (MFE) values do not always correlate with structural compactness or complexity, with aptamers of similar MFE values exhibiting variations in attributes like loop size and guanine content. A novel Sequence Similarity Check (SSC) algorithm is introduced focused on internal sequence comparisons and secondary structures, revealing that aptamers with similar base compositions could have distinct folding states and stability. The Base Randomization Algorithm (BRA) generated RNA aptamer libraries was further benchmarked, highlighting a critical threshold for aptamer length and demonstrating Gaussian distribution in base compositions. Virtual screening of aptamers using the T_SELEX program against pre-miRNA-10b and their mature 5p and 3p arm, identified aptamers557 and 899 as effective binders for the 3p and 5p arms, respectively. Extensive quantum mechanical and molecular dynamics simulations confirmed the stability of the aptamer-RNA complexes. Due to the understanding of the flexibility of these RNA-RNA complexes, we further proposed the stability matrices method as a calculus-based method to evaluate the relative stability of the complexes without being biased during MD analysis. MM-GBSA calculations supported docking results, identifying aptamers like aptamers557, aptamer274 and aptamer734 as strong inhibitors of the 3p arm. Overall, this project has proposed novel approaches for aptamer in silico design and validation, particularly in targeting miRNA-10b for cancer therapy. , Thesis (MSc) -- Faculty of Science, Chemistry, 2025
- Full Text:
- Date Issued: 2025-04-02
- Authors: Mokgopa, Kabelo Phuti
- Date: 2025-04-02
- Subjects: Aptamer , MicroRNA , Drug discovery , Python (Computer program language) , Molecular dynamics , Cheminformatics , Bioinformatics
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/479174 , vital:78267
- Description: Cancer remains a leading cause of death worldwide, characterized by uncontrolled cell growth and spread. The challenge of effectively treating cancer has spurred interest in novel therapeutic strategies that target specific biological or biochemical mechanisms involved in cancer progression. Although many enzymes have been labelled as inducers of cancer development, microRNAs (miRNAs) are also emerging as significant contributors to cancer progression. This is because miRNAs play a crucial role in regulating gene expression, while cancer develops and grows due to genetic mutations, variations, and alterations. Among these miRNAs, miRNA-10b is notable for its involvement in promoting cancer cell proliferation, migration, and metastasis across various cancers, including breast cancer, glioblastoma, and esophageal squamous cell carcinoma. For this reason, we propose inhibiting miRNA-10b using RNA aptamers as a novel and promising approach for developing new anti-cancer therapeutics. RNA aptamers are short, non-coded, synthetic, and single-stranded nucleic acid molecules capable of binding to a wide range of targets, including metal ions, chemical compounds, proteins, cells, and microorganisms. They are used for a range of applications due to their well-known specificity and selectivity, starting from drug delivery to diagnostics. In this project we aimed to design and discover novel RNA aptamers that can effectively inhibit miRNA-10b using advanced computational methods. However, major challenges were encountered due to the lack of databases or tools available to design and predict secondary and tertiary structures of RNA aptamers at a large scale. Furthermore, no tools were available to perform high throughput virtual screening of these aptamers against macromolecular targets at a large scale. Prompted by that, we developed the T_SELEX program, which encompasses the various algorithms and tools dedicated to designing RNA aptamer sequences, predicting their secondary and tertiary structures, and, lastly, virtually screening aptamers. These algorithms and advanced tools are designed to handle the complexities of aptamer selection and virtual screening. By employing virtual screening methods, the aptamer discovery process was streamlined, offering a cost-effective and efficient alternative to traditional SELEX techniques. Prior to the main purpose application, the T_SELEX program was tested by designing aptamers for targeting HIV-1 protease, and a few applications were also done to assess its aptamer design approach. The study explored RNA aptamer sequences, revealing important insights into nucleotide composition, sequence patterns, and their role in aptamer efficacy and design. Analysis of secondary and tertiary structure predictions showed that Minimum Free Energy (MFE) values do not always correlate with structural compactness or complexity, with