Intrinsically disordered proteins and disordered regions (collectively termed IDPs) perform vital biological functions in transcriptional regulation, cell differentiation, and DNA condensation. IDPs rapidly interconvert between different conformations, imparting plasticity, forming transient contacts and promoting allostery. IDPs also participate in phase transitions, forming liquid droplets. The droplets facilitate diverse biological processes that require localization in different regions in the cell. Yet, principles for understanding how a protein's sequence shapes its ensemble of disordered conformations to perform its function and to promote phase separation are still lacking. While the simple metric of amino acid composition explains broad conformational features (radius, scaling exponents) and trends, minor variations in sequence, caused by post-translational modifications (PTMs)/mutations can drastically alter disordered conformations and their functions. IDPs also elude traditional sequence alignment tools to classify functionally similar proteins across species. We propose to build a novel computational framework based on physico-chemical principles to describe the ensemble of disordered conformations for IDPs with arbitrary sequence. To understand how PTMs/mutations couple with diverse solution conditions to alter IDP conformation and the propensity of IDPs to phase separate, we need computationally efficient models. The models must be capable of handling the combinatorial challenge of analyzing multiple sequences and their variants due to preferential mutations/modifications, alternate splicing under diverse conditions. The same challenge is faced when seeking evolutionary signatures of multiple sequences across different species. An integrated approach combining polymer physics, all-atom simulation, and multiple experiments will build coarse-grain models for such high-throughput analysis. The proposed theoretical approach will i) provide guidance to determine how IDP conformations differ in vitro and in vivo, ii) harness limited data (smFRET between specific probes) to make predictions for distances between arbitrary residue pairs and iii) build a rigorous framework for comparing residue-pair specific interaction parameters between different force fields and experiments, and suggest improvements, if needed. The computationally efficient formalism will be applied at a large scale to provide a detailed description of conformational ensembles, including residue-pair specific distance maps (beyond simple observables as radius of gyration, end-to-end-distance, scaling exponents) for sets of disordered proteins to understand functional similarities/dissimilarities, not possible by sequence alignment alone. The formalism will also quantify IDP's susceptibility to chemical modifications/mutations, and environmental changes (pH, salinity) to alter conformations, function and promote or suppress phase separation propensities in IDP solutions.

Public Health Relevance

We propose to develop a novel theoretical framework using mathematical modelling, all-atom simulation and experimental data (in-vitro and in-vivo) to understand sequence-conformation-function relation in disordered proteins. Our work is of biomedical relevance due to its importance in understanding fundamental principles that biology relies on to alter conformation of Intrinsically Disordered Proteins that constitute a large fraction of human proteome and perform great many vital biological functions. Strategies learnt from the work will help design new sequences to control function of these proteins with potential for therapeutic application.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
1R01GM138901-01
Application #
10034318
Study Section
Macromolecular Structure and Function D Study Section (MSFD)
Program Officer
Lyster, Peter
Project Start
2020-08-01
Project End
2025-06-30
Budget Start
2020-08-01
Budget End
2021-06-30
Support Year
1
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of Denver
Department
Physics
Type
Schools of Arts and Sciences
DUNS #
007431760
City
Denver
State
CO
Country
United States
Zip Code
80210