Poster Abstract: When Models Fail: In Silico and Pseudotype-Identified Inhibitors Do Not Translate to Authentic CCHFV Infection

Nallely Espinoza, Research Associate II, BROAD INSTITUTE OF MIT AND HARVARD - Cambridge, MA

Abstract

Introduction: Crimean–Congo hemorrhagic fever virus (CCHFV) is a tick-borne virus that causes severe disease in humans, while licensed countermeasures remain limited. Viral entry is mediated by the M-segment glycoprotein precursor, which is processed into GP38, Gn, and Gc to enable attachment and low pH–dependent membrane fusion.

Methods: Here, we developed a vesicular stomatitis virus glycoprotein-deleted, luciferase reporter pseudotype bearing CCHFV glycoproteins (rVSV-ΔG-CCHFV-M) as a quantitative BSL-2 platform to study glycoprotein-dependent entry. Using this system, we screened a panel of 186 small molecules and identified eltrombopag olamine and quercetin as inhibitors of viral entry with low-micromolar activity and minimal cytotoxicity.

Time-of-addition and synchronized entry assays demonstrated that both compounds act during early stages of infection. To link molecular interactions with functional outcomes, we performed in silico docking and compared predicted binding sites with in vitro phenotypes. Docking analyses identified candidate interaction sites at the GP38–Gn interface and within a Gc fusion-loop pocket. Importantly, only compounds predicted to engage fusion-relevant regions inhibited membrane fusion, supporting a structure–function relationship between binding site and antiviral mechanism.

However, when advanced to validation with authentic CCHFV under BSL-4 conditions, these compounds did not demonstrate significant antiviral activity. This discrepancy highlights limitations of pseudotyped systems and docking-based predictions in fully recapitulating native viral entry and underscores the importance of orthogonal validation in high-containment models.

Conclusion: Together, these results establish a robust pseudotype-based platform for dissecting CCHFV entry while emphasizing the challenges of translating computational and in vitro findings into efficacy against authentic virus, informing future antiviral discovery strategies.