CAREER: A Computational Design Approach for Predicting and Reengineering Plasticity and Selectivity in Protein-protein Interfaces

University Of California-San Francisco, San Francisco CA

Investigators

Abstract

The overall research objective of this CAREER project is to develop and assess improved computational modeling and design approaches focused on protein-protein interactions, to facilitate engineering of selective molecules to characterize, perform and control biological functions. In Aim 1, a model will be developed that will allow to optimize the fitness of a protein sequence for multiple selective criteria, such as binding to preferred partners while simultaneously avoiding unwanted interactions. In Aim 2, methods to more accurately model changes in protein conformation in response to binding events and designed mutations will be improved and evaluated. These models will be used to predict not only the optimal sequence, but also sets of tolerated sequences that capture the observed sequence, conformational and functional plasticity of protein-protein interactions. This research will build foundational approaches to quantitatively characterize plasticity and selectivity of protein interfaces. A practical outcome of this work will be a computational method to design sequence libraries and provide testable predictions for new proteins that are precise enough to have the desired function within complex biological environments. Computational methods developed under this project will be employed in teaching activities, integrating research and educational aims to introduce graduate, undergraduate and high-school students to structure-based biological engineering. As part of a new core graduate curriculum in Quantitative Biology, lecture-based, project-planning and hands-on practical course modules in protein biocomputing will be designed to teach a foundational understanding of current capabilities and limitations of modeling, and an appreciation of opportunities resulting from tight integration of theory and experiment. Project planning and practical units will emphasize multidisciplinary approaches allowing students with experimental and theoretical backgrounds to learn from each other. Undergraduate and high-school students will carry out summer projects in protein design and synthetic biology. New and improved computational methods will be disseminated broadly via the Rosetta package of computational tools that is available free-of-charge to academic users.