COMPUTATIONAL CHARACTERIZATION AND COMPARATIVE EVOLUTIONARY ANALYSIS OF AN UNCHARACTERIZED MEMBRANE-ASSOCIATED PROTEIN LOC410154 IN APIS MELLIFERA
DOI:
https://doi.org/10.63075/x52a2806Keywords:
Apis Mellifera, Computational characterization, Honey bees, Phylogenatic Analysis, EvolutionAbstract
Un characterized proteins demonstrate huge knowledge gap in modern genome studies. This gap further widens in insects’ studies such as Apis Mellifera which has economic and ecological significance. One third of its predicted proteins don’t possess functional annotation. Apis Mellifera largely contributes in production of honey, beeswax, royal jelly and pollen which benefit food, cosmetics and pharmaceutical industries. Despite much research, many proteins associated with honeybees such as Apis mellifera remained unstudied, limiting our knowledge about understanding its survival instincts and evolutionary conservation across Hymenoptera. These proteins may play important role in immunity, sensory perception, cell signaling, transportation or pathogen interaction. LOC410154 in Apis mellifera is a large (1460aa) uncharacterized protein highly found across various honeybees and wasp species with identity exceeding 80-100% but still remained functionally or structurally unstudied. To uncover its biological role, it is necessary to study its placement, predicted localization and functional properties. Domain archetechture analysis presents EGF-like and adhesion related motifs suggesting a role in cell-cell interaction. Post translational modification profile predicted numerous O-glycosylation and Phosphorylation sites implying regulatory complexity. Structural modelling using Phyre2, RoseTTAFold/Robetta, and complementary approaches supported the presence of moduler domans. Furthermore, transmembrane analysis identified eight membrane associated helices. In silico approach provides powerful opportunity to explore its characteristics and annotate it without needing any laboratory experiment. This study aims to bridge the gap by in silico characterization of LOC410154 using sequence homology, domain prediction, physiochemical properties, subcellular localization, structural analysis and phylogenetic reconstruction.