Bioinformatics tool and web server development focusing on structural bioinformatics applications
- Authors: Nabatanzi, Margaret
- Date: 2022-10-14
- Subjects: Structural bioinformatics , Proteins Structure , Protein structure prediction , Proteins Conformation , Protein complex
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/365700 , vital:65777 , DOI https://doi.org/10.21504/10962/365700
- Description: This thesis is divided into two main sections: Part 1 describes the design, and evaluation of the accuracy of a new web server – PRotein Interactive MOdeling (PRIMO-Complexes) for modeling protein complexes and biological assemblies. The second part describes the development of bioinformatics tools to predict HIV-1 drug resistance and support bioinformatics research and education. Recent technological advances have resulted in a tremendous increase in the number of sequences and protein structures deposited in the Universal Protein Resource Knowledgebase (UniProtKB) and the Protein Data Bank (PDB). However, the number of sequences has increased at a higher rate compared with the experimentally solved multimeric protein structures. This is partly due to advances in high-throughput sequencing technology. To fill this protein sequence-structure gap, computational approaches have been developed to predict protein structures from available sequences. Computational approaches include template-based and ab initio modeling with the former being the most reliable. Template-based modeling process can be achieved using either standalone software or automated modeling web servers. However, using standalone software requires familiarity with command-line interfaces as well as utilising other intermediate programs which could be daunting to novice users. To alleviate some of these problems, the modeling process has been automated, however, it still has numerous challenges. To date, only a few web servers that support multimeric protein modeling have been developed and even these provide little, if any user involvement in the process. To address some of these issues, a new web server – PRIMO-Complexes – was developed to model protein complexes and biological assemblies. The existing PRIMO web server could only model monomeric proteins. Part 1 of this thesis provides a detailed account of the development and evaluation of PRIMO-Complexes. The rationale for developing this new web server was based on the understanding that most proteins function as protein multimers and often the ligand-binding sites, and enzyme active sites are located at the protein-protein interfaces. It, therefore, necessitated developing capabilities for modeling multimeric proteins. PRIMO-Complexes web server was developed using the Waterfall system development life cycle model, is based on the Django web framework and makes use of high-performance computing resources to execute jobs. The accuracy of the algorithms embedded in PRIMO- Complexes was evaluated and the results were promising. Additionally, PRIMO-Complexes performs comparatively well in relation to other web servers that offer multimeric protein modeling. Another unique feature of PRIMO-Complexes is its interactivity. The webserver was developed with capabilities for allowing users to model multimeric proteins with an appreciable degree of control over the process. In the second part of the thesis several other bioinformatics tools are described, for example, a webserver for predicting HIV-1 drug resistance, the RUBi protein model repository, and a bioinformatics web portal for education and research resources. RUBi protein model repository stores verified theoretical models built using various modeling approaches. This enables users to easily access models to reproduce and/or further the research. This is described in chapter 5. Chapter 6 describes the design and development of the Human Immunodeficiency type 1 Resistance Predictor (HIV-1 ResPredictor), a web application that employs artificial neural networks (ANN) to predict drug resistance in patients infected with HIV-1 subtype B. The ANNs and subtype classifiers performed well making this web application potentially useful to both clinicians and researchers in this era of personalised medicine. Finally, chapter 7 describes a bioinformatics education web portal that equips students with information on how to use bioinformatics online resources. Being aware of these resources is not enough without a deeper understanding and guidance on how to apply bioinformatics methods to solve practical problems. This web portal was aimed at familiarising students with the basic terminology and approaches in structural bioinformatics. Students will potentially gain skills to conduct real-life bioinformatics research to obtain biological insights. , Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 2022
- Full Text:
- Authors: Nabatanzi, Margaret
- Date: 2022-10-14
- Subjects: Structural bioinformatics , Proteins Structure , Protein structure prediction , Proteins Conformation , Protein complex
