Post-high-throughput screening analysis: an empirical compound prioritization scheme. Academic Article uri icon

start page

  • 419

end page

  • 426

abstract

  • 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.

date/time value

  • 2005

Digital Object Identifier (DOI)

  • 10.1177/1087057104272660

PubMed Identifier

  • 16093551

volume

  • 10

number

  • 5

keywords

  • Automation
  • Chemistry, Pharmaceutical
  • Combinatorial Chemistry Techniques
  • Computational Biology
  • Computer Simulation
  • Dose-Response Relationship, Drug
  • Drug Evaluation, Preclinical
  • Drug Industry
  • Models, Chemical
  • Models, Molecular
  • Pharmaceutical Preparations
  • Solubility
  • Structure-Activity Relationship