Benzo[d]isothiazole 1,1-dioxide derivatives as dual functional inhibitors of 5-lipoxygenase and microsomal prostaglandin E(2) synthase-1

Microsomal prostaglandin E2 synthase-1 and its inhibitors: Molecular mechanisms and therapeutic significance

Inflammation is closely linked to the abnormal phospholipid metabolism chain of cyclooxygenase-2/microsomal prostaglandin E₂ synthase-1/prostaglandin E₂ (COX-2/mPGES-1/PGE₂). In clinical practice, non-steroidal anti-inflammatory drugs (NSAIDs) as upstream COX-2 enzyme activity inhibitors are widely used to block COX-2 cascade to relieve inflammatory response. However, NSAIDs could also cause cardiovascular and gastrointestinal side effects due to its inhibition on other prostaglandins generation. To avoid this, targeting downstream mPGES-1 instead of upstream COX is preferable to selectively block overexpressed PGE₂ in inflammatory diseases. Some mPGES-1 inhibitor candidates including synthetic compounds, natural products and existing anti-inflammatory drugs have been proved to be effective in in vitro experiments. After 20 years of in-depth research on mPGES-1 and its inhibitors, ISC 27864 have completed phase II clinical trial. In this review, we intend to summarize mPGES-1 inhibitors focused on their inhibitory specificity with perspectives for future drug development.

Assessment of anti-inflammatory-like, antioxidant activities and molecular docking of three alkynyl-substituted 3-ylidene-dihydrobenzo[d]isothiazole 1,1-dioxide derivatives

The presence of enyne and benzoisothiazole functions in the molecular architecture of compounds 1, 2 and 3 were expected to provide biochemical activities. In the present work, we first examined the molecular surface contact of three alkynyl-substituted 3-ylidenedihydrobenzo[d] isothiazole 1,1-dioxides. The analysis of the Hirshfeld surfaces reveals that only compound 3 exhibited a well-defined red spots, indicating intermolecular interactions identified as S-O⋯H, C-H⋯O and C-O⋯H contacts. Comparative fingerprint histograms of the three compounds show that close pair interactions are dominated by C-H⋯H-C contact. By UV-visible analysis, compound 1 showed the most intense absorbances at 407 and 441 nm, respectively. The radical scavenging activity explored in the DPPH test, shows that only 1 exhibited low anti-radical activity. Furthermore, cellular antioxidant capacity of benzoisothiazoles 1-3 was investigated with PMA-activated HL-60 cells using chemiluminescence and fluorescence techniques in the presence of L-012 and Amplex Red probe, respectively. Results highlight that compound 1 exhibited moderate anti-ROS capacity while compounds 2 and 3 enhanced ROS production. The cytotoxicity test performed on HL-60 cells, using the MTS assay, confirmed the lack of toxicity of the tested benzoisothiazole 1 compared to 2 and 3 which show low cytotoxicity (≤30%). Anti-catalytic activity was evaluated by following the inhibitory potential of the benzoisothiazoles on MPO activity and depicted benzoisothiazoles-MPO interactions by docking. Both SIEFED and docking studies demonstrated an anti-catalytic activity of the tested benzoisothiazoles towards MPO with the best activity for compound 2.

Clinical data mining reveals analgesic effects of lapatinib in cancer patients

Microsomal prostaglandin E2 synthase 1 (mPGES-1) is recognized as a promising target for a next generation of anti-inflammatory drugs that are not expected to have the side effects of currently available anti-inflammatory drugs. Lapatinib, an FDA-approved drug for cancer treatment, has recently been identified as an mPGES-1 inhibitor. But the efficacy of lapatinib as an analgesic remains to be evaluated. In the present clinical data mining (CDM) study, we have collected and analyzed all lapatinib-related clinical data retrieved from clinicaltrials.gov. Our CDM utilized a meta-analysis protocol, but the clinical data analyzed were not limited to the primary and secondary outcomes of clinical trials, unlike conventional meta-analyses. All the pain-related data were used to determine the numbers and odd ratios (ORs) of various forms of pain in cancer patients with lapatinib treatment. The ORs, 95% confidence intervals, and P values for the differences in pain were calculated and the heterogeneous data across the trials were evaluated. For all forms of pain analyzed, the patients received lapatinib treatment have a reduced occurrence (OR 0.79; CI 0.70–0.89; P = 0.0002 for the overall effect). According to our CDM results, available clinical data for 12,765 patients enrolled in 20 randomized clinical trials indicate that lapatinib therapy is associated with a significant reduction in various forms of pain, including musculoskeletal pain, bone pain, headache, arthralgia, and pain in extremity, in cancer patients. Our CDM results have demonstrated the significant analgesic effects of lapatinib, suggesting that lapatinib may be repurposed as a novel type of analgesic.

