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PLoS Computational Biology Issue Image | Vol. 10(9) September 2014

Matching drug binding pockets in protein models using sequence order-independent structure alignments.

Drugs are typically developed to modulate the function of specific proteins, which are directly associated with particular disease states. Nonetheless, protein-drug interactions are rather promiscuous and the majority of pharmaceuticals exhibit activity against multiple, often unrelated targets; for instance, ATP-dependent DNA ligase and histamine N-methyltransferase shown here bind the same compound. To detect those binding sites having the capability to bind similar molecules, Michal Brylinski developed eMatchSite, which constructs local sequence order-independent alignments using computer-generated protein models. This approach opens up the possibility to investigate drug-protein interactions for complete proteomes with prospective systems-level applications in polypharmacology and rational drug repositioning.

Image Credit: Michal Brylinski

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Matching drug binding pockets in protein models using sequence order-independent structure alignments.

Drugs are typically developed to modulate the function of specific proteins, which are directly associated with particular disease states. Nonetheless, protein-drug interactions are rather promiscuous and the majority of pharmaceuticals exhibit activity against multiple, often unrelated targets; for instance, ATP-dependent DNA ligase and histamine N-methyltransferase shown here bind the same compound. To detect those binding sites having the capability to bind similar molecules, Michal Brylinski developed eMatchSite, which constructs local sequence order-independent alignments using computer-generated protein models. This approach opens up the possibility to investigate drug-protein interactions for complete proteomes with prospective systems-level applications in polypharmacology and rational drug repositioning.

Image Credit: Michal Brylinski

https://doi.org/10.1371/image.pcbi.v10.i09.g001