Jung-Eun Park

Discovery of 1-(3-(benzyloxy)pyridin-2-yl)-3-(2-(piperazin-1-yl)ethyl)urea: A new modulator for amyloid beta-induced mitochondrial dysfunction

Herein, we report a new series of aliphatic substituted pyridyl-urea small molecules synthesized as potential modulators for amyloid beta (Aβ) induced mitochondrial dysfunction. Their blocking activities against Aβ-induced mitochondrial permeability transition pore (mPTP) opening were evaluated by JC-1 assay which measures the change of mitochondrial membrane potential (ΔΨm). The inhibitory activity of sixteen compounds against Aβ-induced mPTP opening was superior or almost similar to that of the standard Cyclosporin A (CsA). Among them, 1-(3-(benzyloxy)pyridin-2-yl)-3-(2-(piperazin-1-yl)ethyl)urea (5x) effectively maintained mitochondrial function and cell viabilities on ATP assay, MTT assay, and ROS assay. Using CDocker algorithm, a molecular docking model presented a plausible binding mode for 5x with cyclophilin D (CypD) receptor as a major component of mPTP. Moreover, hERG and BBB-PAMPA assays presented safe cardiotoxicity and high CNS bioavailability profiles for 5x. Taken as a whole, this report presents compound 5x as a new nonpeptidyl mPTP blocker may hold a promise for further development of Alzheimers disease (AD) therapeutics.

Design, synthesis, biological evaluation and molecular modelling of 2-(2-aryloxyphenyl)-1,4-dihydroisoquinolin-3(2H)-ones: A novel class of TSPO ligands modulating amyloid-β-induced mPTP opening

Abstract Translocator protein (TSPO) is involved in modulating mitochondrial permeability transition pore (mPTP) opening/closure leading to either apoptotic cell death via opening of mPTP or cell protection mediated by mPTP blocking and hence intercepting mPTP induced apoptosis. Herein, 2‐(2‐aryloxyphenyl)‐1,4‐dihydroisoquinolin‐3(2H)‐one derivatives have been designed and synthesized as new modulators for amyloid‐&bgr;‐induced mPTP opening. Among all, compound 7c remarkably enhanced mPTP opening while compound 7e showed the highest mPTP blocking activity. Molecular modelling study revealed different binding modes which might underlie the observed opposing biological activities. Both compounds bound to the translocator protein 18 kDa (TSPO) in low micromolar range and elicited good profiles on CYP2D6 and CYP1A2. Taken as a whole, this report presents compound 7e as a hit TSPO ligand for treatment of neurodegenerative diseases and compound 7c as a hit TSPO ligand for promoting cell death of cells over‐expressing TSPO. Graphical abstract Figure. No Caption available.

Synthesis and evaluation of 2-(3-arylureido)pyridines and 2-(3-arylureido)pyrazines as potential modulators of Aβ-induced mitochondrial dysfunction in Alzheimer's disease

A series of 2-(3-arylureido)pyridines and 2-(3-benzylureido)pyridines were synthesized and evaluated as potential modulators for amyloid beta (Aβ)-induced mitochondrial dysfunction in Alzheimers disease (AD). The blocking activities of forty one small molecules against Aβ-induced mitochondrial permeability transition pore (mPTP) opening were evaluated by JC-1 assay which measures the change of mitochondrial membrane potential (ΔΨm). The inhibitory activity of twenty five compounds against Aβ-induced mPTP opening was superior to that of the standard cyclosporin A (CsA). Six hit compounds have been identified as likely safe in regards to mitochondrial and cellular safety and subjected to assessment for their protective effect against Aβ-induced deterioration of ATP production and cytotoxicity. Among them, compound 7fb has been identified as a lead compound protecting neuronal cells against 67% of neurocytotoxicity and 43% of suppression of mitochondrial ATP production induced by 5 μM concentrations of Aβ. Using CDocker algorithm, a molecular docking model presented a plausible binding mode for these compounds with cyclophilin D (CypD) receptor as a major component of mPTP. Hence, this report presents compound 7fb as a new nonpeptidyl mPTP blocker which would be promising for further development of Alzheimers disease (AD) therapeutics.

Discovery of a broad spectrum antiproliferative agent with selectivity for DDR1 kinase: cell line-based assay, kinase panel, molecular docking, and toxicity studies

Abstract Herein, we report compound KST9046, a new agent possessing quinazoline-urea scaffold. Preliminary biological evaluation done by the National Cancer Institute (NCI), USA, showed a great inhibitory effect of KST9046 over the 60 cell-line tumor panel. Accordingly, it was selected for a dose-response assay; a broad spectrum antiproliferative activity with GI50 ranging from 1.3 to 3.9 µM was exerted. To explore a potential kinase inhibitory effect, KST9046 was applied at a single dose of 10 µM against a kinase panel of 347 different enzymes representing >50% of the predicted human protein kinome. Interestingly, selective inhibition of 76% was observed on DDR1 kinase. Further, KST9046 showed an IC50 value of 4.38 µM for DDR1. A molecular docking model presented KST9046 as a potential type III inhibitor for DDR1 kinase with an allosteric mode of interaction, which may offer an explanation for its selectivity. As further investigation, CYP450 assay was carried out for KST9046, it showed a promising toxicity profile against four different isoforms. Based on these findings, KST9046 can be further evaluated as a promising safe new hit for the development of broad spectrum anticancer agents with a selectivity for DDR1 kinase.

