ArticleFrontiers in immunology2021
Information-Driven Docking for TCR-pMHC Complex Prediction.
Article in Frontiers in immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 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
17 citing papers in PubMed.
- Structural T-Cell Receptor Analysis in the Age of Machine Learning.Immunological reviews · 2026Review
- SwiftTCR: efficient computational docking protocol of TCRpMHC-I complexes using restricted rotation matrices.Briefings in bioinformatics · 2026Article
- Article
- A roadmap for T cell receptor-peptide-bound major histocompatibility complex binding prediction by machine learning: glimpse and foresight.Briefings in bioinformatics · 2025Review
- Exploring Placental Protein-Target Protein Interactions:Current protein & peptide science · 2025Article
- AI/ML-empowered approaches for predicting T Cell-mediated immunity and beyond.Frontiers in immunology · 2025Article
- Strengths and limitations of web servers for the modeling of TCRpMHC complexes.Computational and structural biotechnology journal · 2024Article
- Using In silico models to predict lymphocyte activation and development in a data rich era.Immunoinformatics (Amsterdam, Netherlands) · 2024Article
- Can AlphaFold's breakthrough in protein structure help decode the fundamental principles of adaptive cellular immunity?Nature methods · 2024Review
- Review
- Developing a universal multi-epitope protein vaccine candidate for enhanced borna virus pandemic preparedness.Frontiers in immunology · 2024Article
- Molecular mechanism of phosphopeptide neoantigen immunogenicity.Nature communications · 2023Article
- CrossDome: an interactive R package to predict cross-reactivity risk using immunopeptidomics databases.Frontiers in immunology · 2023Article
- Large-scale template-based structural modeling of T-cell receptors with known antigen specificity reveals complementarity features.Frontiers in immunology · 2023Article
- Insight into the first multi-epitope-based peptide subunit vaccine against avian influenza A virus (H5N6): An immunoinformatics approach.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2022Article
- Peptide-Based Vaccines for Tuberculosis.Frontiers in immunology · 2022Review
- Predicting T Cell Receptor Antigen Specificity From Structural Features Derived From Homology Models of Receptor-Peptide-Major Histocompatibility Complexes.Frontiers in physiology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
T cell receptor (TCR) recognition of peptides presented by major histocompatibility complex (MHC) molecules is a fundamental process in the adaptive immune system. An understanding of this recognition process at the molecular level is crucial for TCR based therapeutics and vaccine design. The broad nature of TCR diversity and cross-reactivity presents a challenge for traditional structural resolution. Computational modelling of TCR-pMHC complexes offers an efficient alternative. This study compares the ability of four general-purpose docking platforms (ClusPro, LightDock, ZDOCK and HADDOCK) to make use of varying levels of binding interface information for accurate TCR-pMHC modelling. Each platform was tested on an expanded benchmark set of 44 TCR-pMHC docking cases. In general, HADDOCK is shown to be the best performer. Docking strategy guidance is provided to obtain the best models for each platform for future research. The TCR-pMHC docking cases used in this study can be downloaded from https://github.com/innate2adaptive/ExpandedBenchmark.
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.