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Heo, Muyoung,Kim, Suhkmann,Moon, Eun-Joung,Cheon, Mookyung,Chung, Kwanghoon,Chang, Iksoo Published by the American Physical Society through 2005 Physical review. E, Statistical, nonlinear, and so Vol.72 No.1
<P>Although a coarse-grained description of proteins is a simple and convenient way to attack the protein folding problem, the construction of a global pairwise energy function which can simultaneously recognize the native folds of many proteins has resulted in partial success. We have sought the possibility of a systematic improvement of this pairwise-contact energy function as we extended the parameter space of amino acids, incorporating local environments of amino acids, beyond a 20 x 20 matrix. We have studied the pairwise contact energy functions of 20 x 20, 60 x 60, and 180 x 180 matrices depending on the extent of parameter space, and compared their effect on the learnability of energy parameters in the context of a gapless threading, bearing in mind that a 20 x 20 pairwise contact matrix has been shown to be too simple to recognize the native folds of many proteins. In this paper, we show that the construction of a global pairwise energy function was achieved using 1006 training proteins of a homology of less than 30%, which include all representatives of different protein classes. After parametrizing the local environments of the amino acids into nine categories depending on three secondary structures and three kinds of hydrophobicity (desolvation), the 16290 pairwise contact energies (scores) of the amino acids could be determined by perceptron learning and protein threading. These could simultaneously recognize all the native folds of the 1006 training proteins. When these energy parameters were tested on the 382 test proteins of a homology of less than 90%, 370 (96.9%) proteins could recognize their native folds. We set up a simple thermodynamic framework in the conformational space of decoys to calculate the unfolded fraction and the specific heat of real proteins. The different thermodynamic stabilities of E.coli ribonuclease H (RNase H) and its mutants were well described in our calculation, agreeing with the experiment.</P>
Yu, Wookyung,Lee, Woonghee,Lee, Weontae,Kim, Suhkmann,Chang, Iksoo Springer 2011 Journal of biomolecular NMR Vol.51 No.4
<P>Unravelling the complex correlation between chemical shifts of (13) C (α),?(13) C (β),?(13) C',?(1) H (α),?(15) N,?(1) H ( N ) atoms in amino acids of proteins from NMR experiment and local structural environments of amino acids facilitates the assignment of secondary structures of proteins. This is an important impetus for both determining the three-dimensional structure and understanding the biological function of proteins. The previous empirical correlation scores which relate chemical shifts of (13) C (α),?(13) C (β),?(13) C',?(1) H (α),?(15) N,?(1) H ( N ) atoms to secondary structures resulted in progresses toward assigning secondary structures of proteins. However, the physical-mathematical framework for these was elusive partly due to both the limited and orthogonal exploration of higher-dimensional chemical shifts of hetero-nucleus and the lack of physical-mathematical understanding underlying those correlation scores. Here we present a simple multi-dimensional hetero-nuclear chemical shift score function (MDHN-CSSF) which captures systematically the salient feature of such complex correlations without any references to a random coil state of proteins. We uncover the symmetry-breaking vector and its reliability order not only for distinguishing different secondary structures of proteins but also for capturing the delicate sensitivity interplayed among chemical shifts of (13) C (α),?(13) C (β),?(13) C',?(1) H (α),?(15) N,?(1) H ( N ) atoms simultaneously, which then provides a straightforward framework toward assigning secondary structures of proteins. MDHN-CSSF could correctly assign secondary structures of training (validating) proteins with the favourable (comparable) Q3 scores in comparison with those from the previous correlation scores. MDHN-CSSF provides a simple and robust strategy for the systematic assignment of secondary structures of proteins and would facilitate the de novo determination of three-dimensional structures of proteins.</P>
Jeong, Tae-Yong,Yoon, Dahye,Kim, Suhkmann,Kim, Hyun Young,Kim, Sang Don Elsevier 2018 Environmental pollution Vol.233 No.-
<P><B>Abstract</B></P> <P>Studies are underway to gather information about the mode of action (MOA) of emerging pollutants that could guide practical environmental decision making. Previously, we showed that propranolol, an active pharmaceutical ingredient, had adverse effects on <I>Daphnia magna</I> that were similar to its pharmaceutical action. In order to characterize the mode of action of propranolol in <I>D. magna</I>, which is suspected to be organ-specific pharmaceutical action or baseline toxicity, we performed time-series monitoring of behavior along with heart rate measurements and nuclear magnetic resonance (NMR) based metabolite profiling. Principle component analysis (PCA) and hierarchical clustering were used to categorize the mode of action of propranolol among 5 chemicals with different modes of action. The findings showed that the mode of action of propranolol in <I>D. magna</I> is organ-specific and vastly different from those of narcotics, even though metabolite regulation is similar between narcotic and non-narcotic candidates. The method applied in this study seems applicable to rapid characterization of the MOA of other cardiovascular pharmaceutical ingredients.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Monitoring of D. magna in behavior, heart rate and NMR based metabolite profiling was investigated. </LI> <LI> The MOA of propranolol was revealed to be not baseline toxicity but heart and organ specific. </LI> <LI> Results prove the usability of response monitoring and molecular biomarkers in rapid MOA characterization. </LI> <LI> Multiple responses have been confirmed for rapid decision making in additive mixture model in ERA. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>
Antioxidant Enzyme-Enhancing Effects of Jeju Water Containing Vanadium in vivo
김아름다슬,강경아,Rui Zhang,Mei Jing Piao,Suhkmann Kim,지영흔,이남호,Ho Jin You,고경수,현진원 대한암예방학회 2011 Journal of cancer prevention Vol.16 No.1
Recently, we reported that Jeju water containing vanadium (S3, 26.0±2.0 μg/l) exhibits an antioxidant effect via the scavenging of reactive oxygen species and by enhancing of antioxidant enzyme activities in vitro. In the present study, we examined the antioxidant effect of S3 with regard to antioxidant enzymes in vivo. C57BL/6 mice were given tap water or S3 for 90 days, and then the liver tissues were analyzed. Compared to tap water, S3 enhanced the activities of superoxide dismutase, catalase, glutathione peroxidase, and heme oxygenase-1. S3 also enhanced the level of reduced glutathione, which was determined by high-resolution magic angle spinning nuclear magnetic resonance spectroscopy and by a colorimetric assay. These results suggested that vanadium-containing Jeju water has antioxidant effects via enhancing antioxidant enzyme activities in vivo. (Cancer Prev Res 16, 58-64, 2011)
HR-MAS NMR Technique for Metabolic Profiling of Powdery Ginseng
Yoon, Dahye,Jo, Ick-Hyun,Kim, Suhkmann Korean Magnetic Resonance Society 2016 Journal of the Korean Magnetic Resonance Society Vol.20 No.3
Ginseng is used as a medicinal ingredient. The quality control of species, age, origin and manufacturing process is important. The metabolome of ginseng about quality was studied in many reports. Almost studies carried out the extract of ginseng, however, the reproducibility cannot be obtained using extracted sample. In this study, powdery ginseng samples were analyzed using high resolution-magic angle spinning nuclear magnetic resonance (HR-MAS NMR)-based metabolomics except extraction step. Sample was measured three times using 600 MHz NMR spectrometer equipped with nano probe. Reproducibility can be enhanced using this method and the metabolic profiles of ginseng were identified and quantified.