Cyclooxygenase-1 as an anti-stroke target: potential inhibitor identification and non-synonymous single nucleotide polymorphism analysis
- Authors: Muronzi, Tendai
- Date: 2020
- Subjects: Cerebrovascular disease , Cerebrovascular disease -- Treatment , Cerebrovascular disease -- Chemotherapy , Cyclooxygenases , High throughput screening (Drug development) , Drug development , Molecular dynamics , South African Natural Compounds Database , ZINC database
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/143404 , vital:38243
- Description: Stroke is the third leading cause of death worldwide, with 87% of cases being ischemic stroke. The two primary therapeutic strategies to reduce post-ischemic brain damage are cellular and vascular approaches. The vascular strategy aims to rapidly re-open obstructed blood vessels, while the cellular approach aims to interfere with the signalling pathways that facilitate neuron damage and death. Unfortunately, popular vascular treatments have adverse side effects, necessitating the need for alternative chemotherapeutics. In this study, cyclooxygenase-1 (COX-1), which plays a significant role in the post- ischemic neuroinflammation and neuronal death, was targeted for identification of novel drug compounds and to assess the effect of nsSNPs on its structure and function. In a drug discovery part, ligands from the South African Natural Compounds Database (SANCDB-https://sancdb.rubi.ru.ac.za/) and ZINC database (http://zinc15.docking.org/) were used for high-throughput virtual screening (HVTS) against COX-1. Additionally, five nsSNPs were being investigated to assess their impact on protein structure and function. Three of these SNPs were in the COX-1 dimer interface. Molecular docking and molecular dynamics simulations revealed asymmetric nature of the protein. Several ligands, peculiar to each monomer, exhibited favourable binding energies in the respective active sites. SNP analysis indicated effects on inter-monomer interactions and protein stability.
- Full Text:
- Authors: Muronzi, Tendai
- Date: 2020
- Subjects: Cerebrovascular disease , Cerebrovascular disease -- Treatment , Cerebrovascular disease -- Chemotherapy , Cyclooxygenases , High throughput screening (Drug development) , Drug development , Molecular dynamics , South African Natural Compounds Database , ZINC database
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/143404 , vital:38243
- Description: Stroke is the third leading cause of death worldwide, with 87% of cases being ischemic stroke. The two primary therapeutic strategies to reduce post-ischemic brain damage are cellular and vascular approaches. The vascular strategy aims to rapidly re-open obstructed blood vessels, while the cellular approach aims to interfere with the signalling pathways that facilitate neuron damage and death. Unfortunately, popular vascular treatments have adverse side effects, necessitating the need for alternative chemotherapeutics. In this study, cyclooxygenase-1 (COX-1), which plays a significant role in the post- ischemic neuroinflammation and neuronal death, was targeted for identification of novel drug compounds and to assess the effect of nsSNPs on its structure and function. In a drug discovery part, ligands from the South African Natural Compounds Database (SANCDB-https://sancdb.rubi.ru.ac.za/) and ZINC database (http://zinc15.docking.org/) were used for high-throughput virtual screening (HVTS) against COX-1. Additionally, five nsSNPs were being investigated to assess their impact on protein structure and function. Three of these SNPs were in the COX-1 dimer interface. Molecular docking and molecular dynamics simulations revealed asymmetric nature of the protein. Several ligands, peculiar to each monomer, exhibited favourable binding energies in the respective active sites. SNP analysis indicated effects on inter-monomer interactions and protein stability.
