The Experts below are selected from a list of 465 Experts worldwide ranked by ideXlab platform

Victor Guallar - One of the best experts on this subject based on the ideXlab platform.

  • A new view of the bacterial cytosol environment.
    PLOS Computational Biology, 2011
    Co-Authors: Benjamin P. Cossins, Matthew P. Jacobson, Victor Guallar
    Abstract:

    The cytosol is the major environment in all bacterial cells. The true physical and dynamical nature of the cytosol solutIon is not fully understood and here a modeling approach is applied. Using recent and detailed data on metabolite concentratIons, we have created a molecular mechanical model of the prokaryotic cytosol environment of Escherichia coli, containing proteins, metabolites and Monatomic Ions. We use 200 ns molecular dynamics simulatIons to compute diffusIon rates, the extent of contact between molecules and dielectric constants. Large metabolites spend ∼80% of their time in contact with other molecules while small metabolites vary with some only spending 20% of time in contact. Large non-covalently interacting metabolite structures mediated by hydrogen-bonds, Ionic and π stacking interactIons are common and often associate with proteins. Mg2+ Ions were prominent in NIMS and almost absent free in solutIon. Κ+ is generally not involved in NIMSs and populates the solvent fairly uniformly, hence its important role as an osmolyte. In simulatIons containing ubiquitin, to represent a protein component, metabolite diffusIon was reduced owing to long lasting protein-metabolite interactIons. Hence, it is likely that with larger proteins metabolites would diffuse even more slowly. The dielectric constant of these simulatIons was found to differ from that of pure water only through a large contributIon from ubiquitin as metabolite and Monatomic Ion effects cancel. These findings suggest regIons of influence specific to particular proteins affecting metabolite diffusIon and electrostatics. Also some proteins may have a higher propensity for associatIons with metabolites owing to their larger electrostatic fields. We hope that future studies may be able to accurately predict how binding interactIons differ in the cytosol relative to dilute aqueous solutIon.

  • A New View of the Bacterial Cytosol Environment
    2010
    Co-Authors: Benjamin P. Cossins, Matthew P. Jacobson, Victor Guallar
    Abstract:

    The cytosol is the major environment in all bacterial cells. The true physical and dynamical nature of the cytosol solutIon is not fully understood and here a modeling approach is applied. Using recent and detailed data on metabolite concentratIons, we have created a molecular mechanical model of the prokaryotic cytosol environment of Escherichia coli, containing proteins, metabolites and Monatomic Ions. We use 200 ns molecular dynamics simulatIons to compute diffusIon rates, the extent of contact between molecules and dielectric constants. Large metabolites spend,80 % of their time in contact with other molecules while small metabolites vary with some only spending 20 % of time in contact. Large noncovalently interacting metabolite structures mediated by hydrogen-bonds, Ionic and p stacking interactIons are common and often associate with proteins. Mg 2+ Ions were prominent in NIMS and almost absent free in solutIon. K + is generally not involved in NIMSs and populates the solvent fairly uniformly, hence its important role as an osmolyte. In simulatIons containing ubiquitin, to represent a protein component, metabolite diffusIon was reduced owing to long lasting proteinmetabolite interactIons. Hence, it is likely that with larger proteins metabolites would diffuse even more slowly. The dielectric constant of these simulatIons was found to differ from that of pure water only through a large contributIon from ubiquitin as metabolite and Monatomic Ion effects cancel. These findings suggest regIons of influence specific to particular proteins affecting metabolite diffusIon and electrostatics. Also some proteins may have a higher propensity for associatIon

Satoshi Hamaguchi - One of the best experts on this subject based on the ideXlab platform.

  • characterizatIon of descriptors in machine learning for data based sputtering yield predictIon
    Physics of Plasmas, 2021
    Co-Authors: Hiori Kino, Kazumasa Ikuse, Hieuchi Dam, Satoshi Hamaguchi
    Abstract:

    Sputtering of a single-element material surface by Monatomic Ion impact is one of the simplest and most fundamental phenomena of plasma–surface interactIon. Despite its seemingly simple and well-defined nature, its collisIon cascade dynamics is so complex that no widely applicable formula of the sputtering yield has ever been derived analytically from the first principles. When the first-principles approach to a complex problem fails to unveil its nature, a data-driven approach, or machine learning, may be used to transform the problem into a tractable model. In this study, regressIon models of sputtering yields of such systems were constructed based on publicly available data derived from a large number of past experiments. The analysis has also identified the descriptors (i.e., physical variables characterizing the surface and incident Ion species) on which the sputtering phenomena depend most strongly and presented quantitative evaluatIon on how sensitively the regressIon models depend on each descriptor or group of descriptors. InformatIon obtained in this study can facilitate an understanding of the fundamental workings of the sputtering phenomena in the absence of rigorous analytical theory.

