Classifying compound mechanism of action for linking whole cell phenotypes to molecular targets
Year: 2012
Type: article
Abstract: Drug development programs have proven successful when performed at a whole cell level, thus incorporating solubility and permeability into the primary screen. However, linking those results to the target within the cell has been a major setback. The Phenotype Microarray system, marketed and sold by Biolog, seeks to address this need by assessing the phenotype in combination with a variety of chemicals with known mechanism of action (MOA). We have evaluated this system for usefulness in deducing the MOA for three test compounds. To achieve this, we constructed a database with 21 known antimicrobials, which served as a comparison for grouping our unknown MOA compounds. Pearson correlation and Ward linkage calculations were used to generate a dendrogram that produced clustering largely by known MOA, although there were exceptions. Of the three unknown compounds, one was definitively placed as an antifolate. The second and third compounds' MOA were not clearly identified, likely because the unique MOA was not represented within the database. The availability of the database generated in this report for Staphylococcus aureus ATCC 29213 will increase the accessibility of this technique to other investigators. From our analysis, the Phenotype Microarray system can group compounds with clear MOA, but the distinction of unique or broadly acting MOA at this time is less clear.
Source: Journal of Molecular Recognition
DOI: 10.1002/jmr.2174
Institution: Oklahoma State University
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W1668360130