Persistent Laplacian projected Omicron BA.4 and BA.5 to become new dominating variants

被引:38
作者
Chen, Jiahui [1 ]
Qiu, Yuchi [1 ]
Wang, Rui [1 ]
Wei, Guo-Wei [1 ,2 ,3 ]
机构
[1] Michigan State Univ, Dept Math, E Lansing, MI 48824 USA
[2] Michigan State Univ, Dept Elect & Comp Engn, E Lansing, MI 48824 USA
[3] Michigan State Univ, Dept Biochem & Mol Biol, E Lansing, MI 48824 USA
基金
美国国家科学基金会;
关键词
SARS-CoV-2; Evolution; Infectivity; Deep learning; Persistent Laplacian; RESPIRATORY-SYNDROME-CORONAVIRUS; AFFINITY CHANGES; PROTEIN; MUTATIONS; TOPOLOGY; DATABASE; ACE2; AB;
D O I
10.1016/j.compbiomed.2022.106262
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Due to its high transmissibility, Omicron BA.1 ousted the Delta variant to become a dominating variant in late 2021 and was replaced by more transmissible Omicron BA.2 in March 2022. An important question is which new variants will dominate in the future. Topology-based deep learning models have had tremendous success in forecasting emerging variants in the past. However, topology is insensitive to homotopic shape evolution in virus-human protein-protein binding, which is crucial to viral evolution and transmission. This challenge is tackled with persistent Laplacian, which is able to capture both the topological change and homotopic shape evolution of data. Persistent Laplacian-based deep learning models are developed to systematically evaluate variant infectivity. Our comparative analysis of Alpha, Beta, Gamma, Delta, Lambda, Mu, and Omicron BA.1, BA.1.1, BA.2, BA.2.11, BA.2.12.1, BA.3, BA.4, and BA.5 unveils that Omicron BA.2.11, BA.2.12.1, BA.3, BA.4, and BA.5 are more contagious than BA.2. In particular, BA.4 and BA.5 are about 36% more infectious than BA.2 and are projected to become new dominant variants by natural selection. Moreover, the proposed models outperform the state-of-the-art methods on three major benchmark datasets for mutation-induced protein- protein binding free energy changes. Our key projection about BA4 and BA.5's dominance made on May 1, 2022 (see arXiv:2205.00532) became a reality in late June 2022.
引用
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页数:9
相关论文
共 61 条
[1]   Signatures in SARS-CoV-2 spike protein conferring escape to neutralizing antibodies [J].
Alenquer, Marta ;
Ferreira, Filipe ;
Lousa, Diana ;
Valerio, Mariana ;
Medina-Lopes, Monica ;
Bergman, Marie-Louise ;
Goncalves, Juliana ;
Demengeot, Jocelyne ;
Leite, Ricardo B. ;
Lilue, Jingtao ;
Ning, Zemin ;
Penha-Goncalves, Carlos ;
Soares, Helena ;
Soares, Claudio M. ;
Amorim, Maria Joao .
PLOS PATHOGENS, 2021, 17 (08)
[2]  
[Anonymous], BA2 REINFECTION
[3]   Categorification of Persistent Homology [J].
Bubenik, Peter ;
Scott, Jonathan A. .
DISCRETE & COMPUTATIONAL GEOMETRY, 2014, 51 (03) :600-627
[4]   Representability of algebraic topology for biomolecules in machine learning based scoring and virtual screening [J].
Cang, Zixuan ;
Mu, Lin ;
Wei, Guo-Wei .
PLOS COMPUTATIONAL BIOLOGY, 2018, 14 (01)
[5]   TopologyNet: Topology based deep convolutional and multi-task neural networks for biomolecular property predictions [J].
Cang, Zixuan ;
Wei, Guowei .
PLOS COMPUTATIONAL BIOLOGY, 2017, 13 (07)
[6]   TOPOLOGY AND DATA [J].
Carlsson, Gunnar .
BULLETIN OF THE AMERICAN MATHEMATICAL SOCIETY, 2009, 46 (02) :255-308
[7]   Omicron BA.2 (B.1.1.529.2): High Potential for Becoming the Next Dominant Variant [J].
Chen, Jiahui ;
Wei, Guo-Wei .
JOURNAL OF PHYSICAL CHEMISTRY LETTERS, 2022, 13 (17) :3840-3849
[8]   Omicron Variant (B.1.1.529): Infectivity, Vaccine Breakthrough, and Antibody Resistance [J].
Chen, Jiahui ;
Wang, Rui ;
Gilby, Nancy Benovich ;
Wei, Guo-Wei .
JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2022, 62 (02) :412-422
[9]   Prediction and mitigation of mutation threats to COVID-19 vaccines and antibody therapies [J].
Chen, Jiahui ;
Gao, Kaifu ;
Wang, Rui ;
Wei, Guo-Wei .
CHEMICAL SCIENCE, 2021, 12 (20) :6929-6948
[10]  
Chen JH, 2021, J MOL BIOL, V433, DOI [10.1016/j.jmb.2021.167155, 10.1101/2021.04.12.439473]