• Title/Summary/Keyword: Generalized Born model

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Effects of generalized-Born implicit solvent models in NMR structure refinement

  • Jee, Jun-Goo
    • Journal of the Korean Magnetic Resonance Society
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    • v.17 no.1
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    • pp.11-18
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    • 2013
  • Rapid advances of computational power and method have made it practical to apply the time-consuming calculations with all-atom force fields and sophisticated potential energies into refining NMR structure. Added to the all-atom force field, generalized-Born implicit solvent model (GBIS) contributes substantially to improving the qualities of the resulting NMR structures. GBIS approximates the effects that explicit solvents bring about even with fairly reduced computational times. Although GBIS is employed in the final stage of NMR structure calculation with experimental restraints, the effects by GBIS on structures have been reported notable. However, the detailed effect is little studied in a quantitative way. In this study, we report GBIS refinements of ubiquitin and GB1 structures by six GBIS models of AMBER package with experimental distance and backbone torsion angle restraints. Of GBIS models tested, the calculations with igb=7 option generated the closest structures to those determined by X-ray both in ubiquitin and GB1 from the viewpoints of root-mean-square deviations. Those with igb=5 yielded the second best results. Our data suggest that the degrees of improvements vary under different GBIS models and the proper selection of GBIS model can lead to better results.

Refinement of Protein NMR Structure under Membrane-like Environments with an Implicit Solvent Model

  • Jee, Jun-Goo;Ahn, Hee-Chul
    • Bulletin of the Korean Chemical Society
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    • v.30 no.5
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    • pp.1139-1142
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    • 2009
  • Refinement of NMR structures by molecular dynamics (MD) simulations with a solvent model has improved the structural quality. In this study, we applied MD refinement with the generalized Born (GB) implicit solvent model to protein structure determined under membrane-like environments. Despite popularity of the GB model, its applications to the refinement of NMR structures of hydrophobic proteins, in which detergents or organic solvents enclose proteins, are limited, and there is little information on the use of another GB parameter for these cases. We carried out MD refinement of crambin NMR structure in dodecylphosphocholine (DPC) micelles (Ahn et al., J. Am. Chem. Soc. 2006, 128, 4398-4404) with GB/Surface area model and two different surface tension coefficients, one for aquatic and the other for hydrophobic conditions. Our data show that, of two structures by MD refinement with GB model, the one refined with the parameter to consider hydrophobic condition had the better qualities in terms of precision and solvent accessibility.

Computational Studies of the β-D Glucopyranose Structure (계산화학적 방법을 통한 β-D-glucopyranose 구조 연구)

  • Yang, Ji-Hyun;Kim, Jinah;Lee, Sangmin;Ahn, Ik-Sung;Mhin, ByungJin
    • Journal of the Korean Chemical Society
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    • v.57 no.5
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    • pp.554-559
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    • 2013
  • In this study, we have investigated potential energy of ${\beta}$-D-glucopyranose in vacuum and implicit water condition. By Comparing two conditions we find that how solvation energy influence ${\beta}$-D-glucopyranose structure. We use AMBER package program and GLYCAM_06 force field. Solvation model was used for the generalized Born model with Hawkins, Cramer, Truhlar has been proposed. We conclude that difference of contour map of two conditions is caused by solvation effect by reducing hydrogen bonding interaction.

Systematic Assessment of the Effects of an All-Atom Force Field and the Implicit Solvent Model on the Refinement of NMR Structures with Subsets of Distance Restraints

  • Jee, Jun-Goo
    • Bulletin of the Korean Chemical Society
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    • v.35 no.7
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    • pp.1944-1950
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    • 2014
  • Employment of a time consuming, sophisticated calculation using the all-atom force field and generalized-Born implicit solvent model (GBIS) for refinement of NMR structures has become practical through advances in computational methods and capacities. GBIS refinement improves the qualities of the resulting NMR structures with reduced computational times. However, the contribution of GBIS to NMR structures has not been sufficiently studied in a quantitative way. In this paper, we report the effects of GBIS on the refined NMR structures of ubiquitin (UBQ) and GB1 with subsets of distance restraints derived from experimental data. Random omission prepared a series of distance restraints 0.05, 0.1, 0.3, 0.5, and 0.7 times smaller. For each number, we produced five different restraints for statistical analysis. We then recalculated the NMR structures using CYANA software, followed by GBIS refinements using the AMBER package. GBIS improved both the precision and accuracy of all the structures, but to varied levels. The degrees of improvement were significant when the input restraints were insufficient. In particular, GBIS enabled GB1 to form an accurate structure even with distance restraints of 5%, revealing that the root-mean-square deviation was less than 1 ${\AA}$ from the X-ray backbone structure. We also showed that the efficiency of searching the conformational space was more important for finding accurate structures with the calculation of UBQ with 5% distance restraints than the number of conformations generated. Our data will provide a meaningful guideline to judge and compare the structural improvements by GBIS.