DREAM-in-CDM Approach and Identification of a New Generation of Anti-inflammatory Drugs Targeting mPGES-1

Microsomal prostaglandin E2 synthase-1 (mPGES-1) is known as an ideal target for next generation of anti-inflammatory drugs without the side effects of currently available anti-inflammatory drugs. However, there has been no clinically promising mPGES-1 inhibitor identified through traditional drug discovery and development route. Here we report a new approach, called DREAM-in-CDM (Drug Repurposing Effort Applying Integrated Modeling-in vitro/vivo-Clinical Data Mining), to identify an FDA-approved drug suitable for use as an effective analgesic targeting mPGES-1. The DREAM-in-CDM approach consists of three steps: computational screening of FDA-approved drugs; in vitro and/or in vivo assays; and clinical data mining. By using the DREAM-in-CDM approach, lapatinib has been identified as a promising mPGES-1 inhibitor which may have significant anti-inflammatory effects to relieve various forms of pain and possibly treat various inflammation conditions involved in other inflammation-related diseases such as the lung inflammation caused by the newly identified COVID-19. We anticipate that the DREAM-in-CDM approach will be used to repurpose FDA-approved drugs for various new therapeutic indications associated with new targets.

Druggable Prostanoid Pathway

Prostanoids (prostaglandins, prostacyclin and thromboxane) belong to the oxylipin family of biologically active lipids generated from arachidonic acid (AA). Protanoids control numerous physiological and pathological processes. Cyclooxygenase (COX) is a rate-limiting enzyme involved in the conversion of AA into prostanoids. There are two COX isozymes: the constitutive COX-1 and the inducible COX-2. COX-1 and COX-2 have similar structures, catalytic activities, and subcellular localizations but differ in patterns of expression and biological functions. Non-selective COX-1/2 or traditional, non-steroidal anti-inflammatory drugs (tNSAIDs) target both COX isoforms and are widely used to relieve pain, fever and inflammation. However, the use of NSAIDs is associated with various side effects, particularly in the gastrointestinal tract. NSAIDs selective for COX-2 inhibition (coxibs) were purposefully designed to spare gastrointestinal toxicity, but predisposed patients to increased cardiovascular risks. These health complications from NSAIDs prompted interest in the downstream effectors of the COX enzymes as novel drug targets. This chapter describes various safety issues with tNSAIDs and coxibs, and discusses the current development of novel classes of drugs targeting the prostanoid pathway, including nitrogen oxide- and hydrogen sulfide-releasing NSAIDs, inhibitors of prostanoid synthases, dual inhibitors, and prostanoid receptor agonists and antagonists.

Structure-based discovery of mPGES-1 inhibitors suitable for preclinical testing in wild-type mice as a new generation of anti-inflammatory drugs

Human mPGES-1 is recognized as a promising target for next generation of anti-inflammatory drugs without the side effects of currently available anti-inflammatory drugs, and various inhibitors have been reported in the literature. However, none of the reported potent inhibitors of human mPGES-1 has shown to be also a potent inhibitor of mouse or rat mPGES-1, which prevents using the well-established mouse/rat models of inflammation-related diseases for preclinical studies. Hence, despite of extensive efforts to design and discover various human mPGES-1 inhibitors, the promise of mPGES-1 as a target for the next generation of anti-inflammatory drugs has never been demonstrated in any wild-type mouse/rat model using an mPGES-1 inhibitor. Here we report discovery of a novel type of selective mPGES-1 inhibitors potent for both human and mouse mPGES-1 enzymes through structure-based rational design. Based on in vivo studies using wild-type mice, the lead compound is indeed non-toxic, orally bioavailable, and more potent in decreasing the PGE₂ (an inflammatory marker) levels compared to the currently available drug celecoxib. This is the first demonstration in wild-type mice that mPGES-1 is truly a promising target for the next generation of anti-inflammatory drugs.

