Evidence map›Paper›PMID 27094295›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2016

Generating High-Accuracy Peptide-Binding Data in High Throughput with Yeast Surface Display and SORTCERY.

Lothar Luther Reich, Sanjib Dutta, Amy E Keating

Abstract read
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
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  4. Article
  5. Review
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  8. Review
  9. Peptide design by optimization on a data-parameterized protein interaction landscape.Proceedings of the National Academy of Sciences of the United States of America · 2018
    Article
  10. Review
  11. 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.

Lothar Luther ReichDepartment of Biology, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Rm 68-622A, Cambridge, MA, 02139, USA.
Sanjib DuttaDepartment of Biology, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Rm 68-622A, Cambridge, MA, 02139, USA.
Amy E KeatingDepartment of Biology, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Rm 68-622A, Cambridge, MA, 02139, USA. keating@mit.edu.

Funding

Very large datasets and new models to predict and design protein interactionsR01GM096466 · NIGMS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI KEATING, AMY E · 2010 to 2014
$2.0M
NIGMS NIH HHS GM096466NIGMS NIH HHS R01 GM096466
6 · The paper itself

Abstract

Library methods are widely used to study protein-protein interactions, and high-throughput screening or selection followed by sequencing can identify a large number of peptide ligands for a protein target. In this chapter, we describe a procedure called "SORTCERY" that can rank the affinities of library members for a target with high accuracy. SORTCERY follows a three-step protocol. First, fluorescence-activated cell sorting (FACS) is used to sort a library of yeast-displayed peptide ligands according to their affinities for a target. Second, all sorted pools are deep sequenced. Third, the resulting data are analyzed to create a ranking. We demonstrate an application of SORTCERY to the problem of ranking peptide ligands for the anti-apoptotic regulator Bcl-xL.

Indexed as

Cell SeparationFlow CytometryFungal ProteinsLigandsPeptidesProtein BindingYeastsFungal ProteinsLigandsPeptidesBcl-2 familyDeep sequencingHigh-throughput assayProtein–protein interactionYeast surface display

Identifiers

PMID27094295
PMCPMC4912380

What OpenQuestion holds

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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.