Name
In silico Discovery of Potential Antiviral Compounds Against Rotavirus alphagastroenteritidis Through Structure-Based Virtual Screening
Presenter
Ricardo Gabriel Díaz Alarcón, National University of Misiones
Co-Author(s)
Ricardo Gabriel Díaz Alarcón; National Council for Scientific and Technical Research (CONICET)
Melanie Schroder; Molecular Biotechnology Laboratory. Dr. María Ebe Reca Institute of Biotechnology of Misiones. Faculty of Exact, Chemical, and Natural Sciences (FCEQyN). National University of Misiones (UNaM), Argentina.
Domingo Javier Liotta, National Institute of Tropical Medicine (INMeT)—ANLIS “Dr. Carlos Malbrán”, Puerto Iguazú CP3370,
Misiones, Argentina.
German Tráglia; Genomics and Bioinformatics Unit, Department of Biological Sciences, CENUR Litoral Norte, University of the Republic, Salto, Uruguay.
Samuel Miño; National Institute of Agricultural Technology (INTA), Argentina.
Abstract Category
Vaccines
Abstract
Rotavirus alphagastroenteritidis is a major etiological agent of acute gastroenteritis worldwide. The viral VP4 proteins plays a pivotal role in host cell recognition and entry. VP4 exhibits high genetic variability, with 58 P-genotypes identified to date. This study aimed to identify potential antiviral compounds by targeting a proposed binding pocket through structure-based virtual screening (SBVS), focused on P[4], P[6], and P[8] human genotypes.
Three-dimensional structures of the VP8* and VP5* subunits were generated using Swiss Model Server, followed by assembly and loops refinement on UCSF Chimera. The proposed binding pocket was structurally characterized and selected as target for docking simulations. For drugs repurposing, virtual screening against a FDA-approved compounds from the DrugBank database was performed. For novel candidates, the whole ZINC database was analyzed. Binding affinities were estimated based on free energies (ΔG), and top-scoring complexes were subjected to detailed 2D and 3D interaction analysis using LIGPLOT and Chimera.
From the FDA-approved compounds, n = 2,115 were found. Twenty candidates were selected, ΔG ranging from –10.2 to –8.2 kcal/mol. From the ZINC database n=22,724,825 compounds were found. One thousand compounds were selected by affinity ΔG (ΔG<-8 Kcal/mol). Chemical and structural analyses revealed that several compounds belong to known pharmacological classes, aiding potential drug repurposing strategies.
This research highlights the efficacy of computational approaches for identification of new antivirals. The selected compounds are starting points for experimental validation. Our methodology provides a scalable platform adaptable for accelerated in vitro and in vivo testing, and expansion to other clinically relevant viral targets.
Three-dimensional structures of the VP8* and VP5* subunits were generated using Swiss Model Server, followed by assembly and loops refinement on UCSF Chimera. The proposed binding pocket was structurally characterized and selected as target for docking simulations. For drugs repurposing, virtual screening against a FDA-approved compounds from the DrugBank database was performed. For novel candidates, the whole ZINC database was analyzed. Binding affinities were estimated based on free energies (ΔG), and top-scoring complexes were subjected to detailed 2D and 3D interaction analysis using LIGPLOT and Chimera.
From the FDA-approved compounds, n = 2,115 were found. Twenty candidates were selected, ΔG ranging from –10.2 to –8.2 kcal/mol. From the ZINC database n=22,724,825 compounds were found. One thousand compounds were selected by affinity ΔG (ΔG<-8 Kcal/mol). Chemical and structural analyses revealed that several compounds belong to known pharmacological classes, aiding potential drug repurposing strategies.
This research highlights the efficacy of computational approaches for identification of new antivirals. The selected compounds are starting points for experimental validation. Our methodology provides a scalable platform adaptable for accelerated in vitro and in vivo testing, and expansion to other clinically relevant viral targets.