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Current progress, challenges, and future perspectives of language models for protein representation and protein design

The sequence-structure-function paradigm of protein is the basis of molecular biology. What is the underlying mechanism of such sequence and structure/function corresponding relationship? We reviewed the methods for protein representation and protein design. With these protein representation models,...

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Detalles Bibliográficos
Autores principales: Huang, Tao, Li, Yixue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10362512/
https://www.ncbi.nlm.nih.gov/pubmed/37485078
http://dx.doi.org/10.1016/j.xinn.2023.100446
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author Huang, Tao
Li, Yixue
author_facet Huang, Tao
Li, Yixue
author_sort Huang, Tao
collection PubMed
description The sequence-structure-function paradigm of protein is the basis of molecular biology. What is the underlying mechanism of such sequence and structure/function corresponding relationship? We reviewed the methods for protein representation and protein design. With these protein representation models, we can accurately predict many properties of proteins, such as stability and binding affinity. Progen, Chroma, RF Diffusion, SCUBA, and other protein design models have demonstrated how human-designed artificial proteins can have desired biological functions. The protein design will revolutionize drug development. And more efficient artificial enzymes that break down industrial waste or plastics will contribute to carbon neutrality. We also discussed the three greatest challenges of protein design in future and possible solutions.
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spelling pubmed-103625122023-07-23 Current progress, challenges, and future perspectives of language models for protein representation and protein design Huang, Tao Li, Yixue Innovation (Camb) Perspective The sequence-structure-function paradigm of protein is the basis of molecular biology. What is the underlying mechanism of such sequence and structure/function corresponding relationship? We reviewed the methods for protein representation and protein design. With these protein representation models, we can accurately predict many properties of proteins, such as stability and binding affinity. Progen, Chroma, RF Diffusion, SCUBA, and other protein design models have demonstrated how human-designed artificial proteins can have desired biological functions. The protein design will revolutionize drug development. And more efficient artificial enzymes that break down industrial waste or plastics will contribute to carbon neutrality. We also discussed the three greatest challenges of protein design in future and possible solutions. Elsevier 2023-05-21 /pmc/articles/PMC10362512/ /pubmed/37485078 http://dx.doi.org/10.1016/j.xinn.2023.100446 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Perspective
Huang, Tao
Li, Yixue
Current progress, challenges, and future perspectives of language models for protein representation and protein design
title Current progress, challenges, and future perspectives of language models for protein representation and protein design
title_full Current progress, challenges, and future perspectives of language models for protein representation and protein design
title_fullStr Current progress, challenges, and future perspectives of language models for protein representation and protein design
title_full_unstemmed Current progress, challenges, and future perspectives of language models for protein representation and protein design
title_short Current progress, challenges, and future perspectives of language models for protein representation and protein design
title_sort current progress, challenges, and future perspectives of language models for protein representation and protein design
topic Perspective
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10362512/
https://www.ncbi.nlm.nih.gov/pubmed/37485078
http://dx.doi.org/10.1016/j.xinn.2023.100446
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