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/365700 , vital:65777 , DOI https://doi.org/10.21504/10962/365700
- Description: This thesis is divided into two main sections: Part 1 describes the design, and evaluation of the accuracy of a new web server – PRotein Interactive MOdeling (PRIMO-Complexes) for modeling protein complexes and biological assemblies. The second part describes the development of bioinformatics tools to predict HIV-1 drug resistance and support bioinformatics research and education. Recent technological advances have resulted in a tremendous increase in the number of sequences and protein structures deposited in the Universal Protein Resource Knowledgebase (UniProtKB) and the Protein Data Bank (PDB). However, the number of sequences has increased at a higher rate compared with the experimentally solved multimeric protein structures. This is partly due to advances in high-throughput sequencing technology. To fill this protein sequence-structure gap, computational approaches have been developed to predict protein structures from available sequences. Computational approaches include template-based and ab initio modeling with the former being the most reliable. Template-based modeling process can be achieved using either standalone software or automated modeling web servers. However, using standalone software requires familiarity with command-line interfaces as well as utilising other intermediate programs which could be daunting to novice users. To alleviate some of these problems, the modeling process has been automated, however, it still has numerous challenges. To date, only a few web servers that support multimeric protein modeling have been developed and even these provide little, if any user involvement in the process. To address some of these issues, a new web server – PRIMO-Complexes – was developed to model protein complexes and biological assemblies. The existing PRIMO web server could only model monomeric proteins. Part 1 of this thesis provides a detailed account of the development and evaluation of PRIMO-Complexes. The rationale for developing this new web server was based on the understanding that most proteins function as protein multimers and often the ligand-binding sites, and enzyme active sites are located at the protein-protein interfaces. It, therefore, necessitated developing capabilities for modeling multimeric proteins. PRIMO-Complexes web server was developed using the Waterfall system development life cycle model, is based on the Django web framework and makes use of high-performance computing resources to execute jobs. The accuracy of the algorithms embedded in PRIMO- Complexes was evaluated and the results were promising. Additionally, PRIMO-Complexes performs comparatively well in relation to other web servers that offer multimeric protein modeling. Another unique feature of PRIMO-Complexes is its interactivity. The webserver was developed with capabilities for allowing users to model multimeric proteins with an appreciable degree of control over the process. In the second part of the thesis several other bioinformatics tools are described, for example, a webserver for predicting HIV-1 drug resistance, the RUBi protein model repository, and a bioinformatics web portal for education and research resources. RUBi protein model repository stores verified theoretical models built using various modeling approaches. This enables users to easily access models to reproduce and/or further the research. This is described in chapter 5. Chapter 6 describes the design and development of the Human Immunodeficiency type 1 Resistance Predictor (HIV-1 ResPredictor), a web application that employs artificial neural networks (ANN) to predict drug resistance in patients infected with HIV-1 subtype B. The ANNs and subtype classifiers performed well making this web application potentially useful to both clinicians and researchers in this era of personalised medicine. Finally, chapter 7 describes a bioinformatics education web portal that equips students with information on how to use bioinformatics online resources. Being aware of these resources is not enough without a deeper understanding and guidance on how to apply bioinformatics methods to solve practical problems. This web portal was aimed at familiarising students with the basic terminology and approaches in structural bioinformatics. Students will potentially gain skills to conduct real-life bioinformatics research to obtain biological insights. , Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 2022
- Full Text:
Identification of novel compounds against Plasmodium falciparum Cytochrome bc1 Complex inhibiting the trans-membrane electron transfer pathway: an In Silico study
- Authors: Chebon, Lorna Jemosop
- Date: 2022-10-14
- Subjects: Malaria , Plasmodium falciparum , Molecular dynamics , Antimalarials , Molecules Models , Docking , Cytochromes , Drug resistance , Computer simulation , Drugs Computer-aided design , System analysis
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/365666 , vital:65774 , DOI https://doi.org/10.21504/10962/365666
