Structure-based virtual screening of unbiased and RNA-focused libraries to identify new ligands for the HCV IRES model system
| dc.contributor.author | Kallert, Elisabeth | |
| dc.contributor.author | Rodriguez, Laura Almena | |
| dc.contributor.author | Husmann, Jan-Åke | |
| dc.contributor.author | Blatt, Kathrin | |
| dc.contributor.author | Kersten, Christian | |
| dc.date.accessioned | 2025-01-09T09:05:25Z | |
| dc.date.available | 2025-01-09T09:05:25Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | Targeting RNA including viral RNAs with small molecules is an emerging field. The hepatitis C virus internal ribosome entry site (HCV IRES) is a potential target for translation inhibitor development to raise drug resistance mutation preparedness. Using RNA-focused and unbiased molecule libraries, a structure-based virtual screening (VS) by molecular docking and pharmacophore analysis was performed against the HCV IRES subdomain IIa. VS hits were validated by a microscale thermophoresis (MST) binding assay and a Förster resonance energy transfer (FRET) assay elucidating ligand-induced conformational changes. Ten hit molecules were identified with potencies in the high to medium micromolar range proving the suitability of structure-based virtual screenings against RNA-targets. Hit compounds from a 2-guanidino-quinazoline series, like the strongest binder, compound 8b with an EC50 of 61 μM, show low molecular weight, moderate lipophilicity and reduced basicity compared to previously reported IRES ligands. There | en_GB |
| dc.identifier.doi | http://doi.org/10.25358/openscience-11203 | |
| dc.identifier.uri | https://openscience.ub.uni-mainz.de/handle/20.500.12030/11224 | |
| dc.language.iso | eng | de |
| dc.rights | CC-BY-4.0 | * |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | * |
| dc.subject.ddc | 540 Chemie | de_DE |
| dc.subject.ddc | 540 Chemistry and allied sciences | en_GB |
| dc.subject.ddc | 610 Medizin | de_DE |
| dc.subject.ddc | 610 Medical sciences | en_GB |
| dc.title | Structure-based virtual screening of unbiased and RNA-focused libraries to identify new ligands for the HCV IRES model system | en_GB |
| dc.type | Zeitschriftenaufsatz | de |
| jgu.journal.title | RSC medicinal chemistry | de |
| jgu.journal.volume | 15 | de |
| jgu.organisation.department | FB 09 Chemie, Pharmazie u. Geowissensch. | de |
| jgu.organisation.name | Johannes Gutenberg-Universität Mainz | |
| jgu.organisation.number | 7950 | |
| jgu.organisation.place | Mainz | |
| jgu.organisation.ror | https://ror.org/023b0x485 | |
| jgu.pages.end | 1538 | de |
| jgu.pages.start | 1527 | de |
| jgu.publisher.doi | 10.1039/d3md00696d | de |
| jgu.publisher.issn | 2632-8682 | de |
| jgu.publisher.name | Royal Society of Chemistry | de |
| jgu.publisher.place | Cambridge | de |
| jgu.publisher.year | 2024 | |
| jgu.rights.accessrights | openAccess | |
| jgu.subject.ddccode | 540 | de |
| jgu.subject.ddccode | 610 | de |
| jgu.subject.dfg | Naturwissenschaften | de |
| jgu.type.contenttype | Scientific article | de |
| jgu.type.dinitype | Article | en_GB |
| jgu.type.resource | Text | de |
| jgu.type.version | Published version | de |