Discovery of novel cathepsin S inhibitors by pharmacophore-based virtual high-throughput screening

Optimization of covalent docking for organophosphates interaction with Anopheles acetylcholinesterase

Organophosphates (OPs) used as potent insecticides for malaria vector control, covalently phosphorylate the catalytic serine residue of Anopheles gambiae AChE (AgAChE) in a reaction that liberates their leaving groups. In the recent 10-year insecticide use assessment, OPs were the most frequently used World Health Organization prequalified insecticides. Molecular modelling programs are best suited to display molecular interactions between ligands and the target proteins. The docking modes that generate ligand poses closer to the binding site show high accuracy in predicting the ligand binding mode. The implicit solvation approach such as molecular mechanics-generalized born surface area (MM-GBSA) is a more reliable method to predict ligand onformations and binding affinities. Apart from covalent docking studies being scarce, current molecular docking programs do not adequately possess the covalent docking reaction algorithm to display the molecular mechanism of OPs at the AgAChE catalytic site. This results into OP docking studies commonly being conducted through noncovalent pannels. The aim of this study was to establish the optimim covalent docking system for OPs through manual customization of Schrödinger's Glide covalent docking reaction algorithm. To achieve this, a newly customized covalent reaction algorithm was assessed on a set of ligands covering aromatic, non-aromatic and hydrophobic OPs and compared to the noncovalent docking results in terms of reliability based on the reported X-ray diffraction molecular interactions and crystal poses. The study established that by virtue of omitting the well-known OP hydrolysis, noncovalent mode suggested molecular interactions that were further from the catalytic triad and could not otherwise occur when the molecule is hydrolyzed as in the customized covalent docking mode. Moreover, the MM-GBSA concurred with the optimized covalent docking in eliminating such inaccurate molecular interactions. Additionally, the covalent docking mode confined the interactions and ligand poses to the catalytic site indicating relatively high accuracy and reliability. This study reports the optimized covalent docking panel that effectively confirmed the molecular mechanisms of OPs, as well as indentifying the corresponding amino acid residues required to stabilize the aromatic, non-aromatic and hydrophobic OPs at the AgAChE catalytic site in line with the reported X-ray diffraction studies. As such, the proposed manual customization of the Schrödinger's Glide covalent docking platform can be used to reliably predict molecular interactions between OPs and AgAChE target.

Molecular modeling assisted identification and biological evaluation of potent cathepsin S inhibitors

Cathepsin S (CatS) is one of the cysteinyl cathepsins widely studied for its clinical significance and found to be a promising therapeutic target for several diseases; to name a few is arthritis, allergic inflammation, cancer, diabetes, obesity, and cystic fibrosis. Elevated CatS level is a contributing factor for related disorders, and therefore among different strategies to regulate the activity of CatS, one is to design a quality inhibitor. Earlier, we have demonstrated a highly selective CatS inhibitor, RO5444101 interacts primarily with the S2 pocket of the protein which is structurally unique in contrast to other variants of cathepsin. However, the molecular properties of RO5444101 can question its efficacy at the clinical level. In the present study, we have implemented a series of molecular modeling methods to screen the Maybridge library considering the pharmacophoric features of RO5444101 and other relevant inhibitors of CatS. Based on the priority list, eight hits were subjected to biological evaluation. Subsequently, KM07987 was found to be most potent, with the IC₅₀ of <5 μM. Molecular dynamics simulations also relate to our experimental findings and propose the importance of CatS's S2 pocket, which primarily interacts with the inhibitors. Based on the S2 pocket interactions, structural modifications of the promising hits can further be translated into novel scaffolds for improved inhibition of CatS.

CovaDOTS: In Silico Chemistry-Driven Tool to Design Covalent Inhibitors Using a Linking Strategy

We recently reported an integrated fragment-based optimization strategy called DOTS (Diversity Oriented Target-focused Synthesis) that combines automated virtual screening (VS) with semirobotized organic synthesis coupled to in vitro evaluation. The molecular modeling part consists of hit-to-lead chemistry, based on the growing paradigm. Here, we have extended the applicability of the DOTS strategy by adding new functionalities, allowing a generic chemistry-driven linking approach with a particular emphasis on covalent drugs. Indeed, the covalent mode of action can be described as a specific case of linking, where suitable linkers are sought to fuse a bound organic compound with a nucleophilic protein side chain. The proof of concept is established using three retrospective study cases in which known noncovalent inhibitors have been converted to covalent inhibitors. Our method is able to automatically design reference covalent inhibitors (and/or analogs) from an initial activated substructure and predict their binding mode. More importantly, the reference compounds are ranked high among several hundred putative adducts, demonstrating the utility of the approach to design covalent inhibitors.

