Yong Jung Kwon

Bio: Yong Jung Kwon is an academic researcher from Kangwon National University. The author has contributed to research in topics: Virtual screening & Pharmacophore. The author has an hindex of 7, co-authored 10 publications receiving 212 citations.

3D QSAR pharmacophore based virtual screening and molecular docking for identification of potential HSP90 inhibitors.

Abstract: Chemical features based 3D pharmacophore models were developed for HSP90 based on the known inhibitors using Discovery Studio V2.1. An optimal pharmacophore model was brought forth and validated using a decoy set, external test set and Fischer's randomization method. The best five features pharmacophore model, Hypo1, includes two hydrogen bond acceptors, three hydrophobic features, which has the highest correlation coefficient (0.93), cost difference (73.88), low RMS (1.24), as well as it shows a high goodness of fit and enrichment factor. Hypo1 was used as a 3D query for virtual screening to retrieve potential inhibitors from Maybridge and Scaffold databases. The hit compounds were subsequently subjected to molecular docking studies and finally, 36 compounds were obtained based on consensus scoring function.

Molecular dynamics simulation study of PTP1B with allosteric inhibitor and its application in receptor based pharmacophore modeling

Abstract: Allosteric inhibition of protein tyrosine phosphatase 1B (PTP1B), has paved a new path to design specific inhibitors for PTP1B, which is an important drug target for the treatment of type II diabetes and obesity. The PTP1B1–282-allosteric inhibitor complex crystal structure lacks α7 (287–298) and moreover there is no available 3D structure of PTP1B1–298 in open form. As the interaction between α7 and α6–α3 helices plays a crucial role in allosteric inhibition, α7 was modeled to the PTP1B1–282 in open form complexed with an allosteric inhibitor (compound-2) and a 5 ns MD simulation was performed to investigate the relative orientation of the α7–α6–α3 helices. The simulation conformational space was statistically sampled by clustering analyses. This approach was helpful to reveal certain clues on PTP1B allosteric inhibition. The simulation was also utilized in the generation of receptor based pharmacophore models to include the conformational flexibility of the protein-inhibitor complex. Three cluster representative structures of the highly populated clusters were selected for pharmacophore model generation. The three pharmacophore models were subsequently utilized for screening databases to retrieve molecules containing the features that complement the allosteric site. The retrieved hits were filtered based on certain drug-like properties and molecular docking simulations were performed in two different conformations of protein. Thus, performing MD simulation with α7 to investigate the changes at the allosteric site, then developing receptor based pharmacophore models and finally docking the retrieved hits into two distinct conformations will be a reliable methodology in identifying PTP1B allosteric inhibitors.

Ginger ( Zingiber officinale ) phytochemicals—gingerenone-A and shogaol inhibit SaHPPK: molecular docking, molecular dynamics simulations and in vitro approaches

Abstract: Antibiotic resistance is a defense mechanism, harbored by pathogens to survive under unfavorable conditions. Among several antibiotic resistant microbial consortium, Staphylococcus aureus is one of the most havoc microorganisms. Staphylococcus aureus encodes a unique enzyme 6-hydroxymethyl-7,8-dihydropterin pyrophosphokinase (SaHPPK), against which, none of existing antibiotics have been reported. Computational approaches have been instrumental in designing and discovering new drugs for several diseases. The present study highlights the impact of ginger phytochemicals on Staphylococcus aureus SaHPPK. Herein, we have retrieved eight ginger phytochemicals from published literature and investigated their inhibitory interactions with SaHPPK. To authenticate our work, the investigation proceeds considering the known antibiotics alongside the phytochemicals. Molecular docking was performed employing GOLD and CDOCKER. The compounds with the highest dock score from both the docking programmes were tested for their inhibitory capability in vitro. The binding conformations that were seated within the binding pocket showing strong interactions with the active sites residues rendered by highest dock score were forwarded towards the molecular dynamic (MD) simulation analysis. Based on molecular dock scores, molecular interaction with catalytic active residues and MD simulations studies, two ginger phytochemicals, gingerenone-A and shogaol have been proposed as candidate inhibitors against Staphylococcus aureus. They have demonstrated higher dock scores than the known antibiotics and have represented interactions with the key residues within the active site. Furthermore, these compounds have rendered considerable inhibitory activity when tested in vitro. Additionally, their superiority was corroborated by stable MD results conducted for 100 ns employing GROMACS package. Finally, we suggest that gingerenone-A and shogaol may either be potential SaHPPK inhibitors or can be used as fundamental platforms for novel SaHPPK inhibitor development.

Novel chemical scaffolds of the tumor marker AKR1B10 inhibitors discovered by 3D QSAR pharmacophore modeling.

