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Biological Activity Profiles of Multitarget Ligands from X-ray Structures
Christian Feldmann1, Jürgen Bajorath1
1Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Endenicher Allee 19c, D-53115 Bonn, Germany.
Molecules (Basel, Switzerland)
|February 16, 2020
Summary
Understanding compound promiscuity in pharmaceutical research is key. Analyzing multitarget ligand (MTL) activity data from various sources reveals significant profile variations, highlighting the need for careful consistency checks in drug discovery.
Area of Science:
- Pharmaceutical Research
- Computational Chemistry
- Drug Discovery
Background:
- Multitarget ligands (MTLs) are crucial in pharmaceutical research for polypharmacology but can cause side effects.
- Understanding the molecular basis of multitarget activity is essential for drug development.
- Estimating compound promiscuity computationally requires robust analysis of activity data.
Purpose of the Study:
- To systematically determine activity annotations and profiles of known MTLs using data from diverse sources.
- To investigate the consistency of activity data across different sources for MTLs.
- To understand how MTLs behave in biological screens and address data variations.
Main Methods:
- Systematic determination of activity annotations and profiles for confirmed MTLs.
- Analysis of activity data from multiple sources, considering data confidence and consistency.
- Utilizing X-ray crystallography data to confirm MTLs with multiple targets.
Main Results:
- Significant variations in MTL activity profiles were observed across different data sources.
- The consistency of activity data across sources is a critical, yet under-investigated, aspect of promiscuity analysis.
- MTL behavior in biological screens shows considerable variability.
Conclusions:
- Variations in activity data from different sources must be carefully considered in promiscuity analysis.
- This study emphasizes the importance of data consistency and provides guidance for large-scale activity data analysis in drug discovery.
- Awareness of data source variability is crucial for accurate assessment of compound promiscuity.
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