From in Silico Discovery to Intracellular Activity: Targeting JNK–Protein Interactions with Small Molecules

Kaoud, Tamer S.; Cheng, Yan; Mitra, Sugata; Tseng, Chun Chia; Jose, Jiney; Taliaferro, Juliana M.; Tuohetahuntila, Maidina; Devkota, Ashwini K.; Sammons, Rachel M.; Park, Jihyun; Park, Heekwang; Shi, Yue; Hong, Jiyong; Ren, Pengyu; Dalby, Kevin N.

doi:10.1021/ml300129b

Cited by 26 publications

(32 citation statements)

References 26 publications

(54 reference statements)

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“…[6] The S 2 is mainly defined by another hydrophobic pocket that is usually occupied by Pro158 of pepJIP1 (ϕ A -2). RMSD cluster analysis revealed 14 unique binding poses for each zuonin A enantiomer yielding 28 total configurations.…”

Section: Resultsmentioning

confidence: 99%

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Elucidating binding modes of zuonin A enantiomers to JNK1 via in silico methods

Dykstra

Dalby

Ren

2013

Journal of Molecular Graphics and Modelling

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Aberrant c-Jun N-terminal kinase (JNK) signaling is associated with a number of diseases, including neurological conditions and cancer. Enantiomers of the lignan zuonin A, (−)-zuonin A and (+)-zuonin A bind isoforms of JNK with similar affinity and disrupt protein-protein interactions at JNK’s D-recruitment site. Thus, they are of interest as lead non-ATP competitive inhibitors of the JNKs. While (−)-zuonin A inhibits the activity of JNK towards c-Jun by 80% when saturating, (+)-zuonin A only inhibits by 15%. Molecular docking and molecular dynamics simulations were performed to gain a better understanding of how these inhibitors interact with JNK. The results of this study provide new insight into potential binding modes for (−)-zuonin A and suggest that (−)-zuonin A interacts with JNK via an induced fit mechanism near the highly conserved ϕA-X-ϕB recognition site. Binding of (+)-zuonin A to JNK displays no such dynamic feature. The different binding modes may help explain differences in the inhibitory properties of the enantiomers although further experimental work would be necessary to fully confirm this interpretation.

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Section: Resultsmentioning

confidence: 99%

“…[6] One compound of interest isolated from this study was the lignan (−)-zuonin A, figure 1A, which has a 100-fold greater selectivity toward inhibiting JNK–protein interactions over ERK2 and p38 MAPKα. To the best of our knowledge, the zuonin is perhaps the most specific non-ATP competitive MAP kinase inhibitors reported to date.…”

Section: Introductionmentioning

confidence: 99%

Elucidating binding modes of zuonin A enantiomers to JNK1 via in silico methods

Dykstra

Dalby

Ren

2013

Journal of Molecular Graphics and Modelling

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“…81 chemical compounds identified by virtual screening and used in kinase assays were obtained from The National Cancer Institute (NCI) and used without further characterization. TRPM7 [24] and ERK2 [25] were prepared as previously reported.…”

Section: Methodsmentioning

confidence: 99%

Reversible Covalent Inhibition of eEF‐2K by Carbonitriles

et al. 2014

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eEF-2K is a potential target for treating cancer. However, potent specific inhibitors for this enzyme are lacking. Previously, we identified 2,6-diamino-4-(2-fluorophenyl)-4H-thiopyran-3,5-dicarbonitrile (DFTD) as an inhibitor of eEF-2K. Here we describe its mechanism of action against eEF-2K, on the basis of kinetic, mutational, and docking studies, and use chemoinformatic approaches to identify a similar class of carbonitrile-containing compounds that exhibit the same mechanism of action. We show that DFTD behaves as a reversible covalent inhibitor of eEF-2K with a two-step mechanism of inhibition: a fast initial binding step, followed by a slower reversible inactivation step. Molecular docking suggests that a nitrile group of DFTD binds within 4.5 Å of the active site Cys146 to form a reversible thioimidate adduct. Because Cys146 is not conserved amongst other related kinases, targeting this residue holds promise for the development of selective covalent inhibitors of eEF-2K.

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“…Additionally, MACCS fingerprints are routinely used to improve the VS hit rate by identifying structural analogs of hit compounds [52,[90][91][92]. Although the shape similarity alone was sufficient to retrieve highly potent binders [44,45,[96][97][98][99], the true potential of shape similarity was realized when it was combined with molecular docking in hierarchical manner. Steric complementarity between ligand and receptor is one of the key factors determining the strength of binding.…”

Section: Similarity Search -Molecular Dockingmentioning

confidence: 99%

Hierarchical virtual screening approaches in small molecule drug discovery

Kumar¹,

Zhang²

2015

Methods

130

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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.

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From in Silico Discovery to Intracellular Activity: Targeting JNK–Protein Interactions with Small Molecules

Cited by 26 publications

References 26 publications

Elucidating binding modes of zuonin A enantiomers to JNK1 via in silico methods

Elucidating binding modes of zuonin A enantiomers to JNK1 via in silico methods

Reversible Covalent Inhibition of eEF‐2K by Carbonitriles

Hierarchical virtual screening approaches in small molecule drug discovery

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