The National Cancer Institute’s Plated Compound Sets Can Be a Valuable Resource for Academic Researchers

Abstract

Academic researchers looking for material to screen may benefit from plated compound collections provided at no cost except shipping by the U.S. National Cancer Institute (NCI). Four plated sets are available, two of which comprise diverse synthetic compounds. These collections, of ~900 and ~1500 compounds, are a convenient size to screen without automated equipment, and a great deal of data about the compounds is available that increases their usefulness. Despite these positive attributes, the collections contain a relatively large number of compounds that are pan-assay interfering and nonspecific (PAINS) or may have other chemical liabilities. Our experience with the compound collections suggests that, perhaps because they contain PAINS and other compounds with liabilities, the collections will yield hits in many assays. This makes them a valuable resource for testing primary screens and follow-up workflows, but by the same token means that hits might not be attractive leads for further development. The NCI sets have a great deal of value for academic researchers as a source of material for early screening. It might be possible, however, to create a better collection specifically for this purpose. One possibility is to pool ~5000–10,000 carefully selected lead-like compounds into ~1000 wells. A collection like this might also generate hits in a wide variety of assays but avoid the downside of those hits often having liabilities.

Identification of small molecules that suppress cell invasion and metastasis promoted by WASF3 activation

“…Consequently, we used the crystal structure of the WASF regulatory complex site to identify small molecules that were predicted to interact with the WASF3 structure. The National Cancer Institute (NCI) diversity set VI, consisting of 1584 compounds, was used primarily because these molecules are generally well characterized, structurally diverse, and freely available [ 25 ]. The scoring algorithm in this in silico approach is based on molecular mechanics force fields that estimate the energy of the pose within the binding site.…”