Discovery of Potent Inhibitors of Soluble Epoxide Hydrolase by Combinatorial Library Design and Structure-Based Virtual Screening

Li, Xing; McDonald, Joseph J.; Kolodziej, Stephen A.; Kurumbail, Ravi G.; Williams, Jennifer M.; Warren, Chad J.; O’Neal, Janet M.; Skepner, Jill; Roberds, Steven L.

doi:10.1021/jm101382t

Cited by 55 publications

(72 citation statements)

References 40 publications

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“…The Merck group also developed aminobenzisoxazoles, including compound 13 in Figure 2, which succeeded in replacing the urea or amide pharmacophore with a benzisoxazole (62). Pfizer chemists recently used structure-based virtual screening driven by new X-ray structures to design a combinatorial library that yielded nanomolar benzoxazole derivatives (Figure 2, compound 14 ) (63). …”

Section: Soluble Epoxide Hydrolase Inhibitorsmentioning

confidence: 99%

Impact of Soluble Epoxide Hydrolase and Epoxyeicosanoids on Human Health

Morisseau

Hammock

2013

Annu. Rev. Pharmacol. Toxicol.

465

495

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The presence of epoxyeicosatrienoic acids (EETs) in tissues and their metabolism by soluble epoxide hydrolase (sEH) to 1,2-diols were first reported 30 years ago. However, appreciation of their importance in cell biology and physiology has greatly accelerated over the past decade with the discovery of metabolically stable inhibitors of sEH, the commercial availability of EETs, and the development of analytical methods for the quantification of EETs and their diols. Numerous roles of EETs in regulatory biology now are clear, and the value of sEH inhibition in various animal models of disease has been demonstrated. Here, we review these results and discuss how the pharmacological stabilization of EETs and other natural epoxy-fatty acids could lead to possible disease therapies.

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Section: Soluble Epoxide Hydrolase Inhibitorsmentioning

confidence: 99%

Impact of Soluble Epoxide Hydrolase and Epoxyeicosanoids on Human Health

Morisseau

Hammock

2013

Annu. Rev. Pharmacol. Toxicol.

465

495

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“…Structure-based computational techniques [11], [12] such as virtual screening [13]–[15], docking [16], [17], and molecular dynamics [18], [19] have proven useful in the development of drugs. Even if there have not been many successful drug discovery stories based on computation alone, the use of structure-based computational techniques has helped gain better understanding of how a putative drug compound binds to its target receptor, and has reduced the drug development time and costs [20]–[22].…”

Section: Introductionmentioning

confidence: 99%

Binding Modes of Peptidomimetics Designed to Inhibit STAT3

2012

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STAT3 is a transcription factor that has been found to be constitutively activated in a number of human cancers. Dimerization of STAT3 via its SH2 domain and the subsequent translocation of the dimer to the nucleus leads to transcription of anti-apoptotic genes. Prevention of the dimerization is thus an attractive strategy for inhibiting the activity of STAT3. Phosphotyrosine-based peptidomimetic inhibitors, which mimic pTyr-Xaa-Yaa-Gln motif and have strong to weak binding affinities, have been previously investigated. It is well-known that structures of protein-inhibitor complexes are important for understanding the binding interactions and designing stronger inhibitors. Experimental structures of inhibitors bound to the SH2 domain of STAT3 are, however, unavailable. In this paper we describe a computational study that combined molecular docking and molecular dynamics to model structures of 12 peptidomimetic inhibitors bound to the SH2 domain of STAT3. A detailed analysis of the modeled structures was performed to evaluate the characteristics of the binding interactions. We also estimated the binding affinities of the inhibitors by combining MMPB/GBSA-based energies and entropic cost of binding. The estimated affinities correlate strongly with the experimentally obtained affinities. Modeling results show binding modes that are consistent with limited previous modeling studies on binding interactions involving the SH2 domain and phosphotyrosine(pTyr)-based inhibitors. We also discovered a stable novel binding mode that involves deformation of two loops of the SH2 domain that subsequently bury the C-terminal end of one of the stronger inhibitors. The novel binding mode could prove useful for developing more potent inhibitors aimed at preventing dimerization of cancer target protein STAT3.