Benjamin P. Cossins - One of the best experts on this subject based on the ideXlab platform.

  • A new view of the bacterial cytosol environment.
    PLOS Computational Biology, 2011
    Co-Authors: Benjamin P. Cossins, Matthew P. Jacobson, Victor Guallar
    Abstract:

    The cytosol is the major environment in all bacterial cells. The true physical and dynamical nature of the cytosol solutIon is not fully understood and here a modeling approach is applied. Using recent and detailed data on metabolite concentratIons, we have created a molecular mechanical model of the prokaryotic cytosol environment of Escherichia coli, containing proteins, metabolites and Monatomic Ions. We use 200 ns molecular dynamics simulatIons to compute diffusIon rates, the extent of contact between molecules and dielectric constants. Large metabolites spend ∼80% of their time in contact with other molecules while small metabolites vary with some only spending 20% of time in contact. Large non-covalently interacting metabolite structures mediated by hydrogen-bonds, Ionic and π stacking interactIons are common and often associate with proteins. Mg2+ Ions were prominent in NIMS and almost absent free in solutIon. Κ+ is generally not involved in NIMSs and populates the solvent fairly uniformly, hence its important role as an osmolyte. In simulatIons containing ubiquitin, to represent a protein component, metabolite diffusIon was reduced owing to long lasting protein-metabolite interactIons. Hence, it is likely that with larger proteins metabolites would diffuse even more slowly. The dielectric constant of these simulatIons was found to differ from that of pure water only through a large contributIon from ubiquitin as metabolite and Monatomic Ion effects cancel. These findings suggest regIons of influence specific to particular proteins affecting metabolite diffusIon and electrostatics. Also some proteins may have a higher propensity for associatIons with metabolites owing to their larger electrostatic fields. We hope that future studies may be able to accurately predict how binding interactIons differ in the cytosol relative to dilute aqueous solutIon.

  • A New View of the Bacterial Cytosol Environment
    2010
    Co-Authors: Benjamin P. Cossins, Matthew P. Jacobson, Victor Guallar
    Abstract:

    The cytosol is the major environment in all bacterial cells. The true physical and dynamical nature of the cytosol solutIon is not fully understood and here a modeling approach is applied. Using recent and detailed data on metabolite concentratIons, we have created a molecular mechanical model of the prokaryotic cytosol environment of Escherichia coli, containing proteins, metabolites and Monatomic Ions. We use 200 ns molecular dynamics simulatIons to compute diffusIon rates, the extent of contact between molecules and dielectric constants. Large metabolites spend,80 % of their time in contact with other molecules while small metabolites vary with some only spending 20 % of time in contact. Large noncovalently interacting metabolite structures mediated by hydrogen-bonds, Ionic and p stacking interactIons are common and often associate with proteins. Mg 2+ Ions were prominent in NIMS and almost absent free in solutIon. K + is generally not involved in NIMSs and populates the solvent fairly uniformly, hence its important role as an osmolyte. In simulatIons containing ubiquitin, to represent a protein component, metabolite diffusIon was reduced owing to long lasting proteinmetabolite interactIons. Hence, it is likely that with larger proteins metabolites would diffuse even more slowly. The dielectric constant of these simulatIons was found to differ from that of pure water only through a large contributIon from ubiquitin as metabolite and Monatomic Ion effects cancel. These findings suggest regIons of influence specific to particular proteins affecting metabolite diffusIon and electrostatics. Also some proteins may have a higher propensity for associatIon

Hiori Kino - One of the best experts on this subject based on the ideXlab platform.

