ArticlePloS one2018
In silico approaches for predicting the half-life of natural and modified peptides in blood.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 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
59 citing papers in PubMed.
- In silico design and In Vitro validation of WK15: a promising antimicrobial peptide for aquaculture applications.World journal of microbiology & biotechnology · 2026Article
- Cyclic Peptides as Modulators of Protein-Protein Interactions: A Survival Guide from Discovery Platforms to AI-Driven Design.International journal of molecular sciences · 2026Review
- Comparative Biological and Functional Profiling of Single-Position Cysteine Substitutions in the HNP-1-Derived Peptide Pep-H AgainstAntibiotics (Basel, Switzerland) · 2026Article
- Deep Learning-Based Protein Half-Life Prediction for Identifying Rate-Limiting Enzymes in Metabolic Pathways to Alleviate Bottleneck Reactions.Journal of microbiology and biotechnology · 2026Article
- Curing the brain: in search for new astrocyte-specific therapies.Experimental & molecular medicine · 2026Review
- Prediction of Chemically Modified Antimicrobial Peptides and Their Sub-functional Activities Using Hybrid Features.Probiotics and antimicrobial proteins · 2026Article
- Lab to codes: multimodel advanced AI-driven pipelines to drive antimicrobial peptide design for the post-antibiotic era.Frontiers in cellular and infection microbiology · 2026Review
- A Machine Learning-Empowered Quantitative Structure-Activity Relationship Model for Predicting the Plasma Half-life of Drugs in Dogs.The AAPS journal · 2025Article
- Targeting Microglial Connexin43 Hemichannels: A Novel Therapeutic Avenue for Alzheimer's Disease.Neuroscience bulletin · 2025Article
- Deep Learning-Based Drug Half-Life Classification to Enhance Drug Development and Pharmacokinetics.Advanced pharmaceutical bulletin · 2025Article
- Plant Antimicrobial Oligopeptides with Anticancer Properties as a Source of Biologically Active Peptides-AnInternational journal of molecular sciences · 2025Article
- Deep learning in the discovery of antiviral peptides and peptidomimetics: databases and prediction tools.Molecular diversity · 2025Review
- Surface Functionalization of Cellulose-Based Packaging with a New Antimicrobial Decapeptide: A Sustainable Solution to Improve the Quality of Meat Products.Foods (Basel, Switzerland) · 2025Article
- Discovery of a Potent Antimicrobial Peptide Through Rational Design: A New Frontier in Pathogen Control.Biomolecules · 2025Article
- Connexin43 hemichannel blockade turns microglia neuroprotective and mitigates cognitive deficits in a mouse model of amyloidosis.Nature communications · 2025Article
- Improvement of the Antimicrobial Peptide Activity by Means of Chitosan-Based Nanoparticles.Biotechnology journal · 2025Article
- Discovery of antimicrobial peptides with notable antibacterial potency by an LLM-based foundation model.Science advances · 2025Article
- Article
- TRPA1-Activated Peptides from Saiga Antelope Horn: Screening, Interaction Mechanism, and Bioactivity.International journal of molecular sciences · 2025Article
- Computational investigation of antiviral peptide interactions with Mpox DNA polymerase.In silico pharmacology · 2025Article
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper describes a web server developed for designing therapeutic peptides with desired half-life in blood. In this study, we used 163 natural and 98 modified peptides whose half-life has been determined experimentally in mammalian blood, for developing in silico models. Firstly, models have been developed on 261 peptides containing natural and modified residues, using different chemical descriptors. The best model using 43 PaDEL descriptors got a maximum correlation of 0.692 between the predicted and the actual half-life peptides. Secondly, models were developed on 163 natural peptides using amino acid composition feature of peptides and achieved a maximum correlation of 0.643. Thirdly, models were developed on 163 natural peptides using chemical descriptors and attained a maximum correlation of 0.743 using 45 selected PaDEL descriptors. In order to assist researchers in the prediction and designing of half-life of peptides, the models developed have been integrated into PlifePred web server (http://webs.iiitd.edu.in//raghava/plifepred/).
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.