Novel Pyrazino[1,2-<i>a</i>]indole-1,3(2<i>H</i>,4<i>H</i>)-dione Derivatives Targeting the Replication of <i>Flaviviridae</i> Viruses: Structural and Mechanistic Insights

oleh: Erofili Giannakopoulou, Ifigeneia Akrani, George Mpekoulis, Efseveia Frakolaki, Marios Dimitriou, Vassilios Myrianthopoulos, Niki Vassilaki, Grigoris Zoidis

Format: Article
Diterbitkan: MDPI AG 2024-08-01

Deskripsi

Infections with <i>Flaviviridae</i> viruses, such as hepatitis C (HCV), dengue (DENV), and yellow fever (YFV) viruses, are major public health problems worldwide. In the case of HCV, treatment is associated with drug resistance and high costs, while there is no clinically approved therapy for DENV and YFV. Consequently, there is still a need for new chemotherapies with alternative modes of action. We have previously identified novel 2-hydroxypyrazino[1,2-<i>a</i>]indole-1,3(2<i>H</i>,4<i>H</i>)-diones as metal-chelating inhibitors targeting HCV RNA replication. Here, by utilizing a structure-based approach, we rationally designed a second series of compounds by introducing various substituents at the indole core structure and at the imidic nitrogen, to improve specificity against the RNA-dependent RNA polymerase (RdRp). The resulting derivatives were evaluated for their potency against HCV genotype 1b, DENV2, and YFV-17D using stable replicon cell lines. The most favorable substitution was nitro at position 6 of the indole ring (compound <b>36</b>), conferring EC<sub>50</sub> 1.6 μM against HCV 1b and 2.57 μΜ against HCV 1a, with a high selectivity index. Compound <b>52</b>, carrying the acetohydroxamic acid functionality (-CH<sub>2</sub>CONHOH) on the imidic nitrogen, and compound <b>78</b>, the methyl-substituted molecule at the position 4 indolediketopiperazine counterpart, were the most effective against DENV and YFV, respectively. Interestingly, compound <b>36</b> had a high genetic barrier to resistance and only one resistance mutation was detected, T181I in NS5B, suggesting that the compound target HCV RdRp is in accordance with our predicted model.