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DC Field | Value | Language |
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dc.contributor.author | Nelapati, A.K. | - |
dc.contributor.author | Das, B.K. | - |
dc.contributor.author | Ponnan, Ettiyappan, J.B. | - |
dc.contributor.author | Chakraborty, D. | - |
dc.date.accessioned | 2020-03-31T08:35:29Z | - |
dc.date.available | 2020-03-31T08:35:29Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Process Biochemistry, 2020, Vol., , pp.- | en_US |
dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/11719 | - |
dc.description.abstract | The clinical utilization of Uricase against gout is limited due to the immunogenicity. In the present article, we identified the antigenic determinants of Uricase and reduced their immunogenicity via in-silico mutagenesis. Multiple sequence alignment and motif analysis were carried out to identify the conserved residues in evolutionary process. Emini surface accessibility, Parker hydrophilicity, and Karplus & Schulz flexibility methods were employed to predict the linear B-cell epitopes of both Ag-Uricase and Bf-Uricase. Deimmunization approach identified T-cell epitopes and the hot spot residues. Reduced antigenic probability was obtained in case of T159W, D169C, N264W and Y203D mutations for Ag-Uricase, while S139 V, K215W, G216 F and I172 P mutations for Bf-Uricase. The binding affinity values of uric acid towards the catalytic pocket of Ag-Uricase and Bf-Uricase models were found to be -48.71 kcal/mol and -40.93 kcal/mol, respectively. This energy is further stabilized in the mutant model by -6.36 kcal/mol and -1.45 kcal/mol for Ag-Uricase and Bf-Uricase, respectively. About 100 ns molecular dynamics simulation was performed to evaluate the conformational stability of both native and mutated Uricase. Insights obtained from this study provide guidelines for experimental design of Uricase muteins with reduced antigenicity. 2020 Elsevier Ltd | en_US |
dc.title | In-silico epitope identification and design of Uricase mutein with reduced immunogenicity | en_US |
dc.type | Article | en_US |
Appears in Collections: | 1. Journal Articles |
Files in This Item:
File | Description | Size | Format | |
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3 In-silico epitope identification.pdf | 5.21 MB | Adobe PDF | View/Open |
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