In silico prediction of in vitro protein liquid–liquid phase separation experiments outcomes with multi-head neural attention | Zendy

Daniele Raimondi | Zendy; Gabriele Orlando | Zendy; Emiel Michiels | Zendy; Donya Pakravan | Zendy; Anna BratekSkicki | Zendy; Ludo Van Den Bosch | Zendy; Yves Moreau | Zendy; Frédéric Rousseau | Zendy; Joost Schymkowitz | Zendy

Open Access

In silico prediction of in vitro protein liquid–liquid phase separation experiments outcomes with multi-head neural attention

Author(s) -

Daniele Raimondi,

Gabriele Orlando,

Emiel Michiels,

Donya Pakravan,

Anna BratekSkicki,

Ludo Van Den Bosch,

Yves Moreau,

Frédéric Rousseau,

Joost Schymkowitz

Publication year - 2021

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btab350

Subject(s) - in silico , separation (statistics) , phase (matter) , head (geology) , liquid phase , liquid liquid , computer science , chromatography , biological system , chemistry , machine learning , biology , physics , biochemistry , thermodynamics , gene , paleontology , organic chemistry

Proteins able to undergo liquid-liquid phase separation (LLPS) in vivo and in vitro are drawing a lot of interest, due to their functional relevance for cell life. Nevertheless, the proteome-scale experimental screening of these proteins seems unfeasible, because besides being expensive and time-consuming, LLPS is heavily influenced by multiple environmental conditions such as concentration, pH and temperature, thus requiring a combinatorial number of experiments for each protein.

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