Evidence map›Paper›PMID 40815918›Full record

ReviewCurrent opinion in structural biology2025

Advances in Protein-RNA aptamer recognition and modeling: Current trends and future perspectives.

Liming Qiu, Xiaoqin Zou

Abstract readReview
In one paragraph

Review in Current opinion in structural biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Liming QiuDalton Cardiovascular Research Center, University of Missouri, Columbia, MO, USA.
Xiaoqin ZouDalton Cardiovascular Research Center, University of Missouri, Columbia, MO, USA; Department of Physics, University of Missouri, Columbia, MO, USA; Department of Biochemistry, University of Missouri, Columbia, MO, USA; Institute for Data Science and Informatics, University of Missouri, Columbia, MO, USA. Electronic address: zoux@missouri.edu.

Funding

Structure prediction and in silico screening of protein-peptide interactionsR35GM136409 · NIGMS · UNIVERSITY OF MISSOURI-COLUMBIA · PI XIAOQIN ZOU · 2020 to 2026
$2.9M
NIGMS NIH HHS R35 GM136409
6 · The paper itself

Abstract

RNA aptamers possess a remarkable ability to selectively target a diverse spectrum of biomolecules with exceptional affinity and specificity. Their distinctive physical and chemical attributes have driven extensive research into their therapeutic, diagnostic, and analytical applications. However, experimental approaches alone are insufficient to meet the growing demand. As a result, accurate and efficient computational methods are playing an increasingly vital role in RNA aptamer sequence design and structural modeling. Recent breakthroughs in biomolecular structure prediction, particularly through deep learning, have further spurred the development of innovative algorithms. In this review, we summarize current computational models for RNA aptamer structure prediction and design, highlighting recent advances in the field.

Indexed as

Aptamers, NucleotideModels, MolecularProteinsComputational BiologyDeep LearningHumansNucleic Acid ConformationProtein BindingAptamers, NucleotideProteins

Identifiers

PMID40815918
PMCPMC12360483

What OpenQuestion holds

Textmetadata
LicenceTDM
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.