Back

Erythrocyte-targeted immunomodulatory antigens enabled by in vivo selection of D-peptides

Loftis, A. R.; Zhang, G.; Backlund, C.; Quartararo, A. J.; Pishesha, N.; Schissel, C. K.; Garafola, D.; Loas, A.; Collier, R. J.; Ploegh, H.; Irvine, D. J.; Pentelute, B. L.

2020-07-15 bioengineering
10.1101/2020.07.15.203331 bioRxiv
Show abstract

Targeting of antigens to erythrocytes can be used to selectively mitigate their immunogenicity, but the methods to equip a variety of cargoes with erythrocyte-targeting properties are limited. Here we identified a D-peptide that targets murine erythrocytes and decreases anti-drug antibody responses when conjugated to the protective antigen from Bacillus anthracis, a protein of therapeutic interest. The D-peptide likewise decreases inflammatory anti-ovalbumin (OVA) CD8+ T cell responses when attached to a peptide antigen derived from OVA. To discover this targeting ligand, we leveraged mass spectrometry to decode a randomized D-peptide library selected in mice, extending the application of synthetic libraries to in vivo affinity selections.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
Nature Communications
○ 5641 papers in training set
Top 8%
18.9%
Similar papers in this journal
2
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 2%
12.2%
Similar papers in this journal
3
ACS Chemical Biology
● 167 papers in training set
Top 0.3%
7.4%
Similar papers in this journal
4
eLife
● 5828 papers in training set
Top 21%
5.6%
Similar papers in this journal
5
Journal of the American Chemical Society
● 217 papers in training set
Top 0.7%
5.3%
Similar papers in this journal
6
Science Advances
● 1243 papers in training set
Top 7%
4.5%
50% of probability mass above
7
Nature Chemical Biology
○ 119 papers in training set
Top 0.6%
4.1%
8
Nature Biomedical Engineering
○ 47 papers in training set
Top 0.3%
3.6%
9
Bioconjugate Chemistry
● 20 papers in training set
Top 0.1%
2.8%
10
Cell Chemical Biology
○ 94 papers in training set
Top 0.5%
2.4%
11
Advanced Science
○ 286 papers in training set
Top 4%
1.9%
12
Communications Biology
○ 993 papers in training set
Top 13%
1.8%
13
ACS Nano
● 113 papers in training set
Top 1%
1.8%
14
RSC Chemical Biology
● 39 papers in training set
Top 0.4%
1.2%
15
Nature Biotechnology
○ 172 papers in training set
Top 4%
1.0%
16
Angewandte Chemie International Edition
○ 93 papers in training set
Top 2%
0.9%
17
Science Signaling
● 65 papers in training set
Top 1%
0.9%
18
Scientific Reports
○ 3612 papers in training set
Top 71%
0.9%
19
PNAS Nexus
◐ 159 papers in training set
Top 3%
0.9%
20
ACS Central Science
● 71 papers in training set
Top 1%
0.9%
21
Molecular Therapy
○ 81 papers in training set
Top 2%
0.9%
22
Biomaterials
○ 84 papers in training set
Top 1%
0.9%
23
Chemical Science
● 73 papers in training set
Top 2%
0.6%
24
ACS Chemical Neuroscience
● 67 papers in training set
Top 2%
0.6%
25
PLOS ONE
● 5266 papers in training set
Top 61%
0.6%
26
Science
● 477 papers in training set
Top 10%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.