Back

Antibody evasion and receptor binding of SARS-CoV-2 variants PQ.16.1.1 and RK.1

He, P.; Song, Y.; Guo, C.; Yu, L.; Yu, Y.; Jian, F.; Shao, F.; Cao, Y.

2026-07-23 immunology
10.64898/2026.07.21.739818 bioRxiv
Show abstract

The recent global expansion of the SARS-CoV-2 variant NB.1.8.1 has driven the emergence of sublineages PQ.16.1.1 and RK.1, which independently acquired the D420N mutation in their receptor-binding domains and and now dominate the Asia-Pacific region. Evaluations utilizing surface plasmon resonance and pseudovirus assays demonstrate that these sublineages exhibit significantly reduced human ACE2 receptor engagement compared to their parental strain. However, this functional cost is offset by a marked ability to evade humoral immunity, specifically demonstrating profound resistance to Class 1 neutralizing monoclonal antibodies and convalescent plasma from Wuhan-Hu-1-primed individuals. This convergent evolution exemplifies a classical viral trade-off, sacrificing receptor binding efficiency to escape population-level immune pressure. Consequently, these findings suggest these variants will soon spread globally and emphasize the critical need for ongoing surveillance to monitor D420N-carrying lineages.

Published in The Lancet Infectious Diseases (predicted rank #11) · training set

Matching journals

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

1
Cell Reports
○ 1498 papers in training set
Top 0.8%
12.9%
Similar papers in this journal
2
Nature Communications
○ 5641 papers in training set
Top 15%
12.4%
Similar papers in this journal
3
Nature
○ 645 papers in training set
Top 2%
8.7%
Similar papers in this journal
4
Immunity
○ 67 papers in training set
Top 0.1%
7.7%
Similar papers in this journal
5
Cell
○ 431 papers in training set
Top 1%
6.1%
Similar papers in this journal
6
Cell Host & Microbe
126 papers in training set
Top 0.4%
5.4%
50% of probability mass above
7
eLife
● 5828 papers in training set
Top 26%
4.8%
8
Science
● 477 papers in training set
Top 2%
3.4%
9
Cell Reports Medicine
○ 153 papers in training set
Top 1%
3.1%
10
Science Advances
● 1243 papers in training set
Top 13%
2.7%
The Lancet Infectious Diseases · published here
○ 73 papers in training set
Top 0.4%
2.7%
12
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 21%
2.4%
13
iScience
○ 1154 papers in training set
Top 12%
2.3%
14
Science Immunology
● 88 papers in training set
Top 1%
1.9%
15
Nature Medicine
○ 125 papers in training set
Top 2%
1.7%
16
Emerging Microbes & Infections
○ 74 papers in training set
Top 0.7%
1.7%
17
Nature Immunology
○ 79 papers in training set
Top 1%
1.4%
18
Science Translational Medicine
● 127 papers in training set
Top 2%
1.3%
19
Gut
● 40 papers in training set
Top 0.7%
1.1%
20
PLOS Pathogens
● 820 papers in training set
Top 8%
1.1%
21
Med
○ 39 papers in training set
Top 0.6%
1.0%
22
Communications Biology
○ 993 papers in training set
Top 31%
0.8%
23
eBioMedicine
○ 183 papers in training set
Top 7%
0.8%
24
Cell Discovery
○ 57 papers in training set
Top 1%
0.8%
25
Nature Microbiology
○ 155 papers in training set
Top 3%
0.8%
26
mBio
● 833 papers in training set
Top 11%
0.8%
27
Journal of Clinical Investigation
● 179 papers in training set
Top 6%
0.8%
28
Journal of Experimental Medicine
● 119 papers in training set
Top 3%
0.8%
29
Cell Research
○ 51 papers in training set
Top 2%
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.