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Binding site characterization - similarity, promiscuity, and druggability.

Christiane EhrtTobias BrinkjostOliver Koch
Published in: MedChemComm (2019)
The elucidation of non-obvious binding site similarities has provided useful indications for the establishment of polypharmacology, the identification of potential off-targets, or the repurposing of known drugs. The concept underlying all of these approaches is promiscuous binding which can be analyzed from a ligand-based or a binding site-based perspective. Herein, we applied methods for the automated analysis and comparison of protein binding sites to study promiscuous binding on a novel dataset of sites in complex with ligands sharing common shape and physicochemical properties. We show the suitability of this dataset for the benchmarking of novel binding site comparison methods. Our investigations also reveal promising directions for further in-depth analyses of promiscuity and druggability in a pocket-centered manner. Drawbacks concerning binding site similarity assessment and druggability prediction are outlined, enabling researchers to avoid the typical pitfalls of binding site analyses.
Keyphrases
  • binding protein
  • machine learning
  • social media
  • genome wide
  • healthcare
  • dna binding
  • deep learning
  • human health
  • risk assessment
  • bioinformatics analysis