Research Spotlight: Meiler Lab
RosettaCM drives computational modeling for antibody regions with high variability
Structural information on antibody-antigen interactions is a crucial resource for understanding antibody-mediated immunity, but experimental structural information is often elusive and time-consuming to acquire. Computational modeling of antibodies and their docking to antigens has therefore become an important driver in antibody and vaccine design. The Meiler group recently published findings in the journal Proteins comparing the different computational protocols for predicting antibody structure from sequence in the biomolecular modeling software Rosetta. The three protocols, RosettaAntibody, AbPredict and RosettaCM, all use multiple existing antibody structures to guide modeling, though the latter two were developed solely for antibodies.
The paper found that, especially in the case of modeling long HCDR3 regions, the general protocol RosettaCM outperformed the other two protocols. These Heavy chain Complementarity Defining Regions are formed by gene recombination, and their structural diversity makes them resistant to classification. Using a strategy based on combining sparse templates with fragment insertion rather than picking single templates or de novo modeling, RosettaCM was found to improve the results for structure prediction, especially in cases when the loops were long and the template availability was limited. The multi-template method using RosettaCM performed comparably to AbPredict and improved slightly on results from RosettaAntibody when modeling the entire variable region backbone. The paper concludes that in cases where template availability is sparse, such as when long HCDR3s are present, an approach involving multiple protocols and building a consensus model is likely to give the best results.
This project was part of the Vanderbilt Program for Next Generation Vaccines to integrate big data and structural biology into the design pipeline for new vaccines and therapeutic antibodies. It was led by Pranav Kodali, a Vanderbilt undergraduate student and Max Kade Fellow working in the Meiler group. Pranav is now on his way to medical school at the University of Pennsylvania. ~Swati Balakrishnan
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