aptamers of similar MFE values exhibiting variations in attributes like loop size and guanine content. A novel Sequence Similarity Check (SSC) algorithm is introduced focused on internal sequence comparisons and secondary structures, revealing that aptamers with similar base compositions could have distinct folding states and stability. The Base Randomization Algorithm (BRA) generated RNA aptamer libraries was further benchmarked, highlighting a critical threshold for aptamer length and demonstrating Gaussian distribution in base compositions. Virtual screening of aptamers using the T_SELEX program against pre-miRNA-10b and their mature 5p and 3p arm, identified aptamers557 and 899 as effective binders for the 3p and 5p arms, respectively. Extensive quantum mechanical and molecular dynamics simulations confirmed the stability of the aptamer-RNA complexes. Due to the understanding of the flexibility of these RNA-RNA complexes, we further proposed the stability matrices method as a calculus-based method to evaluate the relative stability of the complexes without being biased during MD analysis. MM-GBSA calculations supported docking results, identifying aptamers like aptamers557, aptamer274 and aptamer734 as strong inhibitors of the 3p arm. Overall, this project has proposed novel approaches for aptamer in silico design and validation, particularly in targeting miRNA-10b for cancer therapy. , Thesis (MSc) -- Faculty of Science, Chemistry, 2025
- Full Text:
- Date Issued: 2025-04-02
Insights: elucidation of squalene monooxygenase inhibitors for lowering cholesterol in cardiovascular diseases
- Authors: Leoma, Mofeli Benedict
- Date: 2024-04-04
- Subjects: Squalene monooxygenase , Cholesterol , Cardiovascular system Diseases , Anticholesteremic agents , Molecular dynamics , High throughput screening (Drug development) , Molecular Docking
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/434861 , vital:73111
- Description: Statins have been used to lower high cholesterol levels in the past few decades. However, several studies have shown that some people taking statins experience side effects over time, especially elderly patients, women of childbirth possibility, and children. Several studies have shown that the majority of people with underlying cardiovascular complications caused by high cholesterol are at a greater risk of fatality due to COVID-19, regardless of age and sex. The literature suggests that antimycotic squalene monooxygenase inhibitors, terbinafine and its derivatives, and anticholesterolemic squalene monooxygenase (SM) inhibitors could be another option and a safer remedy for lowering cholesterol in mammals. Molecular docking calculations, molecular dynamics (MD) simulations, molecular mechanics generalized born surface area (MM-GBSA) calculations, quantum mechanics/molecular mechanics calculations (QM/MM), and density functional theory (DFT) calculations were used in this study. An early stage in drug discovery, in which small molecular hits from high- throughput screening (HTS) are evaluated and undergo limited optimization to identify promising lead compounds, is referred to as lead generation. To address the first step of lead generation, the number of compounds to be tested was narrowed down, and the hit compounds that could be taken for further tests were obtained. Thus, the molecular docking technique was taken advantage of, which assisted us in identifying the antimycotic ligand SDZ 18, which had a good binding affinity of about -8,4 kcal mol−1. Another widely employed strategy, the molecular mechanics-generalized born surface area (MM-GBSA), was used to investigate the binding free energies of the protein-ligand complexes to validate the binding affinities obtained from molecular docking. Despite the excellent docking results, it must be emphasized that the stability of the ligand in the binding pocket must be investigated. To address this, the protein-ligand complexes were then taken through molecular dynamics for 100 ns simulations calculations which showed that the inhibitors stayed in the binding pocket with the RMSD values below 3.5 Å for most systems. This provided insight into a realistic model because the docked complexes were placed in conditions closer to the physiological environment at 300 K and 1.01325 bar, and in an explicitly solvated dynamic environment. Density functional theory (DFT) at the B3LPY level of theory using the standard 6-31G(d,p) basis set was used to assess the reactivity and other properties of the SM inhibitors. ONIOM calculations were performed to explain what was happening at the microscopic level by calculating the total energy of the complex. The aim of this project was to efficiently uncover the non-physical aspects of SM