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A method to confer Protein L binding ability to any antibody fragment

Overview of attention for article published in mAbs, December 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • Good Attention Score compared to outputs of the same age and source (73rd percentile)

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2 X users
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32 patents
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1 Facebook page

Readers on

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100 Mendeley
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1 CiteULike
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Article details
Title
A method to confer Protein L binding ability to any antibody fragment
Published in
mAbs, December 2015
DOI 10.1080/19420862.2015.1116657
Pubmed ID
Authors
Abstract

Recombinant antibody single-chain variable fragments (scFv) are difficult to purify homogeneously from a protein complex mixture. The most effective, specific and fastest method of purification is an affinity chromatography on Protein L (PpL) matrix. This protein is a multi-domain bacterial surface protein that is able to interact with conformational patterns on kappa light chains. It mainly recognizes amino acid residues located at the VL FR1 and some residues in the variable and constant (CL) domain. Not all kappa chains are recognized, however, and the lack of CL can reduce the interaction. From a scFv composed of IGKV10-94 according to IMGT®, it is possible, with several mutations, to transfer the motif from the IGKV12-46 naturally recognized by the PpL, and, with the single mutation T8P, to confer PpL recognition with a higher affinity. A second mutation S24R greatly improves the affinity, in particular by modifying the dissociation rate (kd). The equilibrium dissociation constant (KD) was measured at 7.2 10(-11) M by surface plasmon resonance. It was possible to confer PpL recognition to all kappa chains. This protein interaction can be modulated according to the characteristics of scFv (e.g., stability) and their use with conjugated PpL. This work could be extrapolated to recombinant monoclonal antibodies, and offers an alternative for protein A purification and detection.

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X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 100 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Japan 1 1%
Switzerland 1 1%
Unknown 98 98%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 27 27%
Student > Master 15 15%
Student > Ph. D. Student 9 9%
Student > Bachelor 8 8%
Other 4 4%
Other 9 9%
Unknown 28 28%
Readers by discipline
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 23 23%
Agricultural and Biological Sciences 20 20%
Immunology and Microbiology 5 5%
Pharmacology, Toxicology and Pharmaceutical Science 4 4%
Medicine and Dentistry 4 4%
Other 15 15%
Unknown 29 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 May 2026.
All research outputs
#3,392,172
of 33,825,399 outputs
Outputs from mAbs
#354
of 1,467 outputs
Outputs of similar age
#44,128
of 439,869 outputs
Outputs of similar age from mAbs
#7
of 26 outputs
Altmetric has tracked 33,825,399 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.8. This one has done well, scoring higher than 75% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 439,869 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 26 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.