As members of the papain superfamily,1
cathepsins are involved in many biological processes related to human diseases and disorders.1–4
Previously identified cathepsins include cathepsin B, D, H, K, L, and S. Several of these proteins have been selected as biological targets to develop therapeutic treatments, and a number of inhibitors have been identified and developed for many of these enzymes. Cathepsin B inhibitors are highly sought after chemical agents since many diseases, such as neurodegenerative disorder, cardiovascular disease, cancer, inflammation, rheumatoid arthritis, and Alzheimer’s disease5–12
, have been connected with unusual levels or abnormal function of cathepsin B. As an ubiquitous lysosomal cysteine proteases, cathepsin B has been found to be responsible for intracellular as well as extracellular proteolysis in mammalian cells and can facilitate cell migration by dissolving the extracellular barriers, which result in tumor metastasis and angiogenesis.13–15
The biological activity and function of cathepsin B is also important during viral infection and replication for several viruses, such as Ebola, SARS (Severe Acute Respiratory Syndrome) in human cells.16, 17
Due to its important biological functions, which are directly related to several important human diseases, cathepsin B has been chosen as a drug development target in many efforts.
A number of compounds have been found to inhibit cathepsin B activity, and some of these compounds have been tested and are effective in animal experiments.5–12, 18–20
Most of these cathepsin inhibitors disable the biological activity of cathepsin B through forming irreversible covalent chemical bond in the catalytic site of the enzyme. These irreversible inhibitors include dipeptidyl nitriles21
, vinyl sulfones, expoxysuccinates, acyloxymethyl ketones, fluoromethyl ketones, hydrazides, and bis
Structural studies have provided detailed insights into the biological mechanisms of these inhibitors. Inhibitors bind to the catalytic active site of cathepsin B, and form an irreversible covalent bond with the protein in the active site.21, 23
Meanwhile, computational studies, such as docking and virtual screening, were also used to explore the binding and inhibition mechanism of these inhibitors.24–26
These computational approaches have proved efficient and essential for optimizing and designing chemical agents with improved biological activities.27–29
In an effort to identify chemical probes through high throughput screening technology (HTS), a number of chemicals have been found to be active against cathepsin B in the screening campaign for inhibitor identification, with the NIH Molecular Libraries Program (MLP). The screening results were deposited into the PubChem (http://pubchem.ncbi.nlm.nih.gov
), a database for molecular structures and associated biological activities which is available to general public. The database contains the 2D structures and the biological activity (IC50
) derived from dose-response HTS experiments for the active compounds tested.
In a previous study,30, 31
docking simulation was used to model the binding structures of the active compounds identified by the high throughput screening (HTS) tests to the binding site of the protein. A relative binding affinity was calculated for each compound studied based on the respective modeled bound structure using the linear response molecular mechanics Poisson Boltzmann-surface area method (LR-MM-PBSA). Strong correlations between the calculated binding affinities and experimental biological activities were obtained.30, 31
Three-dimension (3D) Comparative Molecular Field Analysis (CoMFA) quantitative structure-activity relationships (QSAR) models were also established based on the multi-conformation method with high correlation coefficients for these active compounds (to be published). Given the importance of the enzyme in disease treatment and the broad research interest to screen and identify potent inhibitors, efforts have been taken further to build the QSAR models to correlate the molecular and physicochemical properties with the biological activities of the compounds tested in the Cathepsin B inhibition screening experiments. Efforts were also undertaken to build statistical models to classify inhibition activities against Cathepsin B for specific compounds. This work reports the results of the continuous (continuous in bioactivity space) and binary (two discrete bioactivity status, e.g. ‘active’ vs
‘inactive’) QSAR models in order to obtain insight into the relationship of chemical structure and physicochemical properties/biological activity. Additionally, the results of this work may provide means to pre-screen compounds to facilitate in silico
design of de novo cathepsin B inhibitors and the development of drugs for the treatment of varies human diseases using some other molecular targets.