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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Molecular Plant Pathology Laboratory » Research » Publications at this Location » Publication #434626
Research Project: Developing Biotechnologies to Improve Pest and Pathogen Resistance, Yield, and Quality in Sugarbeet

Location: Molecular Plant Pathology Laboratory

Title: Predicted protein-protein interactions between sugar beet root maggot trypsins and sugar beet Kunitz trypsin inhibitors using deep learning

Author
item LEE, YERANG - Towson University
item RAHIM, SIDRA - Towson University
item ALKHAROUF, NADIM - Towson University
item Chu, Chenggen
item Klink, Vincent

Submitted to: Data in Brief
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/22/2026
Publication Date: 6/27/2026
Citation: Lee, Y., Rahim, S.S., Alkharouf, N.W., Chu, C.N., Klink, V.P. 2026. Predicted protein-protein interactions between sugar beet root maggot trypsins and sugar beet Kunitz trypsin inhibitors using deep learning. Data in Brief. 67. Article e113020. https://doi.org/10.1016/j.dib.2026.113020.
DOI: https://doi.org/10.1016/j.dib.2026.113020

Interpretive Summary: Sugar beet is one of only two plants in the world from which significant amounts of raw sugar is produced. In the U.S. its value is $1 billion with a global value of $4.6 B. In North America, the sugar beet root maggot (SBRM) is the most devastating sugar beet pathogen, decreasing production by up to 100%. The recently sequenced sugar beet root maggot genome has been used to identify proteins it uses to infect sugar beet. The analysis has identified a trypsin family of proteins shown to interact with sugar beet proteins known as trypsin inhibitors that have protective value to the plant, possibly preventing infection. The research shows the developed public genome database information aids in SBRM genetic and extension scientist partnerships with stakeholders and growers.

Technical Abstract: Sugar beet ( Beta vulgaris ssp. vulgaris), SB, is one of two plants from which sugar is broadly extracted, annually ac- counting for 55% of U.S. sugar ($1B, U.S.), and 35% global raw sugar ($4.6B). The sugar beet cDNA DV501688, encoding a serine threonine protease inhibitor (Bv STI) was shown to have increased relative transcript abundance in sugar beet during a resistant reaction to the Dipteran sugar beet root maggot, Tetanops myopaeformis SBRM, pest. BLASTp searches of the sugar beet proteome identified 21 additional proteins, each having homology to Kunitz trypsin inhibitors (KTIs) with Bv STI annotated as Bv KTI1. Prior deep learning analyses predicted that Bv KTI1 bound each of the 9 T. myopaeformis trypsins in the predicted binding loop region located between ß-strands 4 and 5 of KTI proteins. The identification of 21 additional Bv KTI proteins suggested the plant-insect pest interaction may be more complex, requiring further analysis. The deep learning analysis presented here, using AlphaFold, suggests the different Bv KTIs may not be equally effective in binding the T. myopaeformis trypsins. Bv KTI13 is predicted to have intermediate capabilities to bind T. myopaeformis trypsins, having predicted binding for some and lacking predicted binding for the others. However, the AlphaFold-based results are predictive and not scientific justification/evidence.