Automated Molecular Design in BRADSHAW, Applied to the Optimization of ERAP1 Inhibitors

Clinical Snapshot

Key Findings

• P Value: Not reported

• Effect Size: Not specified in abstract

• Primary Outcome: Successful identification of in vitro and in vivo tool molecules through automated design

• Nnt Or Sensitivity: Improved scoring accuracy through ML model refinement (specific metrics not provided)

• Confidence Interval: Not reported

Clinical Application

Requires specialized computational infrastructure and expertise Relevant to Australian pharmaceutical research institutions and TGA drug development pathways, though ERAP1 inhibitors not yet in clinical use Researchers developing ERAP1 inhibitors for cancer immunotherapy and autoimmune diseases

Abstract

Generative design and machine learning are increasingly prevalent in medicinal chemistry. To pilot the comprehensive use of automated molecular design on a project, the BRADSHAW platform was used to optimize a series of inhibitors of Endoplasmic Reticulum Aminopeptidase 1 (ERAP1), an emerging target in cancer immunotherapy and autoimmune diseases. Through four consecutive iterations applying in silico molecular generation, property prediction and filtering, we conducted a multiparameter optimization of potency, physicochemical properties and pharmacokinetics. Continuous refinement of Machine Learning (ML) models led to improved scoring accuracy and compound quality, culminating in identification of in vitro and in vivo tool molecules. We also discuss our reflections on the pilot and integration of automated design into medicinal chemistry projects, including observations of the human factors resulting from increased use of computational design, and recommendations for future projects.

References

1. 1.Law, R. P., Wall, I. D., Lonsdale, R., Hryczanek, R. P., Barker, D., Barrett, T. N., Bit, R. A., Coward, J. J., Gray, M. W., Green, D. V. S., Hall, C. J., Hancock, A. P., Haslam, C., Hirst, D. J., Hryczanek, H. F., Hutchinson, J. P., Kitchen, S., Marcus, D., Marklew, J., Mason, J., Measom, N. D., Neu, M., Peace, S., Phillipou, A., Pickett, S. D., Pogány, P., Rowedder, J., Rowland, P., Scott-Stevens, P., Seal, G. A. L., Sheehan, H., Stratikos, E., Tayler, C., Taylor, J. A., Tinworth, C. P., & Vitulli, G. (2026). Automated molecular design in BRADSHAW, applied to the optimization of ERAP1 inhibitors. Journal of Medicinal Chemistry. https://doi.org/10.1021/acs.jmedchem.5c03071