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Satvati S, Ghasemi Y, Najafipour S, Eskandari S, Mahmoodi S, Nezafat N, Hashemzaei M. Finding and engineering the newly found bacterial superoxide dismutase enzyme to increase its thermostability and decrease the immunogenicity: a computational and experimental research. Arch Microbiol 2023; 205:260. [PMID: 37291420 DOI: 10.1007/s00203-023-03601-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 05/23/2023] [Accepted: 05/29/2023] [Indexed: 06/10/2023]
Abstract
Superoxide dismutase (SOD) is one of the most important antioxidant enzymes that can reduce oxidative stress in the cell environment. Nowadays, bacterial sources of enzyme are commercially applicable in the cosmetics and pharmaceutical industries, but the allergenic effect of proteins from non-human sources has been mentioned as disadvantage of these kinds of enzymes. In this study, to find the suitable bacterial SOD candidate for decreasing immunogenicity, the sequences of five thermophilic bacteria were selected as reference species. Then, linear and conformational B-cell epitopes of the SOD were analyzed by different servers. The stability and immunogenicity of mutant positions were also evaluated. The mutant gene was inserted into the pET-23a expression vector and transformed into E. Coli BL21 (DE3) for expression of the recombinant enzyme. Afterward, the expression of the mutant enzyme was evaluated by SDS-PAGE analysis and the recombinant enzyme activity was assessed. Anoxybacillus gonensis was selected as a reasonable SOD source according to BLAST search, physicochemical properties analysis, and prediction of allergenic features. Regarding our results, five residues including E84, E142, K144, G147, and M148 were predicted as candidates for mutagenesis. Finally, the K144A was chosen as the final modification due to the increase in the stability of the enzyme and decreased immunogenicity of the enzyme as well. The enzyme activity was 240 U/ml at room temperature. Alternation in K144 to alanine caused increased stability of the enzyme. In silico studies confirmed non-antigenic protein after mutation.
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Affiliation(s)
- Saha Satvati
- Department of Medical Biotechnology, School of Advanced Technologies in Medicine, Fasa University of Medical Sciences, Fasa, Iran
| | - Younes Ghasemi
- Department of Pharmaceutical Biotechnology, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran
- Computational vaccine and Drug Design Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Sohrab Najafipour
- Department of Medical Biotechnology, School of Advanced Technologies in Medicine, Fasa University of Medical Sciences, Fasa, Iran
- Department of Tissue Engineering, School of Advanced Technologies in Medicine, Fasa University of Medical Sciences, Fasa, Iran
| | - Sedigheh Eskandari
- Computational vaccine and Drug Design Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Shirin Mahmoodi
- Department of Medical Biotechnology, School of Advanced Technologies in Medicine, Fasa University of Medical Sciences, Fasa, Iran.
| | - Navid Nezafat
- Department of Pharmaceutical Biotechnology, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran.
- Computational vaccine and Drug Design Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
- Pharmaceutical Science Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
| | - Masoud Hashemzaei
- Department of Pharmaceutical Biotechnology, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran
- Computational vaccine and Drug Design Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
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Chen Z, Wang X, Chen X, Huang J, Wang C, Wang J, Wang Z. Accelerating therapeutic protein design with computational approaches toward the clinical stage. Comput Struct Biotechnol J 2023; 21:2909-2926. [PMID: 38213894 PMCID: PMC10781723 DOI: 10.1016/j.csbj.2023.04.027] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 04/11/2023] [Accepted: 04/27/2023] [Indexed: 01/13/2024] Open
Abstract
Therapeutic protein, represented by antibodies, is of increasing interest in human medicine. However, clinical translation of therapeutic protein is still largely hindered by different aspects of developability, including affinity and selectivity, stability and aggregation prevention, solubility and viscosity reduction, and deimmunization. Conventional optimization of the developability with widely used methods, like display technologies and library screening approaches, is a time and cost-intensive endeavor, and the efficiency in finding suitable solutions is still not enough to meet clinical needs. In recent years, the accelerated advancement of computational methodologies has ushered in a transformative era in the field of therapeutic protein design. Owing to their remarkable capabilities in feature extraction and modeling, the integration of cutting-edge computational strategies with conventional techniques presents a promising avenue to accelerate the progression of therapeutic protein design and optimization toward clinical implementation. Here, we compared the differences between therapeutic protein and small molecules in developability and provided an overview of the computational approaches applicable to the design or optimization of therapeutic protein in several developability issues.
