Evidence map›Paper›PMID 39026653›Full record

ReviewRSC medicinal chemistry2024

Rational design of small-sized peptidomimetic inhibitors disrupting protein-protein interaction.

Junyuan Wang, Ping Zheng, Jianqiang Yu, Xiuyan Yang, Jian Zhang

Abstract readReview
In one paragraph

Review in RSC medicinal chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. 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.

Junyuan WangSchool of Pharmacy, Ningxia Medical University Yinchuan 750004 China.
Ping ZhengSchool of Pharmacy, Ningxia Medical University Yinchuan 750004 China.
Jianqiang YuSchool of Pharmacy, Ningxia Medical University Yinchuan 750004 China.ORCID https://orcid.org/0000-0003-3752-6527
Xiuyan YangMedicinal Chemistry and Bioinformatics Center, School of Medicine, Shanghai Jiao Tong University Shanghai 200025 China.ORCID https://orcid.org/0000-0002-3459-5490
Jian ZhangKey Laboratory of Protection, Development and Utilization of Medicinal Resources in Liupanshan Area, Ministry of Education, Peptide & Protein Drug Research Center, School of Pharmacy, Ningxia Medical University Yinchuan 750004 China.ORCID https://orcid.org/0000-0002-6558-791X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protein-protein interactions are fundamental to nearly all biological processes. Due to their structural flexibility, peptides have emerged as promising candidates for developing inhibitors targeting large and planar PPI interfaces. However, their limited drug-like properties pose challenges. Hence, rational modifications based on peptide structures are anticipated to expedite the innovation of peptide-based therapeutics. This review comprehensively examines the design strategies for developing small-sized peptidomimetic inhibitors targeting PPI interfaces, which predominantly encompass two primary categories: peptidomimetics with abbreviated sequences and low molecular weights and peptidomimetics mimicking secondary structural conformations. We have also meticulously detailed several instances of designing and optimizing small-sized peptidomimetics targeting PPIs, including MLL1-WDR5, PD-1/PD-L1, and Bak/Bcl-xL, among others, to elucidate the potential application prospects of these design strategies. Hopefully, this review will provide valuable insights and inspiration for the future development of PPI small-sized peptidomimetic inhibitors in pharmaceutical research endeavors.

Identifiers

PMID39026653
PMCPMC11253864

What OpenQuestion holds

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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.