Active learning of the thermodynamics-dynamics trade-off in protein condensates.
Sci Adv
; 10(1): eadj2448, 2024 Jan 05.
Article
de En
| MEDLINE
| ID: mdl-38181073
ABSTRACT
Phase-separated biomolecular condensates exhibit a wide range of dynamic properties, which depend on the sequences of the constituent proteins and RNAs. However, it is unclear to what extent condensate dynamics can be tuned without also changing the thermodynamic properties that govern phase separation. Using coarse-grained simulations of intrinsically disordered proteins, we show that the dynamics and thermodynamics of homopolymer condensates are strongly correlated, with increased condensate stability being coincident with low mobilities and high viscosities. We then apply an "active learning" strategy to identify heteropolymer sequences that break this correlation. This data-driven approach and accompanying analysis reveal how heterogeneous amino acid compositions and nonuniform sequence patterning map to a range of independently tunable dynamic and thermodynamic properties of biomolecular condensates. Our results highlight key molecular determinants governing the physical properties of biomolecular condensates and establish design rules for the development of stimuli-responsive biomaterials.
Texte intégral:
1
Collection:
01-internacional
Base de données:
MEDLINE
Sujet principal:
Apprentissage par problèmes
/
Protéines intrinsèquement désordonnées
Langue:
En
Journal:
Sci Adv
Année:
2024
Type de document:
Article
Pays d'affiliation:
États-Unis d'Amérique
Pays de publication:
États-Unis d'Amérique