COMPUTATIONAL DOCKING AND FUNCTIONAL PREDICTION OF UNCHARACTERIZED PROTEINS FROM WHITE YAM (DIOSCOREA ROTUNDATA) THROUGH STRUCTURAL ANALYSIS

White yam (Dioscorea rotundata) is an important food crop, yet many of its proteins remain uncharacterized. This study used computational methods to predict the structure and possible functions of selected uncharacterized proteins from D. rotundata. Protein sequences were retrieved from online databases and their 3D structures were predicted using AlphaFold. The models were validated using standard structural quality tools. Active and allosteric sites were identified through pocket and residue analysis. A set of biologically relevant ligands—including ATP, NADH, amino acids, and plant defense molecules such as salicylic acid and jasmonic acid—were used for molecular docking with AutoDock Vina. Docking results showed different binding affinities and interaction patterns, suggesting that the proteins may play roles in metabolism, catalysis, stress signaling, or regulatory processes. Overall, the study demonstrates that structural modeling and docking can help predict the potential functions of unknown yam proteins and provide a foundation for future experimental studies.