Biomedical subjects

Kotoko Nakata

Publications and source records attributed to Kotoko Nakata.

11 recordsLinked to original sources

PubMed2006

Nuclear receptor-mediated transcriptional regulation in Phase I, II, and III xenobiotic metabolizing systems.

Studies of the genetic regulation involved in drug metabolizing enzymes and drug transporters are of great interest to understand the molecular mechanisms of drug response and toxic events. Recent reports have revealed that hydrophobic ligands and several nuclear receptors are involved in the induction or down-regulation of various enzymes and transporters involved in Phase I, II, and III xenobiotic metabolizing systems. Nuclear receptors (NRs) form a family of ligand-activated transcription factors (TFs). These proteins modulate the regulation of target genes by contacting their promoter or enhancer sequences at specific recognition sites. These target genes include metabolizing enzymes such as cytochrome P450s (CYPs), transporters, and NRs. Thus it was now recognized that these NRs play essential role in sensing processing xenobiotic substances including drugs, environmental chemical pollutants and nutritional ingredients. From literature, we picked up target genes of each NR in xenobiotic response systems. Possible cross-talk, by which xenobiotics may exert undesirable effects, was listed. For example, the role of NRs was comprehensively drawn up in cholesterol and bile acid homeostasis in human hepatocyte. Summarizing current states of related research, especially for in silico response element search, we tried to elucidate nuclear receptor mediated xenobiotic processing loops and direct future research.

Animals↗

PubMed2005

Ab initio quantum mechanical study of the binding energies of human estrogen receptor alpha with its ligands: an application of fragment molecular orbital method.

We have theoretically examined the relative binding affinities (RBA) of typical ligands, 17beta-estradiol (EST), 17alpha-estradiol (ESTA), genistein (GEN), raloxifene (RAL), 4-hydroxytamoxifen (OHT), tamoxifen (TAM), clomifene (CLO), 4-hydroxyclomifene (OHC), diethylstilbestrol (DES), bisphenol A (BISA), and bisphenol F (BISF), to the alpha-subtype of the human estrogen receptor ligand-binding domain (hERalpha LBD), by calculating their binding energies. The ab initio fragment molecular orbital (FMO) method, which we have recently proposed for the calculations of macromolecules such as proteins, was applied at the HF/STO-3G level. The receptor protein was primarily modeled by 50 amino acid residues surrounding the ligand. The number of atoms in these model complexes is about 850, including hydrogen atoms. For the complexes with EST, RAL, OHT, and DES, the binding energies were calculated again with the entire ERalphaLBD consisting of 241 residues or about 4000 atoms. No significant difference was found in the calculated binding energies between the model and the real protein complexes. This indicates that the binding between the protein and its ligands is well characterized by the model protein with the 50 residues. The calculated binding energies relative to EST were very well correlated with the experimental RBA (the correlation coefficient r=0.837) for the ligands studied in this work. We also found that the charge transfer between ER and ligands is significant on ER-ligand binding. To our knowledge, this is the first achievement of ab initio quantum mechanical calculations of large molecules such as the entire ERalphaLBD protein.

Binding Sites↗

PubMed2004

Development of KiBank, a database supporting structure-based drug design.

KiBank is a database of inhibition constant (Ki) values with 3D structures of target proteins and chemicals. Ki values were accumulated from peer-reviewed literature searched via PubMed. The 3D structure files of target proteins were originally from Protein Data Bank (PDB), while the 2D structure files of the chemicals were collected together with the Ki values and then converted into 3D ones. In KiBank, the chemical and protein 3D structures with hydrogen atoms were optimized by energy minimization and stored in MDL MOL and PDB format, respectively. KiBank is designed to support structure-based drug design. It provides structure files of proteins and chemicals ready for use in virtual screening through automated docking methods, while the Ki values can be applied for tests of docking/scoring combinations, program parameter settings, and calibration of empirical scoring functions. Additionally, the chemical structures and corresponding Ki values in KiBank are useful for lead optimization based on quantitative structure-activity relationship (QSAR) techniques. KiBank is updated on a daily basis and is freely available at . As of August 2004, KiBank contains 8000 Ki values, over 6000 chemicals and 166 proteins covering the subtypes of receptors and enzymes.