- Description: Malaria continues to be a burden globally with a myriad of challenges deterring eradication efforts. With most antimalarials facing drug resistance, such as atovaquone (ATQ), alternative compounds that can withstand resistance are warranted. The Plasmodium falciparum cytochrome b (PfCytb), a subunit of P. falciparum cytochrome bc1 complex, is a validated drug target. Structurally, cytochrome b, cytochrome c1, and iron sulphur protein (ISP) subunits form the catalytic domain of the protein complex having heme bL, heme bH and iron-sulphur [2FE-2S] cluster cofactors. These cofactos have redox centres to aid in the electron transfer (ET) process. These subunits promote ET mainly through the enzyme’s ubiquinol oxidation (Qo) and ubiquinone reduction (Qi) processes in the catalytic domain. ATQ drug has been used in the prevention and treatment of uncomplicated malaria by targeting PfCytb protein. Once the mitochondrial transmembrane ET pathway is inhibited, it causes a collapse in its membrane potential. Previously reported ATQ drug resistance has been associated with the point mutations Y268C, Y268N and Y268S. Thus, in finding alternatives to the ATQ drug, this research aimed to: i) employ in silico approaches incorporating protein into phospholipid bilayer for the first time to understand the parasites’ resistance mechanism; ii) determine any sequence and structural differences that could be explored in drug design studies; and iii) screen for PfCytb-iron sulphur protein (Cytb-ISP) hit compounds from South African natural compound database (SANCDB) and Medicines for Malaria Venture (MMV) that can withstand the identified mutations. Using computational tools, comparative sequence and structural analyses were performed on the cytochrome b protein, where the ultimate focus was on P. falciparum cytochrome b and its human homolog. Through multiple sequence alignment, motif discovery and phylogeny, differences between P. falciparum and H. sapiens cytochrome b were identified. Protein modelling of both P. falciparum and H. sapiens cytochrome b - iron sulphur protein (PfCytb-ISP and HsCytb-ISP) was performed. Results showed that at the sequence level, there were few amino acid residue differences because the protein is highly conserved. Important to note is the four-residue deletion in Plasmodium spp. absent in the human homolog. Motif analysis discovered five unique motifs in P. falciparum cytochrome b protein which were mapped onto the predicted protein model. These motifs were not in regions of functional importance; hence their function is still unknown. At a structural level, the four-residue deletion was observed to alter the Qo substrate binding pocket as reported in previous studies and confirmed in this study. This deletion resulted in a 0.83 Å structural displacement. Also, there are currently no in silico studies that have performed experiments with P. falciparum cytochrome b protein incorporated into a phospholipid bilayer. Using 350 ns molecular dynamics (MD) simulations of the holo and ATQ-bound systems, the study highlighted the resistance mechanism of the parasite protein where the loss of active site residue-residue interactions was identified, all linked to the three mutations. The identified compromised interactions are likely to destabilise the protein’s function, specifically in the Qo substrate binding site. This showed the possible effect of mutations on ATQ drug activity, where all three mutations were reported to share a similar resistance mechanism. Thereafter, this research work utilised in silico approaches where both Qo active site and interface pocket were targeted by screening the South African natural compounds database (SANCDB) and Medicines for Malaria Venture (MMV) compounds to identify novel selective hits. SANCDB compounds are known for their structural complexity that preserves the potency of the drug molecule. Both SANCDB and MMV compounds have not been explored as inhibitors against the PfCytb drug target. Molecular docking, molecular dynamics (MD) simulations, principal component, and dynamic residue network (DRN; global and local) analyses were utilised to identify and confirm the potential selective inhibitors. Docking results identified compounds that bound selectively onto PfCytb-ISP with a binding energy ≤ -8.7 kcal/mol-1. Further, this work validated a total of eight potential selective compounds to inhibit PfCytb-ISP protein (Qo active site) not only in the wild-type but also in the presence of the point mutations Y268C, Y268N and Y268S. The selective binding of these hit compounds could be linked to the differences reported at sequence/residue level in chapter 3. DRN and residue contact map analyses of the eight compounds in holo and ligand-bound systems revealed reduced residue interactions and decreased protein communication. This suggests that the eight compounds show the possibility of inhibiting the parasite and disrupting important residue-residue interactions. Additionally, 13 selective compounds were identified to bind at the protein’s heterodimer interface, where global and local analysis confirmed their effect on active site residues (distal location) as well as on the communication network. Based on the sequence differences between PfCytb and the human homolog, these findings suggest these selective compounds as potential allosteric modulators of the parasite enzyme, which may serve as possible replacements of the already resistant ATQ drug. Therefore, these findings pave the way for further in vitro studies to establish their anti-plasmodial inhibition levels. , Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 2022