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Prediction of mass spectra for natural products using an ab initio approach
- Authors: Novokoza, Yolanda
- Date: 2020
- Subjects: Molecular dynamics , Molecular dynamics -- Computer simulation , Mass spectroscopy , Electron impact ionization
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/167166 , vital:41443
- Description: Mass spectrometry (MS) is a technique that measures the fragmentation of molecules, dependent on the molecule’s chemical composition and structure, by first introducing a charge on the molecules. The instrument records the mass to charge ratio, but the energy from the ionization process causes the molecule to fragment. The resultant mass spectrum is highly indicative of not only the molecule analyzed, but also its chemical composition. MS is used in research and industry for both routine and research purposes. One such way to ionize molecules for MS is by bombarding the molecule with electrons which is the basis of electron impact mass spectrometry (EIMS). Although EIMS is widely used, prediction of electron impact mass spectra from first principles is a challenging problem due to a need to accurately determine the probability of different fragmentation pathways of a molecule. Ab initio molecular dynamics based methods are able to explore in an automatic fashion the energetically available fragmentation paths thus give reaction mechanisms in an unbiased way. The mass spectra of five molecules have been explored in work-flows leading to the prediction of mass spectra. These molecules include three natural products alpha-hispanolol, PFB oxime derivative and boronolide (for which experimental mass spectra were not available) and two compounds from the NIST database (for which experimental mass spectra were available). For each of these systems many random conformations were generated using the RDKit library. To all conformations random velocities were applied to each atom. Ab initio molecular dynamics was performed on each conformer, using these initial random velocities using CP2K software, at DFTB+ level at a variety of highly raised temperatures (to accelerate the formation of fragments) Fragmentation was monitored by iterating through all bonds, and identifying bond breakages during dynamics. Graph theoretical packages were used then to track distinct fragments generated. For each of these fragments, charges were determined from Mulliken analysis for all atoms on the fragment from the QM calculations and sum of atomic spin densities per fragment was also plotted. The fragment with the greatest charge (corresponding to the formation of a cation fragment) was taken for plotting on the mass spectrum. Finally, from the mass of the fragment and its elemental composition, the isotopic distribution for the fragment was determined, and this distribution was included by addition in to the mass spectrum. For all trajectories, the sum of all isotopic distributions determined the final mass spectrum.
- Full Text:
- Authors: Novokoza, Yolanda
- Date: 2020
- Subjects: Molecular dynamics , Molecular dynamics -- Computer simulation , Mass spectroscopy , Electron impact ionization
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/167166 , vital:41443
- Description: Mass spectrometry (MS) is a technique that measures the fragmentation of molecules, dependent on the molecule’s chemical composition and structure, by first introducing a charge on the molecules. The instrument records the mass to charge ratio, but the energy from the ionization process causes the molecule to fragment. The resultant mass spectrum is highly indicative of not only the molecule analyzed, but also its chemical composition. MS is used in research and industry for both routine and research purposes. One such way to ionize molecules for MS is by bombarding the molecule with electrons which is the basis of electron impact mass spectrometry (EIMS). Although EIMS is widely used, prediction of electron impact mass spectra from first principles is a challenging problem due to a need to accurately determine the probability of different fragmentation pathways of a molecule. Ab initio molecular dynamics based methods are able to explore in an automatic fashion the energetically available fragmentation paths thus give reaction mechanisms in an unbiased way. The mass spectra of five molecules have been explored in work-flows leading to the prediction of mass spectra. These molecules include three natural products alpha-hispanolol, PFB oxime derivative and boronolide (for which experimental mass spectra were not available) and two compounds from the NIST database (for which experimental mass spectra were available). For each of these systems many random conformations were generated using the RDKit library. To all conformations random velocities were applied to each atom. Ab initio molecular dynamics was performed on each conformer, using these initial random velocities using CP2K software, at DFTB+ level at a variety of highly raised temperatures (to accelerate the formation of fragments) Fragmentation was monitored by iterating through all bonds, and identifying bond breakages during dynamics. Graph theoretical packages were used then to track distinct fragments generated. For each of these fragments, charges were determined from Mulliken analysis for all atoms on the fragment from the QM calculations and sum of atomic spin densities per fragment was also plotted. The fragment with the greatest charge (corresponding to the formation of a cation fragment) was taken for plotting on the mass spectrum. Finally, from the mass of the fragment and its elemental composition, the isotopic distribution for the fragment was determined, and this distribution was included by addition in to the mass spectrum. For all trajectories, the sum of all isotopic distributions determined the final mass spectrum.
- Full Text:
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