Evidence map›Paper›PMID 36574400›Full record

ArticleACS synthetic biology2023

Genetically Encoded Detection of Biosynthetic Protease Inhibitors.

Levi Kramer, Ankur Sarkar, Tom Foderaro, Andrew L Markley, Jessica Lee, Hannah Edstrom, Shajesh Sharma, Eden Gill, Matthew J Traylor, Jerome M Fox

Abstract read
In one paragraph

Article in ACS synthetic biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Levi KramerDepartment of Chemical and Biological Engineering, University of Colorado, Boulder, 3415 Colorado Avenue, Boulder, Colorado80303, United States.
Ankur SarkarDepartment of Chemical and Biological Engineering, University of Colorado, Boulder, 3415 Colorado Avenue, Boulder, Colorado80303, United States.
Tom FoderaroThink Bioscience, Inc., 1945 Colorado Avenue, Boulder, Colorado80309, United States.
Andrew L MarkleyThink Bioscience, Inc., 1945 Colorado Avenue, Boulder, Colorado80309, United States.
Jessica LeeThink Bioscience, Inc., 1945 Colorado Avenue, Boulder, Colorado80309, United States.
Hannah EdstromDepartment of Chemical and Biological Engineering, University of Colorado, Boulder, 3415 Colorado Avenue, Boulder, Colorado80303, United States.
Shajesh SharmaDepartment of Chemical and Biological Engineering, University of Colorado, Boulder, 3415 Colorado Avenue, Boulder, Colorado80303, United States.
Eden GillDepartment of Chemical and Biological Engineering, University of Colorado, Boulder, 3415 Colorado Avenue, Boulder, Colorado80303, United States.
Matthew J TraylorThink Bioscience, Inc., 1945 Colorado Avenue, Boulder, Colorado80309, United States.
Jerome M FoxDepartment of Chemical and Biological Engineering, University of Colorado, Boulder, 3415 Colorado Avenue, Boulder, Colorado80303, United States.ORCID 0000-0002-3739-1899

Funding

Microbially guided discovery and biosynthesis of biologically active natural productsR35GM143089 · NIGMS · UNIVERSITY OF COLORADO · PI FOX, JEROME · 2021 to 2025
$1.8M
NIGMS NIH HHS R35 GM143089
6 · The paper itself

Abstract

Proteases are an important class of drug targets that continue to drive inhibitor discovery. These enzymes are prone to resistance mutations, yet their promise for treating viral diseases and other disorders continues to grow. This study develops a general approach for detecting microbially synthesized protease inhibitors and uses it to screen terpenoid pathways for inhibitory compounds. The detection scheme relies on a bacterial two-hybrid (B2H) system that links protease inactivation to the transcription of a swappable reporter gene. This system, which can accomodate multiple biochemical outputs (i.e., luminescence and antibiotic resistance), permitted the facile incorporation of four disease-relevant proteases. A B2H designed to detect the inactivation of the main protease of severe acute respiratory syndrome coronavirus 2 enabled the identification of a terpenoid inhibitor of modest potency. An analysis of multiple pathways that make this terpenoid, however, suggested that its production was necessary but not sufficient to confer a survival advantage in growth-coupled assays. This finding highlights an important challenge associated with the use of genetic selection to search for inhibitors─notably, the influence of pathway toxicity─and underlines the value of including multiple pathways with overlapping product profiles in pathway screens. This study provides a detailed experimental framework for using microbes to screen libraries of biosynthetic pathways for targeted protease inhibitors.

Indexed as

Coronavirus 3C ProteasesProtease InhibitorsSARS-CoV-2Coronavirus 3C ProteasesProtease Inhibitorsbiological selectionnatural productsnon-ribosomal peptide synthetasesSARS-CoV-2viral proteases

Identifiers

PMID36574400
PMCPMC10072156

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.