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Identification of multitarget activity ridges in high-dimensional bioactivity spaces
Disha Gupta-Ostermann1, Jürgen Bajorath
1Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Dahlmannstr. 2, D-53113 Bonn, Germany.
This study introduces multitarget activity ridges, a novel data structure for analyzing complex drug interactions across multiple targets. These ridges reveal valuable structure-activity relationship (SAR) information, aiding in the discovery of potent kinase inhibitors.
Area of Science:
- Medicinal Chemistry
- Computational Chemistry
- Drug Discovery
Background:
- Activity cliffs identify potency differences in similar compounds.
- Activity ridges extend this concept, grouping compounds with varying potencies against a single target.
- Previous research focused solely on single-target activity ridges.
Purpose of the Study:
- To investigate the existence and characteristics of multitarget activity ridges.
- To develop methods for representing and analyzing these complex structures.
- To explore their utility in structure-activity relationship (SAR) analysis.
Main Methods:
- Analysis of a high-dimensional kinase inhibitor dataset.
- Development of a scaffold-target matrix representation for multitarget ridges.
- Implementation of a scoring scheme to identify compounds with target differentiation potential.
Main Results:
- Identification of multitarget activity ridges involving up to 43 inhibitors and 26 kinase targets.
- Successful representation of complex multitarget ridge architectures.
- Development of a scoring method to pinpoint compounds with significant target differentiation.
Conclusions:
- Multitarget activity ridges are a valid and informative data structure.
- They offer a novel approach for SAR exploration in high-dimensional drug discovery spaces.
- This work facilitates the identification of compounds with selective activity across multiple targets.
