# Laws of mechanics and function in proteins as evolved molecular machines

> **NIH NIH F32** · UNIVERSITY OF CHICAGO · 2021 · $68,562

## Abstract

PROJECT SUMMARY/ABSTRACT
The adaptive immune system has evolved to remember primary exposures to specific antigens and launch
effective attacks to subsequent exposures. However, rapidly evolving viruses like influenza and HIV present
new challenges to the human immune system as they mutate, making them harder to recognize and respond
to during subsequent exposures. In order for secondary responses to these pathogens to succeed, the primary
response must generate a memory response that balances specificity to the original antigen with diversity
against the multitude of possible variants of subsequent exposures. For an individual of a given species
interacting with other individuals within a larger population, the efficacy of a given balance between specificity
and diversity depends on a number of factors, including how likely the individual is to be exposed to the same
pathogen in the future, the rate at which the antigen is mutating, and constraints on the biological processes
which control the generation of immunological memory within that species. This research program aims to
construct a theoretical framework for characterizing the benefits and trade-offs associated with diversity in the
adaptive immune response and the mechanisms by which said diversity is generated. This study will then use
computational analyses of several datasets to evaluate the extent to which the antibody responses of different
species generate levels of diversity which are well-adapted to their biological needs, using mice and humans
as representative examples.

## Key facts

- **NIH application ID:** 10459896
- **Project number:** 3F32GM134721-02S1
- **Recipient organization:** UNIVERSITY OF CHICAGO
- **Principal Investigator:** Lauren McGough
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $68,562
- **Award type:** 3
- **Project period:** 2019-09-01 → 2022-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10459896

## Citation

> US National Institutes of Health, RePORTER application 10459896, Laws of mechanics and function in proteins as evolved molecular machines (3F32GM134721-02S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10459896. Licensed CC0.

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