The COVID-19 pandemic (2019-2023) demonstrated the need for safe and effective, stockpiled broad-spectrum antiviral drugs to suppress unexpected viral outbreaks. The inability of the pharmaceutical industry to create such a therapeutic in the 6 years since the onset of COVID-19 demonstrates antiviral drug development must undergo a paradigm shift for this to occur. AI-based target and medicinal chemistry discovery platforms such as GALILEO and its geometric graph convolutional network tool ChemPrint, which we recently published, hold promise in accelerating and reimagining the drug development process. GALILEO identified the Thumb-1 site (an allosteric subdomain of the viral RNA polymerase) to be structurally conserved across numerous viral species and MDL-001 (an orally available therapeutic with a favorable pharmacokinetics and safety profile in humans) to be a potent inhibitor thereof. Published preclinical proof-of-concept studies demonstrated MDL-001 as a first-in-class broad-spectrum antiviral drug. This study leverages GALILEO’s generative and multimodal discovery tools to create trillions of new chemical entities (NCEs) from MDL-001’s pharmacophoric scaffold and select a library of highly specific and optimized compounds for next-generation broad-spectrum antiviral development. Specifically, ChemPrint’s one-shot predictions identified 12 NCEs with predicted affinity to Thumb-1 and significantly reduced, or no, affinity to MDL-001’s original target. In vitro bioassays demonstrated a 100% hit rate, with all 12 NCEs having antiviral activity against Hepatitis C Virus (HCV) and/or human Coronavirus 229E. In vitro studies also demonstrated reduced activity of 800-fold to greater than 15,000-fold relative to MDL-001’s originally designed mechanism of action (MoA). In Tanimoto similarity plots, the 12 NCEs lacked chemical relatedness to known antiviral drugs, including MDL-001 (average Tanimoto coefficient: 0.38) and Beclabuvir, (average Tanimoto coefficient: 0.13) a HCV Thumb-1 ligand that lacks broad-spectrum activity. This study showcases GALILEO’s ability to generate vast NCE libraries and ChemPrint’s extrapolative capabilities to discover large, potent NCE libraries of compounds, specific to a complex target that are novel to known chemistry at high hit-rates.