Evidence map›Paper›PMID 41940160›Full record

ReviewaBIOTECH2026

Deep learning-driven protein binder design for crop improvement.

Muhammad Salman Iqbal, Revocatus Bahitwa, Abdul Ali Azam, Hui Xu, Hai Wang

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in aBIOTECH, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

5 authors.

Muhammad Salman IqbalState Key Laboratory of Maize Bio-breeding, Frontiers Science Center for Molecular Design Breeding, National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China.
Revocatus BahitwaState Key Laboratory of Maize Bio-breeding, Frontiers Science Center for Molecular Design Breeding, National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China.
Abdul Ali AzamState Key Laboratory of Maize Bio-breeding, Frontiers Science Center for Molecular Design Breeding, National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China.
Hui XuState Key Laboratory of Maize Bio-breeding, Frontiers Science Center for Molecular Design Breeding, National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China.
Hai WangState Key Laboratory of Maize Bio-breeding, Frontiers Science Center for Molecular Design Breeding, National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Deep learning (DL) now enables the end-to-end design of protein binders-proteins that bind to specific targets-to precisely modulate protein-protein interactions (PPIs). Models and tools such as BindCraft, AlphaFold, RoseTTAFold, RFdiffusion, and ProteinMPNN predict the structures of these binders and their targets, generate binder sequences, and refine their binding interfaces with increasing accuracy. Most progress so far has been in the therapeutics field, where

Indexed as

AI in agricultureCrop breedingDeep learningPrecision agricultureProtein binder designSynthetic biology

Identifiers

PMID41940160
PMCPMC12973395

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.