Optimized pipeline and designer cells for synthetic-biology-based high-throughput screening of viral protease inhibitors

Shlomi Edri, Shayma El-Atawneh, Tehila Ernst, Maayan Elnekave, Chaja Katzman, Tali Lanton, Ido Aldar, Omri Wolk, Noa Stern, Amiram Goldblum, Lior Nissim

Research output: Contribution to journalArticlepeer-review

Abstract

A reliable, efficient, high-throughput pipeline to evaluate viral protease inhibitors would enhance antiviral drug discovery. Methods such as crystallography and phenotypic screening are often constrained by complex assay conditions, limited physiological relevance, or live virus handling safety concerns. Proof-of-concept studies previously demonstrated synthetic gene circuits that produce a quantitative reporter upon protease inhibition, enabling functional virus-independent evaluation of viral protease inhibitors in live cells. Using the SARS-CoV-2 3-chymotrypsin-like protease (3CLpro) as a model, we advanced this approach into a high-throughput first-pass qualitative assay (“hit/no-hit”) to rapidly identify promising drug candidates. Our optimized circuit design was used to produce stable HEK293T and HeLa designer cells that generate two distinct fluorescence outputs, simultaneously reporting protease inhibition and cytotoxicity. The screening pipeline is designed to minimize labor, costs, and false-positive observations, thus enabling versatile, safe, and efficient functional drug screening suitable for any conventional biological laboratory.

Original languageEnglish
Article number101139
JournalCell Reports Methods
Volume5
Issue number8
DOIs
StatePublished - 18 Aug 2025
Externally publishedYes

Keywords

  • 3CLpro
  • COVID-19
  • CP: biotechnology
  • SARS-CoV-2
  • antiviral drugs
  • biomedicine
  • biotechnology
  • functional drug screen
  • high-throughput drug screen
  • synthetic biology
  • synthetic gene circuits

ASJC Scopus subject areas

  • Biotechnology
  • Biochemistry
  • Biochemistry, Genetics and Molecular Biology (miscellaneous)
  • Genetics
  • Radiology Nuclear Medicine and imaging
  • Computer Science Applications

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