Use of Multi-template Comparative Modeling for Improving Quality of Antibody 3D Structure Prediction

Project Abstract

The Vanderbilt Program for Next Generation Vaccines aims to integrate big data and structural biology into the design pipeline for new vaccines. One crucial step in this process is the modeling of the 3D structures of antibodies from their amino acid sequences. Comparative modeling of antibodies is usually applied using only one structure as a template (single-template modeling). However, the use of multiple templates (multi-template modeling) has been shown to improve the accuracy of modeling in some cases. To evaluate whether or not multi-template comparative modeling can improve the modeling accuracy of antibodies over single-template methods, this study will compare the two modeling algorithms in cases where differences in sequence homology exist. This study will utilize known structures to evaluate the model quality. A comparison of models with the lowest scores produced by these two techniques will be used to simulate the real-world usage of the two methods. The results will help to identify the best strategy for converting antibody amino acid sequences into three-dimensional models.

Training Plan

Jens Meiler will supervise Pranav in all aspects of his research. They will meet bi-weekly to review his progress and plan the next experimental steps. If needed, Pranav can also additionally meet with Jens on short notice in the afternoons during the time when I usually meet with other students in the group. Pranav will be supervised on a day-to-day basis by a Post-Doctoral Fellow, Nina Bozhanova, who is working on related antibody-focused projects. In addition, he always will be able to get help from other experienced group members by discussing his project on topic-specific subgroup meetings or general group meetings, asking questions using online team communication tools, or setting up meetings with other lab members.

Mentors

Primary: Jens Meiler