Synthesis of N-alkyl glycine amides as potent inhibitors of leukotriene A4 hydrolase

Drug discovery strategies for novel leukotriene A4 hydrolase inhibitors

IntroductionLeukotriene A4 hydrolase (LTA4H) is the final and rate limiting enzyme regulating the biosynthesis of leukotriene B4 (LTB4), a pro-inflammatory lipid mediator implicated in a large number of inflammatory pathologies. Inhibition of LTA4H not only prevents LTB4 biosynthesis but also induces a lipid mediator class-switch within the 5-lipoxygenase pathway, elevating biosynthesis of the anti-inflammatory lipid mediator Lipoxin A4. Ample preclinical evidence advocates LTA4H as attractive drug target for the treatment of chronic inflammatory diseases.Areas coveredThis review covers details about the biochemistry of LTA4H and describes its role in regulating pro- and anti-inflammatory mediator generation. It summarizes recent efforts in medicinal chemistry toward novel LTA4H inhibitors, recent clinical trials testing LTA4H inhibitors in pulmonary inflammatory diseases, and potential reasons for the discontinuation of former development programs.Expert opinionGiven the prominent role of LTB4 in initiating and perpetuating inflammation, LTA4H remains an appealing drug target. The reason former attempts targeting this enzyme have not met with success in the clinic can be attributed to compound-specific liabilities of first-generation inhibitors and/or choice of target indications to test this mode of action. A new generation of highly potent and selective LTA4H inhibitors is currently undergoing clinical testing in indications with a strong link to LTB4 biology.

Classification and QSAR models of leukotriene A4 hydrolase (LTA4H) inhibitors by machine learning methods

Leukotriene A4 hydrolase (LTA4H) is an important anti-inflammatory target which can convert leukotriene A4 (LTA4) into pro-inflammatory substance leukotriene B4 (LTB4). In this paper, we built 18 classification models for 463 LTA4H inhibitors by using support vector machine (SVM), random forest (RF) and K-Nearest Neighbour (KNN). The best classification model (Model 2A) was built from RF and MACCS fingerprints. The prediction accuracy of 88.96% and the Matthews correlation coefficient (MCC) of 0.74 had been achieved on the test set. We also divided the 463 LTA4H inhibitors into six subsets using K-Means. We found that the highly active LTA4H inhibitors mostly contained diphenylmethane or diphenyl ether as the scaffold and pyridine or piperidine as the side chain. In addition, six quantitative structure-activity relationship (QSAR) models for 172 LTA4H inhibitors were built by multiple linear regression (MLR) and SVM. The best QSAR model (Model 6A) was built by using SVM and CORINA Symphony descriptors. The coefficients of determination of the training set and the test set were equal to 0.81 and 0.79, respectively. Classification and QSAR models could be used for subsequent virtual screening, and the obtained fragments that were important for highly active inhibitors would be helpful for designing new LTA4H inhibitors.

Development of predictive quantitative structure–activity relationship model and its application in the discovery of human leukotriene A4 hydrolase inhibitors

Background: Human LTA4H catalyzes the conversion of LTA4 to LTB4 and plays a key role in innate immune responses. Inhibition of this enzyme can be a valid method in the treatment of inflammatory response exhibited through LTB4. Results & discussion: The quantitative structure–activity relationship (QSAR) models were developed using genetic function approximation and validated. A training set of 26 diverse compounds and their molecular descriptors were used to develop highly correlating QSAR models. A six-descriptor model explaining the biological activity of the training and test sets with correlation values of 0.846 and 0.502, respectively, was selected as the best model and used in a database screening of drug-like Maybridge database followed by molecular docking. Conclusion: Based on the predicted potent inhibitory activities, expected binding mode and molecular interactions at the active site of hLTA4H final leads were selected as to be utilized in designing future hLTA4H inhibitors.

Leukotriene A4 Hydrolase: Biology, Inhibitors and Clinical Applications

Leukotriene A4 hydrolase is a zinc-containing cytosolic enzyme with both hydrolase and aminopeptidase activity. LTA4H stereospecifically catalyzes the transformation of the unstable epoxide LTA4 to the potent pro-inflammatory mediator LTB4. Variations in the lta4h gene have been linked to susceptibility to multiple diseases including myocardial infarction, stroke and asthma. Pre-clinical animal models and human biomarker data have implicated LTB4 in inflammatory diseases. Several groups have now identified selective inhibitors of LTA4H, many of which were influenced by the disclosure of a protein crystal structure a decade ago. Clinical validation of LTA4H remains elusive despite the progression of inhibitors into pre-clinical and clinical development.

Discovery of 4-[(2S)-2-{[4-(4-chlorophenoxy)phenoxy]methyl}-1-pyrrolidinyl]butanoic acid (DG-051) as a novel leukotriene A4 hydrolase inhibitor of leukotriene B4 biosynthesis

Both in-house human genetic and literature data have converged on the identification of leukotriene 4 hydrolase (LTA(4)H) as a key target for the treatment of cardiovascular disease. We combined fragment-based crystallography screening with an iterative medicinal chemistry effort to optimize inhibitors of LTA(4)H. Ligand efficiency was followed throughout our structure-activity studies. As applied within the context of LTA(4)H inhibitor design, the chemistry team was able to design a potent compound 20 (DG-051) (K(d) = 26 nM) with high aqueous solubility (>30 mg/mL) and high oral bioavailability (>80% across species) that is currently undergoing clinical evaluation for the treatment of myocardial infarction and stroke. The structural biology-chemistry interaction described in this paper provides a sound alternative to conventional screening techniques. This is the first example of a gene-to-clinic paradigm enabled by a fragment-based drug discovery effort.

Discovery of leukotriene A4 hydrolase inhibitors using metabolomics biased fragment crystallography

We describe a novel fragment library termed fragments of life (FOL) for structure-based drug discovery. The FOL library includes natural small molecules of life, derivatives thereof, and biaryl protein architecture mimetics. The choice of fragments facilitates the interrogation of protein active sites, allosteric binding sites, and protein−protein interaction surfaces for fragment binding. We screened the FOL library against leukotriene A4 hydrolase (LTA4H) by X-ray crystallography. A diverse set of fragments including derivatives of resveratrol, nicotinamide, and indole were identified as efficient ligands for LTA4H. These fragments were elaborated in a small number of synthetic cycles into potent inhibitors of LTA4H representing multiple novel chemotypes for modulating leukotriene biosynthesis. Analysis of the fragment-bound structures also showed that the fragments comprehensively recapitulated key chemical features and binding modes of several reported LTA4H inhibitors.

Discovery of novel and potent aryl diamines as leukotriene A4 hydrolase inhibitors

The synthesis and biological evaluation of a series of aryl diamines as inhibitors of LTA(4)-h inhibitors are described. The optimization which led to the identification of the optimal para-substitution on the diphenyl ether moiety and diamine spacer is discussed. The resulting compounds such as 3l have excellent enzyme and cellular potency as well as desirable pharmacokinetic properties.