A fast topological analysis algorithm for large-scale similarity evaluations of ligands and binding pockets

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Abstract

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.

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ElGamacy, M., & Van Meervelt, L. (2015). A fast topological analysis algorithm for large-scale similarity evaluations of ligands and binding pockets. Journal of Cheminformatics, 7(1). https://doi.org/10.1186/s13321-015-0091-5

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