X-ray screening identifies active site and allosteric inhibitors of SARS-CoV-2 main protease.
X-ray screening identifies active site and allosteric inhibitors of SARS-CoV-2 main protease.
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DOI：
10.1126/science.abf7945
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发表时间：
2021-05-07
期刊：
影响因子：
--
通讯作者：
Meents A
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文献类型：
--
作者：
Günther S;Reinke PYA;Fernández-García Y;Lieske J;Lane TJ;Ginn HM;Koua FHM;Ehrt C;Ewert W;Oberthuer D;Yefanov O;Meier S;Lorenzen K;Krichel B;Kopicki JD;Gelisio L;Brehm W;Dunkel I;Seychell B;Gieseler H;Norton-Baker B;Escudero-Pérez B;Domaracky M;Saouane S;Tolstikova A;White TA;Hänle A;Groessler M;Fleckenstein H;Trost F;Galchenkova M;Gevorkov Y;Li C;Awel S;Peck A;Barthelmess M;Schlünzen F;Lourdu Xavier P;Werner N;Andaleeb H;Ullah N;Falke S;Srinivasan V;França BA;Schwinzer M;Brognaro H;Rogers C;Melo D;Zaitseva-Kinneberg JI;Knoska J;Peña-Murillo GE;Mashhour AR;Hennicke V;Fischer P;Hakanpää J;Meyer J;Gribbon P;Ellinger B;Kuzikov M;Wolf M;Beccari AR;Bourenkov G;von Stetten D;Pompidor G;Bento I;Panneerselvam S;Karpics I;Schneider TR;Garcia-Alai MM;Niebling S;Günther C;Schmidt C;Schubert R;Han H;Boger J;Monteiro DCF;Zhang L;Sun X;Pletzer-Zelgert J;Wollenhaupt J;Feiler CG;Weiss MS;Schulz EC;Mehrabi P;Karničar K;Usenik A;Loboda J;Tidow H;Chari A;Hilgenfeld R;Uetrecht C;Cox R;Zaliani A;Beck T;Rarey M;Günther S;Turk D;Hinrichs W;Chapman HN;Pearson AR;Betzel C;Meents A
严重急性呼吸综合征冠状病毒2（SARS-CoV-2）基因组最初表达为两个大的多聚蛋白。它的主要蛋白酶Mpro是产生功能性病毒蛋白质所必需的，使其成为关键的药物靶标。Günther等人使用X射线晶体学筛选了超过5000种化合物，这些化合物要么是批准的药物，要么是临床试验中的药物。筛选鉴定了37种与Mpro结合的化合物。高分辨率结构显示，大多数化合物结合在活性位点，但也揭示了两个变构位点，其中药物的结合导致影响活性位点的构象变化。在基于细胞的测定中，七个化合物具有抗病毒活性而没有毒性。最有效的钙肽酶在活性位点共价结合，而第二有效的pelitinib在变构位点结合。《科学》杂志，本期第642页。一个重新利用的药物库筛选揭示了SARS-CoV-2主要蛋白酶的两个变构药物结合位点。由SARS-CoV-2引起的冠状病毒疾病（COVID-19）正在给人类带来巨大的痛苦。迄今为止，没有有效的药物可用于直接治疗该疾病。在寻找抗COVID-19药物的过程中，我们对两种针对SARS-CoV-2主要蛋白酶（Mpro）的再利用药物库进行了高通量X射线晶体学筛选，该蛋白酶对病毒复制至关重要。与常用的低复杂度分子的X射线片段筛选实验相反，我们的筛选测试了已经批准的药物和临床试验中的药物。从三维蛋白质结构，我们确定了37种化合物，结合Mpro。在随后的基于细胞的病毒减少试验中，一种肽模拟物和六种非肽化合物在无毒浓度下显示出抗病毒活性。我们确定了两个变构结合位点，代表了针对SARS-CoV-2的药物开发的有吸引力的靶点。
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome is initially expressed as two large polyproteins. Its main protease, Mpro, is essential to yield functional viral proteins, making it a key drug target. Günther et al. used x-ray crystallography to screen more than 5000 compounds that are either approved drugs or drugs in clinical trials. The screen identified 37 compounds that bind to Mpro. High-resolution structures showed that most compounds bind at the active site but also revealed two allosteric sites where binding of a drug causes conformational changes that affect the active site. In cell-based assays, seven compounds had antiviral activity without toxicity. The most potent, calpeptin, binds covalently in the active site, whereas the second most potent, pelitinib, binds at an allosteric site. Science, this issue p. 642 A repurposed drug-library screen reveals two allosteric drug binding sites of the SARS-CoV-2 main protease. The coronavirus disease (COVID-19) caused by SARS-CoV-2 is creating tremendous human suffering. To date, no effective drug is available to directly treat the disease. In a search for a drug against COVID-19, we have performed a high-throughput x-ray crystallographic screen of two repurposing drug libraries against the SARS-CoV-2 main protease (Mpro), which is essential for viral replication. In contrast to commonly applied x-ray fragment screening experiments with molecules of low complexity, our screen tested already-approved drugs and drugs in clinical trials. From the three-dimensional protein structures, we identified 37 compounds that bind to Mpro. In subsequent cell-based viral reduction assays, one peptidomimetic and six nonpeptidic compounds showed antiviral activity at nontoxic concentrations. We identified two allosteric binding sites representing attractive targets for drug development against SARS-CoV-2.
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影响因子：
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作者：
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通讯作者：
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影响因子：
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作者：
Kuzikov M;Costanzi E;Reinshagen J;Esposito F;Vangeel L;Wolf M;Ellinger B;Claussen C;Geisslinger G;Corona A;Iaconis D;Talarico C;Manelfi C;Cannalire R;Rossetti G;Gossen J;Albani S;Musiani F;Herzog K;Ye Y;Giabbai B;Demitri N;Jochmans D;Jonghe S;Rymenants J;Summa V;Tramontano E;Beccari AR;Leyssen P;Storici P;Neyts J;Gribbon P;Zaliani A
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Zaliani A
原始：一种预测蛋白质配合物中互变异物和质子化态的整体方法。
影响因子：
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作者：
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通讯作者：
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影响因子：
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作者：
Erlichman, Charles;Hidalgo, Manuel;Rowinsky, Eric K.
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DOI：
10.1107/s2059798320003198
发表时间：
2020-04-01
影响因子：
2.2
作者：
Beilsten-Edmands, James;Winter, Graeme;Evans, Gwyndaf
通讯作者：
Evans, Gwyndaf