ReviewOpen biology2020
Anti-cancer peptides: classification, mechanism of action, reconstruction and modification.
Review in Open biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 122 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
122 citing papers in PubMed, 256 citations in OpenAlex.
- Anticancer Peptides: Design Principles, Translational Bottlenecks, and Emerging Opportunities.Molecules (Basel, Switzerland) · 2026Review
- DeepACPred: an integrated multistage framework for anticancer peptide discovery and activity prediction.Briefings in bioinformatics · 2026Article
- Valorization of rabbit viscera by enzymatic hydrolysis: bioactive peptides with antioxidant and cell viability properties.Food science of animal resources · 2026Article
- The effect of monomers number in peptides on Escherichia coli strain productivity and inclusion bodies-associated target protein accumulation.Folia microbiologica · 2026Article
- From Innate Immunity to Cancer Therapy: Antimicrobial Peptides as Emerging Anticancer Agents.International journal of molecular sciences · 2026Review
- Streptococcus-derived CpsA-CpsC fusion protein induces apoptosis in cervical cancer cells through in silico and in vitro methods.Scientific reports · 2026Article
- Potential medical applicability of N-β-Ala and N-His dipeptidomimetics against breast cancer: short in vitro and in silico screening.Scientific reports · 2026Article
- A Comprehensive Review on the Anticancer Activity of Plant Peptides and Their Mechanisms of Action.Foods (Basel, Switzerland) · 2026Review
- Cationic lipid-based nanoparticles for therapeutic delivery in cancer treatment: physicochemical characteristics, therapeutic cargos, and clinical potential.Applied microscopy · 2026Review
- ACP-EPC: an interpretable deep learning framework for anticancer peptide prediction utilizing pre-trained protein language model and multi-view feature extracting strategy.Molecular diversity · 2026Article
- Anticancer Bioactive Peptides from Plants: Sources, Action Mechanisms, and Potential Superiority to Conventional Chemotherapy.Probiotics and antimicrobial proteins · 2026Review
- OBIMAP (One-Bead Interchain Multipeptide Assembly Platform).ACS bio & med chem Au · 2026Article
- Advances in molecular dynamics approaches for investigating cell-penetrating peptides.Biophysical reviews · 2026Review
- Peptide-Functionalized Iron Oxide Nanoparticles for Cancer Therapy: Targeting Strategies, Mechanisms, and Translational Opportunities.Molecules (Basel, Switzerland) · 2026Review
- Recent advances in structural and functional diversities of cancer lncRNA-encoded peptides: current opportunities and challenges for enhancing cancer diagnosis and treatment.Cancer cell international · 2026Review
- Next-Generation Anticancer Peptides: Engineering, Nanotheranostics and Clinical Translation.Nanotheranostics · 2026Review
- The Dual Role of Natural Peptides in Cancer Therapy: Anticancer and Immunomodulatory Perspectives.Oncology research · 2026Review
- MetaPepticon: automated prediction of anticancer peptides from microbial genomes and metagenomes.PeerJ · 2026Article
- AttBiLSTM_DE: enhancing anticancer peptide prediction using word embedding and an optimized attention-based BiLSTM framework.Scientific reports · 2025Article
- A scalable reinforcement learning approach for screening large peptide libraries for bioactive peptide discovery.Nature communications · 2025Article
62 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Anti-cancer peptides (ACPs) are a series of short peptides composed of 10-60 amino acids that can inhibit tumour cell proliferation or migration, or suppress the formation of tumour blood vessels, and are less likely to cause drug resistance. The aforementioned merits make ACPs the most promising anti-cancer candidate. However, ACPs may be degraded by proteases, or result in cytotoxicity in many cases. To overcome these drawbacks, a plethora of research has focused on reconstruction or modification of ACPs to improve their anti-cancer activity, while reducing their cytotoxicity. The modification of ACPs mainly includes main chain reconstruction and side chain modification. After summarizing the classification and mechanism of action of ACPs, this paper focuses on recent development and progress about their reconstruction and modification. The information collected here may provide some ideas for further research on ACPs, in particular their modification.
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.