Biomedical subjects

Kyoung Tai No

Publications and source records attributed to Kyoung Tai No.

9 recordsLinked to original sources

PubMed2006

Classification of dopamine, serotonin, and dual antagonists by decision trees.

Dopamine antagonists (DA), serotonin antagonists (SA), and serotonin-dopamine dual antagonists (Dual) are being used as antipsychotics. A lot of dopamine and serotonin antagonists reveal non-selective binding affinity against these two receptors because the antagonists share structurally common features originated from conserved residues of binding site of the aminergic receptor family. Therefore, classification of dopamine and serotonin antagonists into their own receptors can be useful in the designing of selective antagonist for individual therapy of antipsychotic disorders. Data set containing 1135 dopamine antagonists (D2, D3, and D4), 1251 serotonin antagonists (5-HT1A, 5-HT2A, and 5-HT2C), and 386 serotonin-dopamine dual antagonists was collected from the MDDR database. Cerius2 descriptors were employed to develop a classification model for the 2772 compounds with antipsychotic activity. LDA (linear discriminant analysis), SIMCA (soft independent modeling of class analogy), RP (recursive partitioning), and ANN (artificial neural network) algorithms successfully classified the active class of each compound at the average 73.6% and predicted at the average 69.8%. The decision trees from RP, the best model, were generated to identify and interpret those descriptors that discriminate the active classes more easily. These classification models could be used as a virtual screening tool to predict the active class of new candidates.

Algorithms↗

PubMed2005

The development of 3D-QSAR study and recursive partitioning of heterocyclic quinone derivatives with antifungal activity.

It was reported that some 1,4-quinone derivatives such as 6-(N-arylamino)-7-chloro/6,7-bis[S-(aryl)thio]-5,8-quinolinedione and 6-arylthio-/5,6-arylamino-4,7-dioxobenzothiazoles have antifungal effects. To understand the structural basis for antifungal activity and guide in the design of more potent agents, we performed three-dimensional quantitative structure-activity relationship studies for a series of compounds using comparative molecular field analysis (CoMFA). The MIC values of 1,4-quinone derivatives on Aspergillus niger exhibited a strong correlation with steric and electrostatic factors of the 3D structure of molecules. The statistical results of the training set, cross-validated q(2) (0.683) and conventional r(2) (0.877) values, gave reliability to the prediction of inhibitory activity of a series of compounds. We also performed recursive partitioning (RP) analysis, used for the classification of molecules with activity using CART methods. Physicochemical, structural, and topological connectivity indices and E-state key descriptors were used for obtaining the decision tree models. The decision tree could classify the inhibitory activity of 1,4-quinone derivatives and its essential descriptors were S_aaN, Hbond donor, and Kappa-3.

Antifungal Agents↗

PubMed2005

Classification of dopamine antagonists using functional feature hypothesis and topological descriptors.

The designing of selective dopamine antagonists for their own subreceptors can be useful in individual therapy of various neuropsychiatric disorders. Three-dimensional pharmacophore hypothesis and two-dimensional topological descriptors were used to investigate and compare different classes of dopamine antagonists. The structurally diverse D(3) and D(4) antagonists above preclinical trials were selected to map common structural features of highly selective and efficacious antagonists. The generated pharmacophore hypotheses were successfully employed as discriminative probe for database screening. To filter out the false positive from screening hits, the classification models by two-dimensional topological descriptors were built. Molconn-Z and BCUT topological descriptors were employed to develop a classification model for 1328 dopamine antagonists from MDDR database. The soft independent modeling of class analogy and artificial neural network, two supervised classification techniques, successfully classified D(1), D(3), and D(4) antagonists at the average of 80% rates into their own active classes. The mean classification rates for D(2) antagonists were obtained to 60% due to insufficient selective D(2) antagonists. In this paper, we report the validity of our models generated using functional feature hypotheses and topological descriptors. The combining both of classification using functional feature hypotheses and topological descriptors would be a useful tool to predict selective antagonists.

Algorithms↗

PubMed2005

Synthesis of tripeptides as potent Yersinia protein tyrosine phosphatase inhibitors.

We report the synthesis of a series of monoanionic phosphotyrosyl (pTyr) mimetic-containing tripeptides based on 'Fmoc-Glu(OBn)-Xxx-Leu-amide' (where Xxx = pTyr mimetic) and their N-terminally modified derivatives. The inhibitory potencies of compounds were tested against YopH and human PTP1B enzymes. Several compounds exhibited noteworthy activity against both YopH and PTP1B. Among the N-terminally modified analogues, 5-methylindole derivative 30 was found to be the best moiety to replace base-labile Fmoc group. A mode of binding with YopH is proposed for tripeptides 21, 30, and 31.

Bacterial Outer Membrane Proteins↗

PubMed2005

Three-dimensional structure of Plasmodium falciparum Ca2+ -ATPase(PfATP6) and docking of artemisinin derivatives to PfATP6.

Construction of the 3D structure of PfATP6 by homology modeling and docking simulation of artemisinin derivatives to this protein model are reported. Docking and consequent LUDI scores show good relation with in vitro antimalarial activities. The main binding source of artemisinins to the PfATP6 is hydrophobic interaction and biologically important peroxide bonds were exposed to outside of the binding pocket. This study suggests binding of artemisinin to PfATP6 precedes activation of peroxide bond by Fe(2+) species.

Amino Acid Sequence↗

PubMed2003

Distortion of the three-dimensional structure of the vnd/NK-2 homeodomain bound to DNA induced by an embryonically lethal A35T point mutation.