Abstract: Recent evidence suggests that aldo-keto reductase family 1 B10 (AKR1B10) may be a potential diagnostic or prognostic marker of human tumors, and that AKR1B10 inhibitors offer a promising choice for treatment of many types of human cancers. The aim of this study was to identify novel chemical scaffolds of AKR1B10 inhibitors using in silico approaches. The 3D QSAR pharmacophore models were generated using HypoGen. A validated pharmacophore model was selected for virtual screening of 4 chemical databases. The best mapped compounds were assessed for their drug-like properties. The binding orientations of the resulting compounds were predicted by molecular docking. Density functional theory calculations were carried out using B3LYP. The stability of the protein-ligand complexes and the final binding modes of the hit compounds were analyzed using 10 ns molecular dynamics (MD) simulations. The best pharmacophore model (Hypo 1) showed the highest correlation coefficient (0.979), lowest total cost (102.89) and least RMSD value (0.59). Hypo 1 consisted of one hydrogen-bond acceptor, one hydrogen-bond donor, one ring aromatic and one hydrophobic feature. This model was validated by Fischer's randomization and 40 test set compounds. Virtual screening of chemical databases and the docking studies resulted in 30 representative compounds. Frontier orbital analysis confirmed that only 3 compounds had sufficiently low energy band gaps. MD simulations revealed the binding modes of the 3 hit compounds: all of them showed a large number of hydrogen bonds and hydrophobic interactions with the active site and specificity pocket residues of AKR1B10. Three compounds with new structural scaffolds have been identified, which have stronger binding affinities for AKR1B10 than known inhibitors.

A lazy learning-based QSAR classification study for screening potential histone deacetylase 8 (HDAC8) inhibitors

Abstract: Histone deacetylases 8 (HDAC8) is an enzyme repressing the transcription of various genes including tumour suppressor gene and has already become a target of human cancer treatment. In an effort to facilitate the discovery of HDAC8 inhibitors, two quantitative structure–activity relationship (QSAR) classification models were developed using K nearest neighbours (KNN) and neighbourhood classifier (NEC). Molecular descriptors were calculated for the data set and database compounds using ADRIANA.Code of Molecular Networks. Principal components analysis (PCA) was used to select the descriptors. The developed models were validated by leave-one-out cross validation (LOO CV). The performances of the developed models were evaluated with an external test set. Highly predictive models were used for database virtual screening. Furthermore, hit compounds were subsequently subject to molecular docking. Five hits were obtained based on consensus scoring function and binding affinity as potential HDAC8 inhibitors. Final...

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Bioactive compounds and bioactivities of ginger (zingiber officinale roscoe)

Abstract: Ginger (Zingiber officinale Roscoe) is a common and widely used spice. It is rich in various chemical constituents, including phenolic compounds, terpenes, polysaccharides, lipids, organic acids, and raw fibers. The health benefits of ginger are mainly attributed to its phenolic compounds, such as gingerols and shogaols. Accumulated investigations have demonstrated that ginger possesses multiple biological activities, including antioxidant, anti-inflammatory, antimicrobial, anticancer, neuroprotective, cardiovascular protective, respiratory protective, antiobesity, antidiabetic, antinausea, and antiemetic activities. In this review, we summarize current knowledge about the bioactive compounds and bioactivities of ginger, and the mechanisms of action are also discussed. We hope that this updated review paper will attract more attention to ginger and its further applications, including its potential to be developed into functional foods or nutraceuticals for the prevention and management of chronic diseases.

Inside the human cancer tyrosine phosphatome

Abstract: The protein tyrosine phosphatase (Ptp) family dephosphorylates target proteins and counters the activities of protein tyrosine kinases. Accumulating evidence indicates that some PTPs have an important role in the inhibition or control of growth, whereas some PTPs exert oncogenic functions. This Review discusses the relevance of PTPs to cancer biology and their potential as therapeutic targets.

Novel protein tyrosine phosphatase 1B inhibitors: interaction requirements for improved intracellular efficacy in type 2 diabetes mellitus and obesity control.

Abstract: Resistance to the hormones insulin and leptin are hallmarks in common for type 2 diabetes mellitus and obesity. Both conditions are associated with increased activity and expression of protein tyrosine phosphatase (PTP)1B. Therefore, inhibition of PTP1B activity or down-regulation of its expression should ameliorate insulin and leptin resistance, and may hold therapeutic utility in type 2 diabetes mellitus and obesity control. This background has motivated the fervent search for PTP1B inhibitors, carried out in the recent years. The purpose of this review is to provide the most recent advances in understanding the structural details of PTP1B molecule relevant to the interactions with inhibitors, and the progress towards compounds with enhanced membrane permeability, affinity, specificity, and potency on intracellular PTP1B; several inhibitors of benefit in type 2 diabetes mellitus and obesity control are presented and discussed.