ReviewMolecular medicine (Cambridge, Mass.)2022
Peptidomimetics in cancer targeting.
Review in Molecular medicine (Cambridge, Mass.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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.
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.
Who cites it
10 citing papers in PubMed, 28 citations in OpenAlex.
- Potential medical applicability of N-β-Ala and N-His dipeptidomimetics against breast cancer: short in vitro and in silico screening.Scientific reports · 2026Article
- Disrupting the Undruggable: Emerging Modalities for Targeting Protein-Protein Interactions in Oncology.Biology · 2026Review
- CAMPER: mechanistic artificial intelligence for designing peptides that target MRSA persisters.Nature communications · 2026Article
- The Role of p66Shc in Cancer: Molecular Mechanisms and Therapeutic Implications.Journal of cellular and molecular medicine · 2025Review
- Advance in peptide-based drug development: delivery platforms, therapeutics and vaccines.Signal transduction and targeted therapy · 2025Review
- Dynamic regulation of neutrophil immunometabolism by platelet-derived metabolites.Frontiers in immunology · 2025Review
- New insights into protein-protein interaction modulators in drug discovery and therapeutic advance.Signal transduction and targeted therapy · 2024Review
- Development and Prospects of Furin Inhibitors for Therapeutic Applications.International journal of molecular sciences · 2024Review
- Peptoids: Smart and Emerging Candidates for the Diagnosis of Cancer, Neurological and Autoimmune Disorders.International journal of molecular sciences · 2023Review
- Peptides as Therapeutic Agents: Challenges and Opportunities in the Green Transition Era.Molecules (Basel, Switzerland) · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The low efficiency of treatment strategies is one of the main obstacles to developing cancer inhibitors. Up to now, various classes of therapeutics have been developed to inhibit cancer progression. Peptides due to their small size and easy production compared to proteins are highly regarded in designing cancer vaccines and oncogenic pathway inhibitors. Although peptides seem to be a suitable therapeutic option, their short lifespan, instability, and low binding affinity for their target have not been widely applicable against malignant tumors. Given the peptides' disadvantages, a new class of agents called peptidomimetic has been introduced. With advances in physical chemistry and biochemistry, as well as increased knowledge about biomolecule structures, it is now possible to chemically modify peptides to develop efficient peptidomimetics. In recent years, numerous studies have been performed to the evaluation of the effectiveness of peptidomimetics in inhibiting metastasis, angiogenesis, and cancerous cell growth. Here, we offer a comprehensive review of designed peptidomimetics to diagnose and treat cancer.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.