ArticleJournal of chemical information and modeling2015
Matched Peptides: Tuning Matched Molecular Pair Analysis for Biopharmaceutical Applications.
Article in Journal of chemical information and modeling, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Field outbreak investigation and immunoinformatic analysis suggest potential immune evasion by Newcastle disease virus Sub-Genotype XIV.2 in Nigeria.Scientific reports · 2025Article
- In Silico and In Vitro Potential Antifungal Insights of Insect-Derived Peptides in the Management ofInternational journal of molecular sciences · 2025Article
- PepFuNN: Novo Nordisk Open-Source Toolkit to Enable Peptide in Silico Analysis.Journal of peptide science : an official publication of the European Peptide Society · 2025Article
- Automatic Identification of Analogue Series from Large Compound Data Sets: Methods and Applications.Molecules (Basel, Switzerland) · 2021Review
- Computer-aided drug design at Boehringer Ingelheim.Journal of computer-aided molecular design · 2017Article
- Matched Molecular Pair Analysis in Short: Algorithms, Applications and Limitations.Computational and structural biotechnology journal · 2017Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Biopharmaceuticals hold great promise for the future of drug discovery. Nevertheless, rational drug design strategies are mainly focused on the discovery of small synthetic molecules. Herein we present matched peptides, an innovative analysis technique for biological data related to peptide and protein sequences. It represents an extension of matched molecular pair analysis toward macromolecular sequence data and allows quantitative predictions of the effect of single amino acid substitutions on the basis of statistical data on known transformations. We demonstrate the application of matched peptides to a data set of major histocompatibility complex class II peptide ligands and discuss the trends captured with respect to classical quantitative structure-activity relationship approaches as well as structural aspects of the investigated protein-peptide interface. We expect our novel readily interpretable tool at the interface of cheminformatics and bioinformatics to support the rational design of biopharmaceuticals and give directions for further development of the presented methodology.
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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.