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. 2003 Nov 17;13(22):3989-92.
doi: 10.1016/j.bmcl.2003.08.066.

Identifying inhibitors of the SARS coronavirus proteinase

Affiliations

Identifying inhibitors of the SARS coronavirus proteinase

Ekachai Jenwitheesuk et al. Bioorg Med Chem Lett. .

Abstract

The Severe Acute Respiratory Syndrome (SARS) is a serious respiratory illness that has recently been reported in parts of Asia and Canada. In this study, we use molecular dynamics (MD) simulations and docking techniques to screen 29 approved and experimental drugs against the theoretical model of the SARS CoV proteinase as well as the experimental structure of the transmissible gastroenteritis virus (TGEV) proteinase. Our predictions indicate that existing HIV-1 protease inhibitors, L-700,417 for instance, have high binding affinities and may provide good starting points for designing SARS CoV proteinase inhibitors.

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Figures

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Graphical abstract
Figure 1
Figure 1
Predicted binding affinities of 29 compounds to the TGEV proteinase. The calculated binding energies are converted into inhibitory constants (Ki) to give a measure of the binding affinities (the lower the Ki the greater the binding affinities). AG7088, shown in orange, is the inhibitor proposed by the authors of the model of the SARS CoV proteinase. The compound with the highest binding affinity is L-700,417, shown in green.
Figure 2
Figure 2
Comparison of the predicted binding modes of the TGEV proteinase and its putative inhibitors: (a) depicts the binding mode of the inhibitor, AG7088, proposed by Anand et al., to the TGEV proteinase structure; (b) depicts the binding mode of the inhibitor L-700,417 (VAC) predicted to have the highest affinity using the molecular dynamics simulation and docking techniques. The AG7088 inhibitor only partially fits into the binding pocket that the substrate would occupy, whereas the inhibitor with the highest binding affinity, L-700,417, mimics the substrate binding mode very well.
Figure 3
Figure 3
Chemical structures of AG7088 and L-70,417 (VAC).

References

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