[HTML][HTML] Predicting peptide presentation by major histocompatibility complex class I: an improved machine learning approach to the immunopeptidome
Background To further our understanding of immunopeptidomics, improved tools are
needed to identify peptides presented by major histocompatibility complex class I (MHC-I) …
needed to identify peptides presented by major histocompatibility complex class I (MHC-I) …
Predicted MHC peptide binding promiscuity explains MHC class I 'hotspots' of antigen presentation defined by mass spectrometry eluted ligand data
Peptides that bind to and are presented by MHC class I and class II molecules collectively
make up the immunopeptidome. In the context of vaccine development, an understanding of …
make up the immunopeptidome. In the context of vaccine development, an understanding of …
[HTML][HTML] MS2Rescore: data-driven rescoring dramatically boosts immunopeptide identification rates
A Declercq, R Bouwmeester, A Hirschler… - Molecular & Cellular …, 2022 - ASBMB
Immunopeptidomics aims to identify major histocompatibility complex (MHC)-presented
peptides on almost all cells that can be used in anti-cancer vaccine development. However …
peptides on almost all cells that can be used in anti-cancer vaccine development. However …
NetMHCpan-4.0: improved peptide–MHC class I interaction predictions integrating eluted ligand and peptide binding affinity data
Cytotoxic T cells are of central importance in the immune system's response to disease.
They recognize defective cells by binding to peptides presented on the cell surface by MHC …
They recognize defective cells by binding to peptides presented on the cell surface by MHC …
[HTML][HTML] MHCSeqNet: a deep neural network model for universal MHC binding prediction
Background Immunotherapy is an emerging approach in cancer treatment that activates the
host immune system to destroy cancer cells expressing unique peptide signatures …
host immune system to destroy cancer cells expressing unique peptide signatures …
Evaluation of machine learning methods to predict peptide binding to MHC Class I proteins
Binding of peptides to Major Histocompatibility Complex (MHC) proteins is a critical step in
immune response. Peptides bound to MHCs are recognized by CD8+ (MHC Class I) and …
immune response. Peptides bound to MHCs are recognized by CD8+ (MHC Class I) and …
DeepLigand: accurate prediction of MHC class I ligands using peptide embedding
H Zeng, DK Gifford - Bioinformatics, 2019 - academic.oup.com
Motivation The computational modeling of peptide display by class I major histocompatibility
complexes (MHCs) is essential for peptide-based therapeutics design. Existing …
complexes (MHCs) is essential for peptide-based therapeutics design. Existing …
Computational tools for the identification and interpretation of sequence motifs in immunopeptidomes
Recent advances in proteomics and mass‐spectrometry have widely expanded the
detectable peptide repertoire presented by major histocompatibility complex (MHC) …
detectable peptide repertoire presented by major histocompatibility complex (MHC) …
[PDF][PDF] Accurate modeling of peptide-MHC structures with AlphaFold
V Mikhaylov, CA Brambley, GLJ Keller, AG Arbuiso… - Structure, 2024 - cell.com
Major histocompatibility complex (MHC) proteins present peptides on the cell surface for T
cell surveillance. Reliable in silico prediction of which peptides would be presented and …
cell surveillance. Reliable in silico prediction of which peptides would be presented and …
MetaMHC: a meta approach to predict peptides binding to MHC molecules
X Hu, W Zhou, K Udaka, H Mamitsuka… - Nucleic acids …, 2010 - academic.oup.com
As antigenic peptides binding to major histocompatibility complex (MHC) molecules is the
prerequisite of cellular immune responses, an accurate computational predictor will be of …
prerequisite of cellular immune responses, an accurate computational predictor will be of …