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Post-High-Throughput Screening Analysis: An Empirical Compound Prioritization Scheme
Division of Biocomputing and Cancer Research and Treatment Center, University of New Mexico, Albuquerque.
Department of Pathology and Cancer Research and Treatment Center, University of New Mexico, Albuquerque. An empirical scheme to evaluate and prioritize screening hits from high-throughput screening (HTS) is proposed. Negative scores are given when chemotypes found in the HTS hits are present in annotated databases such as MDDR and WOMBAT or for testing positive in toxicity-related experiments reported in TOXNET. Positive scores were given for higher measured biological activities, for testing negative in toxicity-related literature, and for good overlap when profiled against drug-related properties. Particular emphasis is placed on estimating aqueous solubility to prioritize in vivo experiments. This empirical scheme is given as an illustration to assist the decision-making process in selecting chemotypes and individual compounds for further experimentation, when confronted with multiple hits from high-throughput experiments. The decision-making process is discussed for a set of G-protein coupled receptor antagonists and validated on a literature example for dihydrofolate reductase inhibition.
Key Words: chemoinformatics • DHFR inhibition • GPCR antagonism • hit evaluation • lead discovery • post-HTS analysis • structure-activity relationships
This version was published on August
1, 2005 Journal of Biomolecular Screening, Vol. 10, No. 5,
419-426 (2005) This article has been cited by other articles:
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