Binding Sites↗

PubMed2004

[KiBank: a database for computer-aided drug design based on protein-chemical interaction analysis].

KiBank is a database for computer-aided drug design and consists of binding affinities and chemical and target protein structures. Each chemical or protein structure with hydrogen atoms added was optimized by energy minimization and stored in PDB or MDL MOL file format, so that the structural data can be directly used for in silico binding studies. To describe the extent of inhibition, the inhibition constant (K(i)) value is used to simplify comparisons of strengths among chemical-protein bindings. As of April 2004, KiBank contained 142 proteins, over 5000 chemicals, and over 6000 binding affinity values that were published in peer-reviewed journals. The binding affinity values are currently mostly for membrane and nuclear receptors but are soon being expanded to other drug targets. KiBank is updated daily and can be accessed on the Web at http://kibank.iis.u-tokyo.ac.jp/at no charge.

Computer-Aided Design↗

PubMed2004

Improvement in reliability of probabilistic test of significant differences in GeneChip experiments.

A probabilistic test (FUMI theory) for GeneChip experiments has been proposed for selecting the genes which show significant differences in the gene expression levels between a single pair of treatment and control. This paper describes that the reliability of the judgment by the FUMI theory can be enhanced, when the selected genes are referred to biomolecular-functional networks of a commercial database. The genes judged as being differently expressed are grouped into a cluster in the biomolecular networks. It is also demonstrated that false positive genes have a trend in the networks to be isolated from each other, and also away from the clustered genes, since the false positive genes are randomly selected.

Algorithms↗

PubMed2004

[Status of NIHS Computer Network System (NIHS-NET)].

We described the development of National Institute of Health Sciences Computer Network System (NIHS-NET), which was named NIHS Information and Computing Infrastructure (NICI) previously. In the system, the main server machines and common machines were replaced and the network lines were upgraded from 100 Mbps to 1Gbps. The connection nodes were changed from Inter Ministry Network (IMnet) to Science Information Network (SINET), and the dedicated lines between NIHS (yoga, osaka, tsukuba) and SINET were constructed. The Internet connection speed from each campus to SINET was upgraded. We also performed security audit in this system.

Computer Communication Networks↗

PubMed2003

Global information network on chemicals (GINC) and its Asian component.

The Global Information Network on Chemicals (GINC) is an effort to build a global information network that links international, national, and other organizations working for the safe management of chemicals in order to exchange information and improve communications. The project was originally proposed in 1993 by one of the authors then at the National Institute of Health Sciences (NIHS) of Japan to the International Program on Chemical Safety (IPCS), which is a joint project of World Health Organization (WHO), International Labor Organization (ILO), and United Nations Environment Program (UNEP). The base support system was first implemented at NIHS using the Internet/World Wide Web (WWW) technology in 1995. The project was then endorsed by the Intergovernmental Forum on Chemical Safety (IFCS) and was adopted by the Inter-Organization Program for the Sound Management of Chemicals (IOMC). However, the base system (http://www.nihs.go.jp/GINC/index.html) has been developed and maintained solely by the NIHS group under the support of the Ministry of Health and Welfare (MHW), Japan. Asia, particularly East Asia and the Pacific region, was chosen as the feasibility study region for this project. During the period from December 1994 to July 2002, NIHS hosted eight meetings on this project held in Tokyo.

Asia↗

PubMed2003

Test of significant differences with a priori probability in microarray experiments.

A traditional method for comparing two expression levels of genes in microarray experiments is the two-sample t-test. Because of the difficulty in using a large number of microarrays, an alternative method is required which can provide a reliable judgment of the comparison from a small number of replicates, even from a single pair of control and treatment. We present a method for detecting the changes in the gene expression levels under two different conditions in microarray experiments. Our method targets a single experiment for each condition, while retaining the statistical advantages of the t-test. The new proposals are: 1) standard deviation (SD) estimates of the expression levels which are an indicator for significant differences are given a priori as a function of the expression levels; 2) the limit of detection (LOD) for the expression levels is used to eliminate the majority of genes expressed at extremely low levels. The a priori SD estimates are obtained from six replicates under a fixed condition and are shown to be the approximate, but proper description of the expression uncertainty covering diverse conditions (e.g., different samples (human and rat) and different DNA chips). The LOD is defined as three times blank SD according to the IUPAC recommendation. A cell line (HL60) which will undergo macrophage differentiation on treatment with 12-O-tetradecanoylphorbol 13-acetate (TPA) is taken as an example. Our method is compared with the t-test for the data on duplicate TPA experiments and the former alone is evaluated with the data on a single TPA experiment. The errors from sample preparation and instrumental analysis are discussed.

