The recent breakthroughs of Large Language Models (LLMs) in the context of natural language processing have opened the way to significant advances in protein research. Indeed, the relationships between human natural language and the “language of proteins” invite the application and adaptation of LLMs to protein modelling and design. Considering the impressive results of GPT-4 and other recently developed LLMs in processing, generating and translating human languages, we anticipate analogous results with the language of proteins. Indeed, protein language models have been already trained to accurately predict protein properties, generate novel functionally characterized proteins, achieving state-of- the-art results. In this paper we discuss the promises and the open challenges raised by this novel and exciting research area, and we propose our perspective on how LLMs will affect protein modeling and design.

The promises of large language models for protein design and modeling / G. Valentini, D. Malchiodi, J. Gliozzo, M. Mesiti, M. Soto Gomez, A. Cabri, J. Reese, E. Casiraghi, P.N. Robinson. - In: FRONTIERS IN BIOINFORMATICS. - ISSN 2673-7647. - 3:(2023), pp. 1304099.1-1304099.11. [10.3389/fbinf.2023.1304099]

The promises of large language models for protein design and modeling

G. Valentini
Primo
;
D. Malchiodi
Secondo
;
J. Gliozzo;M. Mesiti;M. Soto Gomez;A. Cabri;E. Casiraghi
Penultimo
;
2023

Abstract

The recent breakthroughs of Large Language Models (LLMs) in the context of natural language processing have opened the way to significant advances in protein research. Indeed, the relationships between human natural language and the “language of proteins” invite the application and adaptation of LLMs to protein modelling and design. Considering the impressive results of GPT-4 and other recently developed LLMs in processing, generating and translating human languages, we anticipate analogous results with the language of proteins. Indeed, protein language models have been already trained to accurately predict protein properties, generate novel functionally characterized proteins, achieving state-of- the-art results. In this paper we discuss the promises and the open challenges raised by this novel and exciting research area, and we propose our perspective on how LLMs will affect protein modeling and design.
large language models; protein modeling; protein design; protein engineering; transformers; deep learning
Settore INF/01 - Informatica
2023
https://www.frontiersin.org/articles/10.3389/fbinf.2023.1304099/full?&utm_source=Email_to_authors_&utm_medium=Email&utm_content=T1_11.5e1_author&utm_campaign=Email_publication&field=&journalName=Frontiers_in_Bioinformatics&id=1304099
Article (author)
File in questo prodotto:
File Dimensione Formato  
fbinf-03-1304099.pdf

accesso aperto

Descrizione: Perspective
Tipologia: Publisher's version/PDF
Dimensione 1.66 MB
Formato Adobe PDF
1.66 MB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1018572
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact