# Computational scoring and experimental evaluation of enzymes generated by neural networks

*PRI Rank #12 · Topics and Trends in Most Cited Microbial Metabolic Engineering and Bioproduction Papers, Class of 2026*

*Canonical URL: https://pri.pepkio.com/top-papers/microbial-metabolic-engineering-and-bioproduction/2026/rank-12*

| Field | Value |
| --- | --- |
| Rank | #12 |
| 18m citations | 47 |
| Journal | Nature Biotechnology |
| Year | 2024 |
| DOI | 10.1038/s41587-024-02214-2 |
| Corresponding authors | Aleksej Zelezniak, Kevin Yang |
| Institution | New England Biolabs, United States |

**Ranking page:** [Topics and Trends in Most Cited Microbial Metabolic Engineering and Bioproduction Papers, Class of 2026](https://pri.pepkio.com/top-papers/microbial-metabolic-engineering-and-bioproduction/2026)

**Paper link:** [10.1038/s41587-024-02214-2](https://doi.org/10.1038/s41587-024-02214-2)

## Topics

generative protein sequence models · ancestral sequence reconstruction · generative adversarial network · protein language model · computational metrics · Enzyme function prediction · in vitro enzyme activity · protein expression and purification · Sequence similarity · computational filter · experimental success rate · Enzyme engineering · enzyme families · generated sequences · natural sequences · benchmarking generative models · Enzyme function prediction · variant selection

## Cite this ranking

```
Pepkio Research Index (PRI). Topics and Trends in Most Cited Microbial Metabolic Engineering and Bioproduction Papers, Class of 2026. https://pri.pepkio.com/top-papers/microbial-metabolic-engineering-and-bioproduction/2026. Accessed 2026-07-29.

Zheng Su, Tinsley Li, Thematic Shifts in Early-High-Impact Cancer Genomics and Diagnostics Research: A Bibliometric and Semantic Analysis. bioRxiv 2026.07.04.736459; doi: https://doi.org/10.64898/2026.07.04.736459
```