title: Evaluating chemical structure similarity as an indicator of cellular growth inhibition.
abstract: Chemical variations of small compounds are commonly used to probe biological systems and potentially discover lead-like compounds with selective target activity. Molecular probes are either generated by synthesis or acquired through directed searches of commercially available compound libraries. The data generated when testing the probes in various biological systems constitutes a structure/activity analysis. The ability to detect variations and classify biological responses requires the analysis of a compound in multiple assays. While the concept of a structure/activity relationship is straightforward, its implementation can vary considerably depending on the biological system under study and the probe library selected for testing. The analysis presented here will focus on the accumulated compound library used to screen for growth inhibition across the National Cancer Institute's panel of 60 tumor cells. The considerable chemical and biological diversity inherent in these data offers an opportunity to establish a quantifiable connection between chemical structure and biological activity. We find that the connection between structure and biological response is not symmetric, with biological response better at predicting chemical structure than vice versa. Structurally and functionally similar compounds can have distinguishable biological responses reflecting different mechanisms of action.
authors.affiliation: National Cancer Institute, Developmental Therapeutics Program, Screening Technologies Branch, Frederick, Maryland 21702, USA. wallqvist@ncifcrf.gov
authors.forename: Anders
authors.initials: A
authors.lastname: Wallqvist
authors.forename: Ruili
authors.initials: R
authors.lastname: Huang
authors.forename: Narmada
authors.initials: N
authors.lastname: Thanki
authors.forename: David G
authors.initials: DG
authors.lastname: Covell
mesh_terms: D000970:Antineoplastic Agents / Q000737:chemistry* / Q000494:pharmacology*; D002455:Cell Division / Q000187:drug effects; D003198:Computer Simulation; D004305:Dose-Response Relationship, Drug; D009369:Neoplasms / Q000473:pathology; D013329:Structure-Activity Relationship
chemical_list: D000970:Antineoplastic Agents