Effects of force fields for refining protein NMR structures with atomistic force fields and generalized-Born implicit solvent model

  • Jee, Jun-Goo
    • Journal of the Korean Magnetic Resonance Society
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    • v.18 no.1
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    • pp.24-29
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    • 2014
  • Atomistic molecular dynamics (MD) simulation has become mature enabling close approximation of the real behaviors of biomolecules. In biomolecular NMR field, atomistic MD simulation coupled with generalized implicit solvent model (GBIS) has contributed to improving the qualities of NMR structures in the refinement stage with experimental restraints. Here all-atom force fields play important roles in defining the optimal positions between atoms and angles, resulting in more precise and accurate structures. Despite successful applications in refining NMR structure, however, the research that has studied the influence of force fields in GBIS is limited. In this study, we compared the qualities of NMR structures of two model proteins, ubiquitin and GB1, under a series of AMBER force fields-ff99SB, ff99SB-ILDN, ff99SB-NMR, ff12SB, and ff13-with experimental restraints. The root mean square deviations of backbone atoms and packing scores that reflect the apparent structural qualities were almost indistinguishable except ff13. Qualitative comparison of parameters, however, indicates that ff99SB-ILDN is more recommendable, at least in the cases of ubiquitin and GB1.

Computational Study of Human Calcitonin (hCT) Oligomer

  • Pak, Young-Shang;Shin, Jung-Ho;Jang, Soon-Min
    • Bulletin of the Korean Chemical Society
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    • v.30 no.12
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    • pp.3006-3010
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    • 2009
  • We have performed long time REMD simulation on 15-19 residues of human calcitonin hormone (DFNKF) which is known to form highly ordered amyloid fibril. The simulation started from randomly oriented multiple DFNKF strand. Using all-atom level simulations with the generalized Born solvation (GB) model (param99MOD3), we observed spontaneous formation of ${\beta}$-sheet for tetramer. Interestingly, the current simulation gives anti-parallel sheet as a major conformation, consistent with experiments. The major interaction stabilizing the anti-parallel sheet seems to be the inter-strand hydrogen bond.

Development of Fertility Assumptions for the Future Population Projection (장래인구추계를 위한 출산력 가정치의 설정)

  • Jun, Kwang-Hee
    • Korea journal of population studies
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    • v.29 no.2
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    • pp.53-88
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    • 2006
  • The major aim of this paper is to develop a hypothetical set of age-specific fertility rates which are logically derived and reasonably accurate in the projection of future population. The first procedure is to select a generalized log-gamma distribution model, which includes Coale-McNeil nuptiality model, in order to estimate and project a set of age-specific fertility rates by birth cohort and birth order. The second is to apply the log-gamma model with an empirical adjustment to the actual data to estimate and project the future fertility rates for relatively young birth cohorts who did not complete their reproductive career. This study reconstructs or translates a set of cohort age-specific fertility rates into a set of period age-specific fertility rates which must be hypothesized in order to establish the broader framework of future population projection. For example, the fertility at age 20 in the year of 2020 is the fertility at age 20 for the cohort born in 1990, while the fertility at age 21 in the year of 2020 is the fertility at 21 for the cohort born in 1989. In turn, once a set of age-specific fertility rates for the cohorts who were born up to the year of 2010, it is possible for one to establish an hypothetical set of period age-specific fertility rates which will be needed to project the future population until the year of 2055. The difference in the hypothetical system of age-specific fertility rates between this study and the 2005 special population projection comes from the fact that the fertility estimation/projection model used in this study was skillfully exploited to reflect better actual trend of fertility decline caused by rise in marriage age and increasing proportion of those who remain single until their end of reproduction. In this regard, this paper argues that the set of age-specific fertility rates derived from this study is more logical and reasonably accurate than the set of those used for the 2005 special projection. In the population projection, however, the fundamental issue of the hypothetical setting of age-specific fertility rates in relation to the fertility estimation/projection model is about how skillfully one can handle the period effects. It is not easy for one to completely cope with the problem of period effects except for the a minor period adjustment based on recent actual data, along with the given framework of a cohort-based fertility estimation/projection model.

