Molecular Mimicry Map of SARS-CoV-2

Introduction

Molecular Mimicry Map of SARS-CoV-2 Graph Setting Panel

General Setting

Plot height is

pixels

B Cell Cross-Reactivity Prediction Data

Y axis represents

Size of point (or width of line) represents

Opacity of point represents

Plot top

most significant

for window size of

amino acids.

Represent each alignment with a

on a

image.

T Cell Cross-Reactivity Prediction Data

Y axis represents

Plot top

most significant

for MHC class I and II molecules.

Represent each pair of predicted binding scores with a

(human/virus) on a

image.

Tracks

Mutation Counts

Accessible Surface

IEDB Positive T-Cell Assay Counts

MHC-I Binding Peptide Counts (MHCflurry)

MHC-I Ligand Processing Score Pred. (MHCflurry)

IEDB Positive B-Cell Assay Counts

MHC-II Binding Peptide Counts (netMHCIIpan)

Linear B-Cell Epitope Pred. Score (BepiPred)

Y-axis:

from 0 to

Molecular Mimicry Map of SARS-CoV-2

Supplementary Graph Setting Panel

B Cell Cross-Reactivity Prediction Metrics

Select columns

T Cell Cross-Reactivity Prediction Metrics

Select columns

Human Protein Metrics

Select columns

Data Tables

datatable

Expression

Single Cell Expression

Publication

GTEx Expression

Aligned Sequences

Aligned Structures

Virus Protein Structure

Human Protein Structure

Choose FASTA files for Peptide Vaccine Candidate Inputs

Load Local Fasta Files

Usage of files

Files will be loaded and processed locally in the internet browser and will not be uploaded to any kind of servers.

Loading Multiple FASTA Files

When multiple files are be given, duplicated header lines of peptide will be appended by "_dup_{duplicate index}".

Choose FASTA file(s)

Load Peptide Vaccine Candidates from OptiVax

OptiVax citation:
Liu, G., Carter, B., Bricken, T., Jain, S., Viard, M., Carrington, M., & Gifford, D. K. (2020). Computationally Optimized SARS-CoV-2 MHC Class I and II Vaccine Formulations Predicted to Target Human Haplotype Distributions. Cell systems, 11(2), 131–144.e6.

Select Peptides for Peptide-Based Vaccine Design

Automatic Selection through Thresholding

Include Exclude

Above Below

Manual Selection Setting

Show Info. Include Exclude

when click/select peptides with mousepointer/lasso/box.

Generate Peptides for Peptide-Based Vaccine Design

Generate peptides from the consensus SARS-CoV-2 protein sequences

Peptides are

amino acids in length.

Total number of peptides:

Keyboard Shortcuts

General

Press Ctrl or Cmd + s(screenshot) to capture the current view and download it as a PNG file

Press Ctrl or Cmd + i(introduction) to toggle the introduction and instructions

Press Ctrl or Cmd + a(information on hover) to toggle the click/hover events of the main graph.

Press Ctrl or Cmd + h(help messages) to toggle tooltip messages that are shown when mouse pointers are on buttons.

Press Ctrl or Cmd + u(UP) to move to the top of the page.

Press Ctrl or Cmd + d(Down) to move to the bottom of the page.

Peptide Vaccine Design

Press a(add) when clicking/selecting peptides to include peptides in the selection.

Press r(remove) when clicking/selecting peptides to exclude peptides from the selection.

Press Ctrl or Cmd + r(reset) to reset selection of peptides.

Panel Control

Press Ctrl or Cmd + b(B-cell Cross Reactivity Pred.) to show/hide the parallel coordinates plot showing B-cell cross reactivity prediction metrics

Press Ctrl or Cmd + g(T-cell Cross Reactivity Pred.) to show/hide the parallel coordinates plot showing T-cell cross reactivity prediction metrics

Press Ctrl or Cmd + p(Human Protein) to show/hide the parallel coordinates plot for filtering human proteins

Press Ctrl or Cmd + t(Table) to show/hide the DataTable panel

Molecular Mimicry Map of SARS-CoV-2

Documentation
Citation
Feedback

Introduction

Download Documentation

introduction images

Abstract

The development of autoimmune diseases following SARS-CoV-2 infection, including multisystem inflammatory syndrome, has been reported, and several mechanisms have been suggested, including molecular mimicry. We developed a scalable, comparative immunoinformatics pipeline called cross-reactive-epitope-search-using-structural-properties-of-proteins (CRESSP) to identify cross-reactive epitopes between a collection of SARS-CoV-2 proteomes and the human proteome using the structural properties of the proteins. Overall, by searching 4 911 245 proteins from 196 352 SARS-CoV-2 genomes, we identified 133 and 648 human proteins harboring potential cross-reactive B-cell and CD8+ T-cell epitopes, respectively. To demonstrate the robustness of our pipeline, we predicted the cross-reactive epitopes of coronavirus spike proteins, which were recognized by known cross-neutralizing antibodies. Using single-cell expression data, we identified PARP14 as a potential target of intermolecular epitope spreading between the virus and human proteins. Finally, we developed a web application (https://ahs2202.github.io/3M/) to interactively visualize our results. We also made our pipeline available as an open-source CRESSP package (https://pypi.org/project/cressp/), which can analyze any two proteomes of interest to identify potentially cross-reactive epitopes between the proteomes. Overall, our immunoinformatic resources provide a foundation for the investigation of molecular mimicry in the pathogenesis of autoimmune and chronic inflammatory diseases following COVID-19.

Our Publication

Usages

Explore cross-reactive immune epitopes

Visualize Aligned Structures

Filter cross-reactive immune epitopes

Visualize Aligned Structures

This program has been developed by Hyunsu An at Gwangju Institute of Science and Technology under the supervision of Professor JiHwan Park.