Structure-based discovery of mPGES-1 inhibitors suitable for preclinical testing in wild-type mice as a new generation of anti-inflammatory drugs

Human mPGES-1 is recognized as a promising target for next generation of anti-inflammatory drugs without the side effects of currently available anti-inflammatory drugs, and various inhibitors have been reported in the literature. However, none of the reported potent inhibitors of human mPGES-1 has shown to be also a potent inhibitor of mouse or rat mPGES-1, which prevents using the well-established mouse/rat models of inflammation-related diseases for preclinical studies. Hence, despite of extensive efforts to design and discover various human mPGES-1 inhibitors, the promise of mPGES-1 as a target for the next generation of anti-inflammatory drugs has never been demonstrated in any wild-type mouse/rat model using an mPGES-1 inhibitor. Here we report discovery of a novel type of selective mPGES-1 inhibitors potent for both human and mouse mPGES-1 enzymes through structure-based rational design. Based on in vivo studies using wild-type mice, the lead compound is indeed non-toxic, orally bioavailable, and more potent in decreasing the PGE₂ (an inflammatory marker) levels compared to the currently available drug celecoxib. This is the first demonstration in wild-type mice that mPGES-1 is truly a promising target for the next generation of anti-inflammatory drugs.

Natural products as inhibitors of prostaglandin E2 and pro-inflammatory 5-lipoxygenase-derived lipid mediator biosynthesis

Non-steroidal anti-inflammatory drugs (NSAIDs) inhibit prostanoid formation and represent prevalent therapeutics for treatment of inflammatory disorders. However, NSAIDs are afflicted with severe side effects, which might be circumvented by more selective suppression of pro-inflammatory eicosanoid biosynthesis. This concept led to dual inhibitors of microsomal prostaglandin E₂ synthase (mPGES)-1 and 5-lipoxygenase that are crucial enzymes in the biosynthesis of pro-inflammatory prostaglandin E₂ and leukotrienes. The potential of their dual inhibition in light of superior efficacy and safety is discussed. Focus is placed on natural products, for which direct inhibition of mPGES-1 and leukotriene biosynthesis has been confirmed.

Recent development of lipoxygenase inhibitors as anti-inflammatory agents

Inflammation is favorable in most cases, because it is a kind of body defensive response to external stimuli; sometimes, inflammation is also harmful, such as attacks on the body's own tissues. It could be that inflammation is a unified process of injury and resistance to injury. Inflammation brings extreme pain to patients, showing symptoms of rubor, swelling, fever, pain and dysfunction. As the specific mechanism is not clear yet, the current anti-inflammatory agents are given priority for relieving suffering of patients. Thus it is emergent to find new anti-inflammatory agents with rapid effect. Lipoxygenase (LOX) is a kind of rate-limiting enzyme in the process of arachidonic acid metabolism into leukotriene (LT) which mediates the occurrence of inflammation. The inhibition of LOX can reduce LT, thereby producing an anti-inflammatory effect. In this review, the LOX inhibitors reported in recent years are summarized, and, in particular, their activities, structure-activity relationships and molecular docking studies are emphasized, which will provide new ideas to design novel LOX inhibitors.

Multiple target-centric strategy to tame inflammation

Single-target inhibition is an unsatisfactory therapeutic option to treat multifactorial pathologies, brought into limelight 'paradox of inflammation' beside dearth of innovation, rationalizes a shift toward 'multiple-target' design concept in anti-inflammatory research field. To improvise, two platform strategies, drugs mixture or multitarget drugs, are plausible. Dual cyclooxygenase/lipoxygenase inhibitor 'licofelone' developed after the backfire of rofecoxib due to safety concerns has fetched first light of triumph of the latter strategy. As hitting multiple targets in restraint is perhaps more viable strategy rather than single target, this review, outlines the most germane multiple target agents of synthetic and natural origin placing clear advantage in favors of multitarget strategy as real therapeutic solution for inflammation.

Selective inhibitors of human mPGES-1 from structure-based computational screening

Human mPGES-1 is recognized as a promising target for next generation of anti-inflammatory drugs. Although various mPGES-1 inhibitors have been reported in literature, few have entered clinical trials and none has been proven clinically useful so far. It is highly desired for developing the next generation of therapeutics for inflammation-related diseases to design and discover novel inhibitors of mPGES-1 with new scaffolds. Here, we report the identification of a series of new, potent and selective inhibitors of human mPGES-1 with diverse scaffolds through combined computational and experimental studies. The computationally modeled binding structures of these new inhibitors of mPGES-1 provide some interesting clues for rational design of modified structures of the inhibitors to more favorably bind with mPGES-1.

