SAS: A Platform of Spike Antigenicity for SARS-CoV-2.
SAS: A Platform of Spike Antigenicity for SARS-CoV-2.
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SAS：SARS-CoV-2 刺突抗原性平台
DOI：
10.3389/fcell.2021.713188
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发表时间：
2021
影响因子：
5.5
通讯作者：
Cao Z
中科院分区：
文献类型：
--
作者：
Zhang L;Cao R;Mao T;Wang Y;Lv D;Yang L;Tang Y;Zhou M;Ling Y;Zhang G;Qiu T;Cao Z
Since the outbreak of SARS-CoV-2, antigenicity concerns continue to linger with emerging mutants. As recent variants have shown decreased reactivity to previously determined monoclonal antibodies (mAbs) or sera, monitoring the antigenicity change of circulating mutants is urgently needed for vaccine effectiveness. Currently, antigenic comparison is mainly carried out by immuno-binding assays. Yet, an online predicting system is highly desirable to complement the targeted experimental tests from the perspective of time and cost. Here, we provided a platform of SAS (Spike protein Antigenicity for SARS-CoV-2), enabling predicting the resistant effect of emerging variants and the dynamic coverage of SARS-CoV-2 antibodies among circulating strains. When being compared to experimental results, SAS prediction obtained the consistency of 100% on 8 mAb-binding tests with detailed epitope covering mutational sites, and 80.3% on 223 anti-serum tests. Moreover, on the latest South Africa escaping strain (B.1.351), SAS predicted a significant resistance to reference strain at multiple mutated epitopes, agreeing well with the vaccine evaluation results. SAS enables auto-updating from GISAID, and the current version collects 867K GISAID strains, 15.4K unique spike (S) variants, and 28 validated and predicted epitope regions that include 339 antigenic sites. Together with the targeted immune-binding experiments, SAS may be helpful to reduce the experimental searching space, indicate the emergence and expansion of antigenic variants, and suggest the dynamic coverage of representative mAbs/vaccines among the latest circulating strains. SAS can be accessed at https://www.biosino.org/sas.
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DOI：
10.1074/jbc.m603275200
发表时间：
2006-11-10
期刊：
The Journal of biological chemistry
影响因子：
--
作者：
Hwang WC;Lin Y;Santelli E;Sui J;Jaroszewski L;Stec B;Farzan M;Marasco WA;Liddington RC
通讯作者：
Liddington RC
DOI：
10.1056/nejmoa2035389
发表时间：
2021-02-04
期刊：
The New England journal of medicine
影响因子：
--
作者：
Baden LR;El Sahly HM;Essink B;Kotloff K;Frey S;Novak R;Diemert D;Spector SA;Rouphael N;Creech CB;McGettigan J;Khetan S;Segall N;Solis J;Brosz A;Fierro C;Schwartz H;Neuzil K;Corey L;Gilbert P;Janes H;Follmann D;Marovich M;Mascola J;Polakowski L;Ledgerwood J;Graham BS;Bennett H;Pajon R;Knightly C;Leav B;Deng W;Zhou H;Han S;Ivarsson M;Miller J;Zaks T;COVE Study Group
通讯作者：
COVE Study Group
DOI：
10.1126/science.abf6950
发表时间：
2021-03-12
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
McCarthy KR;Rennick LJ;Nambulli S;Robinson-McCarthy LR;Bain WG;Haidar G;Duprex WP
通讯作者：
Duprex WP
DOI：
10.1093/bioinformatics/btaa739
发表时间：
2021-05-05
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Raybould, Matthew I J;Kovaltsuk, Aleksandr;Deane, Charlotte M
通讯作者：
Deane, Charlotte M
影响因子：
30.3
作者：
Greaney, Allison J;Starr, Tyler N;Bloom, Jesse D
通讯作者：
Bloom, Jesse D