A Structure-Based Computational Pipeline for Broad-Spectrum Antiviral Discovery

Castellanos, M. A.; Payne, A. M.; Scheen, J.; MacDermott-Opeskin, H.; Pulido, I.; Balcomb, B. H.; Griffen, E. J.; Fearon, D.; Barr, H.; Lahav, N.; Cousins, D.; Stacey, J.; Robinson, R.; Lefker, B.; Chodera, J. D.

doi:10.1101/2025.07.29.667267

bioRxiv · 10.1101/2025.07.29.667267

A Structure-Based Computational Pipeline for Broad-Spectrum Antiviral Discovery

Castellanos, M. A.·Payne, A. M.·Scheen, J.·MacDermott-Opeskin, H.·Pulido, I.·Balcomb, B. H.·Griffen, E. J.·Fearon, D.·Barr, H.·Lahav, N.·Cousins, D.·Stacey, J.·Robinson, R.·Lefker, B.·Chodera, J. D.

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Abstract

The rapid emergence of viruses with pandemic potential continues to pose a threat to public health worldwide. With the typical drug discovery pipeline taking an average of 5-10 years to reach clinical readiness, there is an urgent need for strategies to develop broad-spectrum antivirals that can target multiple viral family members and variants of concern. We present a structure-based computational pipeline designed to identify and evaluate broad-spectrum inhibitors across viral family members for a given target in order to support spectrum breadth assessment and prioritization in lead optimization programs. This pipeline comprises three key steps: (1) an automated search to identify viral sequences related to a specified target construct, (2) pose prediction leveraging any available structural data, and (3) scoring of protein-ligand complexes to estimate antiviral activity breadth. The pipeline is implemented using the drugforge package: an open-source toolkit for structure-based antiviral discovery. To validate this framework, we retrospectively evaluated two overlapping datasets of ligands bound to the SARS-CoV-2 and MERS-CoV main protease (Mpro), observing useful predictive power with respect to experimental binding affinities. Additionally, we screened known SARS-CoV-2 Mpro inhibitors against a panel of human and non-human coronaviruses, demonstrating the potential of this approach to assess broad-spectrum antiviral activity. Our computational strategy aims to accelerate the identification of antiviral therapies for current and emerging viruses with pandemic potential, contributing to global preparedness for future outbreaks.

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Castellanos, M. A., Payne, A. M., Scheen, J., MacDermott-Opeskin, H., Pulido, I., Balcomb, B. H., Griffen, E. J., Fearon, D., Barr, H., Lahav, N., Cousins, D., Stacey, J., Robinson, R., Lefker, B., Chodera, J. D.. 2025-07-30. A Structure-Based Computational Pipeline for Broad-Spectrum Antiviral Discovery. https://doi.org/10.1101/2025.07.29.667267

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