Calculate protein-ligand binding affinities with the extended linear interaction energy method: application on the Cathepsin S set in the D3R Grand Challenge 3

We participated in the Cathepsin S (CatS) sub-challenge of the Drug Design Data Resource (D3R) Grand Challenge 3 (GC3) in 2017 to blindly predict the binding poses of 24 CatS-bound ligands, the binding affinity ranking of 136 ligands, and the binding free energies of a subset of 33 ligands in Stage 1A and Stage 2. Our submitted predictions ranked relatively well compared to the submissions from other participants. Here we present our methodologies used in the challenge. For the binding pose prediction, we employed the Glide module in the Schrodinger Suite 2017 and AutoDock Vina. For the binding affinity/free energy prediction, we carried out molecular dynamics simulations of the complexes in explicit water solvent with counter ions, and then estimated the binding free energies with our newly developed model of extended linear interaction energy (ELIE), which is inspired by two other popular end-point approaches: the linear interaction energy (LIE) method, and the molecular mechanics with Poisson-Boltzmann surface area solvation method (MM/PBSA). Our studies suggest that ELIE is a good trade-off between efficiency and accuracy, and it is appropriate for filling the gap between the high-throughput docking and scoring methods and the rigorous but much more computationally demanding methods like free energy perturbation (FEP) or thermodynamics integration (TI) in computer-aided drug design (CADD) projects.

Insights from molecular modeling into the selective inhibition of cathepsin S by its inhibitor

Cathepsin S has been demonstrated to play a crucial role in the remodeling of extracellular matrix proteins such as elastin and collagen, which in turn contribute to the structural integrity of the cardiovascular wall. Atherosclerotic lesions, aneurysm formation, plaque rupture, thrombosis, and calcification are some of the cardiovascular disorders related to cathepsin S. A highly selective inhibitor of human as well as animal cathepsin S, RO5444101, was recently reported to attenuate the progression of atherosclerotic lesions. Here, we attempted to gain insight into the molecular mechanism of action of RO5444101 on cathepsin S by performing molecular docking and molecular dynamics (MD) simulation studies. The results of our studies correlate well with relevant reported experimental data and potentially explain the selectivity of this inhibitor for cathepsin S rather than cathepsin L1/L, cathepsin L2/V, and cathepsin K, which share conserved catalytic sites and have sequence similarities of 49%, 50%, and 55%, respectively, with respect to cathepsin S. In contrast to those closely related cathepsins, 20 ns MD simulation data reveal that the overall interaction of cathepsin S with RO5444101 is more stable and involves more protein-molecule interactions than the interactions of the inhibitor with the other cathepsins. This study therefore considerably improves our understanding of the molecular mechanism responsible for cathepsin S inhibition and facilitates the identification of potential novel selective inhibitors of cathepsin S.

Discovery of novel covalent proteasome inhibitors through a combination of pharmacophore screening, covalent docking, and molecular dynamics simulations

The ubiquitin-proteasome pathway plays a pivotal role in the regulation of cellular protein processing and degradation. Proteasome inhibitors (PIs) have enormous potential to treat multiple myeloma, solid tumors, parasites, inflammation, and immune diseases, which is spurring the development of new types of PIs with enhanced efficacy, fewer side effects, and reduced drug resistance. Nevertheless, virtual screening for covalent PIs has rarely been reported because calculating the covalent binding energy is a challenging task. The aim of this study was to discover new covalent inhibitors of the 20S proteasome. The structures of PIs were manually divided into two parts: a noncovalent binding part resulting from virtual screening, and an epoxyketone group that was pre-selected as a covalent binding part. The SPECS database was screened by noncovalent docking and a pharmacophore model built with the 20S proteasome. After validating the covalent conjugation, 88 hits with epoxyketone were covalently docked into the 20S proteasome to analyze the intermolecular interactions. Four compounds were selected after multiple filtration and validations. Molecular dynamics simulations were performed to check the stability of the noncovalent and covalent docked ligand-enzyme complexes and investigate the interaction patterns of the screened inhibitors. Finally, two compounds with novel aromatic backbones, reasonable interactions, and stable covalent binding modes were retained. These compounds can serve as potential hits for further biological evaluation.