- Full Text:
- Authors: Chebon, Lorna Jemosop
- Date: 2022-10-14
- Subjects: Malaria , Plasmodium falciparum , Molecular dynamics , Antimalarials , Molecules Models , Docking , Cytochromes , Drug resistance , Computer simulation , Drugs Computer-aided design , System analysis
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/365666 , vital:65774 , DOI https://doi.org/10.21504/10962/365666
- Description: Malaria continues to be a burden globally with a myriad of challenges deterring eradication efforts. With most antimalarials facing drug resistance, such as atovaquone (ATQ), alternative compounds that can withstand resistance are warranted. The Plasmodium falciparum cytochrome b (PfCytb), a subunit of P. falciparum cytochrome bc1 complex, is a validated drug target. Structurally, cytochrome b, cytochrome c1, and iron sulphur protein (ISP) subunits form the catalytic domain of the protein complex having heme bL, heme bH and iron-sulphur [2FE-2S] cluster cofactors. These cofactos have redox centres to aid in the electron transfer (ET) process. These subunits promote ET mainly through the enzyme’s ubiquinol oxidation (Qo) and ubiquinone reduction (Qi) processes in the catalytic domain. ATQ drug has been used in the prevention and treatment of uncomplicated malaria by targeting PfCytb protein. Once the mitochondrial transmembrane ET pathway is inhibited, it causes a collapse in its membrane potential. Previously reported ATQ drug resistance has been associated with the point mutations Y268C, Y268N and Y268S. Thus, in finding alternatives to the ATQ drug, this research aimed to: i) employ in silico approaches incorporating protein into phospholipid bilayer for the first time to understand the parasites’ resistance mechanism; ii) determine any sequence and structural differences that could be explored in drug design studies; and iii) screen for PfCytb-iron sulphur protein (Cytb-ISP) hit compounds from South African natural compound database (SANCDB) and Medicines for Malaria Venture (MMV) that can withstand the identified mutations. Using computational tools, comparative sequence and structural analyses were performed on the cytochrome b protein, where the ultimate focus was on P. falciparum cytochrome b and its human homolog. Through multiple sequence alignment, motif discovery and phylogeny, differences between P. falciparum and H. sapiens cytochrome b were identified. Protein modelling of both P. falciparum and H. sapiens cytochrome b - iron sulphur protein (PfCytb-ISP and HsCytb-ISP) was performed. Results showed that at the sequence level, there were few amino acid residue differences because the protein is highly conserved. Important to note is the four-residue deletion in Plasmodium spp. absent in the human homolog. Motif analysis discovered five unique motifs in P. falciparum cytochrome b protein which were mapped onto the predicted protein model. These motifs were not in regions of functional importance; hence their function is still unknown. At a structural level, the four-residue deletion was observed to alter the Qo substrate binding pocket as reported in previous studies and confirmed in this study. This deletion resulted in a 0.83 Å structural displacement. Also, there are currently no in silico studies that have performed experiments with P. falciparum cytochrome b protein incorporated into a phospholipid bilayer. Using 350 ns molecular dynamics (MD) simulations of the holo and ATQ-bound systems, the study highlighted the resistance mechanism of the parasite protein where the loss of active site residue-residue interactions was identified, all linked to the three mutations. The identified compromised interactions are likely to destabilise the protein’s function, specifically in the Qo substrate binding site. This showed the possible effect of mutations on ATQ drug activity, where all three mutations were reported to share a similar resistance mechanism. Thereafter, this research work utilised in silico approaches where both Qo active site and interface pocket were targeted by screening the South African natural compounds database (SANCDB) and Medicines for Malaria Venture (MMV) compounds to identify novel selective hits. SANCDB compounds are known for their structural complexity that preserves the potency of the drug molecule. Both SANCDB and MMV compounds have not been explored as inhibitors against the PfCytb drug target. Molecular docking, molecular dynamics (MD) simulations, principal