<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Jones T</submitter><funding>National Institute of Allergy and Infectious Diseases</funding><funding>National Institute of Neurological Disorders and Stroke</funding><funding>NIAID NIH HHS</funding><funding>NINDS NIH HHS</funding><funding>National Institute of General Medical Sciences</funding><funding>NIGMS NIH HHS</funding><pagination>12459-12467</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC11017374</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>66(17)</volume><pubmed_abstract>Hepatitis B virus (HBV) is a hepatotropic DNA virus that replicates by reverse transcription. It chronically infects >296 million people worldwide, including ∼850,000 in the USA, and kills 820,000 annually worldwide. Current nucleos(t)ide analogue (NA) or pegylated interferon α therapies do not eradicate the virus and would benefit from a complementary antiviral drug. We performed a preliminary screen of 28 dispirotripiperazines against HBV, identifying 9 hits with EC&lt;sub>50&lt;/sub> of 0.7-25 μM. Compound 11826096 displays the most potent activity and represents a promising lead for future optimization. While the mechanism of action is unknown, preliminary assays limit possible targets to activities involved in RNA accumulation, translation, capsid assembly, and/or capsid stability. In addition, we built machine learning models to determine if they were able to predict the activity of this series of compounds. The novelty of these molecules indicated they were outside of the applicability domain of these models.</pubmed_abstract><journal>Journal of medicinal chemistry</journal><pubmed_title>Antiviral Evaluation of Dispirotripiperazines against Hepatitis B Virus.</pubmed_title><pmcid>PMC11017374</pmcid><funding_grant_id>R01 AI122669</funding_grant_id><funding_grant_id>R01 NS102164</funding_grant_id><funding_grant_id>1R01NS102164</funding_grant_id><funding_grant_id>R01AI122669</funding_grant_id><funding_grant_id>R44 GM122196</funding_grant_id><funding_grant_id>R44GM122196</funding_grant_id><pubmed_authors>Riabova O</pubmed_authors><pubmed_authors>Bradley DP</pubmed_authors><pubmed_authors>Ekins S</pubmed_authors><pubmed_authors>Monakhova N</pubmed_authors><pubmed_authors>Makarov V</pubmed_authors><pubmed_authors>Li Q</pubmed_authors><pubmed_authors>Lane TR</pubmed_authors><pubmed_authors>Jones T</pubmed_authors><pubmed_authors>Tavis JE</pubmed_authors></additional><is_claimable>false</is_claimable><name>Antiviral Evaluation of Dispirotripiperazines against Hepatitis B Virus.</name><description>Hepatitis B virus (HBV) is a hepatotropic DNA virus that replicates by reverse transcription. It chronically infects >296 million people worldwide, including ∼850,000 in the USA, and kills 820,000 annually worldwide. Current nucleos(t)ide analogue (NA) or pegylated interferon α therapies do not eradicate the virus and would benefit from a complementary antiviral drug. We performed a preliminary screen of 28 dispirotripiperazines against HBV, identifying 9 hits with EC&lt;sub>50&lt;/sub> of 0.7-25 μM. Compound 11826096 displays the most potent activity and represents a promising lead for future optimization. While the mechanism of action is unknown, preliminary assays limit possible targets to activities involved in RNA accumulation, translation, capsid assembly, and/or capsid stability. In addition, we built machine learning models to determine if they were able to predict the activity of this series of compounds. The novelty of these molecules indicated they were outside of the applicability domain of these models.</description><dates><release>2023-01-01T00:00:00Z</release><publication>2023 Sep</publication><modification>2025-04-03T23:18:16.198Z</modification><creation>2025-04-03T23:18:16.198Z</creation></dates><accession>S-EPMC11017374</accession><cross_references><pubmed>37611244</pubmed><doi>10.1021/acs.jmedchem.3c00974</doi></cross_references></HashMap>