Identification and engineering of highly functional potyviral proteases in cells using co-evolutionary models

Medel B. Lim Suan; Cheyenne Ziegler; Zain Syed; Arjun Yedavalli; Jaimahesh Nagineni; Rodrigo Raposo; Ajay Tunikipati; Jaideep Kaur; Faruck Morcos; P.C. Dave P. Dingal

doi:10.1038/s41467-026-69961-5

Identification and engineering of highly functional potyviral proteases in cells using co-evolutionary models

Nature Communications 2026 Open access

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Authors: Medel B. Lim Suan, Cheyenne Ziegler, Zain Syed, Arjun Yedavalli, Jaimahesh Nagineni, Rodrigo Raposo, Ajay Tunikipati, Jaideep Kaur, Faruck Morcos, P.C. Dave P. Dingal

DOI: 10.1038/s41467-026-69961-5

Cited by: 0

References: 32

Abstract

Efficiency and substrate specificity of proteases in the Potyviridae family have not been comprehensively profiled. Here we develop a model that learns co-evolutionary features to accurately predict and experimentally validate protease performance at single amino-acid resolution. We identify and engineer several proteases that perform better than the commercially available tobacco etch virus protease. To demonstrate the resolving power of our methods, we engineer protease crosstalk to selectively trigger a synthetic cell-death program in human cells.

Fields of Study & Subjects

CRISPR and Genetic Engineering Evolution and Genetic Dynamics Plant Virus Research Studies

Publication details

Journal / source: Nature Communications
Volume: 17
Issue: 1
Publication date: 26 February 2026
Language: EN

References 32