  • characterizatIon of descriptors in machine learning for data based sputtering yield predictIon
    Physics of Plasmas, 2021
    Co-Authors: Hiori Kino, Kazumasa Ikuse, Hieuchi Dam, Satoshi Hamaguchi
    Abstract:

    Sputtering of a single-element material surface by Monatomic Ion impact is one of the simplest and most fundamental phenomena of plasma–surface interactIon. Despite its seemingly simple and well-defined nature, its collisIon cascade dynamics is so complex that no widely applicable formula of the sputtering yield has ever been derived analytically from the first principles. When the first-principles approach to a complex problem fails to unveil its nature, a data-driven approach, or machine learning, may be used to transform the problem into a tractable model. In this study, regressIon models of sputtering yields of such systems were constructed based on publicly available data derived from a large number of past experiments. The analysis has also identified the descriptors (i.e., physical variables characterizing the surface and incident Ion species) on which the sputtering phenomena depend most strongly and presented quantitative evaluatIon on how sensitively the regressIon models depend on each descriptor or group of descriptors. InformatIon obtained in this study can facilitate an understanding of the fundamental workings of the sputtering phenomena in the absence of rigorous analytical theory.

Matthew P. Jacobson - One of the best experts on this subject based on the ideXlab platform.

  • A new view of the bacterial cytosol environment.
    PLOS Computational Biology, 2011
    Co-Authors: Benjamin P. Cossins, Matthew P. Jacobson, Victor Guallar
    Abstract:

    The cytosol is the major environment in all bacterial cells. The true physical and dynamical nature of the cytosol solutIon is not fully understood and here a modeling approach is applied. Using recent and detailed data on metabolite concentratIons, we have created a molecular mechanical model of the prokaryotic cytosol environment of Escherichia coli, containing proteins, metabolites and Monatomic Ions. We use 200 ns molecular dynamics simulatIons to compute diffusIon rates, the extent of contact between molecules and dielectric constants. Large metabolites spend ∼80% of their time in contact with other molecules while small metabolites vary with some only spending 20% of time in contact. Large non-covalently interacting metabolite structures mediated by hydrogen-bonds, Ionic and π stacking interactIons are common and often associate with proteins. Mg2+ Ions were prominent in NIMS and almost absent free in solutIon. Κ+ is generally not involved in NIMSs and populates the solvent fairly uniformly, hence its important role as an osmolyte. In simulatIons containing ubiquitin, to represent a protein component, metabolite diffusIon was reduced owing to long lasting protein-metabolite interactIons. Hence, it is likely that with larger proteins metabolites would diffuse even more slowly. The dielectric constant of these simulatIons was found to differ from that of pure water only through a large contributIon from ubiquitin as metabolite and Monatomic Ion effects cancel. These findings suggest regIons of influence specific to particular proteins affecting metabolite diffusIon and electrostatics. Also some proteins may have a higher propensity for associatIons with metabolites owing to their larger electrostatic fields. We hope that future studies may be able to accurately predict how binding interactIons differ in the cytosol relative to dilute aqueous solutIon.

  • A New View of the Bacterial Cytosol Environment
    2010
    Co-Authors: Benjamin P. Cossins, Matthew P. Jacobson, Victor Guallar
    Abstract:

    The cytosol is the major environment in all bacterial cells. The true physical and dynamical nature of the cytosol solutIon is not fully understood and here a modeling approach is applied. Using recent and detailed data on metabolite concentratIons, we have created a molecular mechanical model of the prokaryotic cytosol environment of Escherichia coli, containing proteins, metabolites and Monatomic Ions. We use 200 ns molecular dynamics simulatIons to compute diffusIon rates, the extent of contact between molecules and dielectric constants. Large metabolites spend,80 % of their time in contact with other molecules while small metabolites vary with some only spending 20 % of time in contact. Large noncovalently interacting metabolite structures mediated by hydrogen-bonds, Ionic and p stacking interactIons are common and often associate with proteins. Mg 2+ Ions were prominent in NIMS and almost absent free in solutIon. K + is generally not involved in NIMSs and populates the solvent fairly uniformly, hence its important role as an osmolyte. In simulatIons containing ubiquitin, to represent a protein component, metabolite diffusIon was reduced owing to long lasting proteinmetabolite interactIons. Hence, it is likely that with larger proteins metabolites would diffuse even more slowly. The dielectric constant of these simulatIons was found to differ from that of pure water only through a large contributIon from ubiquitin as metabolite and Monatomic Ion effects cancel. These findings suggest regIons of influence specific to particular proteins affecting metabolite diffusIon and electrostatics. Also some proteins may have a higher propensity for associatIon