# Studies of the function of membrane and soluble proteins and their biophysical properties.

> **NIH NIH R35** · UNIVERSITY OF CHICAGO · 2023 · $419,639

## Abstract

Over the past 50 years, the field of biophysical chemistry has learned an enormous
amount about the relationships between the function, dynamics and folding of soluble proteins. The next stage in biological science involves addressing more complex problems on more challenging systems using increasingly sophisticated approaches augmented by computational methods. The Sosnick lab has followed this path. We are conducting studies of membrane proteins, condensates and disordered proteins. Our ability to address these topics arises in part from our expertise in the folding of soluble and more recently, membrane proteins. We build on this experience and knowledge to advance new or improve existing methods. The proposed research relies heavily on hydrogen exchange (HX), a method developed to study folding and dynamics yet possessing broad transferability to many methods. We plan to continue this approach and study the metabolite transport across a bilayer, stress-induced phase separation,
and properties of disordered proteins in addition to membrane protein folding. Many of
the projects are collaborative, leveraging our skills and interests with those of other labs,
which further supports the value of our studies.

## Key facts

- **NIH application ID:** 10552333
- **Project number:** 1R35GM148233-01
- **Recipient organization:** UNIVERSITY OF CHICAGO
- **Principal Investigator:** Tobin R Sosnick
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $419,639
- **Award type:** 1
- **Project period:** 2023-03-01 → 2028-02-29

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10552333

## Citation

> US National Institutes of Health, RePORTER application 10552333, Studies of the function of membrane and soluble proteins and their biophysical properties. (1R35GM148233-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10552333. Licensed CC0.

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