# Computational Design of Protein Structures and Complexes

> **NIH NIH R35** · UNIV OF NORTH CAROLINA CHAPEL HILL · 2022 · $791,314

## Abstract

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.

## Key facts

- **NIH application ID:** 10433948
- **Project number:** 5R35GM131923-04
- **Recipient organization:** UNIV OF NORTH CAROLINA CHAPEL HILL
- **Principal Investigator:** BRIAN A KUHLMAN
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $791,314
- **Award type:** 5
- **Project period:** 2019-06-01 → 2024-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10433948

## Citation

> US National Institutes of Health, RePORTER application 10433948, Computational Design of Protein Structures and Complexes (5R35GM131923-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10433948. Licensed CC0.

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