LYRA, a webserver for lymphocyte receptor structural modeling.

Area of Science:

• Immunology
• Structural Biology
• Bioinformatics

Background:

• Accurate structural modeling of B- and T-cell receptors is crucial for understanding immune mechanisms and developing novel therapeutics.
• Existing methods for receptor modeling can be complex and time-consuming, limiting accessibility for researchers.

Purpose of the Study:

• To introduce LYRA, a novel, automated web server for the structural modeling of B- and T-cell receptors.
• To provide a user-friendly and efficient tool for generating 3D receptor models from amino acid sequences.

Main Methods:

• LYRA utilizes an automated pipeline including sequence alignment, hypervariable loop structural class prediction, and template selection based on the canonical structure method.
• The server allows for both fully automated modeling and manual adjustments by experienced users.

Main Results:

• LYRA successfully generates complete 3D structural models of B- and T-cell receptors rapidly and accurately.
• Benchmarking demonstrates an average Root Mean Square Deviation (RMSD) accuracy of 1.29 Å for B-cell receptors and 1.48 Å for T-cell receptors.
• LYRA is the first automated server specifically designed for T-cell receptor (TCR) structure prediction.

Conclusions:

• LYRA offers a valuable, accessible, and automated solution for B- and T-cell receptor structural modeling.
• The server facilitates advancements in immunology research and the development of targeted therapies by providing accurate structural insights.