The three-dimensional solution structure obtained by NMR of the A35T mutant vnd/NK-2 homeodomain bound to the vnd/NK-2 consensus 16 bp DNA sequence was determined. This mutation to threonine from alanine in position 35 in helix II of the vnd/NK-2 homeodomain is associated with early embryonic lethality in Drosophila melanogaster. Although the unbound mutant protein is not structured, in the DNA-bound state it adopts the three-helix fold characteristic of all known homeodomains, but with alterations relative to the structure of the wild-type analogue. These structural modifications occur, and are accompanied by a 50-fold reduction in the DNA binding affinity, even though most of the protein-DNA interactions originally seen for the wild-type homeodomain are found likewise in the threonine analogue. Alterations include torsional angle changes in the loop between helix I and helix II, and in the turn between helix II and helix III, as well as in a distortion of the usual antiparallel orientation of helix I with respect to helix II. The alteration of the position of leucine 40 in the A35T mutant is proposed to explain the observed 1.27 ppm upfield shift of the corresponding amide proton resonance relative to the value observed for the wild-type analogue. A detailed comparison of the structures of the mutant A35T and wild-type vnd/NK-2 homeodomains bound to the cognate DNA is presented. The consequences of the structural alteration of the DNA-bound A35T mutant vnd/NK-2 protein may constitute the basis of the observed early embryonic lethality.

Animals↗

PubMed2003

Nuclear thiol peroxidase as a functional alkyl-hydroperoxide reductase necessary for stationary phase growth of Saccharomyces cerevisiae.

Yeast nucleus-localized thiol peroxidase (nTPx) was characterized as a functional peroxidase. There are two cysteine residues in nTPx. Replacement of Cys-106 or Cys-111 with serine resulted in a complete loss of thioredoxin-linked peroxidase activity. However, when their activities were measured in terms of the ability to inhibit oxidation of glutamine synthetase, C111S showed the same antioxidant activity as the wild type protein. SDS-PAGE gel analysis revealed that only C111S existed as the dimer form. In addition to the identification of Cys-106 as the primary catalytic site, these data suggest the formation of the intradisulfide bond as a part of the catalytic cycle between nTPx and thioredoxin. nTPx preferentially reduced alkyl-hydroperoxides rather than H2O2. Furthermore, a nTPx mutant strain showed higher sensitivity toward alkyl-hydroperoxide than hydrogen peroxide. Also, reduction of the viability of nTPx mutant strain against various oxidants supports an in vivo antioxidant role for nTPx. nTPx transcriptional activity was not significantly detectable in log phase yeast, but the activity was exponentially increased after the diauxic shift. The transcriptional activity was highly induced even in the log phase yeast grown in nonfermentable carbon source. Deletion of Tor1p, Ras1p, and Ras2p resulted in considerable induction when compared with their parent strains, demonstrating the activation of the transcription of nTPx gene at the diauxic shift. Transcription of nTPx gene was induced in response to oxidative stress. Viability of a stationary phase nTPx mutant was considerably reduced compared with the isogenic strain. Collectively, these data demonstrate that nTPx is a thiol peroxidase family acting as alkyl-hydroperoxide reductase in the nucleus during post-diauxic growth.

Gene Expression Regulation, Fungal↗

PubMedDate not supplied

Prediction of glass transition temperature (T(g)) of some compounds in organic electroluminescent devices with their molecular properties.

We have studied the quantitative structure-property relationship between descriptors representing the molecular structure and glass transition temperature (T(g)) for 103 molecules including organic electroluminescent (EL) devices materials. Eighty-six descriptors were introduced and among them seven descriptors (one topological descriptor, one thermodynamic descriptor, one spatial descriptor, one structural descriptor, and three electrostatic descriptors) were selected by Genetic Algorithm (GA). The 81 molecules chosen randomly among 103 compounds were used as a training set, and the remaining 22 molecules were used as a prediction set. The quantitative relationship between these seven descriptors and T(g) was tested by multiple linear regression (MLR) and artificial neural network (ANN). ANN analysis showed no significant advantage over MLR for this study. As the results of the MLR, the square of the correlation coefficient (R(2)) for the T(g) of the 81 training set was 0.989, and the average error was 8.8 K. In prediction for T(g) using the 22 prediction compounds set with MLR, R(2) was 0.976, and the average error was 13.9 K.

Journal Article↗

PubMedDate not supplied

A partition coefficient calculation method with the SFED model.

The Solvation Free Energy Density (SFED) model, a solvation model proposed by No et al. was modified to give better solvation free energies of the molecules having high polarizable groups. The SFED at a point around the molecule was represented by a linear combination of four basis functions, the contribution from the cavitation free energy of a solvent, and a constant. As an application of the SFED model, the linear expansion coefficients of the Hydration Free Energy Density (HFED) and the 1-Octanol Free Energy Density (1-OFED) were determined. Both calculated hydration free energy and 1-octanol solvation free energy of selected 95 organic molecules agreed well with experimental values. The standard errors were 0.47 and 0.39 kcal/mol, respectively. 1-Octanol/water partition coefficients (P) of the molecules were calculated from the difference of the HFE and 1-OFE of the molecules. At the same time, the logP density (LPD) of a molecule was represented by the same basis functional form with the SFED model. The logP of a molecule can be obtained by the integration of the LPD of the molecule. The coefficients of the basis functions were determined by using experimental logP as constraints through an optimization procedure. Both logPs calculated from the free energy difference and from the LPD agreed well with the experimental data. The absolute mean errors were obtained as 0.34 and 0.32, respectively.

1-Octanol↗