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Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
Published on: December 1, 2020
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Detecting similar binding pockets to enable systems polypharmacology.
Miquel Duran-Frigola1, Lydia Siragusa2, Eytan Ruppin3,4,5
1Joint IRB-BSC-CRG Program in Computational Biology, Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Catalonia, Spain.
Plos Computational Biology
|June 30, 2017
Summary
Drug promiscuity, or polypharmacology, can be predicted by identifying similar protein binding sites. This study found thousands of similar binding sites, enabling rational drug design for complex diseases.
Area of Science:
- Computational biology
- Pharmacology
- Systems biology
Background:
- Multi-target drug strategies are crucial for complex diseases.
- Drug promiscuity can be harnessed for polypharmacology.
- Analyzing binding site similarity aids in predicting drug interactions.
Purpose of the Study:
- To explore the potential of drug promiscuity in polypharmacology.
- To identify similar binding sites across the proteome.
- To demonstrate the application of similar binding sites in rational drug design.
Main Methods:
- Pairwise comparison of 90,000 putative binding pockets in 3,700 proteins.
- Identification of protein pairs with similar binding cavities.
- Analysis of protein-protein interaction networks and metabolic models.
Main Results:
- 23,000 pairs of proteins exhibit at least one similar binding site.
- Detection of similar binding sites expands opportunities for polypharmacology.
- Successful illustration of leveraging similar sites in therapeutic networks and leukemia models.
Conclusions:
- Identifying similar binding sites is a viable strategy for rational polypharmacology.
- This approach facilitates the design of multi-target drugs for various diseases.
- The findings support the application of systems biology in drug discovery.
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