Computational models for the classification of mPGES-1 inhibitors with fingerprint descriptors

Human microsomal prostaglandin [Formula: see text] synthase (mPGES)-1 is a promising drug target for inflammation and other diseases with inflammatory symptoms. In this work, we built classification models which were able to classify mPGES-1 inhibitors into two groups: highly active inhibitors and weakly active inhibitors. A dataset of 1910 mPGES-1 inhibitors was separated into a training set and a test set by two methods, by a Kohonen's self-organizing map or by random selection. The molecules were represented by different types of fingerprint descriptors including MACCS keys (MACCS), CDK fingerprints, Estate fingerprints, PubChem fingerprints, substructure fingerprints and 2D atom pairs fingerprint. First, we used a support vector machine (SVM) to build twelve models with six types of fingerprints and found that MACCS had some advantage over the other fingerprints in modeling. Next, we used naïve Bayes (NB), random forest (RF) and multilayer perceptron (MLP) methods to build six models with MACCS only and found that models using RF and MLP methods were better than NB. Finally, all the models with MACCS keys were used to make predictions on an external test set of 41 compounds. In summary, the models built with MACCS keys and using SVM, RF and MLP methods show good prediction performance on the test sets and the external test set. Furthermore, we made a structure-activity relationship analysis between mPGES-1 and its inhibitors based on the information gain of fingerprints and could pinpoint some key functional groups for mPGES-1 activity. It was found that highly active inhibitors usually contained an amide group, an aromatic ring or a nitrogen heterocyclic ring, and several heteroatoms substituents such as fluorine and chlorine. The carboxyl group and sulfur atom groups mainly appeared in weakly active inhibitors.

Computational Multitarget Drug Design

Designing drugs that can simultaneously interact with multiple targets is a promising approach for treating complicated diseases. Compared to using combinations of single target drugs, multitarget drugs have advantages of higher efficacy, improved safety profile, and simpler administration. Many in silico methods have been developed to approach different aspects of this polypharmacology-guided drug design, particularly for drug repurposing and multitarget drug design. In this review, we summarize recent progress in computational multitarget drug design and discuss their advantages and limitations. Perspectives for future drug development will also be discussed.

New Caffeic Acid Phenylethyl Ester Analogs Bearing Substituted Triazole: Synthesis and Structure-Activity Relationship Study towards 5-Lipoxygenase Inhibition

Leukotrienes are biosynthesized by the conversion of arachidonic acid by 5-Lipoxygenase and play a key role in many inflammatory disorders. Inspired by caffeic acid phenylethyl ester (CAPE) (2) and an analog carrying a triazole substituted by cinnamoyl and 5-LO inhibitors recently reported by our team, sixteen new CAPE analogs bearing substituted triazole were synthesized by copper catalyzed Huisgen 1,3-dipolar cycloaddition. Compound10e, an analog bearingp-CF3 phenethyl substituted triazole, was equivalent to CAPE (2) but clearly surpassed Zileuton (2), the only approved 5-LO inhibitor. Substitution of the phenethyl moiety by cyclohexylethyl, as with12g, clearly increased 5-LO inhibition which confirms the importance of hydrophobic interactions. Molecular docking revealed new hydrogen bonds andπ-πinteractions between the enzyme and some of the investigated compounds. Overall, this work highlights the relevance of exploring polyphenolic compounds as leukotrienes biosynthesis inhibitors.

Nonsteroidal Anti-Inflammatory Therapy: A Journey Toward Safety

The efficacy of nonsteroidal anti-inflammatory drugs (NSAIDs) against inflammation, pain, and fever has been supporting their worldwide use in the treatment of painful conditions and chronic inflammatory diseases until today. However, the long-term therapy with NSAIDs was soon associated with high incidences of adverse events in the gastrointestinal tract. Therefore, the search for novel drugs with improved safety has begun with COX-2 selective inhibitors (coxibs) being straightaway developed and commercialized. Nevertheless, the excitement has fast turned to disappointment when diverse coxibs were withdrawn from the market due to cardiovascular toxicity. Such events have once again triggered the emergence of different strategies to overcome NSAIDs toxicity. Here, an integrative review is provided to address the breakthroughs of two main approaches: (i) the association of NSAIDs with protective mediators and (ii) the design of novel compounds to target downstream and/or multiple enzymes of the arachidonic acid cascade. To date, just one phosphatidylcholine-associated NSAID has already been approved for commercialization. Nevertheless, the preclinical and clinical data obtained so far indicate that both strategies may improve the safety of nonsteroidal anti-inflammatory therapy.

