Optimization in Protein Structure and Function Prediction of Silk of Tasar Silkworm, Antheraea mylitta Drury
Ananda Rukmini
RamaDevi Women’s University, Bhubaneswar, Odisha, India and DST-Sericulture Laboratory, Post Graduate Department of Zoology, Shailabala Women’s Autonomous College, Cuttack, Odisha, India.
Priti Pragyan Ray
*
DST-Sericulture Laboratory, Post Graduate Department of Zoology, Shailabala Women’s Autonomous College, Cuttack, Odisha, India.
Purushottam Dash
SERIFED, Directorate of Textiles, Government of Odisha, India.
*Author to whom correspondence should be addressed.
Abstract
Protein structure and function prediction is an arduous task in computational biology. Understanding the structure of protein facilitates in understanding its function. The Tasar silkworm, Antheraea mylitta Drury, is a vital species in sericulture, producing high-quality silk fibres with unique properties. Beyond its economic significance, the Tasar silkworm is a model organism for studying insect biology, development, and evolution. Despite recent advances in genomics and proteomics, which have enabled the exploration of the Tasar silkworm proteome, there still exist hitches in the atomic accuracy of its protein structure prediction in the era of deep learning. Here, we endeavour to bridge the existing knowledge gap of algorithmic modelling techniques, especially deep neural networks in protein prediction methods of this valuable lepidopteran, leading to a better understanding of its biological processes and potential applications.
Keywords: Optimization, protein structure and function, algorithmic modeling, deep neural network