QSAR models for predicting cathepsin B inhibition by small molecules--continuous and binary QSAR models to classify cathepsin B inhibition activities of small molecules

Identification of novel potential cathepsin-B inhibitors through pharmacophore-based virtual screening, molecular docking, and dynamics simulation studies for the treatment of Alzheimer's disease

Cathepsin B is a cysteine protease lysosomal enzyme involved in several physiological functions. Overexpression of the enzyme enhances its proteolytic activity and causes the breakdown of amyloid precursor protein (APP) into neurotoxic amyloid β (Aβ), a characteristic hallmark of Alzheimer's disease (AD). Therefore, inhibition of the enzyme is a crucial therapeutic aspect for treating the disease. Combined structure and ligand-based drug design strategies were employed in the current study to identify the novel potential cathepsin B inhibitors. Five different pharmacophore models were developed and used for the screening of the ZINC-15 database. The obtained hits were analyzed for the presence of duplicates, interfering PAINS moieties, and structural similarities based on Tanimoto's coefficient. The molecular docking study was performed to screen hits with better target binding affinity. The top seven hits were selected and were further evaluated based on their predicted ADME properties. The resulting best hits, ZINC827855702, ZINC123282431, and ZINC95386847, were finally subjected to molecular dynamics simulation studies to determine the stability of the protein-ligand complex during the run. ZINC123282431 was obtained as the virtual lead compound for cathepsin B inhibition and may be a promising novel anti-Alzheimer agent.

Inhibitory assay for degradation of collagen IV by cathepsin B with a surface plasmon resonance sensor

We describe a simple method for evaluating the inhibition of collagen IV degradation by cathepsin B with a surface plasmon resonance (SPR) biosensor. The change in the SPR signal decreased with an increase in the concentration of cathepsin B inhibitors. The order of the inhibitory constant (Ki) obtained by the SPR method was CA074Me≈Z-Phe-Phe-FMK < leupeptin. This order was different from that obtained by benzyloxycarbonyl-Phe-Phe-Fluoromethylketone (Z-Phe-Phe-FMK) as a peptide substrate. The comparison of Ki suggested that CA074 and Z-Phe-Phe-FMK inhibited exopeptidase activity, and leupeptin inhibited the endopeptidase activity of cathepsin B more strongly.

Structure-based design and optimization of antihypertensive peptides to obtain high inhibitory potency against both renin and angiotensin I-converting enzyme

The human renin-angiotensin system (RAS) plays an essential role in regulating blood pressure and systemic vascular resistance. Renin and angiotensin I-converting enzyme (ACE) are two key enzymes in RAS and have long been recognized as attractive antihypertensive targets. Here, a synthetic strategy was proposed integrating quantitative structure-activity relationship (QSAR), molecular dynamics (MD) simulation and binding free energy analysis to discover novel dual renin and ACE peptidic inhibitors. With the strategy a number of candidates were generated virtually, from which eight promising peptides were selected and synthesized for biological assay. Consequently, three peptides (RYLP, YTAWVP and YRAWVL) were successfully identified to have satisfactory inhibitory profile against both renin and ACE with IC₅₀ values of <1 mM and <10 μM, respectively. Structural analysis and energetic dissection revealed different binding modes of peptide to renin and ACE; a peptide only inserts its C-terminus into the active site of ACE, whereas the whole peptide packs tightly against renin. In addition, when limited to structural diversity it is hard to reconcile the renin and ACE inhibitory activities of short peptides such as dipeptides. These findings can be used to guide peptide optimization with improved biological activity.

Multi-conformation 3D QSAR study of benzenesulfonyl-pyrazol-ester compounds and their analogs as cathepsin B inhibitors

Cathepsin B has been found being responsible for many human diseases. Inhibitors of cathepsin B, a ubiquitous lysosomal cysteine protease, have been developed as a promising treatment for human diseases resulting from malfunction and over-expression of this enzyme. Through a high throughput screening assay, a set of compounds were found able to inhibit the enzymatic activity of cathepsin B. The binding structures of these active compounds were modeled through docking simulation. Three-dimensional (3D) quantitative structure-activity relationship (QSAR) models were constructed using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) based on the docked structures of the compounds. Strong correlations were obtained for both CoMFA and CoMSIA models with cross-validated correlation coefficients (q²) of 0.605 and 0.605 and the regression correlation coefficients (r²) of 0.999 and 0.997, respectively. The robustness of these models was further validated using leave-one-out (LOO) method and training-test set method. The activities of eight (8) randomly selected compounds were predicted using models built from training set of compounds with prediction errors of less than 1 unit for most compounds in CoMFA and CoMSIA models. Structural features for compounds with improved activity are suggested based on the analysis of the CoMFA and CoMSIA contour maps and the property map of the protein ligand binding site. These results may help to provide better understanding of the structure-activity relationship of cathepsin B inhibitors and to facilitate lead optimization and novel inhibitor design. The multi-conformation method to build 3D QSAR is very effective approach to obtain satisfactory models with high correlation with experimental results and high prediction power for unknown compounds.

An application of two MIFs-based tools (Volsurf+ and Pentacle) to binary QSAR: the case of a palinurin-related data set of non-ATP competitive glycogen synthase kinase 3β (GSK-3β) inhibitors

VolSurf+ and GRIND descriptors extract the information present in MIFs calculated by GRID: the first are simpler to interpret and generally applied to ADME-Tox topics, whereas the latter are more sophisticated and thus more suited for pharmacodynamics events. Here we present a study which compares binary QSAR models obtained with VolSurf+ descriptors and GRIND for a data set of non-ATP competitive GSK-3β inhibitors chemically related to palinurin for which the biological activity is expressed in binary format. Results suggest not only that the simpler Volsurf+ descriptors are good enough to predict and chemically interpret the investigated phenomenon but also a bioactive conformation of palinurin which may guide future design of ATP non-competitive GSK-3 inhibitors.

3D-QSAR and molecular docking studies on fused pyrazoles as p38α mitogen-activated protein kinase inhibitors

The p38α mitogen-activated protein kinase (MAPK) has become an attractive target for the treatment of many diseases such as rheumatoid arthritis, inflammatory bowel disease and Crohn’s disease. In this paper, 3D-QSAR and molecular docking studies were performed on 59 p38α MAPK inhibitors. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were applied to determine the structural requirements for potency in inhibiting p38α MAPK. The resulting model of CoMFA and CoMSIA exhibited good r²_cv values of 0.725 and 0.609, and r² values of 0.961 and 0.905, respectively. Molecular docking was used to explore the binding mode between the inhibitors and p38α MAPK. We have accordingly designed a series of novel p38α MAPK inhibitors by utilizing the structure-activity relationship (SAR) results revealed in the present study, which were predicted with excellent potencies in the developed models. The results provided a useful guide to design new compounds for p38α MAPK inhibitors.