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Naslov:Amino acid sequence encodes protein abundance shaped by protein stability at reduced synthesis cost
Avtorji:ID Buric, Filip (Avtor)
ID Viknander, Sandra (Avtor)
ID Fu, Xiaozhi (Avtor)
ID Lemke, Oliver (Avtor)
ID Carmona, Oriol Gracia (Avtor)
ID Zrimec, Jan (Avtor)
ID Szyrwiel, Lukasz (Avtor)
ID Mülleder, Michael (Avtor)
ID Ralser, Markus (Avtor)
ID Zelezniak, Aleksej (Avtor)
Datoteke:URL URL - Izvorni URL, za dostop obiščite https://doi.org/10.1002/pro.5239
 
.pdf PDF - Predstavitvena datoteka, prenos (13,19 MB)
MD5: BF2CD3C7F05973F92D16F29719D6C4AC
 
Jezik:Angleški jezik
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:Logo NIB - Nacionalni inštitut za biologijo
Povzetek:Understanding what drives protein abundance is essential to biology, medicine, and biotechnology. Driven by evolutionary selection, an amino acid sequence is tailored to meet the required abundance of a proteome, underscoring the intricate relationship between sequence and functional demand. Yet, the specific role of amino acid sequences in determining proteome abundance remains elusive. Here we show that the amino acid sequence alone encodes over half of protein abundance variation across all domains of life, ranging from bacteria to mouse and human. With an attempt to go beyond predictions, we trained a manageable-size Transformer model to interpret latent factors predictive of protein abundances. Intuitively, the model's attention focused on the protein's structural features linked to stability and metabolic costs related to protein synthesis. To probe these relationships, we introduce MGEM (Mutation Guided by an Embedded Manifold), a methodology for guiding protein abundance through sequence modifications. We find that mutations which increase predicted abundance have significantly altered protein polarity and hydrophobicity, underscoring a connection between protein structural features and abundance. Through molecular dynamics simulations we revealed that abundance-enhancing mutations possibly contribute to protein thermostability by increasing rigidity, which occurs at a lower synthesis cost.
Ključne besede:molecular biology, biotechnology, bioinformatics, deep learning, gene expression, synthetic biology, protein abundance, amino acid sequence, evolutionary selection, transformer model, MGEM (Mutation guided by an embedded manifold)
Status publikacije:Objavljeno
Verzija publikacije:Objavljena publikacija
Datum objave:01.01.2025
Leto izida:2025
Št. strani:str. 1-25
Številčenje:iss. 1, [art. no.] ǂe5239
PID:20.500.12556/DiRROS-21006 Novo okno
UDK:577
ISSN pri članku:0961-8368
DOI:10.1002/pro.5239 Novo okno
COBISS.SI-ID:219372035 Novo okno
Opomba:Soavtorji: Sandra Viknander, Xiaozhi Fu, Oliver Lemke, Oriol Gracia Carmona, Jan Zrimec, Lukasz Szyrwiel, Michael Mülleder, Markus Ralser, Aleksej Zelezniak;
Datum objave v DiRROS:17.12.2024
Število ogledov:24
Število prenosov:10
Metapodatki:XML DC-XML DC-RDF
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Gradivo je del revije

Naslov:Protein science
Skrajšan naslov:Protein sci.
Založnik:Cambridge University Press
ISSN:0961-8368
COBISS.SI-ID:15692293 Novo okno

Gradivo je financirano iz projekta

Financer:Drugi - Drug financer ali več financerjev
Program financ.:Swedish Research Council
Številka projekta:2019-05356, 2022-06725, 2018-05973

Financer:Drugi - Drug financer ali več financerjev
Program financ.:Formas early-career research grant
Številka projekta:2019-01403

Financer:Drugi - Drug financer ali več financerjev
Program financ.:Knut and Alice Wallenberg Foundation
Številka projekta:2021.0198
Naslov:WALP Wallenberg Launchpad project

Financer:Drugi - Drug financer ali več financerjev
Program financ.:Marius Jakulis Jason Foundation

Financer:Drugi - Drug financer ali več financerjev
Program financ.:the National Academic Infrastructure for Supercomputing in Sweden (NAISS), the Swedish National Infrastructure for Computing (SNIC) at the Chalmers Center for Computational Science and Engineering (C3SE), the National Supercomputer Centre in Sweden (NSC) and at the High-Performance Computing Center North

Licence

Licenca:CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:molekularna biologija, biotehnologija, bioinformatika, globoko učenje, izražanje genov, sintetična biologija, obilje beljakovin, aminokislinsko zaporedje, evolucijska selekcija


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