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“…Optimized hit and scaffold based library design NS5B Polymerase: Hepatitis C [147] Docking-based combinatorial library design Soluble epoxide hydrolase: Cardiovascular disease [148] Anchor-based library tailoring approach Receptor tyrosine kinase EphB4: Cancer [150] Combination of substructure-search and pharmacophore-based library design Falcipain-2: Malaria [151] …”

Section: Library Design Methods Target: Disease Referencementioning

confidence: 99%

“…A group from Pfizer applied a structure-based library design methodology to identify hits for soluble epoxide hydrolase (sEH), a potential target against cardiovascular dysfunction and renal damage [148]. The crystal structure complex of sEH with a benzoxazole template compound was used to identify 2000 reagents.…”

Section: Molecular Docking-based Virtual Screeningmentioning

confidence: 99%

“…A focused library of 1175 compounds were docked and filtered based on the pharmacophore and revised scaffold, resulting in a 3 M hit amongst the 10 top ranking molecules. This compound laid the foundation of further focused library generation and low micromolar hit identification.A group from Pfizer applied a structure-based library design methodology to identify hits for soluble epoxide hydrolase (sEH), a potential target against cardiovascular dysfunction and renal damage [148]. The crystal structure complex of sEH with a benzoxazole template compound was used to identify 2000 reagents.…”

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confidence: 99%

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From Laptop to Benchtop to Bedside: Structure-based Drug Design on Protein Targets

Chen¹,

Morrow²,

Tran³

et al. 2012

curr drug metab

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As an important aspect of computer-aided drug design, structure-based drug design brought a new horizon to pharmaceutical development. This in silico method permeates all aspects of drug discovery today, including lead identification, lead optimization, ADMET prediction and drug repurposing. Structure-based drug design has resulted in fruitful successes drug discovery targeting protein-ligand and protein-protein interactions. Meanwhile, challenges, noted by low accuracy and combinatoric issues, may also cause failures. In this review, state-of-the-art techniques for protein modeling (e.g. structure prediction, modeling protein flexibility, etc.), hit identification/optimization (e.g. molecular docking, focused library design, fragment-based design, molecular dynamic, etc.), and polypharmacology design will be discussed. We will explore how structure-based techniques can facilitate the drug discovery process and interplay with other experimental approaches. KeywordsStructure-based drug design; protein modeling; focused library design; pharmacophore; flexible docking; high-throughput virtual screening; de novo design; protein-protein interaction; polypharmacology Modern computational-aided drug design established a novel platform by which researchers perform in-depth in silico simulation prior to labor-extensive wet-lab validation [1]. It comprises of two major parts corresponding to the information of molecular source it utilizes: structure-based (or receptor-based) drug design and ligand-based drug design. Structure-based drug design, which relies on the knowledge of biological target structures, aims to discover small molecules/peptides leads with desired chemistry properties, and orchestrate the following experimental validation and lead optimization. Structure-based approach provides mechanism-based basis, where potential ligands are excavated using receptor-dependent parameters, while ligand-based approaches bypass the consideration of complex biomolecular "black box" in a living cell. This in silico method permeates all aspects of drug discovery today [2], and we expect it will draw more attentions with the unprecedented advances of computational power and modeling accuracy in this decade.* Corresponding author: Shuxing Zhang, Ph.D., The University of Texas M. D. Anderson Cancer Center, Department of Experimental Therapeutics, Unit 1950, 1901 East Rd., Houston, TX 77054, Telephone: (713)-745-2958 794-5577, shuzhang@mdanderson.org. Conflict of interestThe authors declare that they do not have competing interests. NIH Public Access Author ManuscriptCurr Pharm Des. Author manuscript; available in PMC 2013 November 07.Published in final edited form as:Curr Pharm Des. 2012 ; 18(9): 1217-1239. NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author ManuscriptIn this review, we will overview the state-of-the-art structure-based drug discovery techniques ranging from receptor modeling to lead identification and optimization. In each topic, we will also highlight the fruitful successes as well as ch...

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Discovery of Potent Inhibitors of Soluble Epoxide Hydrolase by Combinatorial Library Design and Structure-Based Virtual Screening

Cited by 55 publications

References 40 publications

Impact of Soluble Epoxide Hydrolase and Epoxyeicosanoids on Human Health

Impact of Soluble Epoxide Hydrolase and Epoxyeicosanoids on Human Health

Binding Modes of Peptidomimetics Designed to Inhibit STAT3

From Laptop to Benchtop to Bedside: Structure-based Drug Design on Protein Targets

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