Computational Design of Protein Structures and Complexes

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Project Summary/Abstract Protein design is a rigorous test of our understanding of protein structure and stability and can be used to create proteins that have important applications in research and medicine. This project focuses on three topics in computer-based protein design: (1) the design of protein–protein interfaces, (2) de novo protein design, and (3) development of the molecular modeling program Rosetta. Protein–protein interactions are essential to almost all biological processes. We have developed new adaptive sampling strategies within Rosetta for designing interaction surfaces between protein domains that do not naturally interact. We will continue to improve this method while testing it on diverse design goals such as engineering autoinhibitory domains to regulate the activity of anti-cancer therapeutics and enhancing enzyme activity via the incorporation of substrate recognition domains. Our second area of focus is de novo protein design, and more particularly, an approach that we call requirement-driven protein design, in which the goal is to create well-folded proteins that match a set of user- defined requirements. To perform requirement-driven protein design, we have created a computational method called SEWING for designing proteins from pieces of naturally occurring proteins. We will explore a variety of design requirements with SEWING, including the incorporation of ligand-binding sites and protein interaction motifs. The third area of concentration for this project is the improvement and maintenance of the molecular modeling software Rosetta. We will continue long-standing activities aimed at supporting the large community of Rosetta developers and users. These include running Rosetta “boot camps” that teach people how to code in the Rosetta environment and spearheading code-cleanup activities to improve the extensibility of the software. In addition, we will develop new approaches for rapidly calculating the energy of a protein and create core methods that will allow the community to take better advantage of hardware advances in GPUs. In sum, by pursuing this project, we will expand the capabilities of computational protein design and create molecules that can be used to understand or treat disease.