In silico substrate-binding profiling for SARS-CoV-2 Main protease (Mpro) using Hexapeptide substrates
- Zabo, Sophakama, Lobb, Kevin A
- Authors: Zabo, Sophakama , Lobb, Kevin A
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/452711 , vital:75164 , xlink:href="https://doi.org/10.3390/v15071480"
- Description: The SARS-CoV-2 main protease (Mpro) is essential for the life cycle of the COVID-19 virus. It cleaves the two polyproteins at 11 positions to generate mature proteins for virion formation. The cleavage site on these polyproteins is known to be Leu-Gln↓(Ser/Ala/Gly). A range of hexapeptides that follow the known sequence for recognition and cleavage was constructed using RDKit libraries and complexed with the crystal structure of Mpro (PDB ID 6XHM) through extensive molecular docking calculations. A subset of 131 of these complexes underwent 20 ns molecular dynamics simulations. The analyses of the trajectories from molecular dynamics included principal component analysis (PCA), and a method to compare PCA plots from separate trajectories was developed in terms of encoding PCA progression during the simulations. The hexapeptides formed stable complexes as expected, with reproducible molecular docking of the substrates given the extensiveness of the procedure. Only Lys-Leu-Gln*** (KLQ***) sequence complexes were studied for molecular dynamics. In this subset of complexes, the PCA analysis identified four classifications of protein motions across these sequences. KLQ*** complexes illustrated the effect of changes in substrate on the active site, with implications for understanding the substrate recognition of Mpro and informing the development of small molecule inhibitors.
- Full Text:
- Authors: Zabo, Sophakama , Lobb, Kevin A
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/452711 , vital:75164 , xlink:href="https://doi.org/10.3390/v15071480"
- Description: The SARS-CoV-2 main protease (Mpro) is essential for the life cycle of the COVID-19 virus. It cleaves the two polyproteins at 11 positions to generate mature proteins for virion formation. The cleavage site on these polyproteins is known to be Leu-Gln↓(Ser/Ala/Gly). A range of hexapeptides that follow the known sequence for recognition and cleavage was constructed using RDKit libraries and complexed with the crystal structure of Mpro (PDB ID 6XHM) through extensive molecular docking calculations. A subset of 131 of these complexes underwent 20 ns molecular dynamics simulations. The analyses of the trajectories from molecular dynamics included principal component analysis (PCA), and a method to compare PCA plots from separate trajectories was developed in terms of encoding PCA progression during the simulations. The hexapeptides formed stable complexes as expected, with reproducible molecular docking of the substrates given the extensiveness of the procedure. Only Lys-Leu-Gln*** (KLQ***) sequence complexes were studied for molecular dynamics. In this subset of complexes, the PCA analysis identified four classifications of protein motions across these sequences. KLQ*** complexes illustrated the effect of changes in substrate on the active site, with implications for understanding the substrate recognition of Mpro and informing the development of small molecule inhibitors.
- Full Text:
In silico substrate binding profiling for SARS-COV-2 main protease (mpro) using hexapeptide substrates
- Authors: Zabo, Sophakama
- Date: 2022-10-14
- Subjects: COVID-19 (Disease) , Peptides , Chymotrypsin like , Chymotrypsin , Proteases , Proteolytic enzymes
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/365566 , vital:65760
- Description: COVID-19, as a disease resulting from SARS-CoV-2 infection, and a pandemic has had a devastating effect on the world. There are limited effective measures that control the spread and treatment of COVID-19 illness. The homodimeric cysteine main protease (Mpro) is crucial to the life cycle of the virus, as it cleaves the large polyproteins 1a and 1ab into matured, functional non-structural proteins. The Mpro exhibits high degrees of conservation in sequence, structure and specificity across coronavirus species, making it an ideal drug target. The Mpro substrate-binding profiles remain, despite the resolution of its recognition sequence and cleavage points (Leu-Gln↓(Ser/Ala/Gly)). In this study, a series of hexapeptide sequences containing the appropriate recognition sequence and cleavage points were generated and screened against the Mpro to study these binding profiles, and to further be the basis for efficiency-driven drug design. A multi-conformer hexapeptide substrate library comprising optimised 81000 models of 810 unique sequences was generated using RDKit within the context of python. Terminal capping with ACE and NMe was effected using SMILES and SMARTS matching. Multiple hexapeptides were complexed with chain B of crystallographic Mpro (PDS ID: 6XHM), following the validation of chain B for this purpose using AutoDock Vina at high levels of exhaustiveness (480). The resulting Vina scores ranged between -8.7 and -7.0 kcal.mol-1, and the reproducibility of best poses was validated through redocking. Ligand efficiency indices were calculated to identify substrate residues with high binding efficiency at their respective positions, revealing Val (P3), Ala (P1′); and Gly and Ala (P2′ and P3′) as leading efficient binders. Binding efficiencies were lowered by molecular weight. Substrate recognition was assessed by mapping of binding subsites, and Mpro specificity was evaluated through the resolution of intermolecular interaction at the binding interface. Molecular dynamics simulations for 20 ns were performed to assess the stability and behaviour of 132 Mpro systems complexed with KLQ*** substrates. Principal component analysis (PCA), was performed to assess II protein motions and conformational changes during the simulations. A strategy was formulated to classify and evaluate relations in the Mpro PCA motions, revealing four main clades of similarity. Similarity within a clade (Group 2) and dissimilarity between clades were confirmed. Trajectory visualisation revealed complex stability, substrate unbinding and dimer dissociation for various Mpro systems. , Thesis (MSc) -- Faculty of Science, Biochemistry and Microbiology, 2022
