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The cytolethal distending toxin (CDT), Haemophilus ducreyi, is one of the bacterial toxins that have recently been considered for targeted therapies, especially in cancer therapies. CDT is an A-B2 exotoxin. Its catalytic subunit (CdtB) is capable of inducing DNA double strand breaks, cell cycle arrest and apoptosis in host eukaryotic cells. The sequence alignment indicates that the CdtB is structurally homologyr to phosphatases and deoxyribonucleases I (DNase I). Recently, it has been found that CdtB toxicity is mainly related to its nuclease activity. The immunogenicity of CDT can reduce its effectiveness in targeted therapies. However, the toxin can be very useful if its immunogenicity is significantly reduced. Detecting hotspot ectopic residues by computational servers and then mutating them to eliminate B-cell epitopes is a promising approach to reduce the immunogenicity of foreign protein-based therapeutics. By the mentioned method, in this study, we try to reduce the immunogenicity of the CdtB- protein sequence. This study initially screened residue of the CdtB is B-cell epitopes both linearly and conformationally. By overlapping the B-cell epitopes with the excluded conserve residues, and active and enzymatic sites, four residues were allowed to be mutated. There were two mutein options that show reduced antigenicity probability. Option one was N19F, G74I, and S161F with a VaxiJen score of 0.45 and the immune epitope database (IEDB) score of 1.80, and option two was N19F, G74I, and S161W with a VaxiJen score of 0.45 and IEDB score of 1.88. The 3D structure of the proposed sequences was evaluated and refined. The structural stability of native and mutant proteins was accessed through molecular dynamic simulation. The results showed that the mutations in the mutants caused no considerable changes in their structural stability. However, mutant 1 reveals more thermodynamic stability during the simulation. The applied approaches in this study can be used as rough guidelines for finding hot spot immunogen regions in the therapeutic proteins. Our results provide a new version of CdtB that, due to reduced immunogenicity and increased stability, can be used in toxin-based drugs such as immunotoxins.
Pubmed ID: 34822569 RIS Download
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Collection of data of protein sequence and functional information. Resource for protein sequence and annotation data. Consortium for preservation of the UniProt databases: UniProt Knowledgebase (UniProtKB), UniProt Reference Clusters (UniRef), and UniProt Archive (UniParc), UniProt Proteomes. Collaboration between European Bioinformatics Institute (EMBL-EBI), SIB Swiss Institute of Bioinformatics and Protein Information Resource. Swiss-Prot is a curated subset of UniProtKB.
View all literature mentionsWeb application for sequence analysis and the prediction of protein structure and function. The user interface intakes protein sequences or alignments and returned multiple sequence alignments, motifs, and nuclear localization signals.
View all literature mentionsSoftware tool as fully automated protein structure homology modeling server, accessible via ExPASy web server, or from program DeepView Swiss Pdb-Viewer. Structural bioinformatics web-server dedicated to homology modeling of 3D protein structures. Used to make protein modelling accessible to all biochemists and molecular biologists.
View all literature mentionsWeb server for prediction of protective antigens, tumor antigens and subunit vaccines. Alignment free approach for antigen prediction, which is based on auto cross covariance transformation of protein sequences into uniform vectors of principal amino acid properties.
View all literature mentionsWeb server to predict discontinuous B cell epitopes from protein three dimensional structures.
View all literature mentionsWeb service is extension of classic ProSA program used for refinement and validation of experimental protein structures and in structure prediction and modeling.
View all literature mentionsWeb tool to predict linear antigenic epitopes. Predicts antigenic epitope with latest sequence input from IEDB database. Method to predict antigenic epitopes using support vector machine to integrate Tri-Peptide similarity and propensity.
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