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Updated: Mar 30, 2026

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
Published on: February 23, 2024
A fast topological analysis algorithm for large-scale similarity evaluations of ligands and binding pockets
Mohammad ElGamacy1, Luc Van Meervelt2
1Department of Protein Evolution, Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany ; Biomolecular Architecture, Chemistry Department, KU Leuven, Celestijnenlaan 200F, box 2404, 3001 Leuven (Heverlee), Belgium.
Motivation:
With the rapid increase of the structural data of biomolecular complexes, novel structural analysis methods have to be devised with high-throughput capacity to handle immense data input and to construct massive networks at the minimal computational cost. Moreover, novel methods should be capable of handling a broad range of molecular structural sizes and chemical natures, cognisant of the conformational and electrostatic bases of molecular recognition, and sufficiently accurate to enable contextually relevant biological inferences.
Results:
A novel molecular topology comparison method was developed and tested. The method was tested for both ligand and binding pocket similarity analyses and a PDB-wide ligand topological similarity map was computed.
Conclusion:
The unprecedentedly wide scope of ligand definition and large-scale topological similarity mapping can provide very robust tools, of performance unmatched by the present alignment-based methods. The method remarkably shows potential for application for scaffold hopping purposes. It also opens new frontiers in the areas of ligand-mediated protein connectivity, ligand-based molecular phylogeny, target fishing, and off-target predictions. Graphical abstract:A novel molecular topology comparison method based on a combined shape distribution and charge binning scheme is presented.
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