Evidence map›Paper›PMID 36794431›Full record

ArticleProtein science : a publication of the Protein Society2023

Directed evolution of angiotensin-converting enzyme 2 peptidase activity profiles for therapeutic applications.

Pete Heinzelman, Philip A Romero

Open access · hybridAbstract read
In one paragraph

Article in Protein science : a publication of the Protein Society, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.0field-weighted citation impact, top 26% of its field
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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Activation of Angiotensin-Converting Enzyme 2 Mitigates Gastrointestinal Acute Radiation Syndrome.International journal of radiation oncology, biology, physics · 2026
    Article
  2. Article
  3. Review
  4. 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

2 authors at 1 institution in 1 country.

Pete HeinzelmanDepartment of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin, USA.ORCID 0000-0002-5588-3731
Philip A RomeroDepartment of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin, USA.
University of Wisconsin–Madison · US

Funding

US National Institute of Health 5R35GM119854
6 · The paper itself

Abstract

Angiotensin-converting enzyme 2 (ACE2) has been investigated for its ability to beneficially modulate the angiotensin receptor (ATR) therapeutic axis to treat multiple human diseases. Its broad substrate scope and diverse physiological roles, however, limit its potential as a therapeutic agent. In this work, we address this limitation by establishing a yeast display-based liquid chromatography screen that enabled use of directed evolution to discover ACE2 variants that possess both wild-type or greater Ang-II hydrolytic activity and improved specificity toward Ang-II relative to the off-target peptide substrate Apelin-13. To obtain these results, we screened ACE2 active site libraries to reveal three substitution-tolerant positions (M360, T371, and Y510) that can be mutated to enhance ACE2's activity profile and followed up on these hits with focused double mutant libraries to further improve the enzyme. Relative to wild-type ACE2, our top variant (T371L/Y510Ile) displayed a sevenfold increase in Ang-II turnover number (k

Indexed as

Angiotensin-Converting Enzyme 2Peptidyl-Dipeptidase AAngiotensin IHumansPeptide FragmentsPeptidesAngiotensin-Converting Enzyme 2Angiotensin IPeptide FragmentsPeptidesPeptidyl-Dipeptidase Aangiotensin-converting enzyme 2directed evolutionprotein engineeringyeast surface display

Identifiers

PMID36794431
PMCPMC10019445
OpenAlexW4321003880

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.