ArticleScientific reports2022
ApInAPDB: a database of apoptosis-inducing anticancer peptides.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
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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.
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Who cites it
18 citing papers in PubMed, 31 citations in OpenAlex.
- Deciphering the rules of regulated cell death subroutines by in silico methods.Journal of advanced research · 2026Review
- Niosomal Encapsulation of Anti-cancer Peptides: A Revolutionary Strategy in Cancer Therapy.Current pharmaceutical biotechnology · 2026Review
- Artificial intelligence-driven anticancer peptide discovery.iMetaOmics · 2025Review
- Data-Driven Visualization of the Dynamics of Antimicrobial Peptides in Cell Death.Probiotics and antimicrobial proteins · 2025Review
- Exploring the potential of anticancer peptides as therapeutic agents for cancer treatment.Research in pharmaceutical sciences · 2025Review
- Advance in peptide-based drug development: delivery platforms, therapeutics and vaccines.Signal transduction and targeted therapy · 2025Review
- Advances of deep Neural Networks (DNNs) in the development of peptide drugs.Future medicinal chemistry · 2025Review
- Article
- PeptiHub: a curated repository of precisely annotated cancer-related peptides with advanced utilities for peptide exploration and discovery.Database : the journal of biological databases and curation · 2024Article
- Modeling the Binding of Anticancer Peptides and Mcl-1.International journal of molecular sciences · 2024Article
- In silico design of potential Mcl-1 peptide-based inhibitors.Journal of molecular modeling · 2024Article
- Article
- Article
- Anticancer peptides as novel immunomodulatory therapeutic candidates for cancer treatment.Exploration of targeted anti-tumor therapy · 2024Review
- Bioactive peptides: an alternative therapeutic approach for cancer management.Frontiers in immunology · 2024Review
- Article
- Peptide-Based Agents for Cancer Treatment: Current Applications and Future Directions.International journal of molecular sciences · 2023Review
- Plant Virus Nanoparticles Combat Cancer.Vaccines · 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
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
ApInAPDB (Apoptosis-Inducing Anticancer Peptides Database) consists of 818 apoptosis-inducing anticancer peptides which are manually collected from research articles. The database provides scholars with peptide related information such as function, binding target and affinity, IC50 and etc. In addition, GRAVY (grand average of hydropathy), net charge at pH 7, hydrophobicity and other physicochemical properties are calculated and presented. Another category of information are structural information includes 3D modeling, secondary structure prediction and descriptors for QSAR (quantitative structure-activity relationship) modeling. In order to facilitate the browsing process, three types of user-friendly searching tools are provided: top categories browser, simple search and advanced search. Overall ApInAPDB as the first database presenting apoptosis-inducing anticancer peptides can be useful in the field of peptide design and especially cancer therapy. Researchers can freely access the database at http://bioinf.modares.ac.ir/software/ApInAPDB/ .
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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.