Combinatorial computational approaches to identify tetracycline derivatives as flavivirus inhibitors

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Abstract

Limited structural information of drug targets, cellular toxicity possessed by lead compounds, and large amounts of potential leads are the major issues facing the design-oriented approach of discovering new leads. In an attempt to tackle these issues, we have developed a process of virtual screening based on the observation that conformational rearrangements of the dengue virus envelope protein are essential for the mediation of viral entry into host cells via membrane fusion. Screening was based solely on the structural information of the Dengue virus envelope protein and was focused on a target site that is presumably important for the conformational rearrangements necessary for viral entry. To circumvent the issue of lead compound toxicity, we performed screening based on molecular docking using structural databases of medical compounds. To enhance the identification of hits, we further categorized and selected candidates according to their novel structural characteristics. Finally, the selected candidates were subjected to a biological validation assay to assess inhibition of Dengue virus propagation in mammalian host cells using a plaque formation assay. Among the 10 compounds examined, rolitetracycline and doxycycline significantly inhibited plaque formation, demonstrating their inhibitory effect on dengue virus propagation. Both compounds were tetracycline derivatives with IC50s estimated to be 67.1 μM and 55.6 μM, respectively. Their docked conformations displayed common hydrophobic interactions with critical residues that affected membrane fusion during viral entry. These interactions will therefore position the tetracyclic ring moieties of both inhibitors to bind firmly to the target and, subsequently, disrupt conformational rearrangement and block viral entry. This process can be applied to other drug targets in which conformational rearrangement is critical to function. © 2007 Yang et al.

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Yang, J. M., Chen, Y. F., Tu, Y. Y., Yen, K. R., & Yang, Y. L. (2007). Combinatorial computational approaches to identify tetracycline derivatives as flavivirus inhibitors. PLoS ONE, 2(5). https://doi.org/10.1371/journal.pone.0000428

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