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Identification of chemogenomic features from drug-target interaction networks using interpretable classifiers
- Source :
- Bioinformatics, Bioinformatics, Oxford University Press (OUP), 2012, 28 (18), pp.i487-i494. ⟨10.1093/bioinformatics/bts412⟩
- Publication Year :
- 2012
- Publisher :
- HAL CCSD, 2012.
-
Abstract
- Motivation: Drug effects are mainly caused by the interactions between drug molecules and their target proteins including primary targets and off-targets. Identification of the molecular mechanisms behind overall drug–target interactions is crucial in the drug design process. Results: We develop a classifier-based approach to identify chemogenomic features (the underlying associations between drug chemical substructures and protein domains) that are involved in drug–target interaction networks. We propose a novel algorithm for extracting informative chemogenomic features by using L1 regularized classifiers over the tensor product space of possible drug–target pairs. It is shown that the proposed method can extract a very limited number of chemogenomic features without loosing the performance of predicting drug–target interactions and the extracted features are biologically meaningful. The extracted substructure–domain association network enables us to suggest ligand chemical fragments specific for each protein domain and ligand core substructures important for a wide range of protein families. Availability: Softwares are available at the supplemental website. Contact: yamanishi@bioreg.kyushu-u.ac.jp Supplementary Information: Datasets and all results are available at http://cbio.ensmp.fr/~yyamanishi/l1binary/ .
- Subjects :
- Statistics and Probability
Protein Interactions, Molecular Networks, and Proteomics
Protein family
Computer science
[SDV]Life Sciences [q-bio]
Protein domain
Drug target
Ligands
Machine learning
computer.software_genre
01 natural sciences
Biochemistry
03 medical and health sciences
Drug Delivery Systems
Humans
Molecule
Molecular Biology
ComputingMilieux_MISCELLANEOUS
030304 developmental biology
0303 health sciences
business.industry
Ligand
Proteins
Original Papers
Protein Structure, Tertiary
0104 chemical sciences
Computer Science Applications
010404 medicinal & biomolecular chemistry
Computational Mathematics
Pharmaceutical Preparations
Computational Theory and Mathematics
Drug Design
Proteins metabolism
Linear Models
Artificial intelligence
business
Classifier (UML)
computer
Algorithms
Subjects
Details
- Language :
- English
- ISSN :
- 13674803 and 13674811
- Database :
- OpenAIRE
- Journal :
- Bioinformatics, Bioinformatics, Oxford University Press (OUP), 2012, 28 (18), pp.i487-i494. ⟨10.1093/bioinformatics/bts412⟩
- Accession number :
- edsair.doi.dedup.....13b658ad747a9c841b9d2a01224c160a