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Affiliation(s)
- Zhidong Chen
- Department of Pathology, The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen 518033, China
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
| | - Xinpei Wang
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
| | - Xu Chen
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
| | - Juyang Huang
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
| | - Chenglin Wang
- Shenzhen Qiyu Biotechnology Co., Ltd, Shenzhen 518107, China
| | - Junqing Wang
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
| | - Zhe Wang
- Department of Pathology, The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen 518033, China
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Hennigan JN, Lynch MD. The past, present, and future of enzyme-based therapies. Drug Discov Today 2022; 27:117-133. [PMID: 34537332 PMCID: PMC8714691 DOI: 10.1016/j.drudis.2021.09.004] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 07/15/2021] [Accepted: 09/10/2021] [Indexed: 01/03/2023]
Abstract
Enzyme-based therapeutics (EBTs) have the potential to tap into an almost unmeasurable amount of enzyme biodiversity and treat myriad conditions. Although EBTs were some of the first biologics used clinically, the rate of development of newer EBTs has lagged behind that of other biologics. Here, we review the history of EBTs, and discuss the state of each class of EBT, their potential clinical advantages, and the unique challenges to their development. Additionally, we discuss key remaining technical barriers that, if addressed, could increase the diversity and rate of the development of EBTs.
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Affiliation(s)
| | - Michael D Lynch
- Department of Biomedical Engineering, Duke University, Durham, NC, USA.
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Das B, Chakraborty D. Epitope-Based Potential Vaccine Candidate for Humoral and Cell-Mediated Immunity to Combat Severe Acute Respiratory Syndrome Coronavirus 2 Pandemic. J Phys Chem Lett 2020; 11:9920-9930. [PMID: 33174418 PMCID: PMC7670824 DOI: 10.1021/acs.jpclett.0c02846] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Accepted: 10/29/2020] [Indexed: 05/09/2023]
Abstract
The emergence of severe acute respiratory syndrome from novel Coronavirus (SARS-CoV-2) has put an immense pressure worldwide where vaccination is believed to be an efficient way for developing hard immunity. Herein, we employ immunoinformatic tools to identify B-cell, T-cell epitopes associated with the spike protein of SARS-CoV-2, which is important for genome release. The results showed that the highly immunogenic epitopes located at the stalk part are mostly conserved compared to the receptor binding domain (RDB). Further, two vaccine candidates were computationally modeled from the linear B-cell, T-cell epitopes. Molecular docking reveals the crucial interactions of the vaccines with immune-receptors, and their stability is assessed by MD simulation studies. The chimeric vaccines showed remarkable binding affinity toward the immune cell receptors computed by the MM/PBSA method. van der Waals and electrostatic interactions are found to be the dominant factors for the stability of the complexes. The molecular-level interaction obtained from this study may provide deeper insight into the process of vaccine development against the pandemic of COVID-19.
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MESH Headings
- Amino Acid Sequence
- COVID-19/prevention & control
- COVID-19 Vaccines/chemistry
- COVID-19 Vaccines/immunology
- COVID-19 Vaccines/metabolism
- Epitopes, B-Lymphocyte/chemistry
- Epitopes, B-Lymphocyte/immunology
- Epitopes, B-Lymphocyte/metabolism
- Epitopes, T-Lymphocyte/chemistry
- Epitopes, T-Lymphocyte/immunology
- Epitopes, T-Lymphocyte/metabolism
- Molecular Docking Simulation
- Molecular Dynamics Simulation
- Protein Binding
- Protein Domains
- SARS-CoV-2/immunology
- Spike Glycoprotein, Coronavirus/chemistry
- Spike Glycoprotein, Coronavirus/immunology
- Spike Glycoprotein, Coronavirus/metabolism
- Vaccines, Subunit/chemistry
- Vaccines, Subunit/immunology
- Vaccines, Subunit/metabolism
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Affiliation(s)
- Bratin
Kumar Das
- Biophysical and Computational Laboratory, Department of Chemistry, National Institute of Technology
Karnataka, Surathkal, Mangalore, 575025, India
| | - Debashree Chakraborty
- Biophysical and Computational Laboratory, Department of Chemistry, National Institute of Technology
Karnataka, Surathkal, Mangalore, 575025, India
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