# Calculating Dynamic Ensembles of Intrinsically Disordered Proteins

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA BERKELEY · 2020 · $251,770

## Abstract

The traditional structure-function paradigm has provided significant insights for well-folded proteins in which
structures can be easily and rapidly revealed by X-ray crystallography beamlines and NMR. However
approximately one third of the human proteome are comprised of intrinsically disordered proteins and regions
that do not adopt a dominant well-folded structure, and therefore remain “unseen” by traditional structural
biology methods. Current experimental and computational approaches to structural descriptions of disordered
proteins, while often valuable, still lack predictive power, particularly for dynamic complexes of IDPs, as well as
lack of insight into the relationships between IDP structural ensembles and function. This is because IDPs
require an unprecedented level of integration of multiple and complementary solution-based experiments,
state-of-the art molecular simulations to provide realistic and relevant models for IDP ensembles, selection of
the best ensembles via Bayesian probabilistic approaches given the underdetermined nature of the problem,
and comprehensive analysis to connect observed dynamic structure with function relevant to the biological
questions being addressed. We propose the development of IDP Calculator, which will (1) quantify the
usefulness and information content of a large set of experimental data types such as chemical shifts, scalar
couplings, RDCs, NOEs, PREs, and FRET/FCS; (2) use a variety of advanced atomistic and coarse-grained
models and sampling methods for generating candidate ensembles of IDP and their complexes; (3) apply new
Bayesian models for IDP ensemble selection that both evaluates and optimizes the candidate ensembles with
the best experimental data types; and (4) create a software suite that will integrate these methods along with
tools to perform correlative analysis of structural, sequence, binding and other functional data on a wide range
of IDP problems. The computational approaches to be developed will advance the characterization of structural
ensembles for proteins with intrinsic disorder, not only for the free monomer, but with emphasis on IDP
complexes. We will develop and validate our approaches on a wide range of systems: the dynamic complex of
Sic1:Cdc4 that regulates the yeast cell cycle, complexes formed between protein phosphatase 1 and its
disordered regulators that control diverse cellular processes, and monomeric and phase-separated FUS and
TDP-43 IDPs important for understanding the dynamic intermolecular contacts leading to biological phase
separation and ALS-associated aggregation.

## Key facts

- **NIH application ID:** 9889154
- **Project number:** 5R01GM127627-03
- **Recipient organization:** UNIVERSITY OF CALIFORNIA BERKELEY
- **Principal Investigator:** Julie Forman-Kay
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $251,770
- **Award type:** 5
- **Project period:** 2018-05-01 → 2022-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9889154

## Citation

> US National Institutes of Health, RePORTER application 9889154, Calculating Dynamic Ensembles of Intrinsically Disordered Proteins (5R01GM127627-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9889154. Licensed CC0.

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