Evidence map›Paper›PMID 37647002›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2023

Single-Step Non-Chromatographic Purification of Recombinant Mammalian Proteins Using a Split Intein ELP Tag System.

Sai Vivek Prabhala, David W Wood

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
3.4field-weighted citation impact, top 7% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Article
  3. 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.

Sai Vivek PrabhalaWilliam G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, OH, USA.
David W WoodWilliam G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, OH, USA. Wood.750@osu.edu.
The Ohio State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Glycoprotein therapeutics are currently used by large patient populations and generate significant revenue for the biopharmaceutical industry. These therapeutic proteins are currently purified at industrial scale using individualized processes involving multiple chromatographic steps. In the absence of a viable affinity platform method, the required chromatographic steps are difficult to develop and inevitably lead to significant yield losses. Further, during preclinical development, there is a need for reliable platform technologies capable of performing high-throughput screening for biologic candidates. Although affinity tags can provide a solution to some of these challenges, they require specific affinity resins, and the tag itself can interfere with the target protein characteristics. Fusion protein systems consisting of elastin-like polypeptide (ELP) and self-cleaving split inteins such as Npu DnaE can serve as potential non-chromatographic platform technologies for the single-step purification of tagless glycoproteins expressed in mammalian cells. In this chapter, we demonstrate the use of this technology to obtain highly purified anti-ErbB2 ML39 single-chain variable fragment (scFv) expressed from Expi293F suspension cells.

Indexed as

InteinsSingle-Chain AntibodiesAnimalsChromatographyElastinHigh-Throughput Screening AssaysHumansMammalsElastinSingle-Chain AntibodiesElastin-like polypeptideInteinNon-chromatographic purificationRecombinant protein purificationSplit intein

Identifiers

PMID37647002
OpenAlexW4386272277

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.