201
|
Usmani SS, Kumar R, Bhalla S, Kumar V, Raghava GPS. In Silico Tools and Databases for Designing Peptide-Based Vaccine and Drugs. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2018; 112:221-263. [PMID: 29680238 DOI: 10.1016/bs.apcsb.2018.01.006] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The prolonged conventional approaches of drug screening and vaccine designing prerequisite patience, vigorous effort, outrageous cost as well as additional manpower. Screening and experimentally validating thousands of molecules for a specific therapeutic property never proved to be an easy task. Similarly, traditional way of vaccination includes administration of either whole or attenuated pathogen, which raises toxicity and safety issues. Emergence of sequencing and recombinant DNA technology led to the epitope-based advanced vaccination concept, i.e., small peptides (epitope) can stimulate specific immune response. Advent of bioinformatics proved to be an adjunct in vaccine and drug designing. Genomic study of pathogens aid to identify and analyze the protective epitope. A number of in silico tools have been developed to design immunotherapy as well as peptide-based drugs in the last two decades. These tools proved to be a catalyst in drug and vaccine designing. This review solicits therapeutic peptide databases as well as in silico tools developed for designing peptide-based vaccine and drugs.
Collapse
Affiliation(s)
- Salman Sadullah Usmani
- Center for Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India; Bioinformatics Centre, CSIR-Institute of Microbial Technology, Chandigarh, India
| | - Rajesh Kumar
- Center for Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India; Bioinformatics Centre, CSIR-Institute of Microbial Technology, Chandigarh, India
| | - Sherry Bhalla
- Center for Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India
| | - Vinod Kumar
- Center for Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India; Bioinformatics Centre, CSIR-Institute of Microbial Technology, Chandigarh, India
| | - Gajendra P S Raghava
- Center for Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India; Bioinformatics Centre, CSIR-Institute of Microbial Technology, Chandigarh, India.
| |
Collapse
|
203
|
Zarei M, Nezafat N, Rahbar MR, Negahdaripour M, Sabetian S, Morowvat MH, Ghasemi Y. Decreasing the immunogenicity of arginine deiminase enzyme via structure-based computational analysis. J Biomol Struct Dyn 2018; 37:523-536. [PMID: 29363409 DOI: 10.1080/07391102.2018.1431151] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
The clinical applications of therapeutic enzymes are often limited due to their immunogenicity. B-cell epitope removal is an effective approach to solve this obstacle. The identification of hot spot epitopic residues is a critical step in the removal of protein B-cell epitope. Hereof, computational approaches are a suitable alternative to costly and labor-intensive experimental approaches. Arginine deiminase, a Mycoplasma arginine-catabolizing enzyme, is in the clinical trial for treating arginine auxotrophic cancers, especially hepatocellular carcinomas and melanomas through depleting plasma arginine and causing cell starvation. In this study, arginine deiminase from Mycoplasma hominis (MhADI) was computationally analyzed for recognizing and locating its immune-reactive regions. The 3D structure of the bioactive form of MhADI was modeled. The B-cell epitope mapping of protein was performed using various servers with different algorithms. Six segments: 31-40, 48-55, 131-140, 196-206, 294-314, and 331-344 were predicted to be the consensus immunogenic regions. The modification of epitopic hot spot residue was performed to reduce immune-reactiveness. The hot spot residue was selected considering a high B-cell epitope score, convexity index, surface accessibility, flexibility, and hydrophilicity. The structure stability of native and mutant proteins was evaluated through molecular dynamics simulation. The E304L mutein was suggested as a lower antigenic and stable enzyme derivative.
Collapse
Affiliation(s)
- Mahboubeh Zarei
- a Department of Pharmaceutical Biotechnology, School of Pharmacy , Shiraz University of Medical Sciences , Shiraz , Iran.,b Pharmaceutical Sciences Research Center , Shiraz University of Medical Sciences , Shiraz , Iran
| | - Navid Nezafat
- a Department of Pharmaceutical Biotechnology, School of Pharmacy , Shiraz University of Medical Sciences , Shiraz , Iran.,b Pharmaceutical Sciences Research Center , Shiraz University of Medical Sciences , Shiraz , Iran
| | - Mohammad Reza Rahbar
- a Department of Pharmaceutical Biotechnology, School of Pharmacy , Shiraz University of Medical Sciences , Shiraz , Iran.,b Pharmaceutical Sciences Research Center , Shiraz University of Medical Sciences , Shiraz , Iran
| | - Manica Negahdaripour
- a Department of Pharmaceutical Biotechnology, School of Pharmacy , Shiraz University of Medical Sciences , Shiraz , Iran.,b Pharmaceutical Sciences Research Center , Shiraz University of Medical Sciences , Shiraz , Iran
| | - Soudabeh Sabetian
- b Pharmaceutical Sciences Research Center , Shiraz University of Medical Sciences , Shiraz , Iran
| | | | - Younes Ghasemi
- a Department of Pharmaceutical Biotechnology, School of Pharmacy , Shiraz University of Medical Sciences , Shiraz , Iran.,b Pharmaceutical Sciences Research Center , Shiraz University of Medical Sciences , Shiraz , Iran
| |
Collapse
|
205
|
Motoya T, Nagasawa K, Matsushima Y, Nagata N, Ryo A, Sekizuka T, Yamashita A, Kuroda M, Morita Y, Suzuki Y, Sasaki N, Katayama K, Kimura H. Molecular Evolution of the VP1 Gene in Human Norovirus GII.4 Variants in 1974-2015. Front Microbiol 2017; 8:2399. [PMID: 29259596 PMCID: PMC5723339 DOI: 10.3389/fmicb.2017.02399] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2017] [Accepted: 11/20/2017] [Indexed: 12/14/2022] Open