Comparison of NMR structures refined under implicit and explicit solvents

  • Jee, Jun-Goo
    • Journal of the Korean Magnetic Resonance Society
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    • v.19 no.1
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    • pp.1-10
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    • 2015
  • Refinements with atomistic molecular dynamics (MD) simulation have contributed to improving the qualities of NMR structures. In most cases, the calculations with atomistic MD simulation for NMR structures employ generalized-Born implicit solvent model (GBIS) to take into accounts solvation effects. Developments in algorithms and computational capacities have ameliorated GBIS to approximate solvation effects that explicit solvents bring about. However, the quantitative comparison of NMR structures in the latest GBIS and explicit solvents is lacking. In this study, we report the direct comparison of NMR structures that atomistic MD simulation coupled with GBIS and water molecules refined. Two model proteins, GB1 and ubiquitin, were recalculated with experimental distance and torsion angle restraints, under a series of simulated annealing time steps. Whereas the root mean square deviations of the resulting structures were apparently similar, AMBER energies, the most favored regions in Ramachandran plot, and MolProbity clash scores witnessed that GBIS-refined structures had the better geometries. The outperformance by GBIS was distinct in the structure calculations with sparse experimental restraints. We show that the superiority stemmed, at least in parts, from the inclusion of all the pairs of non-bonded interactions. The shorter computational times with GBIS than those for explicit solvents makes GBIS a powerful method for improving structural qualities particularly under the conditions that experimental restraints are insufficient. We also propose a method to separate the native-like folds from non-violating diverged structures.

Refinement of protein NMR structures using atomistic force field and implicit solvent model: Comparison of the accuracies of NMR structures with Rosetta refinement

  • Jee, Jun-Goo
    • Journal of the Korean Magnetic Resonance Society
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    • v.26 no.1
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    • pp.1-9
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    • 2022
  • There are two distinct approaches to improving the quality of protein NMR structures during refinement: all-atom force fields and accumulated knowledge-assisted methods that include Rosetta. Mao et al. reported that, for 40 proteins, Rosetta increased the accuracies of their NMR-determined structures with respect to the X-ray crystal structures (Mao et al., J. Am. Chem. Soc. 136, 1893 (2014)). In this study, we calculated 32 structures of those studied by Mao et al. using all-atom force field and implicit solvent model, and we compared the results with those obtained from Rosetta. For a single protein, using only the experimental NOE-derived distances and backbone torsion angle restraints, 20 of the lowest energy structures were extracted as an ensemble from 100 generated structures. Restrained simulated annealing by molecular dynamics simulation searched conformational spaces with a total time step of 1-ns. The use of GPU-accelerated AMBER code allowed the calculations to be completed in hours using a single GPU computer-even for proteins larger than 20 kDa. Remarkably, statistical analyses indicated that the structures determined in this way showed overall higher accuracies to their X-ray structures compared to those refined by Rosetta (p-value < 0.01). Our data demonstrate the capability of sophisticated atomistic force fields in refining NMR structures, particularly when they are coupled with the latest GPU-based calculations. The straightforwardness of the protocol allows its use to be extended to all NMR structures.

Impact of Weather on Prevalence of Febrile Seizures in Children (소아의 열성경련에 날씨가 미치는 영향)

  • Woo, Jung Hee;Oh, Seok Bin;Yim, Chung Hyuk;Byeon, Jung Hye;Eun, Baik-Lin
    • Journal of the Korean Child Neurology Society
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    • v.26 no.4
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    • pp.227-232
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    • 2018
  • Purpose: Febrile seizure (FS) is the most common type of seizure in children between 6 months to 5 years of age. A family history of febrile seizures can increase the risk a child will have a FS. Yet, prevalence of FS regarding external environment has not been clearly proved. This study attempts to determine the association between prevalence of FS and weather. Methods: This study included medical records from the Korea National Health Insurance Review and Assessment Service. Data were collected from 29,240 children, born after 2004, diagnosed with FS who were admitted to one of the hospitals in Seoul, Korea, between January 2009 and December 2013. During the corresponding time period, data from the Korea Meteorological Administration on daily monitoring of four meteorological factors (sea-level pressure, amount of precipitation, humidity and temperature) were collected. The relationships of FS prevalence and each meteorological factor will be designed using Poisson generalized additive model (GAM). Also, the contributory effect of viral infections on FS prevalence and weather will be discussed. Results: The amount of precipitation was divided into two groups for comparison: one with less than 5 mm and the other with equal to or more than 5 mm. As a result of Poisson GAM, higher prevalence of FS showed a correlation with smaller amount of precipitation. Smoothing function was used to classify the relationships between three variables (sea-level pressure, humidity, and temperature) and prevalence of FS. FS prevalence was correlated with lower sea-level pressure and lower humidity. FS prevalence was high in two temperature ranges (-7 to $-1^{\circ}C$ and $18-21^{\circ}C$). Conclusion: Low sea-level pressure, small amount of precipitation, and low relative air humidity may increase FS prevalence risk.