High-throughput Screening and Bayesian Machine Learning for Copper-dependent Inhibitors of Staphylococcus aureus
| Autor: | Whitney Narmore, Sean Ekins, Lynn Rasmussen, Frank Wolschendorf, Olaf Kutsch, Alex G. Dalecki, Robert Bostwick, Kimberley M. Zorn, Nichole A. Tower, Alex M. Clark |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
0301 basic medicine
Staphylococcus aureus High-throughput screening In silico Bayesian probability Biophysics Computational biology Microbial Sensitivity Tests medicine.disease_cause Biochemistry Article Biomaterials Machine Learning Small Molecule Libraries 03 medical and health sciences chemistry.chemical_compound medicine Cluster analysis 030102 biochemistry & molecular biology Thiazoline Metals and Alloys Bayes Theorem Anti-Bacterial Agents High-Throughput Screening Assays 030104 developmental biology chemistry Chemistry (miscellaneous) Copper Discovery Studio |
| Popis: | One potential source of new antibacterials is through probing existing chemical libraries for copper-dependent inhibitors (CDIs), i.e., molecules with antibiotic activity only in the presence of copper. Recently, our group demonstrated that previously unknown staphylococcal CDIs were frequently present in a small pilot screen. Here, we report the outcome of a larger industrial anti-staphylococcal screen consisting of 40 771 compounds assayed in parallel, both in standard and in copper-supplemented media. Ultimately, 483 had confirmed copper-dependent IC50 values under 50 μM. Sphere-exclusion clustering revealed that these hits were largely dominated by sulfur-containing motifs, including benzimidazole-2-thiones, thiadiazines, thiazoline formamides, triazino-benzimidazoles, and pyridinyl thieno-pyrimidines. Structure–activity relationship analysis of the pyridinyl thieno-pyrimidines generated multiple improved CDIs, with activity likely dependent on ligand/ion coordination. Molecular fingerprint-based Bayesian classification models were built using Discovery Studio and Assay Central, a new platform for sharing and distributing cheminformatic models in a portable format, based on open-source tools. Finally, we used the latter model to evaluate a library of FDA-approved drugs for copper-dependent activity in silico. Two anti-helminths, albendazole and thiabendazole, scored highly and are known to coordinate copper ions, further validating the model's applicability. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|