Potent Inhibitors of 5-Lipoxygenase Identified using Pseudoreceptors

Emerging Promise of Computational Techniques in Anti-Cancer Research: At a Glance

Research on the immune system and cancer has led to the development of new medicines that enable the former to attack cancer cells. Drugs that specifically target and destroy cancer cells are on the horizon; there are also drugs that use specific signals to stop cancer cells multiplying. Machine learning algorithms can significantly support and increase the rate of research on complicated diseases to help find new remedies. One area of medical study that could greatly benefit from machine learning algorithms is the exploration of cancer genomes and the discovery of the best treatment protocols for different subtypes of the disease. However, developing a new drug is time-consuming, complicated, dangerous, and costly. Traditional drug production can take up to 15 years, costing over USD 1 billion. Therefore, computer-aided drug design (CADD) has emerged as a powerful and promising technology to develop quicker, cheaper, and more efficient designs. Many new technologies and methods have been introduced to enhance drug development productivity and analytical methodologies, and they have become a crucial part of many drug discovery programs; many scanning programs, for example, use ligand screening and structural virtual screening techniques from hit detection to optimization. In this review, we examined various types of computational methods focusing on anticancer drugs. Machine-based learning in basic and translational cancer research that could reach new levels of personalized medicine marked by speedy and advanced data analysis is still beyond reach. Ending cancer as we know it means ensuring that every patient has access to safe and effective therapies. Recent developments in computational drug discovery technologies have had a large and remarkable impact on the design of anticancer drugs and have also yielded useful insights into the field of cancer therapy. With an emphasis on anticancer medications, we covered the various components of computer-aided drug development in this paper. Transcriptomics, toxicogenomics, functional genomics, and biological networks are only a few examples of the bioinformatics techniques used to forecast anticancer medications and treatment combinations based on multi-omics data. We believe that a general review of the databases that are now available and the computational techniques used today will be beneficial for the creation of new cancer treatment approaches.

Multi-dimensional target profiling of N,4-diaryl-1,3-thiazole-2-amines as potent inhibitors of eicosanoid metabolism

Eicosanoids like leukotrienes and prostaglandins play a considerable role in inflammation. Produced within the arachidonic acid (AA) cascade, these lipid mediators are involved in the pathogenesis of pain as well as acute and chronic inflammatory diseases like rheumatoid arthritis and asthma. With regard to the lipid cross-talk within the AA pathway, a promising approach for an effective anti-inflammatory therapy is the development of inhibitors targeting more than one enzyme of this cascade. Within this study, thirty N-4-diaryl-1,3-thiazole-2-amine based compounds with different substitution patterns were synthesized and tested in various cell-based assays to investigate their activity and selectivity profile concerning five key enzymes involved in eicosanoid metabolism (5-, 12-, 15-lipoxygenase (LO), cyclooxygenase-1 and -2 (COX-1/-2)). With compound 7, 2-(4-phenyl)thiazol-2-ylamino)phenol (ST-1355), a multi-target ligand targeting all tested enzymes is presented, whereas compound 9, 2-(4-(4-chlorophenyl)thiazol-2-ylamino)phenol (ST-1705), represents a potent and selective 5-LO and COX-2 inhibitor with an IC50 value of 0.9 ± 0.2 μM (5-LO) and a residual activity of 9.1 ± 1.1% at 10 μM (COX-2 product formation). The promising characteristics and the additional non-cytotoxic profile of both compounds reveal new lead structures for the treatment of eicosanoid-mediated diseases.

Recent advances in the search for novel 5-lipoxygenase inhibitors

5-Lipoxygenase (5-LO) is an important enzyme of the arachidonic acid cascade and catalyses with the help of FLAP, the 5-LO-activating protein, the formation of bioactive leukotrienes (LTs). LTs are inflammatory mediators playing a pathophysiological role in different diseases such as asthma, allergic rhinitis as well as cardiovascular diseases and certain types of cancer. Up to now, only one 5-LO inhibitor is on the market, zileuton for the treatment of asthma. With the rising number of indications for anti-LT therapy, 5-LO inhibitor drug development becomes more and more important. This MiniReview gives an update on 5-LO inhibitors currently under clinical development. Furthermore, the recent advances in the search for novel 5-lipoxygenase inhibitors with a focus on computational methods are summarized. Currently, licofelone is the compound with the highest clinical development status (completed phase III trials). 5-LO inhibitor screening programmes based on computational methods could deliver several promising drug-like new molecules. These activities can be expected to be driven by the newly resolved structure of human 5-LO in the future, enabling structure-based drug design. For the prospective drugs in late-stage clinical development, the future will show their clinical safety and efficacy in the particular diseases.

5-Lipoxygenase inhibitors: a review of recent patents (2010-2012)

INTRODUCTION

5-Lipoxygenase (5-LO) is a crucial enzyme of the arachidonic acid (AA) cascade and catalyzes the formation of bioactive leukotrienes (LTs) with the help of FLAP, the 5-LO-activating protein. LTs are inflammatory mediators playing a pathophysiological role in different diseases like asthma, allergic rhinitis as well as cardiovascular diseases and certain types of cancer. With the rising number of indications for anti-LT therapy, 5-LO inhibitor drug development becomes increasingly important.