Pharmacophore-based virtual screening and experimental validation of novel inhibitors against cyanobacterial fructose-1,6-/sedoheptulose-1,7-bisphosphatase

Cyanobacterial fructose-1,6-/sedoheptulose-1,7-bisphoshatase (cy-FBP/SBPase) is a potential enzymatic target for screening of novel inhibitors that can combat harmful algal blooms. In the present study, we targeted the substrate binding pocket of cy-FBP/SBPase. A series of novel hit compounds from the SPECs database were selected by using a pharmacophore-based virtual screening strategy. Most of the compounds tested exhibited moderate inhibitory activities (IC50 = 20.7-176.9 μM) against cy-FBP/SBPase. Compound 2 and its analogues 10 and 11 exhibited strong inhibitory activities, with IC50 values of 20.7, 13.4, and 19.0 μM against cy-FBP/SBPase in vitro and EC50 values of 12.3, 10.9, and 2.9 ppm against cyanobacteria Synechocystis PCC6803 in vivo, respectively. The compound 10 was selected in order to perform a refined docking study to investigate the rational binding mode of inhibitors with cy-FBP/SBPase. Furthermore, possible interactions of the residues with inhibitors were examined by site-directed mutagenesis, enzymatic assays, and fluorescence spectral analyses. The results provide insight into the binding mode between the inhibitors and the substrate binding pocket. The observed theoretical and experimental results are in concert, indicating that the modeling strategies and screening methods employed are appropriate to search for novel lead compounds having both structural diversity and high inhibitory activity against cy-FBP/SBPase.

Residue-specific annotation of disorder-to-order transition and cathepsin inhibition of a propeptide-like crammer from D. melanogaster

Drosophila melanogaster crammer is a novel cathepsin inhibitor involved in long-term memory formation. A molten globule-to-ordered structure transition is required for cathepsin inhibition. This study reports the use of alanine scanning to probe the critical residues in the two hydrophobic cores and the salt bridges of crammer in the context of disorder-to-order transition and cathepsin inhibition. Alanine substitution of the aromatic residues W9, Y12, F16, Y20, Y32, and W53 within the hydrophobic cores, and charged residues E8, R28, R29, and E67 in the salt bridges considerably decrease the ability of crammer to inhibit Drosophila cathepsin B (CTSB). Far-UV circular dichroism (CD), intrinsic fluorescence, and nuclear magnetic resonance (NMR) spectroscopies show that removing most of the aromatic and charged side-chains substantially reduces thermostability, alters pH-dependent helix formation, and disrupts the molten globule-to-ordered structure transition. Molecular modeling indicates that W53 in the hydrophobic Core 2 is essential for the interaction between crammer and the prosegment binding loop (PBL) of CTSB; the salt bridge between R28 and E67 is critical for the appropriate alignment of the α-helix 4 toward the CTSB active cleft. The results of this study show detailed residue-specific dissection of folding transition and functional contributions of the hydrophobic cores and salt bridges in crammer, which have hitherto not been characterized for cathepsin inhibition by propeptide-like cysteine protease inhibitors. Because of the involvements of cathepsin inhibitors in neurodegenerative diseases, these structural insights can serve as a template for further development of therapeutic inhibitors against human cathepsins.

Redox-based inactivation of cysteine cathepsins by compounds containing the 4-aminophenol moiety

Background

Redox cycling compounds have been reported to cause false positive inhibition of proteases in drug discovery studies. This kind of false positives can lead to unusually high hit rates in high-throughput screening campaigns and require further analysis to distinguish true from false positive hits. Such follow-up studies are both time and resource consuming.

