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The digital and analog worlds of protein engineering

Nature Biotechnology volume 41, pages 1513–1514 (2023)Cite this article

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Over the past decades of protein design research, computational algorithms for studying proteins were often explored for novelty rather than their utility in designing functional proteins — yielding heaps of unvalidated and untranslated research. Marked by the success of AlphaFold, trained on structural databases, only recently have the predictive power of these models become robust enough to start reliably integrating them into workflows of protein engineering companies. Seeing models become an increasing component of a protein engineer’s toolkit, some started to wonder: will models become the primary drivers of value creation, and what role will the wet lab play? We propose that, while models have already been tightly integrated in company engineering workflows, most of their economic value is yet to be realized.

State-of-the-art computational protein design is usually open sourced, with authors openly publishing the model code and parameters for its accessibility and reuse. With architectures like transformers and diffusion-based generation becoming commonplace, it is challenging to establish unique, proprietary advantages based solely on model design. As such, platforms centered around acquiring data, improving the quality of the acquired data, building a diversity of assays to characterize the designed proteins and accessing new variants that normally do not appear in nature started to emerge. Some companies, such as Basecamp Research, are heavily investing in mining proteins from extremophile organisms in hard-to-access parts of the world. Others, such as Ginkgo Bioworks, are using their years-in-development metagenomic libraries and automation to collect large amounts of data on enzyme functions. In the therapeutic realm, A-Alpha Bio centered their thesis on generating wet lab screens for millions of protein–protein interactions.

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Author notes

  1. These authors contributed equally: Lada Nuzhna, Tess van Stekelenburg.

Authors and Affiliations

  1. Impetus Grants, San Francisco, CA, USA

    Lada Nuzhna

  2. Crick Institute, London, UK

    Lada Nuzhna

  3. Lux Capital, New York, NY, USA

    Tess van Stekelenburg

Authors
  1. Lada Nuzhna
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  2. Tess van Stekelenburg
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Corresponding authors

Correspondence to Lada Nuzhna or Tess van Stekelenburg.

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Competing interests

T.v.S. works at Lux Capital, which has invested in A-Alpha Bio and Dyno Therapeutics. L.N. funds aging research, which may involve some of the techniques discussed in the article, through Impetus Grants.

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Nuzhna, L., van Stekelenburg, T. The digital and analog worlds of protein engineering. Nat Biotechnol 41, 1513–1514 (2023). https://doi.org/10.1038/s41587-023-01938-x

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