Deriving Structures for Lead Drug Discovery from Cell-Line Screens
Abstract
A suite of computational tools has been developed for detailed analysis of large-scale high-throughput screening data for the purpose of lead drug discovery and potential identification of novel molecular targets in the treatment of human cancers. The method has been developed and tested against the National Cancer Institute's 60 tumor cell panel. This suite of analytical and display tools is focused in the areas of data conditioning, pattern association, visualization and data presentation, with additional functionalities that address signal scaling issues, missing data elements, and locality/non-linearity features of the data-space. Careful considerations in these areas are found to significantly enhance the extraction of additional information from large, complicated, screening databases as well as provide a general tool well suited for drug discovery. These results find strong correlations between molecular structure and putative mechanism of action for large classes of anticancer agents; with a clear segregation of compounds according to their activities against specific molecular targets. More significantly, screening cells that are found within specific tumor cell panels are found to respond similarly to classes of molecular agents. This information can lead directly to the formulation of alternative chemical analogs and hypotheses about specific molecular targets and their affected biosynthetic pathways.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 01, 2000
- Accession Number
- ADA389712
Entities
People
- David G. Covell
- Robert L. Jernigan
Organizations
- National Cancer Institute