• Reproductive and Developmental Biology
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• v.34 no.3
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• pp.153-159
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• 2010

The 34 potently pig pheromonal odorants (1-32, 5755 & 7113) through structure-based virtual screening and ligand-based virtual screening method were selected and their ADMET and pharmacokinetics characters were evaluated and discussed quantitatively. The pheromonal odorants were projected on the following pre-calculated models, Caco-2 cell permeability, blood-brain barrier permeation, hERG inhibition and volume-distribution. From the results of in silico study, it is found that an optimal compound (31) either penetrating or have a little ($P_{caco2}$=-8.143) for Caco-2 cell permeability, moderate penetrating ability ($P_{BBB}$=0.082) for blood-brain barrier permeation, the low QT prolongation ($P_{hERG}$=1.137) for the hERG $K^+$ channel inhibition, and low distribution into tissues ($P_{VD}$=-5.468) for volume-distribution. Therefore, it is predicted that the compound (31) a topical application may be preferable from these based foundings.

• Biomolecules & Therapeutics
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• v.32 no.3
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• pp.390-398
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• 2024

FoxO1, a member of the Forkhead transcription factor family subgroup O (FoxO), is expressed in a range of cell types and is crucial for various pathophysiological processes, such as apoptosis and inflammation. While FoxO1's roles in multiple diseases have been recognized, the target has remained largely unexplored due to the absence of cost-effective and efficient inhibitors. Therefore, there is a need for natural FoxO1 inhibitors with minimal adverse effects. In this study, docking, MMGBSA, and ADMET analyses were performed to identify natural compounds that exhibit strong binding affinity to FoxO1. The top candidates were then subjected to molecular dynamics (MD) simulations. A natural product library was screened for interaction with FoxO1 (PDB ID-3CO6) using the Glide module of the Schrödinger suite. In silico ADMET profiling was conducted using SwissADME and pkCSM web servers. Binding free energies of the selected compounds were assessed with the Prime-MMGBSA module, while the dynamics of the top hits were analyzed using the Desmond module of the Schrödinger suite. Several natural products demonstrated high docking scores with FoxO1, indicating their potential as FoxO1 inhibitors. Specifically, the docking scores of neochlorogenic acid and fraxin were both below -6.0. These compounds also exhibit favorable drug-like properties, and a 25 ns MD study revealed a stable interaction between fraxin and FoxO1. Our findings highlight the potential of various natural products, particularly fraxin, as effective FoxO1 inhibitors with strong binding affinity, dynamic stability, and suitable ADMET profiles.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.6
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• pp.2883-2888
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• 2016

Background: Breast cancer (BC) is a serious lifestyle disease. There are several prognostic biomarkers like nuclear receptors whose over-expression is associated with BC characteristics. These biomarkers can be blocked by compounds with anti-cancer potential but selection must be made on the basis of no adverse side effects. This study is focused on finding of compounds from a plant source garlic. Materials and Methods: Twenty compounds from garlic and five targets considered involved in BC were retrieved from Pubchem database and Protein Data Bank respectively. They were docked using Accelrys Discovery Studio (DS) 4.0. The compounds which showed interaction were checked for drug likeliness. Results: Docking studies and ADMET evaluation revealed twelve compounds to be active against the targets. All the compounds displayed highly negative dock scores which indicated good interactions. Conclusions: The results of this study should help researchers and scientists in the pharmaceutical field to identify drugs based on garlic.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2018.04a
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• pp.95-95
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• 2018

Uric acid is the end product of purine metabolism in human body, originating from hypoxanthine after enzyme catalysis by Xanthine oxidase (XOD). Hyperuricemia results as a result of either over-generation of uric acid or a reduction in its excretion. In silico modelling methods such as Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) prediction, Autodock 4.2.6 program were used to study the potential inhibitory compounds of XOD. Also we investigated the inhibition of XOD activity by using the extracts of Dendropanax morbifera and Rubus coreanus Miq spectrophotometrically. According to ADMET data, several compounds from D. morbifera and R. coreanus plants, were found to be more potent in inhibiting the XOD activity than allopurinol. XOD inhibitory activity is evaluated by quantifying the formation of uric acid by measuring the absorbance at 290 m ($A_{290}$).D. morbifera extract inhibited XOD activity at $250{\mu}g/ml$, however the extracts from R. coreanus has inhibited XOD activity at $25{\mu}g/ml$. The major compound of R. coreanus, ellagic acid significantly increased the inhibition rate from $9{\mu}g/ml$ and showed a 71% suppression rate at $15{\mu}g/ml$. Finally, these results suggested a potential inhibitory activities of the extracts from D. morbifera and R. coreanus Miq, but further research is needed to validate to ensure their safe usage as drug.

• Genomics & Informatics
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• v.20 no.3
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• pp.33.1-33.17
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• 2022

Nervous necrosis virus (NNV) is a deadly infectious disease that affects several fish species. It has been found that the NNV utilizes grouper heat shock cognate protein 70 (GHSC70) to enter the host cell. Thus, blocking the virus entry by targeting the responsible protein can protect the fishes from disease. The main objective of the study was to evaluate the inhibitory potentiality of 70 compounds of Azadirachta indica (Neem plant) which has been reported to show potential antiviral activity against various pathogens, but activity against the NNV has not yet been reported. The binding affinity of 70 compounds was calculated against the GHSC70 with the docking and molecular dynamics (MD) simulation approaches. Both the docking and MD methods predict 4 (PubChem CID: 14492795, 10134, 5280863, and 11119228) inhibitory compounds that bind strongly with the GHSC70 protein with a binding affinity of -9.7, -9.5, -9.1, and -9.0 kcal/mol, respectively. Also, the ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties of the compounds confirmed the drug-likeness properties. As a result of the investigation, it may be inferred that Neem plant compounds may act as significant inhibitors of viral entry into the host cell. More in-vitro testing is needed to establish their effectiveness.