Computer modeling in predicting the bioactivity of human 5-lipoxygenase inhibitors

5-Lipoxygenase (5-LOX) is a key enzyme in the inflammatory path. Inhibitors of 5-LOX are useful for the treatment of diseases like arthritis, cancer, and asthma. We have collected a dataset including 220 human 5-LOX inhibitors for classification. A self-organizing map (SOM), a support vector machine (SVM), and a multilayer perceptron (MLP) algorithm were used to build models with selected descriptors for classifying 5-LOX inhibitors into active and weakly active ones. MACCS fingerprints were used in this model building process. The accuracy (Q) and Matthews correlation coefficient (MCC) of the best SOM model (Model 1A) were 86.49% and 0.73 on the test set, respectively. The Q and MCC of the best SVM model (Model 2A) were 82.67% and 0.64 on the test set, respectively. The Q and MCC of the best MLP model (Model 3B) were 84.00% and 0.67 on the test set, respectively. In addition, 180 inhibitors with bioactivities measured by fluorescence method were further used for a quantitative prediction. Multiple linear regression (MLR) and SVM algorithms were used to build models to predict the [Formula: see text] values. The correlation coefficients (R) of the MLR model (Model Q1) and the SVM model (Model Q2) were 0.72 and 0.74 on the test set, respectively.

Hit-to-lead optimization of phenylsulfonyl hydrazides for a potent suppressor of PGE2 production: Synthesis, biological activity, and molecular docking study

Preliminary hit-to-lead optimization of a novel series of phenylsulfonyl hydrazide derivatives, which were derived from the high throughput screening hit compound 1 (IC50=5700nM against PGE2 production), for a potent suppressor of PGE2 production is described. Subsequent optimization led to the identification of the potent lead compound 8n with IC50 values of 4.5 and 6.9nM, respectively, against LPS-induced PGE2 production and NO production in RAW 264.7 macrophage cells. In addition, 8n was about 30- and >150-fold more potent against mPGES-1 enzyme in a cell-free assay (IC50=70nM) than MK-886 and hit compound 1, respectively. Molecular docking suggests that compound 8n could inhibit PGE2 production by blocking the PGH2 binding site of human mPGES-1 enzyme.

Diverse ways of perturbing the human arachidonic acid metabolic network to control inflammation

Inflammation and other common disorders including diabetes, cardiovascular disease, and cancer are often the result of several molecular abnormalities and are not likely to be resolved by a traditional single-target drug discovery approach. Though inflammation is a normal bodily reaction, uncontrolled and misdirected inflammation can cause inflammatory diseases such as rheumatoid arthritis and asthma. Nonsteroidal anti-inflammatory drugs including aspirin, ibuprofen, naproxen, or celecoxib are commonly used to relieve aches and pains, but often these drugs have undesirable and sometimes even fatal side effects. To facilitate safer and more effective anti-inflammatory drug discovery, a balanced treatment strategy should be developed at the biological network level. In this Account, we focus on our recent progress in modeling the inflammation-related arachidonic acid (AA) metabolic network and subsequent multiple drug design. We first constructed a mathematical model of inflammation based on experimental data and then applied the model to simulate the effects of commonly used anti-inflammatory drugs. Our results indicated that the model correctly reproduced the established bleeding and cardiovascular side effects. Multitarget optimal intervention (MTOI), a Monte Carlo simulated annealing based computational scheme, was then developed to identify key targets and optimal solutions for controlling inflammation. A number of optimal multitarget strategies were discovered that were both effective and safe and had minimal associated side effects. Experimental studies were performed to evaluate these multitarget control solutions further using different combinations of inhibitors to perturb the network. Consequently, simultaneous control of cyclooxygenase-1 and -2 and leukotriene A4 hydrolase, as well as 5-lipoxygenase and prostaglandin E2 synthase were found to be among the best solutions. A single compound that can bind multiple targets presents advantages including low risk of drug-drug interactions and robustness regarding concentration fluctuations. Thus, we developed strategies for multiple-target drug design and successfully discovered several series of multiple-target inhibitors. Optimal solutions for a disease network often involve mild but simultaneous interventions of multiple targets, which is in accord with the philosophy of traditional Chinese medicine (TCM). To this end, our AA network model can aptly explain TCM anti-inflammatory herbs and formulas at the molecular level. We also aimed to identify activators for several enzymes that appeared to have increased activity based on MTOI outcomes. Strategies were then developed to predict potential allosteric sites and to discover enzyme activators based on our hypothesis that combined treatment with the projected activators and inhibitors could balance different AA network pathways, control inflammation, and reduce associated adverse effects. Our work demonstrates that the integration of network modeling and drug discovery can provide novel solutions for disease control, which also calls for new developments in drug design concepts and methodologies. With the rapid accumulation of quantitative data and knowledge of the molecular networks of disease, we can expect an increase in the development and use of quantitative disease models to facilitate efficient and safe drug discovery.

Rh(iii)-catalyzed tandem oxidative olefination-cyclization of aryl sulfonamides

An efficient Rh(iii)-catalyzed ortho-selective C–H activation and tandem oxidative olefination-cyclization of aryl sulfonamides is described. The protocol has been applied to various substrates with good functional group tolerance.