Animals↗

PubMed2003

Bioinformatics research on inter-racial difference in drug metabolism II. Analysis on relationship between enzyme activities of CYP2D6 and CYP2C19 and their relevant genotypes.

The enzyme activities of CYP2D6 and CYP2C19 show a genetic polymorphism, and the frequency of poor metabolizers (PMs) on these enzymes depends on races. We have analyzed frequencies of mutant alleles and PMs based on the published data in previous study (Shimizu, T. et al.: Bioinformatics research on inter-racial difference in drug metabolism, I. Analysis on frequencies of mutant alleles and poor metabolizers on CYP2D6 and CYP2C19.). The study shows that there were racial differences in the frequencies of each mutant allele and PMs. In the present study, the correlation between genotypes and drug-metabolizing enzyme activities was investigated. The result showed that enzyme activities varied according to the genotypes of subjects even in the same race. On the other hand, if subjects had the same genotypes, almost no racial differences were observed in drug-metabolizing enzyme activities. From these results, it was supposed that the racial differences in activities of these enzymes could be explained by the differences in distribution of genotypes. It would be possible to explain the racial differences in drug-metabolizing enzyme activities based on the differences on individual pharmacogenetic background information, not merely by comparison of frameworks such as races and nations.

Journal Article↗

PubMed2002

Theoretical approach to endocrine disruptors.

Endocrine disruptors are now of scientific and public concern, because there is increasing evidence of their adverse effects on the health of an intact organism or its progeny and on changes in endocrine function. Although numerous substances have been identified as such chemicals, a huge number of chemicals remain to be tested for their endocrine disrupting capabilities. Because of the time and costs required for animal tests, some theoretical or computer-based method for screening this large number of chemicals is needed to reduce the numbers requiring animal testing. Improved quantitative structure activity relationship (QSAR) models were used for screening in combination with other approaches. New receptor-ligand docking simulations were being tested. There was good correlation between experimental and theoretical binding affinities. A database complex system being developed, which enables one to trace cellular signals triggered by the interaction of receptors with xenobiotic chemicals. Perspectives of computer-based screening methods are discussed.

Animals↗

PubMedDate not supplied

VISCANA: visualized cluster analysis of protein-ligand interaction based on the ab initio fragment molecular orbital method for virtual ligand screening.

We have developed a visualized cluster analysis of protein-ligand interaction (VISCANA) that analyzes the pattern of the interaction of the receptor and ligand on the basis of quantum theory for virtual ligand screening. Kitaura et al. (Chem. Phys. Lett. 1999, 312, 319-324.) have proposed an ab initio fragment molecular orbital (FMO) method by which large molecules such as proteins can be easily treated with chemical accuracy. In the FMO method, a total energy of the molecule is evaluated by summation of fragment energies and interfragment interaction energies (IFIEs). In this paper, we have proposed a cluster analysis using the dissimilarity that is defined as the squared Euclidean distance between IFIEs of two ligands. Although the result of an ordered table by clustering is still a massive collection of numbers, we combine a clustering method with a graphical representation of the IFIEs by representing each data point with colors that quantitatively and qualitatively reflect the IFIEs. We applied VISCANA to a docking study of pharmacophores of the human estrogen receptor alpha ligand-binding domain (57 amino acid residues). By using VISCANA, we could classify even structurally different ligands into functionally similar clusters according to the interaction pattern of a ligand and amino acid residues of the receptor protein. In addition, VISCANA could estimate the correct docking conformation by analyzing patterns of the receptor-ligand interactions of some conformations through the docking calculation.

Binding Sites↗