• Bulletin of the Korean Chemical Society
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• v.33 no.2
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• pp.613-619
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• 2012

We applied several machine learning methods for developing QSAR models for prediction of acute toxicity to fathead minnow. The multiple linear regression (MLR) and artificial neural network (ANN) method were applied to predict 96 h $LC_{50}$ (median lethal concentration) of 555 chemical compounds. Molecular descriptors based on 2D chemical structure were calculated by PreADMET program. The recursive partitioning (RP) model was used for grouping of mode of actions as reactive or narcosis, followed by MLR method of chemicals within the same mode of action. The MLR, ANN, and two RP-MLR models possessed correlation coefficients ($R^2$) as 0.553, 0.618, 0.632, and 0.605 on test set, respectively. The consensus model of ANN and two RP-MLR models was used as the best model on training set and showed good predictivity ($R^2$=0.663) on the test set.

• YAKHAK HOEJI
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• v.59 no.4
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• pp.151-157
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• 2015

The purpose of this study is to demonstrate how lead compounds are best optimized with the application of in silico QSAR and PBPK modeling at the early drug discovery stage. Several predictive QSAR models such as $IC_{50}$ potency model, intrinsic clearance model and brain penetration model were built and applied to a set of virtually synthesized library of the BACE1 inhibitors. Selected candidate compounds were also applied to the PBPK modeling for comparison between the predicted animal pharmacokinetic parameters and the observed ones in vivo. This novel lead optimization strategy using QSAR and PBPK modelings could be helpful to expedite the drug discovery process.

• Toxicological Research
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• v.31 no.2
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• pp.137-149
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• 2015

Human hepatocytes, with complete hepatic metabolizing enzymes, transporters and cofactors, represent the gold standard for in vitro evaluation of drug metabolism, drug-drug interactions, and hepatotoxicity. Successful cryopreservation of human hepatocytes enables this experimental system to be used routinely. The use of human hepatocytes to evaluate two major adverse drug properties: drug-drug interactions and hepatotoxicity, are summarized in this review. The application of human hepatocytes in metabolism-based drug-drug interaction includes metabolite profiling, pathway identification, P450 inhibition, P450 induction, and uptake and efflux transporter inhibition. The application of human hepatocytes in toxicity evaluation includes in vitro hepatotoxicity and metabolism-based drug toxicity determination. A novel system, the Integrated Discrete Multiple Organ Co-culture (IdMOC) which allows the evaluation of nonhepatic toxicity in the presence of hepatic metabolism, is described.

• Bulletin of the Korean Chemical Society
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• v.33 no.5
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• pp.1707-1714
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• 2012

Grb2 is an adapter protein involved in the signal transduction and cell communication. The Grb2 is responsible for initiation of kinase signaling by Ras activation which leads to the modification in transcription. Ligand based pharmacophore approach was applied to built the suitable pharmacophore model for Grb2. The best pharmacophore model was selected based on the statistical values and then validated by Fischer's randomization method and test set. Hypo1 was selected as a best pharmacophore model based on its statistical values like high cost difference (182.22), lowest RMSD (1.273), and total cost (80.68). It contains four chemical features, one hydrogen bond acceptor (HBA), two hydrophobic (HY), and one ring aromatic (RA). Fischer's randomization results also shows that Hypo1 have a 95% significant level. The correlation coefficient of test set was 0.97 which was close to the training set value (0.94). Thus Hypo1 was used for virtual screening to find the potent inhibitors from various chemical databases. The screened compounds were filtered by Lipinski's rule of five, ADMET and subjected to molecular docking studies. Totally, 11 compounds were selected as a best potent leads from docking studies based on the consensus scoring function and critical interactions with the amino acids in Grb2 active site.

• Analytical Science and Technology
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• v.24 no.6
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• pp.544-555
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• 2011

The acute toxicity in the rainbow trout (Oncorhynchus mykiss) was analyzed and predicted using quantitative structure-activity relationships (QSAR). The aquatic toxicity, 96h $LC_{50}$ (median lethal concentration) of 275 organic pesticides, was obtained from EU-funded project DEMETRA. Prediction models were derived from 558 2D molecular descriptors, calculated in PreADMET. The linear (multiple linear regression) and nonlinear (support vector machine and artificial neural network) learning methods were optimized by taking into account the statistical parameters between the experimental and predicted p$LC_{50}$. After preprocessing, population based forward selection were used to select the best subsets of descriptors in the learning methods including 5-fold cross-validation procedure. The support vector machine model was used as the best model ($R^2_{CV}$=0.677, RMSECV=0.887, MSECV=0.674) and also correctly classified 87% for the training set according to EU regulation criteria. The MLR model could describe the structural characteristics of toxic chemicals and interaction with lipid membrane of fish. All the developed models were validated by 5 fold cross-validation and Y-scrambling test.