Evidence map›Paper›PMID 42890737›Full record

ArticleACS nano medicine2026

CompELS vs SELEX: Comparative Aptamer Discovery Integrating Rational Libraries and Enzymatic Elution.

Steven Ochoa, Valeria Tohver Milam

Abstract read
In one paragraph

Article in ACS nano medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Steven OchoaSchool of Materials Science & Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.ORCID https://orcid.org/0009-0003-7509-7425
Valeria Tohver MilamSchool of Materials Science & Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.ORCID https://orcid.org/0000-0002-5303-7777

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aptamers are oligonucleotides that fold into structures with target-binding activity comparable to antibodies, yet their discovery remains laborious and inconsistent. Traditional Systematic Evolution of Ligands by Exponential Enrichment (SELEX) screening often relies on randomized sequence libraries, repeated amplification, and harsh elution methods, each of which introduces bias and limits reproducibility. An alternative aptamer screening platform called Competition-Enhanced Ligand Selection (CompELS) employs repeated introduction of unenriched sequence populations while avoiding iterative elution and amplification steps. To elucidate key parameters governing selection outcomes, the effects of screening strategy, screening library design, and elution of bound DNA methodology were evaluated. A parallel study of candidate aptamer selection platforms against fluorescent protein mCherry revealed that SELEX required two additional enrichment cycles to achieve comparable enrichment of the same top 3 sequences selected via CompELS. A GT rich, empirically biased library was the predominant source of binding sequences, out-competing a tetraloop-structured library and random library. Finally, an enzymatic elution strategy enabled gentle recovery of aptamer-target complexes from either screening strategy to effectively reduce nonspecific carryover and improve the fidelity of each platform. These results demonstrate a streamlined, versatile aptamer candidate selection methodology that promises an accelerated aptamer discovery approach for protein targets and reduces bias by integrating CompELS, rational library design, and enzymatic elution.

Indexed as

AlphaFold 3competitive displacementligandnext generation sequencingscreening

Identifiers

PMID42890737
PMCPMC13674330

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.