ABI Innovation: Robotics-inspired modeling & design of proteins

University Of California-San Francisco, San Francisco CA

Investigators

Abstract

This research will permit researchers to design proteins that have new functions, using software tools that improve the success of the production process. By testing and improving the design steps it will also allow researchers and engineers to produce proteins that have functions more complex than could be made before: these new activities have enormous potential to advance basic research and biotechnology. Proteins perform a vast array of complex and important functions in cells and in technology settings: they can speed up the rate of chemical reactions by several hundred fold, they are responsible for how cells communicate, and they are the basic material for building cell structures and tissues. The advantages to designing proteins instead of using those already known include being able to modify what by-products are made so that there is less damage to the environment, make low-toxicity sensors that can probe the action of living cells in real time, and create unique materials that form defined structures at the nanoscale. To ensure the methods are widely available, all approved computational methods will be available as source code via the Rosetta software suite. This software is free of charge for academic users, and is commonly licensed by biotechnology and pharmaceutical companies. The new methods developed under this grant will also be used in classrooms for team-based projects and for interdisciplinary research activities that emphasize collaboration between students in the biological and physical/engineering sciences. This research aims to address a principal barrier in computational protein design: the lack of computational approaches that predict both sequence and structural changes with sufficient accuracy. Design methods change the protein sequence but in the vast majority of cases allow only minimal structural adjustments. Yet conformational changes not captured by current methods are the rule rather than the exception, and a main reason for failed designs. Moreover, new conformations might be required to engineer new functions, e.g. to reshape an existing functional site to accommodate a different binding partner. Finally, many proteins undergo functional conformational changes, such as molecular switches or enzymes and protein machines that cycle between conformational states; such complex activities are currently not designable. Aim 1 seeks to advance methods to model changes in protein structure, and address challenges in both generating relevant protein conformations and distinguishing correct from incorrect predictions; established and new benchmarks will be used to assess limitations and quantify improvements. Aim 2 will develop an approach to design new functions that require substantial changes in protein conformation. The approach will be tested by experimental forward-engineering applications. Aim 3 will provide "protocol capture" documentation for tested methods and utilize developed methods in educational and research activities that seek to broaden participation. Validated methods will be available as source code via https://www.rosettacommons.org.