Crystal structure of SARS-CoV-2 main protease provides a basis for design of improved α-ketoamide inhibitors

By Linlin Zhang, Daizong Lin, Xinyuanyuan Sun, U. Curth, Christian Drosten, Lucie Sauerhering, S. Becker, K. Rox, Rolf Hilgenfeld. Science, 2020

2,780 citations recorded by the source corpus.

Targeting a key enzyme in SARS-CoV-2 Scientists across the world are working to understand severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (COVID-19). Zhang et al. determined the x-ray crystal structure of a key protein in the virus' life cycle: the main protease. This enzyme cuts the polyproteins translated from viral RNA to yield functional viral proteins. The authors also developed a lead compound into a potent inhibitor and obtained a structure with the inhibitor bound, work that may provide a basis for development of anticoronaviral drugs. Science, this issue p. 409 Optimized inhibitor of a key enzyme of the novel coronavirus exhibits pronounced lung tropism. The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2) is a global health emergency. An attractive drug target among coronaviruses is the main protease (Mpro, also called 3CLpro) because of its essential role in processing the polyproteins that are translated from the viral RNA. We report the x-ray structures of the unliganded SARS-CoV-2 Mpro and its complex with an α-ketoamide inhibitor. This was derived from a previously designed inhibitor but with the P3-P2 amide bond incorporated into a pyridone ring to enhance the half-life of the compound in plasma. On the basis of the unliganded structure, we developed the lead compound into a potent inhibitor of the SARS-CoV-2 Mpro. The pharmacokinetic characterization of the optimized inhibitor reveals a pronounced lung tropism and suitability for administration by the inhalative route.

Subfields: Computational Theory and Mathematics, Infectious Diseases, Materials Chemistry

View Paper: https://www.semanticscholar.org/paper/fe378a510b608779e06e6d6227d4bf3c40fbb685

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

  1. Junmei Wang
  2. Kaveh Memarzadeh
  3. Adam Bohr

In Infectious Diseases

  1. Junmei Wang

In Materials Chemistry

  1. Junmei Wang
  2. Kaveh Memarzadeh
  3. Adam Bohr

Citations in the corpus