Connecting Coil-to-Globule Transitions to Full Phase Diagrams for Intrinsically Disordered Proteins.

Journal Article (Journal Article)

Phase separation is thought to underlie spatial and temporal organization that is required for controlling biochemical reactions in cells. Multivalence of interaction motifs, also known as stickers, is a defining feature of proteins that drive phase separation. Intrinsically disordered proteins with stickers uniformly distributed along the linear sequence can serve as scaffold molecules that drive phase separation. The sequence-intrinsic contributions of disordered proteins to phase separation can be discerned by computing or measuring sequence-specific phase diagrams. These help to delineate the combinations of protein concentration and a suitable control parameter, such as temperature, that support phase separation. Here, we present an approach that combines detailed simulations with a numerical adaptation of an analytical Gaussian cluster theory to enable the calculation of sequence-specific phase diagrams. Our approach leverages the known equivalence between the driving forces for single-chain collapse in dilute solutions and the driving forces for phase separation in concentrated solutions. We demonstrate the application of the theory-aided computations through calculation of phase diagrams for a set of archetypal intrinsically disordered low-complexity domains. We also leverage theories to compute sequence-specific percolation lines and thereby provide a thermodynamic framework for hardening transitions that have been observed for many biomolecular condensates.

Full Text

Duke Authors

Cited Authors

  • Zeng, X; Holehouse, AS; Chilkoti, A; Mittag, T; Pappu, RV

Published Date

  • July 2020

Published In

Volume / Issue

  • 119 / 2

Start / End Page

  • 402 - 418

PubMed ID

  • 32619404

Pubmed Central ID

  • PMC7376131

Electronic International Standard Serial Number (EISSN)

  • 1542-0086

International Standard Serial Number (ISSN)

  • 0006-3495

Digital Object Identifier (DOI)

  • 10.1016/j.bpj.2020.06.014

Language

  • eng