Evidence map›Paper›PMID 35482188›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2022

Engineering Proteins by Combining Deep Mutational Scanning and Yeast Display.

Preeti Sharma, Erik Procko, David M Kranz

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.8field-weighted citation impact, top 14% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Dissecting the effects of single amino acid substitutions in SARS-CoV-2 Mpro.Protein science : a publication of the Protein Society · 2025
    Article
  2. 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

3 authors at 2 institutions in 1 country.

Preeti SharmaDepartment of Biochemistry, University of Illinois, Urbana, IL, USA.
Erik ProckoDepartment of Biochemistry, University of Illinois, Urbana, IL, USA.
David M KranzDepartment of Biochemistry, University of Illinois, Urbana, IL, USA. d-kranz@illinois.edu.
University of Illinois System · USUniversity of Illinois Urbana-Champaign · US

Funding

Engineering CARs against cancer-specific glycoproteinsR21CA238628 · NCI · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI KRANZ, DAVID M. · 2019 to 2020
$394k
NCI NIH HHS R21 CA238628
6 · The paper itself

Abstract

Protein engineering using display platforms such as yeast display and phage display has allowed discovery of proteins with therapeutic and industrial applications. Antibodies and T cell receptors developed for therapeutic applications are often engineered by constructing libraries of mutations in loops of five to ten residues called complementarity determining regions that are in proximity to the antigen. In the past decade, deep mutational scanning has become a powerful tool in a protein engineer's toolbox, as it allows one to compare the impact of all 20 amino acids at each position, across the length of the protein. Thus, a single experiment can provide a sequence-activity landscape with information about hotspots or suboptimal binding sites in the original proteins. These residues or regions may be overlooked by engineering methods that are driven solely by structures or directed evolution of error-prone PCR libraries. Here, we describe experimental methods to engineer proteins by combining yeast display and deep mutational scanning mutagenesis, using T cell receptors as an example.

Indexed as

Protein EngineeringSaccharomyces cerevisiaeMutagenesisMutationReceptors, Antigen, T-CellReceptors, Antigen, T-CellDeep mutational scanningEnrichment ratioHeat mapsProtein engineeringSequence-activity landscapeT cell receptorsYeast display

Identifiers

PMID35482188
OpenAlexW4226132928

What OpenQuestion holds

Textmetadata
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.