Computational analysis of the cathepsin B inhibitors activities through LR‐MMPBSA binding affinity calculation based on docked complex

Abstract

Cathepsin B, a ubiquitous lysosomal cysteine protease, is involved in many biological processes related to several human diseases. Inhibitors targeting the enzyme have been investigated as possible diseases treatments. A set of 37 compounds were recently found active in a high throughput screening assay to inhibit the catalytic activity of Cathepsin B, with chemical structures and biological test results available to the public in the PubChem BioAssay Database (AID 820). In the present study, we compare these experimental activities to the results of theoretical predictions from binding affinity calculation with a LR-MM-PNSA approach based on docked complexes. Strong correlations (r2 = 0.919 and q2 = 0.887 for the best) are observed between the theoretical predictions and experimental biological activity. The models are cross-validated by four independent predictive experiments with randomly split compounds into training and test sets. Our results also show that the results based on protein dimer show better correlations with experimental activity when compared to results based on monomer in the in silico calculations.

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