Discovery of Highly Potent Microsomal Prostaglandin E2 Synthase 1 Inhibitors Using the Active Conformation Structural Model and Virtual Screen

Novel 1,2,4-triazoles derived from Ibuprofen: synthesis and in vitro evaluation of their mPGES-1 inhibitory and antiproliferative activity

Some novel triazole-bearing ketone and oxime derivatives were synthesized from Ibuprofen. In vitro cytotoxic activities of all synthesized molecules against five cancer lines (human breast cancer MCF-7, human lung cancer A549, human prostate cancer PC-3, human cervix cancer HeLa, and human chronic myelogenous leukemia K562 cell lines) were evaluated by MTT assay. In addition, mouse embryonic fibroblast cells (NIH/3T3) were also evaluated to determine the selectivity. Compounds 18, 36, and 45 were found to be the most cytotoxic, and their IC50 values were in the range of 17.46-68.76 µM, against the tested cancer cells. According to the results, compounds 7 and 13 demonstrated good anti-inflammatory activity against the microsomal enzyme prostaglandin E2 synthase-1 (mPGES-1) enzyme at IC50 values of 13.6 and 4.95 µM. The low cytotoxicity and non-mutagenity of these compounds were found interesting. Also, these compounds significantly prevented tube formation in angiogenesis studies. In conclusion, the anti-inflammatory and angiogenesis inhibitory activities of these compounds without toxicity suggested that they may be promising agents in anti-inflammatory treatment and they may be supportive agents for the cancer treatment.

Computer-Aided Drug Design of Anti-inflammatory Agents Targeting Microsomal Prostaglandin E2 Synthase-1 (mPGES-1)

Inflammation is a natural process in response to external stimuli associated with organism protection. However, this reaction could be exaggerated, leading to severe damages related to physiopathological processes, such as rheumatoid arthritis, cancer, diabetes, allergies, infections, among others. Inflammation is mainly characterized by pain, increased temperature, flushing, and edema, which can be controlled using anti-inflammatory drugs. In this context, prostaglandin E2 (PGE2) inhibition has been targeted for designing new compounds with anti-inflammatory properties. It is a bioactive lipid overproduced during an inflammatory process, in which its increased production is carried out mainly by COX-1, COX-2, and microsomal prostaglandin E2 synthase-1 (mPGES-1). Recently, studies have demonstrated that mPGES-1 inhibition is a safe strategy to develop anti-inflammatory agents, which could protect against pain, acute inflammation, arthritis, autoimmune diseases, and different types of cancers. To decrease production costs and increase the probability of discovering active substances, computer-aided drug design (CADD) approaches have been increasingly used for designing new inhibitors. Thus, this review will cover all aspects involving high-throughput virtual screening, molecular docking, dynamics, fragment-based drug design, quantitative structure-activity relationship in seeking new promising mPGES-1 inhibitors.

FBXL2 counteracts Grp94 to destabilize EGFR and inhibit EGFR-driven NSCLC growth

Abnormal activation of epidermal growth factor receptor (EGFR) drives non-small cell lung cancer (NSCLC) development. EGFR mutations-mediated resistance to tyrosine-kinase inhibitors (TKIs) is a major hurdle for NSCLC treatment. Here, we show that F-box protein FBXL2 targets EGFR and EGFR TKI-resistant mutants for proteasome-mediated degradation, resulting in suppression of EGFR-driven NSCLC growth. Reduced FBXL2 expression is associated with poor clinical outcomes of NSCLC patients. Furthermore, we show that glucose-regulated protein 94 (Grp94) protects EGFR from degradation via blockage of FBXL2 binding to EGFR. Moreover, we have identified nebivolol, a clinically used small molecule inhibitor, that can upregulate FBXL2 expression to inhibit EGFR-driven NSCLC growth. Nebivolol in combination with osimertinib or Grp94-inhibitor-1 exhibits strong inhibitory effects on osimertinib-resistant NSCLC. Together, this study demonstrates that the FBXL2-Grp94-EGFR axis plays a critical role in NSCLC development and suggests that targeting FBXL2-Grp94 to destabilize EGFR may represent a putative therapeutic strategy for TKI-resistant NSCLC.

Aberrant EGFR activation is commonly found in non-small cell lung cancer (NSCLC). Here the authors show that E3 ubiquitin ligase FBXL2 targets EGFR and EGFR tyrosine kinase inhibitor (TKI)-resistant mutants for proteasome-mediated degradation to inhibit EGFR-driven NSCLC growth and TKI resistance.

Microsomal Prostaglandin E2 Synthase-1 as a New Macromolecular Drug Target in the Prevention of Inflammation and Cancer

BACKGROUND

Cancer is one of the most life-threatening diseases worldwide. Since inflammation is considered to be one of the known characteristics of cancer, the activity of PGE2 has been paired with different tumorigenic steps such as increased tumor cell proliferation, resistance to apoptosis, increased invasiveness, angiogenesis and immunosuppression.

