A multi-pronged approach targeting SARS-CoV-2 proteins using ultra-large virtual screening.
A multi-pronged approach targeting SARS-CoV-2 proteins using ultra-large virtual screening.
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DOI:
10.1016/j.isci.2020.102021
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发表时间:
2021-02-19
期刊:
影响因子:
5.8
通讯作者:
Arthanari H
中科院分区:
文献类型:
--
作者:
Gorgulla C;Padmanabha Das KM;Leigh KE;Cespugli M;Fischer PD;Wang ZF;Tesseyre G;Pandita S;Shnapir A;Calderaio A;Gechev M;Rose A;Lewis N;Hutcheson C;Yaffe E;Luxenburg R;Herce HD;Durmaz V;Halazonetis TD;Fackeldey K;Patten JJ;Chuprina A;Dziuba I;Plekhova A;Moroz Y;Radchenko D;Tarkhanova O;Yavnyuk I;Gruber C;Yust R;Payne D;Näär AM;Namchuk MN;Davey RA;Wagner G;Kinney J;Arthanari H
The unparalleled global effort to combat the continuing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic over the last year has resulted in promising prophylactic measures. However, a need still exists for cheap, effective therapeutics, and targeting multiple points in the viral life cycle could help tackle the current, as well as future, coronaviruses. Here, we leverage our recently developed, ultra-large-scale in silico screening platform, VirtualFlow, to search for inhibitors that target SARS-CoV-2. In this unprecedented structure-based virtual campaign, we screened roughly 1 billion molecules against each of 40 different target sites on 17 different potential viral and host targets. In addition to targeting the active sites of viral enzymes, we also targeted critical auxiliary sites such as functionally important protein-protein interactions. SARS-CoV-2 related proteins were targeted in ultra-large in silico screens. Multiple functional sites on individual target proteins were screened. 17 virus-related targets, 45 screens, and ∼50 billion docking instances were covered. Conservation in some target sites means hits could exhibit pan-coronavirus function. Screening results are available as an interactive web resource and for download. Drugs; High-Performance Computing in Bioinformatics; Structural Biology; Virology
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影响因子:
3.7
作者:
Warren S;Wan XF;Conant G;Korkin D
通讯作者:
Korkin D
影响因子:
56.9
作者:
Anand, K;Ziebuhr, J;Hilgenfeld, R
通讯作者:
Hilgenfeld, R
影响因子:
64.5
作者:
Bouhaddou, Mehdi;Memon, Danish;Krogan, Nevan J.
通讯作者:
Krogan, Nevan J.
影响因子:
7.6
作者:
Báez-Santos YM;St John SE;Mesecar AD
通讯作者:
Mesecar AD
DOI:
10.1038/mt.2013.284
发表时间:
2014-03
期刊:
Molecular therapy : the journal of the American Society of Gene Therapy
影响因子:
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作者:
通讯作者:
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