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Pharmacophore Modeling for Targets with Extensive Ligand Libraries: A Case Study on SARS-CoV-2 Mpro
Published on: September 26, 2025
Matrix-based Molecular Descriptors for Prospective Virtual Compound Screening
Francesca Grisoni1,2, Daniel Reker2, Petra Schneider2,3
1University of Milano-Bicocca, Dept. of Earth and Environmental Sciences, P.za della Scienza 1, 20126, Milano, Italy.
Abstract:
Molecular descriptors capture diverse structural information of molecules and are a prerequisite for ligand-based similarity searching. In this study, we introduce topological matrix-based descriptors to virtual screening for hit discovery. We evaluated the usefulness of matrix-based descriptors in a retrospective setting and compared them with topological pharmacophore descriptors. Special attention was given to the influence of data pre-processing and the applied similarity metric on the virtual screening performance. Overall, the MB descriptors showed a competitive and complementary performance to other descriptors. A prospective screen of a commercial compound library led to the discovery of a novel natural-product-derived cyclooxygenase-2 inhibitor predicted to interact differently with the target protein compared to the query compound ibuprofen. The results of our study motivate the use of matrix-based descriptors for molecular similarity-based virtual screening and scaffold hopping.
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