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Identification of Kinase-substrate Pairs Using High Throughput Screening
Published on: August 29, 2015
Analysis of a high-throughput screening data set using potency-scaled molecular similarity algorithms.
1Department of Life Science Informatics, B-IT, Rheinische Friedrich-Wilhelms-Universität, Dahlmannstrasse 2, D-53113 Bonn, Germany.
Journal of Chemical Information and Modeling
|February 16, 2007
Summary
This study introduces potency scaling into molecular similarity methods for virtual screening (VS). Potency scaling enhances the detection of potent drug candidates during virtual screening, improving hit identification efficiency.
Area of Science:
- Computational Chemistry
- Medicinal Chemistry
- Drug Discovery
Background:
- Ligand-based virtual screening (VS) typically excludes compound potency from search parameters.
- Existing VS methods lack the ability to prioritize more potent compounds during screening.
Purpose of the Study:
- To incorporate a logarithmic potency scaling function into VS algorithms.
- To evaluate the impact of potency scaling on hit identification using a cathepsin B inhibitor dataset.
Main Methods:
- Developed two distinct VS algorithms with integrated logarithmic potency scaling.
- Utilized a high-throughput screening (HTS) dataset of cathepsin B inhibitors.
- Performed virtual screening using template compounds with and without potency scaling.
Main Results:
- Potency scaling led to significant enrichment of potent compounds in screening results.
- Observed enrichment was partly attributed to recentering chemical space around potent compounds.
- The method demonstrated improved preferential detection of potent database hits.
Conclusions:
- Potency scaling is an effective strategy to enhance virtual screening for potent compounds.
- This approach can direct VS towards identifying more effective drug candidates.
- The findings suggest improved efficiency in drug discovery pipelines.
