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Classifying alkaliphilic proteins using embeddings from protein language model.

Meredita Susanty1, Muhammad Khaerul Naim Mursalim2, Rukman Hertadi3

  • 1Institut Teknologi Bandung School of Electrical Engineering and Informatics, Jl. Ganesa 10, Bandung, Jawa Barat, Indonesia; Universitas Pertamina, School of Computer Science, Jl Teuku Nyak Arief Jakarta Selatan DKI Jakarta, Indonesia.

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Summary

Researchers developed ALPACA, a computational method using protein language model embeddings to identify alkaliphilic proteins. This approach accelerates enzyme engineering by offering a faster, more cost-effective alternative to traditional lab experiments.

Keywords:
Alkaliphilic proteinClassificationEmbeddingsProtein disorder

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Area of Science:

  • Biotechnology
  • Protein Engineering
  • Computational Biology

Background:

  • Alkaliphilic proteins are valuable biocatalysts for biotechnology and enzyme engineering.
  • Current identification methods involving lab experiments are time-consuming, labor-intensive, and expensive.
  • A computational approach is needed to streamline the identification of alkaliphilic proteins.

Purpose of the Study:

  • To develop a novel computational method for identifying alkaliphilic proteins.
  • To utilize embeddings from the ESM-2(3B) protein language model within a deep learning framework.
  • To classify alkaliphilic and non-alkaliphilic proteins efficiently.

Main Methods:

  • Constructed a reliable dataset of 1,002 alkaliphilic and 1,866 non-alkaliphilic proteins.
  • Employed embeddings from the ESM-2(3B) protein language model.
  • Utilized a deep learning framework for classification, resulting in the ALPACA model.

Main Results:

  • The ALPACA model achieved high performance on an independent dataset.
  • Accuracy: 0.88
  • F1-score: 0.84
  • Matthew correlation coefficient: 0.75

Conclusions:

  • The developed ALPACA model offers a reliable and efficient computational method for identifying alkaliphilic proteins.
  • This approach can significantly aid protein engineering and design by accelerating the exploration of protein alkalinity.
  • ALPACA presents a valuable resource for researchers in biotechnology and protein science.