In Silico Analysis and 3D Structure Prediction of Putative UDP-Glycosyltransferase 76G1 Protein in Stevia rebaudiana MS007
In Silico Analysis and 3D Structure Prediction of Putative UDP-Glycosyltransferase 76G1
AbstractABSTRACT Stevia rebaudiana is a plant of the Asteraceae family that is used as a natural sweetener. Stevia has been shown to be safe for human consumption and has been utilised as a sweetener substitute for diabetic and obese people. In this study, the structure and gene content involved in the synthesis of putative UDP-glycosyltransferase 76G1 (UGT76G1) protein in S. rebaudiana MS007 was analyzed using an in silico method. Homologous search using blastP revealed the highest percentage of identity, score, and E-value for UDP-glycosyltransferase 76G1-like of Helianthus annuus (ID: XP_021973845.1). The presence of IPR002213 UDP-glucuronosyl/UDP-glucosyltransferase entry, which is available at locations 89bp to 246bp, was also verified by the protein family search using InterPro. MEGA-X software was used to construct a molecular phylogeny study, which revealed that this protein belongs to the Asteraceae protein family. To predict the primary, secondary, and tertiary protein structures of the putative UGT76G1 protein, the ProtParam, ExPasy, PSIPRED, and Phyre2 programmes were implemented. The putative UGT76G1 protein’s tertiary structure prediction was given a score of 100.0% confidence by the single highest scoring template and a coverage of 98% with the dimension of the model being (Å) of X: 52.453, Y: 61.270, and Z: 48.102. The UGT76G1model fulfilled the quality standards and was approved for further analysis after validation performed by PROCHECK, VERIFY3D, and ERRAT. Thus, the findings of this work have contributed to a better knowledge of putative UDP-glycosyltransferase 76G1 features and target recognition processes, which will lead to a better information of protein-protein interaction in S. rebaudiana MS007. Keywords: Phylogenetic, Stevia rebaudiana, UGT76G1, 3D Structure Prediction
Copyright (c) 2022 Nor Iswani Mokthar, Muhammad Amirul Husni Samsulrizal, Afiqah Ramatullah Khan, Zarina Zainuddin, Tamil Chelvan Meenakshi Sundram, Nik Yusnoraini Yusof, Nurul Hidayah Samsulrizal
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