Evidence map›Paper›PMID 23064642›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2012

Construction of a rationally designed antibody platform for sequencing-assisted selection.

H Benjamin Larman, George Jing Xu, Natalya N Pavlova, Stephen J Elledge

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

H Benjamin LarmanDivision of Health Sciences and Technology, Harvard-Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
George Jing Xu
Natalya N Pavlova
Stephen J Elledge

Funding

Howard Hughes Medical Institute
6 · The paper itself

Abstract

Antibody discovery platforms have become an important source of both therapeutic biomolecules and research reagents. Massively parallel DNA sequencing can be used to assist antibody selection by comprehensively monitoring libraries during selection, thus greatly expanding the power of these systems. We have therefore constructed a rationally designed, fully defined single-chain variable fragment (scFv) library and analysis platform optimized for analysis with short-read deep sequencing. Sequence-defined oligonucleotide libraries encoding three complementarity-determining regions (L3 from the light chain, H2 and H3 from the heavy chain) were synthesized on a programmable microarray and combinatorially cloned into a single scFv framework for molecular display. Our unique complementarity-determining region sequence design optimizes for protein binding by utilizing a hidden Markov model that was trained on all antibody-antigen cocrystal structures in the Protein Data Bank. The resultant ~10(12)-member library was produced in ribosome-display format, and comprehensively analyzed over four rounds of antigen selections by multiplex paired-end Illumina sequencing. The hidden Markov model scFv library generated multiple binders against an emerging cancer antigen and is the basis for a next-generation antibody production platform.

Indexed as

Peptide LibrarySequence Analysis, DNAAntibodiesCell Adhesion MoleculesClone CellsFlow CytometryHumansMarkov ChainsSingle-Chain AntibodiesAntibodiesCell Adhesion MoleculesPeptide LibrarySingle-Chain Antibodies

Identifiers

PMID23064642
PMCPMC3494914

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.