OBJECTIVE

It has been successfully demonstrated that inhibition of mPGES-1 prevented inflammation in preclinical studies. However, despite the crucial roles of mPGEs-1 and PGE2 in tumorigenesis, there is not much in vivo study on mPGES-1 inhibition in cancer therapy. The specificity of mPGEs-1 enzyme and its low expression level under normal conditions makes it a promising drug target with a low risk of side effects.

METHODS

A comprehensive literature search was performed for writing this review. An updated view on PGE2 biosynthesis, PGES isoenzyme family and its pharmacology and the latest information about inhibitors of mPGES-1 have been discussed.

RESULTS

In this study, it was aimed to highlight the importance of mPGES-1 and its inhibition in inflammationrelated cancer and other inflammatory conditions. Information about PGE2 biosynthesis, its role in inflammationrelated pathologies were also provided. We kept the noncancer-related inflammatory part short and tried to bring together promising molecules or scaffolds.

CONCLUSION

The information provided in this review might be useful to researchers in designing novel and potent mPGES-1 inhibitors for the treatment of cancer and inflammation.

Medicinal chemistry of vicinal diaryl scaffold: A mini review

The privileged structures have been widely used as a valuable template in new drug discovery. 1,2-Diaryl or vicinal diaryl is a simple scaffold found in many drugs and naturally occurring compounds. From synthetic point of view, the vicinal diaryl derivatives are easily accessible due to their facile and expedient syntheses. These scaffolds have shown numerous interesting pharmacological activities against various diseases with lot of clinical potentials. This review aims to highlight the evidence of vicinal diaryl motif as a privileged scaffold in COX-2 inhibitors and CA-4 analogs.

Activation of Glutathione Peroxidase 4 as a Novel Anti-inflammatory Strategy

The anti-oxidative enzyme, glutathione peroxidase 4 (GPX4), helps to promote inflammation resolution by eliminating oxidative species produced by the arachidonic acid (AA) metabolic network. Up-regulating its activity has been proposed as a promising strategy for inflammation intervention. In the present study, we aimed to study the effect of GPX4 activator on the AA metabolic network and inflammation related pathways. Using combined computational and experimental screen, we identified a novel compound that can activate the enzyme activity of GPX4 by more than two folds. We further assessed its potential in a series of cellular assays where GPX4 was demonstrated to play a regulatory role. We are able to show that GPX4 activation suppressed inflammatory conditions such as oxidation of AA and NF-κB pathway activation. We further demonstrated that this GPX4 activator can decrease the intracellular ROS level and suppress ferroptosis. Our study suggests that GPX4 activators can be developed as anti-inflammatory or cyto-protective agent in lipid-peroxidation-mediated diseases.

Novel Allosteric Activators for Ferroptosis Regulator Glutathione Peroxidase 4

Glutathione peroxidase 4 (GPX4) is essential for cell membrane repair, inflammation suppression, and ferroptosis inhibition. GPX4 upregulation provides unique drug discovery opportunities for inflammation and ferroptosis-related diseases. However, rational design of protein activators is challenging. Until now, no compound has been reported to activate the enzyme activity of GPX4. Here, we identified a potential allosteric site in GPX4 and successfully found eight GPX4 activators using a novel computational strategy and experimental studies. Compound 1 from the virtual screen increased GPX4 activity, suppressed ferroptosis, reduced pro-inflammatory lipid mediator production, and inhibited NF-κB pathway activation. Further chemical synthesis and structure-activity relationship studies revealed seven more activators. The strongest compound, 1d4, increased GPX4 activity to 150% at 20 μM in the cell-free assay and 61 μM in cell extracts. Therefore, we demonstrated that GPX4 can be directly activated using chemical compounds to suppress ferroptosis and inflammation. Meanwhile, the discovery of GPX4 activators verified the possibility of rational design of allosteric activators.

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.

Pharmacophore modelling, atom-based 3D-QSAR generation and virtual screening of molecules projected for mPGES-1 inhibitory activity

COX-2 inhibitors exhibit anticancer effects in various cancer models but due to the adverse side effects associated with these inhibitors, targeting molecules downstream of COX-2 (such as mPGES-1) has been suggested. Even after calls for mPGES-1 inhibitor design, to date there are only a few published inhibitors targeting the enzyme and displaying anticancer activity. In the present study, we have deployed both ligand and structure-based drug design approaches to hunt novel drug-like candidates as mPGES-1 inhibitors. Fifty-four compounds with tested mPGES-1 inhibitory value were used to develop a model with four pharmacophoric features. 3D-QSAR studies were undertaken to check the robustness of the model. Statistical parameters such as r² = 0.9924, q² = 0.5761 and F test = 1139.7 indicated significant predictive ability of the proposed model. Our QSAR model exhibits sites where a hydrogen bond donor, hydrophobic group and the aromatic ring can be substituted so as to enhance the efficacy of the inhibitor. Furthermore, we used our validated pharmacophore model as a three-dimensional query to screen the FDA-approved Lopac database. Finally, five compounds were selected as potent mPGES-1 inhibitors on the basis of their docking energy and pharmacokinetic properties such as ADME and Lipinski rule of five.