- Full Text:
- Authors: Zabo, Sophakama
- Date: 2022-10-14
- Subjects: COVID-19 (Disease) , Peptides , Chymotrypsin like , Chymotrypsin , Proteases , Proteolytic enzymes
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/365566 , vital:65760
- Description: COVID-19, as a disease resulting from SARS-CoV-2 infection, and a pandemic has had a devastating effect on the world. There are limited effective measures that control the spread and treatment of COVID-19 illness. The homodimeric cysteine main protease (Mpro) is crucial to the life cycle of the virus, as it cleaves the large polyproteins 1a and 1ab into matured, functional non-structural proteins. The Mpro exhibits high degrees of conservation in sequence, structure and specificity across coronavirus species, making it an ideal drug target. The Mpro substrate-binding profiles remain, despite the resolution of its recognition sequence and cleavage points (Leu-Gln↓(Ser/Ala/Gly)). In this study, a series of hexapeptide sequences containing the appropriate recognition sequence and cleavage points were generated and screened against the Mpro to study these binding profiles, and to further be the basis for efficiency-driven drug design. A multi-conformer hexapeptide substrate library comprising optimised 81000 models of 810 unique sequences was generated using RDKit within the context of python. Terminal capping with ACE and NMe was effected using SMILES and SMARTS matching. Multiple hexapeptides were complexed with chain B of crystallographic Mpro (PDS ID: 6XHM), following the validation of chain B for this purpose using AutoDock Vina at high levels of exhaustiveness (480). The resulting Vina scores ranged between -8.7 and -7.0 kcal.mol-1, and the reproducibility of best poses was validated through redocking. Ligand efficiency indices were calculated to identify substrate residues with high binding efficiency at their respective positions, revealing Val (P3), Ala (P1′); and Gly and Ala (P2′ and P3′) as leading efficient binders. Binding efficiencies were lowered by molecular weight. Substrate recognition was assessed by mapping of binding subsites, and Mpro specificity was evaluated through the resolution of intermolecular interaction at the binding interface. Molecular dynamics simulations for 20 ns were performed to assess the stability and behaviour of 132 Mpro systems complexed with KLQ*** substrates. Principal component analysis (PCA), was performed to assess II protein motions and conformational changes during the simulations. A strategy was formulated to classify and evaluate relations in the Mpro PCA motions, revealing four main clades of similarity. Similarity within a clade (Group 2) and dissimilarity between clades were confirmed. Trajectory visualisation revealed complex stability, substrate unbinding and dimer dissociation for various Mpro systems. , Thesis (MSc) -- Faculty of Science, Biochemistry and Microbiology, 2022
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Determining the unbinding events and conserved motions associated with the pyrazinamide release due to resistance mutations of Mycobacterium tuberculosis pyrazinamidase:
- Amamuddy, Olivier S, Musyoka, Thommas M, Boateng, Rita A, Zabo, Sophakama, Tastan Bishop, Özlem
- Authors: Amamuddy, Olivier S , Musyoka, Thommas M , Boateng, Rita A , Zabo, Sophakama , Tastan Bishop, Özlem
- Date: 2020
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/148869 , vital:38781 , https://doi.org/10.1016/j.csbj.2020.05.0099
- Description: Pyrazinamide (PZA) is the only first-line antitubercular drug active against latent Mycobacterium tuberculosis (Mtb). It is activated to pyrazinoic acid by the pncA-encoded pyrazinamidase enzyme (PZase). Despite the emergence of PZA drug resistance, the underlying mechanisms of resistance remain unclear. This study investigated part of these mechanisms by modelling a PZA-bound wild type and 82 mutant PZase structures before applying molecular dynamics (MD) with an accurate Fe2+ cofactor coordination geometry.
- Full Text:
- Authors: Amamuddy, Olivier S , Musyoka, Thommas M , Boateng, Rita A , Zabo, Sophakama , Tastan Bishop, Özlem
- Date: 2020
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/148869 , vital:38781 , https://doi.org/10.1016/j.csbj.2020.05.0099
- Description: Pyrazinamide (PZA) is the only first-line antitubercular drug active against latent Mycobacterium tuberculosis (Mtb). It is activated to pyrazinoic acid by the pncA-encoded pyrazinamidase enzyme (PZase). Despite the emergence of PZA drug resistance, the underlying mechanisms of resistance remain unclear. This study investigated part of these mechanisms by modelling a PZA-bound wild type and 82 mutant PZase structures before applying molecular dynamics (MD) with an accurate Fe2+ cofactor coordination geometry.
- Full Text:
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