Targeting 5-lipoxygenase-activating protein in asthma and chronic obstructive pulmonary disease

Antoniu, Sabina A

doi:10.1517/14728222.2014.945425

Cited by 14 publications

(6 citation statements)

References 42 publications

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“…The enzymes that catalyze production of CysLTs can also be targeted by drugs such as the 5-LO inhibitor zileuton. A number of other FLAP inhibitors are currently being developed [28].…”

Section: Leukotriene Antagonistsmentioning

confidence: 99%

Advances in the treatment of virus-induced asthma

Tay

Wark

Bartlett

2016

Expert Review of Respiratory Medicine

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Viral exacerbations continue to represent the major burden in terms of morbidity, mortality and health care costs associated with asthma. Those at greatest risk for acute asthma are those with more severe airways disease and poor asthma control. It is this group with established asthma in whom acute exacerbations triggered by virus infections remain a serious cause of increased morbidity. A range of novel therapies are emerging to treat asthma and in particular target this group with poor disease control, and in most cases their efficacy is now being judged by their ability to reduce the frequency of acute exacerbations. Critical for the development of new treatment approaches is an improved understanding of virus-host interaction in the context of the asthmatic airway. This requires research into the virology of the disease in physiological models in conjunction with detailed phenotypic characterisation of asthma patients to identify targets amenable to therapeutic intervention.

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“…The enzymes that catalyze production of CysLTs can also be targeted by drugs such as the 5-LO inhibitor zileuton. A number of other FLAP inhibitors are currently being developed [28].…”

Section: Leukotriene Antagonistsmentioning

confidence: 99%

Advances in the treatment of virus-induced asthma

Tay

Wark

Bartlett

2016

Expert Review of Respiratory Medicine

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“…Revelation of SAR data along with crystal structure expedites the drug discovery quest against FLAP, leading to the second generation consisting of derivatives of diarylalkanes, biaryl amino-heteroarenes, and benzimidazoles, proposed with renewed interest for treatment of cardiovascular diseases ( Lemurell et al, 2015 ; Macdonald et al, 2008 ; N.; Stock et al, 2010 ). Moreover, several inhibitors proved to be promising readouts for preclinical and clinical studies such as AM103, AM803, BI665915, AZD5718, and AZD6642 and have been shown to ameliorate inflammation-related diseases ( Bain et al, 2010 ; Lorrain et al, 2010 ; Antoniu, 2014 ; Ericsson et al, 2020 ). However, despite several practices, not a single inhibitor has won the race to the market as a drug to date.…”

Section: Introductionmentioning

confidence: 99%

Combined Machine Learning and GRID-Independent Molecular Descriptor (GRIND) Models to Probe the Activity Profiles of 5-Lipoxygenase Activating Protein Inhibitors

Khan

Jabeen

2022

Front. Pharmacol.

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Leukotrienes (LTs) are pro-inflammatory lipid mediators derived from arachidonic acid (AA), and their high production has been reported in multiple allergic, autoimmune, and cardiovascular disorders. The biological synthesis of leukotrienes is instigated by transfer of AA to 5-lipoxygenase (5-LO) via the 5-lipoxygenase-activating protein (FLAP). Suppression of FLAP can inhibit LT production at the earliest level, providing relief to patients requiring anti-leukotriene therapy. Over the last 3 decades, several FLAP modulators have been synthesized and pharmacologically tested, but none of them could be able to reach the market. Therefore, it is highly desirable to unveil the structural requirement of FLAP modulators. Here, in this study, supervised machine learning techniques and molecular modeling strategies are adapted to vaticinate the important 2D and 3D anti-inflammatory properties of structurally diverse FLAP inhibitors, respectively. For this purpose, multiple machine learning classification models have been developed to reveal the most relevant 2D features. Furthermore, to probe the 3D molecular basis of interaction of diverse anti-inflammatory compounds with FLAP, molecular docking studies were executed. By using the most probable binding poses from docking studies, the GRIND model was developed, which indicated the positive contribution of four hydrophobic, two hydrogen bond acceptor, and two shape-based features at certain distances from each other towards the inhibitory potency of FLAP modulators. Collectively, this study sheds light on important two-dimensional and three-dimensional structural requirements of FLAP modulators that can potentially guide the development of more potent chemotypes for the treatment of inflammatory disorders.

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“…Although FLAP has no specific catalytic bioactivity, it is essential for the synthesis of LTs, which could aid the binding of substrates to 5-LOX (Werz, Gerstmeier, & Garscha, 2017). FLAP inhibitors have a better effect than 5-LOX inhibitors in vivo experiment (Antoniu, 2014;Evans, Ferguson, Mosley, & Hutchinson, 2008), so we turned our research goals to FLAP target. It is possible for us to achieve a broad-spectrum anti-LT effect by inhibiting the activity of FLAP.…”

Section: Introductionmentioning

confidence: 99%

Fingerprint‐based computational models of 5‐lipo‐oxygenase activating protein inhibitors: Activity prediction and structure clustering

Qin

Huo

et al. 2020

Chem Biol Drug Des

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Inflammatory diseases can be treated by inhibiting 5-lipo-oxygenase activating protein (FLAP). In this study, a data set containing 2,112 FLAP inhibitors was collected. A total of 25 classification models were built by five machine learning algorithms with five different types of fingerprints. The best model, which was built by support vector machine algorithm with ECFP_4 fingerprint had an accuracy and a Matthews correlation coefficient of 0.862 and 0.722 on the test set, respectively. The predicted results were further evaluated by the application domain d STD-PRO (a distance between one compound to models). Each compound had a d STD-PRO value, which was calculated by the predicted probabilities obtained from all 25 models. The application domain results suggested that the reliability of predicted results depended mainly on the compounds themselves rather than algorithms or fingerprints. A group of customized 10-bit fingerprint was manually defined for clustering the molecular structures of 2,112 FLAP inhibitors into eight subsets by K-Means. According to the clustering results, most of inhibitors in two subsets (subsets 2 and 4) were highly active inhibitors. We found that aryl oxadiazole/oxazole alkanes, biaryl amino-heteroarenes, two aromatic rings (often N-containing) linked by a cyclobutene group, and 1,2,4-triazole group were typical fragments in highly active inhibitors. K E Y W O R D S 5-lipo-oxygenase activating protein inhibitor, classification model, machine learning, structure clustering, support vector machine 932 | TU eT al.

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Targeting 5-lipoxygenase-activating protein in asthma and chronic obstructive pulmonary disease

Cited by 14 publications

References 42 publications

Advances in the treatment of virus-induced asthma

Advances in the treatment of virus-induced asthma

Combined Machine Learning and GRID-Independent Molecular Descriptor (GRIND) Models to Probe the Activity Profiles of 5-Lipoxygenase Activating Protein Inhibitors

Fingerprint‐based computational models of 5‐lipo‐oxygenase activating protein inhibitors: Activity prediction and structure clustering

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