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  4. Vol 8, Issue 1, 2024

Deep Learning-Driven Protein Design

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DOI: 10.23977/acss.2024.080120 | Downloads: 30 | Views: 416

Author(s)

Ao You 1, Xiaobing Xu 1

Affiliation(s)

1 School of Information, Yunnan Normal University, Kunming, China

Corresponding Author

Ao You

ABSTRACT

Protein, the material basis of all living organisms and the primary carrier of life activities, plays a pivotal role in regulating various physiological functions. Composed of specific amino acid sequences, proteins can fold into distinct structures, enabling them to perform diverse functions such as biocatalysis, metabolic regulation, immune defense, transport, and storage. The design of novel proteins with targeted biological functions is a central task in protein engineering, with broad applications in synthetic biology and drug research. This paper provides a comprehensive overview of the recent advancements in deep learning-assisted protein design research. It primarily introduces related language models and generative models, and discusses the associated research and existing challenges from both sequence and structural perspectives. Finally, it offers a forward-looking perspective on the future development of deep learning-assisted protein design research.

KEYWORDS

Deep learning; Protein design; Language model; Generative model; Protein sequence; Protein structure

CITE THIS PAPER

Ao You, Xiaobing Xu, Deep Learning-Driven Protein Design. Advances in Computer, Signals and Systems (2024) Vol. 8: 170-175. DOI: http://dx.doi.org/10.23977/acss.2024.080120.

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