ReviewInternational journal of molecular sciences2024
Virtual Screening of Peptide Libraries: The Search for Peptide-Based Therapeutics Using Computational Tools.
Review in International journal of molecular sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled 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.
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
26 citing papers in PubMed, 1 synthesis or guideline pooled it, 41 citations in OpenAlex.
- Peptides Evaluated In Silico, In Vitro, and In Vivo as Therapeutic Tools for Obesity: A Systematic Review.International journal of molecular sciences · 2024Pooled it
- Structure-based screening and identification of a novel Aurora-A-targeting peptide with antiproliferative activity against prostate cancer cells.Journal of enzyme inhibition and medicinal chemistry · 2026Article
- Molecular dockingDigital discovery · 2026Article
- Special Issue "New Insights into Bioactive Peptides: Design, Synthesis, Structure-Activity Relationship (2nd Edition)".International journal of molecular sciences · 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
- Redefining Therapies for Drug-Resistant Tuberculosis: Synergistic Effects of Antimicrobial Peptides, Nanotechnology, and Computational Design.Advanced healthcare materials · 2026Review
- Inflammation suppressing activity of jellyfish toxin-derived peptide via downregulation of ROS/NF-κB/NLRP3 signaling in LPS/MSU induced fibroblasts in vitro and in vivo gouty arthritis model.Inflammopharmacology · 2026Article
- Prospecting of Novel Angiotensin I-Converting Enzyme Inhibitory Peptides from Bone Collagen ofFoods (Basel, Switzerland) · 2026Article
- Peptide-based drug design using generative AI.Chemical communications (Cambridge, England) · 2026Review
- Article
- Recent advances in multimodal foundation model-enabled peptide screening and optimization for smart biomaterials and functional tissue engineering.Frontiers in bioengineering and biotechnology · 2026Review
- Peptide-Based Therapeutics for Alzheimer's Disease: Medicinal Chemistry, AI-Guided Computational Design, and Blood-Brain Barrier Delivery.Drug design, development and therapy · 2026Review
- Identification of novel potent peptide inhibitors targeting the polo-box domain of PLK1: structure-based pharmacophore modelling, virtual screening, molecular docking, molecular dynamics study and biological evaluation.Journal of enzyme inhibition and medicinal chemistry · 2025Article
- Selection of short Gadd45β-binding peptides through a synergistic computational and biophysical approach.Protein science : a publication of the Protein Society · 2025Article
- A scalable reinforcement learning approach for screening large peptide libraries for bioactive peptide discovery.Nature communications · 2025Article
- PD-L1 targeting in triple negative breast cancer: in silico and in vitro validation of wasp venom peptide MP-1.Medical oncology (Northwood, London, England) · 2025Article
- Organic Fusion of Molecular Simulation and Wet-Lab Validation: A Promising High-Throughput Strategy for Screening Bioactive Food Peptides.Foods (Basel, Switzerland) · 2025Review
- Review
- Molecular Modelling in Bioactive Peptide Discovery and Characterisation.Biomolecules · 2025Review
- Alzheimer's Disease: Exploring Pathophysiological Hypotheses and the Role of Machine Learning in Drug Discovery.International journal of molecular sciences · 2025Review
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
Over the last few decades, we have witnessed growing interest from both academic and industrial laboratories in peptides as possible therapeutics. Bioactive peptides have a high potential to treat various diseases with specificity and biological safety. Compared to small molecules, peptides represent better candidates as inhibitors (or general modulators) of key protein-protein interactions. In fact, undruggable proteins containing large and smooth surfaces can be more easily targeted with the conformational plasticity of peptides. The discovery of bioactive peptides, working against disease-relevant protein targets, generally requires the high-throughput screening of large libraries, and in silico approaches are highly exploited for their low-cost incidence and efficiency. The present review reports on the potential challenges linked to the employment of peptides as therapeutics and describes computational approaches, mainly structure-based virtual screening (SBVS), to support the identification of novel peptides for therapeutic implementations. Cutting-edge SBVS strategies are reviewed along with examples of applications focused on diverse classes of bioactive peptides (i.e., anticancer, antimicrobial/antiviral peptides, peptides blocking amyloid fiber formation).
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.