RosettaAntibody: antibody variable region homology modeling server.

Area of Science:

• Structural biology
• Computational biology
• Immunology

Background:

• Antibody structure prediction is crucial for understanding immune responses and developing therapeutics.
• Accurate modeling of antibody variable regions, including complementarity determining regions (CDRs), is essential for predicting antigen binding.

Purpose of the Study:

• To introduce RosettaAntibody, a web server for predicting antibody variable region structures.
• To provide users with both crude and high-resolution antibody models based on sequence data.

Main Methods:

• The server utilizes sequence homology to identify template structures for framework and CDR regions.
• A crude model is assembled from homologous templates and optimized.
• A high-resolution model is generated using the RosettaAntibody protocol, including CDR H3 loop modeling and optimization of steric clashes.

Main Results:

• RosettaAntibody provides sequence-based prediction of antibody variable region structures.
• The server generates 2000 independent structures, returning the top 10 models with scoring information.
• High-resolution models have been successfully applied to predict antibody-antigen complex structures.

Conclusions:

• RosettaAntibody is a valuable tool for researchers needing antibody structure predictions.
• The generated models facilitate rational selection and ensemble studies, aiding in antibody engineering and drug discovery.