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Frequent Hitters Library

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  • Mg
  • uMol

ChemDiv’s Frequent Hitters Library contains 9,000 compounds.

High throughput screening (HTS) is a crucial technique utilized by pharmaceutical companies to identify potential drug candidates efficiently. However, one of the significant challenges in HTS procedures is the prevalence of false positives among the identified hits. False positives can arise due to various reasons, including non-specific binding, assay interference, or compounds exhibiting "abnormal" activity. These misleading results can lead to wasted resources and efforts in subsequent stages of drug development. Therefore, distinguishing real hits from false positives is essential for the success of HTS and the overall drug discovery process.

To address this challenge, ChemDiv has developed the Frequent Hitters Library. This specialized collection focuses on identifying and cataloging compounds known to frequently appear as false positives in HTS assays. Using a reference database of core structural motifs documented in the literature as common features of frequent hitters, we conducted an extensive in silico screening of our compound stock, which exceeds 8 million molecules. This process involved batch substructural screening to identify molecules that match these problematic motifs. As a result, more than 10,000 compounds were classified as potentially frequent hitters, indicating a predicted promiscuous activity.

By systematically identifying these frequent hitters, the library serves as a valuable tool for improving the accuracy and efficiency of HTS campaigns. Researchers can use this library to filter out compounds with a high likelihood of being false positives before conducting costly and time-consuming follow-up studies. This proactive approach helps to focus resources on more promising candidates with genuine potential for therapeutic development. Additionally, understanding the common structural motifs that contribute to frequent hitting behavior can provide insights into the nature of protein-reactive compounds, ultimately enhancing the design of more selective and effective drug candidates.

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