In silico characterization of selected orchids related protein - Nur Izzatul Shahira, Zulkifli (2025)
This study are focusing on in silico characterization of selected orchid’s glycosaminoglycan - related proteins in which to identify the catalytic regions of selected orchids’. The orchids are a complex and extensive flowering plant family classified scientifically as Orchidaceae. They constitute one of the largest flowering plant families, with approximately 25,000 species and 100,000 hybrids and cultivars. Orchids are valued for their intricate, vivid blossoms and are frequently linked with beauty, elegance, and foreignness. Moreover, glycosaminoglycan or (GAGs) is a long, unbranched polysaccharides composed of repeating disaccharide units. The selected orchid’s that been selected is Vanda Tan Chay Yan, Phalaenopsis equestris, Dendrobium nobile, Dendrobium catenatum and Apostasia shenzhenca. All selected orchids had been chose to do predicted 3D - protein structure by using homology modelling in which the use of online software tools such as Pyrx, SWISS - MODEL, Bioedit, CASTp, SAVEs6.0SERVER, BLASTp, Chimera 1.16 and PyMOL. Three online tools (Verify 3D, Procheck, and ERRAT) are used to analyze the quality of 3D - protein structures. The most suitable models of proteins are then selected through refinement. The Pyrx platform's Autodock Vina software was used to dock interactions between protein and ligand and compare them to CASTp's predicted active site pocket analysis. Chimera software was used to visualize the ligand - binding orientation. All of the online software tools had been using to generate the potential 3D model of selected orchids, it also used to Molecular docking will be used to study the binding sites of possible ligands to the 3D structure of a glycosaminoglycan - related protein from chosen orchids. In this research, there are three type of ligands that been identify which is keratin sulphate, heparin sulphate and chondroitin sulphate and the ligands were separated with different colours to easy identifying of their attachment. Overall, it is a success to generate the predicted molecular docking.