Literature DB >> 29960884

MHCflurry: Open-Source Class I MHC Binding Affinity Prediction.

Timothy J O'Donnell1, Alex Rubinsteyn2, Maria Bonsack3, Angelika B Riemer3, Uri Laserson2, Jeff Hammerbacher4.   

Abstract

Predicting the binding affinity of major histocompatibility complex I (MHC I) proteins and their peptide ligands is important for vaccine design. We introduce an open-source package for MHC I binding prediction, MHCflurry. The software implements allele-specific neural networks that use a novel architecture and peptide encoding scheme. When trained on affinity measurements, MHCflurry outperformed the standard predictors NetMHC 4.0 and NetMHCpan 3.0 overall and particularly on non-9-mer peptides in a benchmark of ligands identified by mass spectrometry. The released predictor, MHCflurry 1.2.0, uses mass spectrometry datasets for model selection and showed competitive accuracy with standard tools, including the recently released NetMHCpan 4.0, on a small benchmark of affinity measurements. MHCflurry's prediction speed exceeded 7,000 predictions per second, 396 times faster than NetMHCpan 4.0. MHCflurry is freely available to use, retrain, or extend, includes Python library and command line interfaces, may be installed using package managers, and applies software development best practices.
Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  HLA; MHC; epitope prediction; neural network

Mesh:

Substances:

Year:  2018        PMID: 29960884     DOI: 10.1016/j.cels.2018.05.014

Source DB:  PubMed          Journal:  Cell Syst        ISSN: 2405-4712            Impact factor:   10.304


  104 in total

1.  Quantification of Uncertainty in Peptide-MHC Binding Prediction Improves High-Affinity Peptide Selection for Therapeutic Design.

Authors:  Haoyang Zeng; David K Gifford
Journal:  Cell Syst       Date:  2019-06-05       Impact factor: 10.304

2.  HLA-Arena: A Customizable Environment for the Structural Modeling and Analysis of Peptide-HLA Complexes for Cancer Immunotherapy.

Authors:  Dinler A Antunes; Jayvee R Abella; Sarah Hall-Swan; Didier Devaurs; Anja Conev; Mark Moll; Gregory Lizée; Lydia E Kavraki
Journal:  JCO Clin Cancer Inform       Date:  2020-07

3.  Markov state modeling reveals alternative unbinding pathways for peptide-MHC complexes.

Authors:  Jayvee R Abella; Dinler Antunes; Kyle Jackson; Gregory Lizée; Cecilia Clementi; Lydia E Kavraki
Journal:  Proc Natl Acad Sci U S A       Date:  2020-11-12       Impact factor: 11.205

4.  A comprehensive review and performance evaluation of bioinformatics tools for HLA class I peptide-binding prediction.

Authors:  Shutao Mei; Fuyi Li; André Leier; Tatiana T Marquez-Lago; Kailin Giam; Nathan P Croft; Tatsuya Akutsu; A Ian Smith; Jian Li; Jamie Rossjohn; Anthony W Purcell; Jiangning Song
Journal:  Brief Bioinform       Date:  2020-07-15       Impact factor: 11.622

5.  The Human Immunopeptidome Project: A Roadmap to Predict and Treat Immune Diseases.

Authors:  Juan Antonio Vizcaíno; Peter Kubiniok; Kevin A Kovalchik; Qing Ma; Jérôme D Duquette; Ian Mongrain; Eric W Deutsch; Bjoern Peters; Alessandro Sette; Isabelle Sirois; Etienne Caron
Journal:  Mol Cell Proteomics       Date:  2019-11-19       Impact factor: 5.911

6.  Mass Spectrometry Based Immunopeptidomics Leads to Robust Predictions of Phosphorylated HLA Class I Ligands.

Authors:  Marthe Solleder; Philippe Guillaume; Julien Racle; Justine Michaux; Hui-Song Pak; Markus Müller; George Coukos; Michal Bassani-Sternberg; David Gfeller
Journal:  Mol Cell Proteomics       Date:  2019-12-17       Impact factor: 5.911

7.  Current challenges for unseen-epitope TCR interaction prediction and a new perspective derived from image classification.

Authors:  Pieter Moris; Joey De Pauw; Anna Postovskaya; Sofie Gielis; Nicolas De Neuter; Wout Bittremieux; Benson Ogunjimi; Kris Laukens; Pieter Meysman
Journal:  Brief Bioinform       Date:  2021-07-20       Impact factor: 11.622

8.  Neoantigen Dissimilarity to the Self-Proteome Predicts Immunogenicity and Response to Immune Checkpoint Blockade.

Authors:  Lee P Richman; Robert H Vonderheide; Andrew J Rech
Journal:  Cell Syst       Date:  2019-10-09       Impact factor: 10.304

9.  Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction.

Authors:  Daniel K Wells; Marit M van Buuren; Kristen K Dang; Vanessa M Hubbard-Lucey; Kathleen C F Sheehan; Katie M Campbell; Andrew Lamb; Jeffrey P Ward; John Sidney; Ana B Blazquez; Andrew J Rech; Jesse M Zaretsky; Begonya Comin-Anduix; Alphonsus H C Ng; William Chour; Thomas V Yu; Hira Rizvi; Jia M Chen; Patrice Manning; Gabriela M Steiner; Xengie C Doan; Taha Merghoub; Justin Guinney; Adam Kolom; Cheryl Selinsky; Antoni Ribas; Matthew D Hellmann; Nir Hacohen; Alessandro Sette; James R Heath; Nina Bhardwaj; Fred Ramsdell; Robert D Schreiber; Ton N Schumacher; Pia Kvistborg; Nadine A Defranoux
Journal:  Cell       Date:  2020-10-09       Impact factor: 41.582

10.  Graph-theoretical formulation of the generalized epitope-based vaccine design problem.

Authors:  Emilio Dorigatti; Benjamin Schubert
Journal:  PLoS Comput Biol       Date:  2020-10-23       Impact factor: 4.475

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