# Computational design of proteins and protein functions

> **NIH NIH R35** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2022 · $336,208

## Abstract

PROJECT SUMMARY/ABSTRACT
Our long-term goals are to advance computational protein design to engineer new biological functions and
molecular/cellular engineering strategies to uncover principles of biological regulation. This proposal combines
our two NIGMS grants in these areas.
In our work on computational protein design, we have computationally engineered proteins that sense and
respond to new small molecule signals in cells, a capability with important applications in metabolic engineering,
diagnostics, bioremediation, and probing fundamental cellular processes. We have also advanced methods to
design proteins with precisely tunable shapes entirely de novo. The proposed work builds on our new methods
to address a central unsolved challenge, to simultaneously design the geometries of de novo proteins and user-
defined functional sites placed into them with atomic accuracy optimized for function. This work should greatly
expand the space of new functions that can be designed. We plan to integrate de novo designed proteins into
modular systems that can control biological behavior in response to new signals.
Our work on natural protein functions seeks to understand how central regulatory proteins operate in
interconnected cellular networks, and how these networks are altered upon perturbations such as mutations.
We studied a two-state switch (a GTPase) controlled by opposing regulators because this motif is prevalent in
biology. Through systematic mutagenesis of the GTPase Gsp1 and integrating measurements at the systems
scale (genetic interaction mapping) with biophysics, we uncovered previously unknown allosteric sites on the
GTPase central to its function. Our findings moreover suggest a new model how the pleiotropic GTPase Gsp1
differentially regulates distinct cellular functions. Here we will build on these results to investigate the mechanism
of allostery in Gsp1 and assess its generality in other GTPases, with implications for understanding mechanisms
of disease mutations and for development of modulators. We also plan to test our model of GTPase regulation
by determining quantitative cellular consequences of fine-tuned perturbations to GTPases regulators. Future
directions include expansion of these perturbation measurements to other central biological switches. The
uncovered principles of cellular control can guide cellular engineering, and in conjunction with computationally
designed new functions may ultimately lead to new ways to counteract misregulation in disease.

## Key facts

- **NIH application ID:** 10406129
- **Project number:** 1R35GM145236-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Tanja Kortemme
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $336,208
- **Award type:** 1
- **Project period:** 2022-07-01 → 2027-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10406129

## Citation

> US National Institutes of Health, RePORTER application 10406129, Computational design of proteins and protein functions (1R35GM145236-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10406129. Licensed CC0.

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