AREAS COVERED

Here, both recent findings regarding the pathophysiological role of 5-LO and the patents claimed for 5-LO inhibitors are discussed. Focusing on direct inhibitors, several patents disclosing FLAP antagonists are also subject of this review. Novel compounds include 1,5-diarylpyrazoles, indolizines and indoles and several natural product extracts.

EXPERT OPINION

Evaluation of the patent activities revealed only quite moderate action. Nevertheless, several auspicious drug-like molecules were disclosed. It seems that in the near future, FLAP inhibitors can be expected to enter the market for the treatment of asthma. With the resolved structure of 5-LO, structure-based drug design is now applicable. Together with the identification of downstream enzyme inhibitors and dual-targeting drugs within the AA cascade, several tools are at hand to cope with 5-LOs increasing pathophysiological roles.

Significance estimation for sequence-based chemical similarity searching (PhAST) and application to AuroraA kinase inhibitors

BACKGROUND

Chemical similarity searching allows the retrieval of preferred screening molecules from a compound database. Candidates are ranked according to their similarity to a reference compound (query). Assessing the statistical significance of chemical similarity scores helps prioritizing significant hits, and identifying cases where the database does not contain any promising compounds.

METHOD

Our text-based similarity measure, Pharmacophore Alignment Search Tool (PhAST), employs pair-wise sequence alignment. We adapted the concept of E-values as significance estimates and employed a sampling technique that incorporates the principle of importance sampling in a Markov chain Monte Carlo simulation to generate distributions of random alignment scores. These distributions were used to compute significance estimates for similarity scores in a preliminary prospective virtual screen for inhibitors of Aurora A kinase.

CONCLUSION

Assessing the significance of compound similarity computed with PhAST allows for a statistically motivated identification of candidate screening compounds. Inhibitors of Aurora A kinase were retrieved from a large compound library.

Structure and ligand based drug design strategies in the development of novel 5- LOX inhibitors

Lipoxygenases (LOXs) are non-heme iron containing dioxygenases involved in the oxygenation of polyunsaturated fatty acids (PUFAs) such as arachidonic acid (AA). Depending on the position of insertion of oxygen, LOXs are classified into 5-, 8-, 9-, 12- and 15-LOX. Among these, 5-LOX is the most predominant isoform associated with the formation of 5-hydroperoxyeicosatetraenoic acid (5-HpETE), the precursor of non-peptido (LTB₄) and peptido (LTC₄, LTD₄, and LTE₄) leukotrienes. LTs are involved in inflammatory and allergic diseases like asthma, ulcerative colitis, rhinitis and also in cancer. Consequently 5-LOX has become target for the development of therapeutic molecules for treatment of various inflammatory disorders. Zileuton is one such inhibitor of 5-LOX approved for the treatment of asthma.

In the recent times, computer aided drug design (CADD) strategies have been applied successfully in drug development processes. A comprehensive review on structure based drug design strategies in the development of novel 5-LOX inhibitors is presented in this article. Since the crystal structure of 5-LOX has been recently solved, efforts to develop 5-LOX inhibitors have mostly relied on ligand based rational approaches. The present review provides a comprehensive survey on these strategies in the development of 5-LOX inhibitors.

Molecular pharmacological profile of a novel thiazolinone-based direct and selective 5-lipoxygenase inhibitor

BACKGROUND AND PURPOSE

The potency of many 5-lipoxygenase (5-LOX) inhibitors depends on the cellular peroxide tone and the mechanism of 5-LOX enzyme activation. Therefore, new inhibitors that act regardless of the mode of enzyme activation need to be developed. Recently, we identified a novel class of thiazolinone-based compounds as potent 5-LOX inhibitors. Here, we present the molecular pharmacological profile of (Z)-5-(4-methoxybenzylidene)-2-(p-tolyl)-5H-thiazol-4-one, compound C06.

EXPERIMENTAL APPROACH

Inhibition of 5-LOX product formation was determined in intact cells [polymorphonuclear leukocytes (PMNL), rat basophilic leukaemia-1, RAW264.7] and in cell-free assays [homogenates, 100, 000×g supernatant (S100), partially purified 5-LOX] applying different stimuli for 5-LOX activation. Inhibition of peroxisome proliferator-activated receptor (PPAR), cytosolic phospholipase A(2) (cPLA(2) ), 12-LOX, 15-LOX-1 and 15-LOX-2 as well as cyclooxygenase-2 (COX-2) were measured in vitro.

KEY RESULTS

C06 induced non-cytotoxic, direct 5-LOX inhibition with IC(50) values about 0.66 µM (intact PMNL, PMNL homogenates) and approximately 0.3 µM (cell-free PMNL S100, partially purified 5-LOX). Action of C06 was independent of the stimulus used for 5-LOX activation and cellular redox tone and was selective for 5-LOX compared with other arachidonic acid binding proteins (PPAR, cPLA(2) , 12-LOX, 15-LOX-1, 15-LOX-2, COX-2). Experimental results suggest an allosteric binding distinct from the active site and the C2-like domain of 5-LOX.

CONCLUSIONS AND IMPLICATIONS

C06 was identified as a potent selective direct 5-LOX inhibitor exhibiting a novel and unique mode of action, different from other established 5-LOX inhibitors. This thiazolinone may possess potential for intervention with inflammatory and allergic diseases and certain types of cancer.