The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the greatest health crisis of this generation and already led to >6.8 million deaths world-wide. Analogous to common cold viruses, SARS-CoV-2 is expected to continue to circulate and pose a significant threat to our society. Despite promising vaccination and booster programs against COVID-19, antiviral drugs will likely be crucial to control the future outbreaks of coronaviruses. Among the proteins encoded by the SARS-CoV-2 genome, the main protease (M^pro) has emerged as a promising target. Inhibition of M^pro blocks the processing of polyproteins produced by translation of the viral RNA, which is an essential step in SARS-CoV-2 replication.

The determination of high-resolution crystal structures of SARS-CoV-2 proteins has enabled virtual screening campaigns to identify hits that can be developed into antiviral drugs. Structure-based docking algorithms can sample and score binding poses in seconds, making it possible to evaluate large libraries and this approach is not restricted to compounds that are physically available. The size of libraries with commercially available compounds is growing rapidly and >30 billion make-on-demand molecules are currently available from chemical suppliers. These libraries provide opportunities to identify potential therapeutic agents that can readily be synthesized and tested for activity, but require development of effective strategies for navigation in this enormous chemical space. We will present approaches to search for M^pro inhibitors in ultralarge chemical libraries using structure-based virtual screening. Synergy between molecular modeling, protein crystallography and organic synthesis led to the discovery of a novel broad-spectrum inhibitor of coronaviruses.

<b><i>Figure 1</i></b><i>: SARS-CoV-2 M<sup>pro</sup> in complex with a novel broad-spectrum inhibitor.</i>

Figure 1: SARS-CoV-2 M^pro in complex with a novel broad-spectrum inhibitor.

Andreas Luttens

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