Robustification of RosettaAntibody and Rosetta SnugDock

Area of Science:

• Structural biology
• Immunoinformatics
• Computational biophysics

Background:

• High-throughput sequencing has vastly increased antibody sequence data, creating a sequence-structure gap.
• Experimental structure determination remains low-throughput, hindering structural analysis of antibodies.

Purpose of the Study:

• To report advances in RosettaAntibody and Rosetta SnugDock for antibody structure prediction and antigen docking.
• To enhance the robustness, speed, ease of use, and accuracy of computational antibody modeling.

Main Methods:

• Simplified user interface and automated template database expansion.
• Generalized antibody-antigen docking kinematics to include single-domain antibodies.
• Incorporated new loop modeling techniques and developed a rigorous benchmarking framework within Rosetta.

Main Results:

• Updated RosettaAntibody identified more structurally similar templates.
• Rosetta SnugDock demonstrated broadened applicability without loss of accuracy.
• Benchmarking confirmed improvements in antibody modeling and docking capabilities.

Conclusions:

• Recent updates to RosettaAntibody and Rosetta SnugDock enhance computational antibody modeling.
• Further improvements in CDR-H3 loop modeling accuracy and speed are necessary for comprehensive antibody modeling.