Chemistry and biology of microsomal prostaglandin E2 synthase-1 (mPGES-1) inhibitors as novel anti-inflammatory agents: recent developments and current status

Prostaglandin (PG) E₂, a key mediator of inflammatory pain and fever, is biosynthesized from PGH₂ by mPGES-1.

DOCK 6: Impact of new features and current docking performance

This manuscript presents the latest algorithmic and methodological developments to the structure-based design program DOCK 6.7 focused on an updated internal energy function, new anchor selection control, enhanced minimization options, a footprint similarity scoring function, a symmetry-corrected root-mean-square deviation algorithm, a database filter, and docking forensic tools. An important strategy during development involved use of three orthogonal metrics for assessment and validation: pose reproduction over a large database of 1043 protein-ligand complexes (SB2012 test set), cross-docking to 24 drug-target protein families, and database enrichment using large active and decoy datasets (Directory of Useful Decoys [DUD]-E test set) for five important proteins including HIV protease and IGF-1R. Relative to earlier versions, a key outcome of the work is a significant increase in pose reproduction success in going from DOCK 4.0.2 (51.4%) → 5.4 (65.2%) → 6.7 (73.3%) as a result of significant decreases in failure arising from both sampling 24.1% → 13.6% → 9.1% and scoring 24.4% → 21.1% → 17.5%. Companion cross-docking and enrichment studies with the new version highlight other strengths and remaining areas for improvement, especially for systems containing metal ions. The source code for DOCK 6.7 is available for download and free for academic users at http://dock.compbio.ucsf.edu/.

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.

Discovery of novel, non-acidic mPGES-1 inhibitors by virtual screening with a multistep protocol

Microsomal prostaglandin E2 synthase-1 (mPGES-1) inhibitors are considered as potential therapeutic agents for the treatment of inflammatory pain and certain types of cancer. So far, several series of acidic as well as non-acidic inhibitors of mPGES-1 have been discovered. Acidic inhibitors, however, may have issues, such as loss of potency in human whole blood and in vivo, stressing the importance of the design and identification of novel, non-acidic chemical scaffolds of mPGES-1 inhibitors. Using a multistep virtual screening protocol, the Vitas-M compound library (∼1.3 million entries) was filtered and 16 predicted compounds were experimentally evaluated in a biological assay in vitro. This approach yielded two molecules active in the low micromolar range (IC50 values: 4.5 and 3.8 μM, respectively).

Targeting microsomal prostaglandin E2synthase-1 (mPGES-1): the development of inhibitors as an alternative to non-steroidal anti-inflammatory drugs (NSAIDs)

AA cascade and several key residues in the 3D structure of mPGES-1.

Hierarchical virtual screening approaches in small molecule drug discovery

Virtual screening has played a significant role in the discovery of small molecule inhibitors of therapeutic targets in last two decades. Various ligand and structure-based virtual screening approaches are employed to identify small molecule ligands for proteins of interest. These approaches are often combined in either hierarchical or parallel manner to take advantage of the strength and avoid the limitations associated with individual methods. Hierarchical combination of ligand and structure-based virtual screening approaches has received noteworthy success in numerous drug discovery campaigns. In hierarchical virtual screening, several filters using ligand and structure-based approaches are sequentially applied to reduce a large screening library to a number small enough for experimental testing. In this review, we focus on different hierarchical virtual screening strategies and their application in the discovery of small molecule modulators of important drug targets. Several virtual screening studies are discussed to demonstrate the successful application of hierarchical virtual screening in small molecule drug discovery.

Discovery of highly potent TNFα inhibitors using virtual screen

Tumor necrosis factor-α (TNFα) is a validated therapeutic target for various autoimmune disorders such as rheumatoid arthritis and asthma. All TNFα inhibitors currently on the market are biologics, making the development of small molecule alternatives in urgent need. However, only a few successful cases of direct TNFα antagonization in vitro have been reported. Here, we present the identification of several small molecule candidates able to effectively reduce TNFα activity in vitro and in cell assays. Virtual screen targeting TNFα dimer was performed on the SPECS database and 101 compounds were selected for experimental testing. Two compounds, 1 and 2, displayed considerable inhibitory activity. Follow-up structure-activity relationship analysis of compound 1 identified 3 molecules with low micromolar cell-level inhibitory activity. Compound 11 showed an IC50 value of 14 μM, making it among the most potent TNFα small molecule inhibitors reported. These compounds provide new scaffolds for future development of small molecule drugs against TNFα.

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

A series of 6-nitro-3-(m-tolylamino) benzo[d]isothiazole 1,1-dioxide analogues were synthesized and evaluated for their inhibition activity against 5-lipoxygenase (5-LOX) and microsomal prostaglandin E2 synthase (mPGES-1). These compounds can inhibit both enzymes with IC50 values ranging from 0.15 to 23.6μM. One of the most potential compounds, 3g, inhibits 5-LOX and mPGES-1 with IC50 values of 0.6μM, 2.1μM, respectively.