Evidence map›Paper›PMID 40060358›Full record

ReviewBBA advances2025

Protein recognition methods for diagnostics and therapy.

Ryne Montoya, Peter Deckerman, Mustafa O Guler

Abstract readReview
In one paragraph

Review in BBA advances, 2025. 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. Aptamer-based DNA nanoswitches for multiplexed protein detection.Chemical communications (Cambridge, England) · 2026
    Article
  2. Article
  3. Review
  4. Aptamer-based DNA nanoswitches for multiplexed protein detection.bioRxiv : the preprint server for biology · 2026
    Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Generation of aInternational journal of molecular sciences · 2025
    Article
  10. Article
  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.

Ryne MontoyaThe Pritzker School of Molecular Engineering, The University of Chicago, 5640 S Ellis Ave Chicago, IL 60637 USA.
Peter DeckermanThe Pritzker School of Molecular Engineering, The University of Chicago, 5640 S Ellis Ave Chicago, IL 60637 USA.
Mustafa O GulerThe Pritzker School of Molecular Engineering, The University of Chicago, 5640 S Ellis Ave Chicago, IL 60637 USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The fundamental biological processes involving highly specific interactions between proteins and other biological motifs are the pillars of protein recognition mechanisms. These interactions are crucial for biological systems, often having significant implications within diagnostics and therapy development. Protein recognition and specificity are reliant on structural compatibility, dynamic conformational changes, and biochemical interactions-all of which are grounded in fundamental molecular forces like hydrogen bonding, ionic interactions, and van der Waals forces. Advanced characterization tools have improved our understanding of protein interactions, revealing the kinetics and thermodynamics of these recognition mechanisms. In parallel, new computing methods, including artificial intelligence, molecular docking, and dynamical simulations, have increased prediction accuracy for molecular interactions, leading to well-defined interaction sites and binding kinetics information. Protein recognition is pivotal in diagnostic methods including ELISAs and biosensors, which are crucial within disease detection applications. In therapeutics, protein recognition plays an important role in drug development, enabling the design of small molecules, peptides, and monoclonal antibodies. Despite recent progress, there are many challenges remaining to fully understand protein recognition, particularly within the complex cell environment. These challenges require future work in protein recognition studies to enhance diagnostic and therapeutic applications. The researchers are using improved detection and screening methods to identify, assess, and optimize interactions for clinical translation.

Indexed as

AntibodiesDiagnosticsEnzymeImmunotherapyProteins

Identifiers

PMID40060358
PMCPMC11889627

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.