Discretization of Continuous-Valued Attributes considering Data Distribution

This paper proposes a new approach that converts continuous-valued attributes to categorical-valued ones considering the distribution of target attributes(classes). In this approach, It can be possible to get optimal interval boundaries by considering the distribution of data itself without any requirements of parameters. For each attributes, the distribution of target attributes is projected to one-dimensional space. And this space is clustered according to the criteria like as the density value of each target attributes and the amount of overlapped areas among each density values of target attributes. Clusters which are made in this ways are based on the probabilities that can predict a target attribute of instances. Therefore it has an interval boundaries that minimize a loss of information of original data. An improved performance of proposed discretization method can be validated using C4.5 algorithm and UCI Machine Learning Data Repository data sets.

Synthesis and evaluation of new pyridyl/pyrazinyl thiourea derivatives: Neuroprotection against amyloid-β-induced toxicity

Herein, we report synthesis and evaluation of new twenty six small molecules against β amyloid (Aβ)-induced opening of mitochondrial permeability transition pore (mPTP) using JC-1 assay which measures the change of mitochondrial membrane potential (ΔΨm). The neuroprotective effect of seventeen compounds against Aβ-induced mPTP opening was superior to that of the standard Cyclosporin A (CsA). Fifteen derivatives eliciting increased green to red fluorescence percentage less than 40.0% were evaluated for their impact on ATP production, cell viability and neuroprotection against Aβ-induced neuronal cell death. Among evaluated compounds, derivatives 9w, 9r and 9k had safe profile regarding ATP production and cell viability. In addition, they exhibited significant neuroprotection (69.3, 51.8 and 48.2% respectively). Molecular modeling study using CDocker algorithm predicted plausible binding modes explaining the elicited mPTP blocking activity. Hence, this study suggests compounds 9w, 9r and 9k as leads for further development of novel therapy to Alzheimers disease.

Design, synthesis and biological evaluation of novel thiazolidinedione derivatives as irreversible allosteric IKK-β modulators

The kinase known as IKK-β activates NF-κB signaling pathway leading to expression of several genes contributing to inflammation, immune response, and cell proliferation. Modulation of IKK-β kinase activity could be useful for treatment and management of such diseases. Starting from a discovered weakly active hit compound, twenty four thiazolidinedione-scaffold based chemical entities belonging to five series have been designed, synthesized and evaluated as potential IKK-β modulators. Among them, compounds 6q, 6r and 6u showed low micromolar IC50 values while compounds 6v, 6w, and 6x elicited submicromolar IC50 values equal to 0.4, 0.7 and 0.9 μM respectively. These submicromolar IC50 values are 243, 139 and 105 folds the value of the reported IC50 of the starting hit compound. Kinetic study of compounds 6v and 6w confirmed this class of modulators as irreversible inhibitors. LPS-treated RAW 264.7 macrophages proved the anti-inflammatory activity of compounds 6q and 6v. Assay of hERG inhibition demonstrated a safe profile of compound 6q suggesting it as a lead for further development of IKK-β modulators.

Pyrazinyl ureas revisited: 1-(3-(Benzyloxy)pyrazin-2-yl)-3-(3,4-dichlorophenyl)urea, a new blocker of Aβ-induced mPTP opening for Alzheimer's disease

Herein, we report synthesis and evaluation of new twenty-eight pyrazinyl ureas against β amyloid (Aβ)-induced opening of mitochondrial permeability transition pore (mPTP) using JC-1 assay which measures the change of mitochondrial membrane potential (ΔΨm). The neuroprotective effect of seventeen compounds against Aβ-induced mPTP opening was superior to that of the standard Cyclosporin A (CsA). Among them, 1-(3-(benzyloxy)pyrazin-2-yl)-3-(3,4-dichlorophenyl)urea (5) effectively maintained mitochondrial function and cell viabilities on ATP assay and MTT assay. Also, hERG channel assay presented safe cardiotoxicity profile for compound 5. In addition, using CDocker algorithm, a molecular docking model presented a plausible explanation for the elicited differences in efficiencies of the synthesized compounds to reduce the green to red fluorescence as indication of mPTP closure. Hence, this report presents compound 5 as the most promising pyrazinyl urea-based mPTP blocker up to date.

A Sparse Data Preprocessing Using Support Vector Regression

In various fields as web mining, bioinformatics, statistical data analysis, and so forth, very diversely missing values are found. These values make training data to be sparse. Largely, the missing values are replaced by predicted values using mean and mode. We can used the advanced missing value imputation methods as conditional mean, tree method, and Markov Chain Monte Carlo algorithm. But general imputation models have the property that their predictive accuracy is decreased according to increase the ratio of missing in training data. Moreover the number of available imputations is limited by increasing missing ratio. To settle this problem, we proposed statistical learning theory to preprocess for missing values. Our statistical learning theory is the support vector regression by Vapnik. The proposed method can be applied to sparsely training data. We verified the performance of our model using the data sets from UCI machine learning repository.