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Choudhury A, Kumar P, Nafidi HA, Almaary KS, Wondmie GF, Kumar A, Bourhia M. Immunoinformatics approaches in developing a novel multi-epitope chimeric vaccine protective against Saprolegnia parasitica. Sci Rep 2024; 14:2260. [PMID: 38278861 PMCID: PMC10817918 DOI: 10.1038/s41598-024-52223-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 01/16/2024] [Indexed: 01/28/2024] Open
Abstract
Saprolegnia parasitica is responsible for devastating infections in fish and poses a tremendous threat to the global aquaculture industry. Presently, no safe and effective control measures are available, on the contrary, use of banned toxic compounds against the pathogen is affecting humans via biomagnification routes. This pioneering study aims to design an effective multi-epitope multi-target vaccine candidate against S. parasitica by targeting key proteins involved in the infection process. The proteins were analyzed and linear B-cell epitopes, MHC class I, and class II epitopes were predicted. Subsequently, highly antigenic epitopes were selected and fused to a highly immunogenic adjuvant, 50S ribosomal protein L7/L12, to design a multi-epitope chimeric vaccine construct. The structure of the vaccine was generated and validated for its stereochemical quality, physicochemical properties, antigenicity, allergenicity, and virulence traits. Molecular docking analyses demonstrated strong binding interactions between the vaccine and piscine immune receptors (TLR5, MHC I, MHC II). Molecular dynamics simulations and binding energy calculations of the complexes, further, reflected the stability and favorable interactions of the vaccine and predicted its cytosolic stability. Immune simulations predicted robust and consistent kinetics of the immune response elicited by the vaccine. The study posits the vaccine as a promising solution to combat saprolegniasis in the aquaculture industry.
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Affiliation(s)
- Abhigyan Choudhury
- Department of Animal Science, Kazi Nazrul University, Asansol, West Bengal, 713 340, India.
| | - Pawan Kumar
- Toxicology and Computational Biology Group, Centre for Bioinformatics, Maharshi Dayanand University, Rohtak, 124 001, India
| | - Hiba-Allah Nafidi
- Department of Food Science, Faculty of Agricultural and Food Sciences, Laval University, Quebec City, QC, 2325G1V 0A6, Canada
| | - Khalid S Almaary
- Department of Botany and Microbiology, College of Science, King Saud University, P. O. Box 2455, 114 51, Riyadh, Saudi Arabia
| | | | - Ajit Kumar
- Toxicology and Computational Biology Group, Centre for Bioinformatics, Maharshi Dayanand University, Rohtak, 124 001, India.
| | - Mohammed Bourhia
- Department of Chemistry and Biochemistry, Faculty of Medicine and Pharmacy, Ibn Zohr University, 700 00, Laayoune, Morocco
- Laboratory of Chemistry-Biochemistry, Environment, Nutrition, and Health, Faculty of Medicine and Pharmacy, University Hassan II, B. P. 5696, Casablanca, Morocco
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Islam SI, Ahmed SS, Sanjida S, Mou MJ, Mahfuj S, Habib N, Ferdous MA, Rahman MDH, Noor MHM. Towards characterizing of Enterocytozoon hepatopenaei (EHP) spore wall proteins with feature identification and analogy modeling. INFORMATICS IN MEDICINE UNLOCKED 2023. [DOI: 10.1016/j.imu.2023.101215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/12/2023] Open
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Soto-Ospina A, Araque Marín P, Bedoya GDJ, Villegas Lanau A. Structural Predictive Model of Presenilin-2 Protein and Analysis of Structural Effects of Familial Alzheimer's Disease Mutations. Biochem Res Int 2021; 2021:9542038. [PMID: 34881055 PMCID: PMC8648483 DOI: 10.1155/2021/9542038] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Accepted: 10/21/2021] [Indexed: 12/12/2022] Open
Abstract
Alzheimer's disease manifests itself in brain tissue by neuronal death, due to aggregation of β-amyloid, produced by senile plaques, and hyperphosphorylation of the tau protein, which produces neurofibrillary tangles. One of the genetic markers of the disease is the gene that translates the presenilin-2 protein, which has mutations that favor the appearance of the disease and has no reported crystallographic structure. In view of this, protein modeling is performed using prediction and structural refinement tools followed by an energetic and stereochemical characterization for its validation. For the simulation, four reported mutations are chosen, which are Met239Ile, Met239Val, Ser130Leu, and Thr122Arg, all associated with various functional responses. From a theoretical analysis, a preliminary bioinformatic study is made to find the phosphorylation patterns in the protein and the hydropathic index according to the polarity and chemical environment. Molecular visualization was carried out with the Chimera 1.14 software, and the theoretical calculation with the hybrid quantum mechanics/molecular mechanics system from the semi-empirical method, with Spartan18 software and an AustinModel1 basis. These relationships allow for studying the system from a structural approach with the determination of small distance changes, potential surfaces, electrostatic maps, and angle changes, which favor the comparison between wild-type and mutant systems. With the results obtained, it is expected to complement experimental data reported in the literature from models that would allow us to understand the effects of the selected mutations.
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Affiliation(s)
- Alejandro Soto-Ospina
- University of Antioquia, Faculty of Medicine, Group Molecular Genetics, Medellín, Colombia
- University of Antioquia, Faculty of Medicine, Group Neuroscience of Antioquia, Medellín, Colombia
| | - Pedronel Araque Marín
- EIA University, School of Life Sciences, Research and Innovation in Chemistry Formulations Group, Envigado, Colombia
| | | | - Andrés Villegas Lanau
- University of Antioquia, Faculty of Medicine, Group Molecular Genetics, Medellín, Colombia
- University of Antioquia, Faculty of Medicine, Group Neuroscience of Antioquia, Medellín, Colombia
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Singh K, Lahiri T. An Improved Protein Surface Extraction Method Using Rotating Cylinder Probe. Interdiscip Sci 2017; 9:65-71. [PMID: 27878456 DOI: 10.1007/s12539-016-0201-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2014] [Revised: 09/07/2015] [Accepted: 09/07/2015] [Indexed: 06/06/2023]
Abstract
For extraction of information on binding sites of a protein, the commonly known geometry-based methods utilize the corresponding PDB file to extract its surface as a first step. Finally, the surface is used to find the binding site atoms. As shown in this paper work, since none of the mostly used surface extraction methods can retrieve a sizeable percentage of the binding site atoms, the scope of development of a better method remains. In this direction, this paper presents a new benchmarking criteria based on utilization of binding site information to compare performance of these surface extraction methods. Also, a new surface extraction method is introduced based on the use of a rotating cylinder probe adapting from the work of Weisel et al. (Chem Cent J 1:7-23, 2007. doi: 10.1186/1752-153X-1-7 ). The result of the new method shows a significant improvement of performance in comparison to the existing methods.
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Affiliation(s)
- Kalpana Singh
- Division of Applied Science, Indian Institute of Information Technology, Jhalwa Campus, Allahabad, UP, 211012, India
| | - Tapobrata Lahiri
- Division of Applied Science, Indian Institute of Information Technology, Jhalwa Campus, Allahabad, UP, 211012, India.
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