Cracking the protein compartmentalization code with ProtGPS

Songtao Ye; Choon Leng So; Danfeng Cai

doi:10.1016/j.tibs.2025.03.008

Cracking the protein compartmentalization code with ProtGPS

Songtao Ye
, Choon Leng So
, Danfeng Cai

Bloomberg School of Public Health

Research output: Contribution to journal › Short survey › peer-review

Abstract

Cellular protein compartmentalization is essential for function, yet the mechanisms directing proteins to their correct destinations remain unclear. Recently, Kilgore, Chinn, Mikhael, and Mitnikov et al. introduced ProtGPS, an artificial intelligence (AI) model that recognizes sequence-encoded localization patterns. ProtGPS predicts condensate-targeting sequences, facilitates peptide design, and identifies pathogenic mutations disrupting protein compartmentalization.

Original language	English (US)
Pages (from-to)	369-371
Number of pages	3
Journal	Trends in biochemical sciences
Volume	50
Issue number	5
DOIs	https://doi.org/10.1016/j.tibs.2025.03.008
State	Published - May 2025

Keywords

AI protein language model
ProtGPS
biomolecular condensates
membrane-less organelles
protein compartmentalization prediction

ASJC Scopus subject areas

Biochemistry
Molecular Biology

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10.1016/j.tibs.2025.03.008

Cite this

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title = "Cracking the protein compartmentalization code with ProtGPS",

abstract = "Cellular protein compartmentalization is essential for function, yet the mechanisms directing proteins to their correct destinations remain unclear. Recently, Kilgore, Chinn, Mikhael, and Mitnikov et al. introduced ProtGPS, an artificial intelligence (AI) model that recognizes sequence-encoded localization patterns. ProtGPS predicts condensate-targeting sequences, facilitates peptide design, and identifies pathogenic mutations disrupting protein compartmentalization.",

keywords = "AI protein language model, ProtGPS, biomolecular condensates, membrane-less organelles, protein compartmentalization prediction",

author = "Songtao Ye and So, \{Choon Leng\} and Danfeng Cai",

note = "Publisher Copyright: {\textcopyright} 2025 Elsevier Ltd",

year = "2025",

month = may,

doi = "10.1016/j.tibs.2025.03.008",

language = "English (US)",

volume = "50",

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T1 - Cracking the protein compartmentalization code with ProtGPS

AU - Ye, Songtao

AU - So, Choon Leng

AU - Cai, Danfeng

PY - 2025/5

Y1 - 2025/5

N2 - Cellular protein compartmentalization is essential for function, yet the mechanisms directing proteins to their correct destinations remain unclear. Recently, Kilgore, Chinn, Mikhael, and Mitnikov et al. introduced ProtGPS, an artificial intelligence (AI) model that recognizes sequence-encoded localization patterns. ProtGPS predicts condensate-targeting sequences, facilitates peptide design, and identifies pathogenic mutations disrupting protein compartmentalization.

AB - Cellular protein compartmentalization is essential for function, yet the mechanisms directing proteins to their correct destinations remain unclear. Recently, Kilgore, Chinn, Mikhael, and Mitnikov et al. introduced ProtGPS, an artificial intelligence (AI) model that recognizes sequence-encoded localization patterns. ProtGPS predicts condensate-targeting sequences, facilitates peptide design, and identifies pathogenic mutations disrupting protein compartmentalization.

KW - AI protein language model

KW - ProtGPS

KW - biomolecular condensates

KW - membrane-less organelles

KW - protein compartmentalization prediction

UR - https://www.scopus.com/pages/publications/105001738349

UR - https://www.scopus.com/pages/publications/105001738349#tab=citedBy

U2 - 10.1016/j.tibs.2025.03.008

DO - 10.1016/j.tibs.2025.03.008

M3 - Short survey

C2 - 40180817

AN - SCOPUS:105001738349

SN - 0968-0004

VL - 50

SP - 369

EP - 371

JO - Trends in biochemical sciences

JF - Trends in biochemical sciences

IS - 5

ER -

Cracking the protein compartmentalization code with ProtGPS

Abstract

Keywords

ASJC Scopus subject areas

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