Abstract
Human norovirus (HuNoV) is a leading cause of viral gastroenteritis worldwide, of which GII.4 is the most predominant genotype. Unlike other genotypes, GII.4 has created various variants that escaped from previously acquired immunity of the host and caused repeated epidemics. However, the molecular evolutionary differences among all GII.4 variants, including recently discovered strains, have not been elucidated. Thus, we conducted a series of bioinformatic analyses using numerous, globally collected, full-length GII.4 major capsid (VP1) gene sequences (466 strains) to compare the evolutionary patterns among GII.4 variants. The time-scaled phylogenetic tree constructed using the Bayesian Markov chain Monte Carlo (MCMC) method showed that the common ancestor of the GII.4 VP1 gene diverged from GII.20 in 1840. The GII.4 genotype emerged in 1932, and then formed seven clusters including 14 known variants after 1980. The evolutionary rate of GII.4 strains was estimated to be 7.68 × 10−3 substitutions/site/year. The evolutionary rates probably differed among variants as well as domains [protruding 1 (P1), shell, and P2 domains]. The Osaka 2007 variant strains probably contained more nucleotide substitutions than any other variant. Few conformational epitopes were located in the shell and P1 domains, although most were contained in the P2 domain, which, as previously established, is associated with attachment to host factors and antigenicity. We found that positive selection sites for the whole GII.4 genotype existed in the shell and P1 domains, while Den Haag 2006b, New Orleans 2009, and Sydney 2012 variants were under positive selection in the P2 domain. Amino acid substitutions overlapped with putative epitopes or were located around the epitopes in the P2 domain. The effective population sizes of the present strains increased stepwise for Den Haag 2006b, New Orleans 2009, and Sydney 2012 variants. These results suggest that HuNoV GII.4 rapidly evolved in a few decades, created various variants, and altered its evolutionary rate and antigenicity.
Collapse
Affiliation(s)
- Takumi Motoya
- Ibaraki Prefectural Institute of Public Health, Mito, Japan.,Laboratory of Laboratory Animal Science and Medicine, Faculty of Veterinary Medicine, Kitasato University, Towada, Japan
| | - Koo Nagasawa
- Infectious Disease Surveillance Center, National Institute of Infectious Diseases, Musashimurayama, Japan
| | - Yuki Matsushima
- Division of Virology, Kawasaki City Institute for Public Health, Kawasaki, Japan
| | - Noriko Nagata
- Ibaraki Prefectural Institute of Public Health, Mito, Japan
| | - Akihide Ryo
- Department of Microbiology, Yokohama City University Graduate School of Medicine, Yokohama, Japan
| | - Tsuyoshi Sekizuka
- Pathogen Genomics Center, National Institute of Infectious Diseases, Musashimurayama, Japan
| | - Akifumi Yamashita
- Pathogen Genomics Center, National Institute of Infectious Diseases, Musashimurayama, Japan
| | - Makoto Kuroda
- Pathogen Genomics Center, National Institute of Infectious Diseases, Musashimurayama, Japan
| | - Yukio Morita
- Department of Food and Nutrition, Tokyo Kasei University, Itabashi-ku, Japan
| | - Yoshiyuki Suzuki
- Graduate School of Natural Sciences, Nagoya City University, Nagoya, Japan
| | - Nobuya Sasaki
- Laboratory of Laboratory Animal Science and Medicine, Faculty of Veterinary Medicine, Kitasato University, Towada, Japan
| | - Kazuhiko Katayama
- Laboratory of Viral Infection I, Kitasato Institute for Life Sciences, Kitasato University, Minato-ku, Japan
| | - Hirokazu Kimura
- Infectious Disease Surveillance Center, National Institute of Infectious Diseases, Musashimurayama, Japan.,Department of Microbiology, Yokohama City University Graduate School of Medicine, Yokohama, Japan.,School of Medical Technology, Faculty of Health Sciences, Gunma Paz University, Takasaki, Japan
| |
Collapse
|
206
|
Computer-Aided Design of an Epitope-Based Vaccine against Epstein-Barr Virus. J Immunol Res 2017; 2017:9363750. [PMID: 29119120 PMCID: PMC5651165 DOI: 10.1155/2017/9363750] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2017] [Revised: 08/07/2017] [Accepted: 08/20/2017] [Indexed: 02/06/2023] Open
Abstract
Epstein-Barr virus is a very common human virus that infects 90% of human adults. EBV replicates in epithelial and B cells and causes infectious mononucleosis. EBV infection is also linked to various cancers, including Burkitt's lymphoma and nasopharyngeal carcinomas, and autoimmune diseases such as multiple sclerosis. Currently, there are no effective drugs or vaccines to treat or prevent EBV infection. Herein, we applied a computer-aided strategy to design a prophylactic epitope vaccine ensemble from experimentally defined T and B cell epitopes. Such strategy relies on identifying conserved epitopes in conjunction with predictions of HLA presentation for T cell epitope selection and calculations of accessibility and flexibility for B cell epitope selection. The T cell component includes 14 CD8 T cell epitopes from early antigens and 4 CD4 T cell epitopes, targeted during the course of a natural infection and providing a population protection coverage of over 95% and 81.8%, respectively. The B cell component consists of 3 experimentally defined B cell epitopes from gp350 plus 4 predicted B cell epitopes from other EBV envelope glycoproteins, all mapping in flexible and solvent accessible regions. We discuss the rationale for the formulation and possible deployment of this epitope vaccine ensemble.
Collapse
|