inhibitors with the help of computational techniques to identify new drugs that can lower high cholesterol levels. From a theoretical perspective, the results obtained from docking indicated that the antimycotic ligands SDZ SBA 586 18 and TNSA 84 (trisnor-squalene alcohol ) have good binding affinities, and the MM-GBSA method provided free energy calculations. MD results indicated that the stability of the ligand in the binding pocket was achieved during the 100 ns simulations. The HOMO-LUMO energy gaps obtained from DFT calculations provided information on the reactivity of the ligands. Other insights into the protein-ligand complexes were obtained from a hybrid ONIOM QM/MM study. , Thesis (MSc) -- Faculty of Science, Chemistry, 2024
- Full Text:
- Date Issued: 2024-04-04
- Authors: Leoma, Mofeli Benedict
- Date: 2024-04-04
- Subjects: Squalene monooxygenase , Cholesterol , Cardiovascular system Diseases , Anticholesteremic agents , Molecular dynamics , High throughput screening (Drug development) , Molecular Docking
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/434861 , vital:73111
- Description: Statins have been used to lower high cholesterol levels in the past few decades. However, several studies have shown that some people taking statins experience side effects over time, especially elderly patients, women of childbirth possibility, and children. Several studies have shown that the majority of people with underlying cardiovascular complications caused by high cholesterol are at a greater risk of fatality due to COVID-19, regardless of age and sex. The literature suggests that antimycotic squalene monooxygenase inhibitors, terbinafine and its derivatives, and anticholesterolemic squalene monooxygenase (SM) inhibitors could be another option and a safer remedy for lowering cholesterol in mammals. Molecular docking calculations, molecular dynamics (MD) simulations, molecular mechanics generalized born surface area (MM-GBSA) calculations, quantum mechanics/molecular mechanics calculations (QM/MM), and density functional theory (DFT) calculations were used in this study. An early stage in drug discovery, in which small molecular hits from high- throughput screening (HTS) are evaluated and undergo limited optimization to identify promising lead compounds, is referred to as lead generation. To address the first step of lead generation, the number of compounds to be tested was narrowed down, and the hit compounds that could be taken for further tests were obtained. Thus, the molecular docking technique was taken advantage of, which assisted us in identifying the antimycotic ligand SDZ 18, which had a good binding affinity of about -8,4 kcal mol−1. Another widely employed strategy, the molecular mechanics-generalized born surface area (MM-GBSA), was used to investigate the binding free energies of the protein-ligand complexes to validate the binding affinities obtained from molecular docking. Despite the excellent docking results, it must be emphasized that the stability of the ligand in the binding pocket must be investigated. To address this, the protein-ligand complexes were then taken through molecular dynamics for 100 ns simulations calculations which showed that the inhibitors stayed in the binding pocket with the RMSD values below 3.5 Å for most systems. This provided insight into a realistic model because the docked complexes were placed in conditions closer to the physiological environment at 300 K and 1.01325 bar, and in an explicitly solvated dynamic environment. Density functional theory (DFT) at the B3LPY level of theory using the standard 6-31G(d,p) basis set was used to assess the reactivity and other properties of the SM inhibitors. ONIOM calculations were performed to explain what was happening at the microscopic level by calculating the total energy of the complex. The aim of this project was to efficiently uncover the non-physical aspects of SM inhibitors with the help of computational techniques to identify new drugs that can lower high cholesterol levels. From a theoretical perspective, the results obtained from docking indicated that the antimycotic ligands SDZ SBA 586 18 and TNSA 84 (trisnor-squalene alcohol ) have good binding affinities, and the MM-GBSA method provided free energy calculations. MD results indicated that the stability of the ligand in the binding pocket was achieved during the 100 ns simulations. The HOMO-LUMO energy gaps obtained from DFT calculations provided information on the reactivity of the ligands. Other insights into the protein-ligand complexes were obtained from a hybrid ONIOM QM/MM study. , Thesis (MSc) -- Faculty of Science, Chemistry, 2024
- Full Text:
- Date Issued: 2024-04-04
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