Methods and Findings

In this study we show that 5-aminoquinoline-8-ol is a time-dependent inactivator of cathepsin B with a k_inact/K_I of 36.7±13.6 M⁻¹s⁻¹ using enzyme kinetics. 5-Aminoquinoline-8-ol inhibited cathepsins H, L and B in the same concentration range, implying a non-specific mechanism of inhibition. Further analogues, 4-aminonaphthalene-1-ol and 4-aminophenol, also displayed time-dependent inhibition of cathepsin B with k_inact/K_I values of 406.4±10.8 and 36.5±1.3 M⁻¹s⁻¹. No inactivation occurred in the absence of either the amino or the hydroxyl group, suggesting that the 4-aminophenol moiety is a prerequisite for enzyme inactivation. Induction of redox oxygen species (ROS) by 4-aminophenols in various redox environments was determined by the fluorescent probe 2′,7′-dichlorodihydrofluorescein diacetate. Addition of catalase to the assay buffer significantly abrogated the ROS signal, indicating that H₂O₂ is a component of the ROS induced by 4-aminophenols. Furthermore, using mass spectrometry, active site probe DCG-04 and isoelectric focusing we show that redox inactivation of cysteine cathepsins by 5-aminoquinoline-8-ol is active site directed and leads to the formation of sulfinic acid.

Conclusions

In this study we report that compounds containing the 4-aminophenol moiety inactivate cysteine cathepsins through a redox-based mechanism and are thus likely to cause false positive hits in the screening assays for cysteine proteases.

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.

Upregulation of cathepsin S in psoriatic keratinocytes

Cathepsin S (CATS) is a cysteine protease, well known for its role in MHC class II-mediated antigen presentation and extracellular matrix degradation. Disturbance of the expression or metabolism of this protease is a concomitant feature of several diseases. Given this importance we studied the localization and regulation of CATS expression in normal and pathological human/mouse skin. In normal human skin CATS-immunostaining is mainly present in the dermis and is localized in macrophages, Langerhans, T- and endothelial cells, but absent in keratinocytes. In all analyzed pathological skin biopsies, i.e. atopic dermatitis, actinic keratosis and psoriasis, CATS staining is strongly increased in the dermis. But only in psoriasis, CATS-immunostaining is also detectable in keratinocytes. We show that cocultivation with T-cells as well as treatment with cytokines can trigger expression and secretion of CATS, which is involved in MHC II processing in keratinocytes. Our data provide first evidence that CATS expression (i) is selectively induced in psoriatic keratinocytes, (ii) is triggered by T-cells and (iii) might be involved in keratinocytic MHC class II expression, the processing of the MHC class II-associated invariant chain and remodeling of the extracellular matrix. This paper expands our knowledge on the important role of keratinocytes in dermatological disease.

Comparison of three preprocessing filters efficiency in virtual screening: identification of new putative LXRbeta regulators as a test case

In silico screening methodologies are widely recognized as efficient approaches in early steps of drug discovery. However, in the virtual high-throughput screening (VHTS) context, where hit compounds are searched among millions of candidates, three-dimensional comparison techniques and knowledge discovery from databases should offer a better efficiency to finding novel drug leads than those of computationally expensive molecular dockings. Therefore, the present study aims at developing a filtering methodology to efficiently eliminate unsuitable compounds in VHTS process. Several filters are evaluated in this paper. The first two are structure-based and rely on either geometrical docking or pharmacophore depiction. The third filter is ligand-based and uses knowledge-based and fingerprint similarity techniques. These filtering methods were tested with the Liver X Receptor (LXR) as a target of therapeutic interest, as LXR is a key regulator in maintaining cholesterol homeostasis. The results show that the three considered filters are complementary so that their combination should generate consistent compound lists of potential hits.

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

Cathepsin B is a potential target for the development of drugs to treat several important human diseases. A number of inhibitors targeting this protein have been developed in the past several years. Recently, a group of small molecules were identified to have inhibitory activity against cathepsin B through high throughput screening (HTS) tests. In this study, traditional continuous and binary QSAR models were built to classify the biological activities of previously identified compounds and to distinguish active compounds from inactive compounds for drug development based on the calculated molecular and physicochemical properties. Strong correlations were obtained for the continuous QSAR models with regression correlation coefficients (r²) and cross-validated correlation coefficients (q²) of 0.77 and 0.61 for all compounds, and 0.82 and 0.68 for the compound set excluding 3 outliers, respectively. The models were further validated through the leave-one-out (LOO) method and the training-test set method. The binary models demonstrated a strong level of predictability in distinguishing the active compounds from inactive compounds with accuracies of 0.89 and 0.94 for active and inactive compounds, respectively, in non-cross-validated models. Similar results were obtained for the cross-validated models. Collectively, these results demonstrate the models’ ability to discriminate between active and inactive compounds, suggesting that the models may be used to pre-screen compounds to facilitate compound optimization and to design novel inhibitors for drug development.