component, and dynamic residue network (DRN; global and local) analyses were utilised to identify and confirm the potential selective inhibitors. Docking results identified compounds that bound selectively onto PfCytb-ISP with a binding energy ≤ -8.7 kcal/mol-1. Further, this work validated a total of eight potential selective compounds to inhibit PfCytb-ISP protein (Qo active site) not only in the wild-type but also in the presence of the point mutations Y268C, Y268N and Y268S. The selective binding of these hit compounds could be linked to the differences reported at sequence/residue level in chapter 3. DRN and residue contact map analyses of the eight compounds in holo and ligand-bound systems revealed reduced residue interactions and decreased protein communication. This suggests that the eight compounds show the possibility of inhibiting the parasite and disrupting important residue-residue interactions. Additionally, 13 selective compounds were identified to bind at the protein’s heterodimer interface, where global and local analysis confirmed their effect on active site residues (distal location) as well as on the communication network. Based on the sequence differences between PfCytb and the human homolog, these findings suggest these selective compounds as potential allosteric modulators of the parasite enzyme, which may serve as possible replacements of the already resistant ATQ drug. Therefore, these findings pave the way for further in vitro studies to establish their anti-plasmodial inhibition levels. , Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 2022
- Full Text:
Identification of selective novel hits against Mycobacterium tuberculosis KasA potential allosteric sites using bioinformatics approaches
- Authors: Hare, Fadzayi Faith
- Date: 2022-10-14
- Subjects: Tuberculosis , Docking , Molecules Models , Virtual screening , Multidrug-resistant tuberculosis , Fatty acids Synthesis , Drugs Design
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/362842 , vital:65367
- Description: Tuberculosis (TB) is a global health threat that has led to approximately 1.5 million deaths annually. According to the World Health Organization (WHO), TB is among the top ten deadly diseases and is the leading cause of death due to a single infectious agent. The main challenge in the effective treatment and control of TB is the ongoing emergence of resistant strains of Mycobacterium tuberculosis (Mtb) which lead to multi-drug resistant (MDR) and extensive-drug resistant (XDR) TB. Hence, the identification and characterization of novel drug targets and drugs that modulate the activity of the pathogen are an urgent priority. The current situation even necessitates the reengineering or repurposing of drugs in order to achieve effective control. The β-ketoacyl-acyl carrier protein synthase I (KasA) of Mycobacterium tuberculosis is an essential enzyme in the mycobacterial fatty acid synthesis (FAS-II) pathway and is believed to be a promising target for drug discovery in TB. It is one of the five main proteins of the FAS-II pathway and catalyzes a key condensation reaction in the synthesis of meromycolate chains, the precursors of mycolic acids involved in cell wall formation. Although this protein has been extensively studied, little research has been devoted to the allosteric inhibition of potential drug compounds. The main aim of this research was to identify the allosteric sites on the protein that could be involved in the inhibition of substrate binding activities and novel drug compounds that bind to these sites by use of in-silico approaches. The bioinformatics approaches used in this study were divided into four main objectives namely identification of KasA homolog sequences, sequence analysis and protein characterization, allosteric site search and lastly virtual screening of DrugBank compounds via molecular docking. Fifteen homolog sequences were identified from the BLASTP analysis and were derived from bacteria, fungi and mammals. In order to discover important residues and regions within the KasA proteins, sequence alignment, motif analysis and phylogenetic studies were performed using Mtb KasA as a reference. Sequence alignment revealed conserved residues in all KasA proteins that have functional importance such as the catalytic triad residues (Cys171, His311 and His345). Motif analysis identified 18 highly conserved motifs within the KasA proteins with structural and functional roles. In addition, motifs unique to the Mtb KasA protein were also identified and explored for inhibitor drug design purposes. Phylogenetic analysis of the homolog sequences showed a distinct clustering of prokaryotes and eukaryotes. A distinctive clustering was also observed for species belonging to the same genus. Since the mechanism of action of most drugs involves the active site, allosteric site search was conducted on Mtb KasA and the human homolog protein using a combination of pocket detection algorithms with the aim of identifying sites that could be utilized in allosteric modulator drug discovery. This was followed by the virtual screening of 2089 FDA approved DrugBank compounds against the entire protein surfaces of Mtb KasA and Hsmt KasA, performed via molecular docking using AutoDock Vina. Screening of the compounds was based on the binding energies, with more focus on identifying ligands that bound exclusively to the acyl-binding tunnel of Mtb KasA. This reduced the data set to 27 promising drug compounds with a relatively high binding affinity for Mtb KasA, however, further experiments need to be performed to validate this result. Among these compounds were DB08889, DB06755, DB09270, DB11226, DB00392, DB12278, DB08936, DB00781, DB13720 and DB00392, which displayed relatively low binding energies for Mtb KasA when compared to the human homolog protein. , Thesis (MSc) -- Faculty of Science, Biochemistry and Microbiology, 2022
- Full Text:
- Authors: Hare, Fadzayi Faith
- Date: 2022-10-14
- Subjects: Tuberculosis , Docking , Molecules Models , Virtual screening , Multidrug-resistant tuberculosis , Fatty acids Synthesis , Drugs Design
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/362842 , vital:65367
- Description: Tuberculosis (TB) is a global health threat that has led to approximately 1.5 million deaths annually. According to the World Health Organization (WHO), TB is among the top ten deadly diseases and is the leading cause of death due to a single infectious agent. The main challenge in the effective treatment and control of TB is the ongoing emergence of resistant strains of Mycobacterium tuberculosis (Mtb) which lead to multi-drug resistant (MDR) and extensive-drug resistant (XDR) TB. Hence, the identification and characterization of novel drug targets and drugs that modulate the activity of the pathogen are an urgent priority. The current situation even necessitates the reengineering or repurposing of drugs in order to achieve effective control. The β-ketoacyl-acyl carrier protein synthase I (KasA) of Mycobacterium tuberculosis is an essential enzyme in the mycobacterial fatty acid synthesis (FAS-II) pathway and is believed to be a promising target for drug discovery in TB. It is one of the five main proteins of the FAS-II pathway and catalyzes a key condensation reaction in the synthesis of meromycolate chains, the precursors of mycolic acids involved in cell wall formation. Although this protein has been extensively studied, little research has been devoted to the allosteric inhibition of potential drug compounds. The main aim of this research was to identify the allosteric sites on the protein that could be involved in the inhibition of substrate binding activities and novel drug compounds that bind to these sites by use of in-silico approaches. The bioinformatics approaches used in this study were divided into four main objectives namely identification of KasA homolog sequences, sequence analysis and protein characterization, allosteric site search and lastly virtual screening of DrugBank compounds via molecular docking. Fifteen homolog sequences were identified from the BLASTP analysis and were derived from bacteria, fungi and mammals. In order to discover important residues and regions within the KasA proteins, sequence alignment, motif analysis and phylogenetic studies were performed using Mtb KasA as a reference. Sequence alignment revealed conserved residues in all KasA proteins that have functional importance such as the catalytic triad residues (Cys171, His311 and His345). Motif analysis identified 18 highly conserved motifs within the KasA proteins with structural and functional roles. In addition, motifs unique to the Mtb KasA protein were also identified and explored for inhibitor drug design purposes. Phylogenetic analysis of the homolog sequences showed a distinct clustering of prokaryotes and eukaryotes. A distinctive clustering was also observed for species belonging to the same genus. Since the mechanism of action of most drugs involves the active site, allosteric site search was conducted on Mtb KasA and the human homolog protein using a combination of pocket detection algorithms with the aim of identifying sites that could be utilized in allosteric modulator drug discovery. This was followed by the virtual screening of 2089 FDA approved DrugBank compounds against the entire protein surfaces of Mtb KasA and Hsmt KasA, performed via molecular docking using AutoDock Vina. Screening of the compounds was based on the binding energies, with more focus on identifying ligands that bound exclusively to the acyl-binding tunnel of Mtb KasA. This reduced the data set to 27 promising drug compounds with a relatively high binding affinity for Mtb KasA, however, further experiments need to be performed to validate this result. Among these compounds were DB08889, DB06755, DB09270, DB11226, DB00392, DB12278, DB08936, DB00781, DB13720 and DB00392, which displayed relatively low binding energies for Mtb KasA when compared to the human homolog protein. , Thesis (MSc) -- Faculty of Science, Biochemistry and Microbiology, 2022
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