Predicting protein diffusion coefficients.
Ontology highlight
ABSTRACT:
SUBMITTER: Brune D
PROVIDER: S-EPMC46400 | biostudies-other | 1993 May
REPOSITORIES: biostudies-other
Publications
Predicting protein diffusion coefficients.
Proceedings of the National Academy of Sciences of the United States of America 19930501 9
Diffusion coefficients for proteins in water are predicted. The numerical method developed is general enough to be applied to a wide range of protein surface shapes, from rodlike to globular. Results are presented for lysozyme and tobacco mosaic virus, and they are compared with actual data and with predictions made by less general methods. ...[more]
Similar Datasets
Project description:Diffusion-ordered nuclear magnetic resonance (NMR) spectroscopy is widely used for the analysis of mixtures, dispersing the signals of different species in a two-dimensional spectrum according to their diffusion coefficients. However, interpretation of these diffusion coefficients is typically purely qualitative, for example, to deduce which species are bigger or smaller. In studies of proteins in solution, important questions concern the molecular weight of the proteins, the presence or absence of aggregation, and the degree of folding. The Stokes-Einstein Gierer-Wirtz estimation (SEGWE) method has been previously developed to simplify the complex relationship between diffusion coefficient and molecular mass, allowing the prediction of a species' diffusion coefficient in a pure solvent based on its molecular weight. Here, we show that SEGWE can be extended to successfully predict both peptide and protein diffusion coefficients in mixed protiated-deuteriated water samples and, hence, distinguish effectively between globular and disordered proteins.
| S-EPMC9376945 | biostudies-literature
Project description:BackgroundThe Abraham general solvation model can be used in a broad set of scenarios involving partitioning and solubility, yet is limited to a set of solvents with measured Abraham coefficients. Here we extend the range of applicability of Abraham's model by creating open models that can be used to predict the solvent coefficients for all organic solvents.ResultsWe created open random forest models for the solvent coefficients e, s, a, b, and v that had out-of-bag R(2) values of 0.31, 0.77, 0.92, 0.47, and 0.63 respectively. The models were used to suggest sustainable solvent replacements for commonly used solvents. For example, our models predict that propylene glycol may be used as a general sustainable solvent replacement for methanol.ConclusionThe solvent coefficient models extend the range of applicability of the Abraham general solvation equations to all organic solvents. The models were developed under Open Notebook Science conditions which makes them open, reproducible, and as useful as possible. Graphical AbstractChemical space for solvents with known Abraham coefficients.
| S-EPMC4369285 | biostudies-literature
Project description:Recently, a new and versatile assay to determine the partitioning coefficient [Formula: see text] as a measure for the affinity of peripheral membrane proteins for lipid bilayers was presented in the research article entitled, "Introducing a fluorescence-based standard to quantify protein partitioning into membranes" [1]. Here, the well-characterized binding of hexahistidine-tag (His6) to NTA(Ni) was utilized. Complementarily, this data article reports the average diffusion coefficient [Formula: see text] of His6-tagged enhanced green fluorescent protein (eGFP-His6) and the fluorescent lipid analog ATTO-647N-DOPE in giant unilamellar vesicles (GUVs) containing different amounts of NTA(Ni) lipids. In addition, dissociation constants [Formula: see text] of the NTA(Ni)/eGFP-His6 system are reported. Further, a conversion between [Formula: see text] and [Formula: see text] is provided.
| S-EPMC4625048 | biostudies-literature
Project description:MotivationBiologistics provides data for quantitative analysis of transport (diffusion) processes and their spatio-temporal correlations in cells. Mobility of proteins is one of the few parameters necessary to describe reaction rates for gene regulation. Although understanding of diffusion-limited biochemical reactions in vivo requires mobility data for the largest possible number of proteins in their native forms, currently, there is no database that would contain the complete information about the diffusion coefficients (DCs) of proteins in a given cell type.ResultsWe demonstrate a method for the determination of in vivo DCs for any molecule--regardless of its molecular weight, size and structure--in any type of cell. We exemplify the method with the database of in vivo DC for all proteins (4302 records) from the proteome of K12 strain of Escherichia coli, together with examples of DC of amino acids, sugars, RNA and DNA. The database follows from the scale-dependent viscosity reference curve (sdVRC). Construction of sdVRC for prokaryotic or eukaryotic cell requires ~20 in vivo measurements using techniques such as fluorescence correlation spectroscopy (FCS), fluorescence recovery after photobleaching (FRAP), nuclear magnetic resonance (NMR) or particle tracking. The shape of the sdVRC would be different for each organism, but the mathematical form of the curve remains the same. The presented method has a high predictive power, as the measurements of DCs of several inert, properly chosen probes in a single cell type allows to determine the DCs of thousands of proteins. Additionally, obtained mobility data allow quantitative study of biochemical interactions in vivo.Contactrholyst@ichf.edu.pl.Supplementary informationSupplementary data are available at Bioinformatics Online.
| S-EPMC3496334 | biostudies-literature
Project description:One of the fundamental tasks in biology is to identify the functions of all proteins to reveal the primary machinery of a cell. Knowledge of the subcellular locations of proteins will provide key hints to reveal their functions and to understand the intricate pathways that regulate biological processes at the cellular level. Protein subcellular location prediction has been extensively studied in the past two decades. A lot of methods have been developed based on protein primary sequences as well as protein-protein interaction network. In this paper, we propose to use the protein-protein interaction network as an infrastructure to integrate existing sequence based predictors. When predicting the subcellular locations of a given protein, not only the protein itself, but also all its interacting partners were considered. Unlike existing methods, our method requires neither the comprehensive knowledge of the protein-protein interaction network nor the experimentally annotated subcellular locations of most proteins in the protein-protein interaction network. Besides, our method can be used as a framework to integrate multiple predictors. Our method achieved 56% on human proteome in absolute-true rate, which is higher than the state-of-the-art methods.
| S-EPMC3900678 | biostudies-literature
Project description:Efflux time courses of endogenous cytosolic proteins were obtained from rabbit psoas muscle fibers skinned in oil and transferred to physiological salt solution. Proteins were separated by gel electrophoresis and compared to load-matched standards for quantitative analysis. A radial diffusion model incorporating the dissociation and dissipation of supramolecular complexes accounts for an initial lag and subsequent efflux of glycolytic and glycogenolytic enzymes. The model includes terms representing protein crowding, myofilament lattice hindrance, and binding to the cytomatrix. Optimization algorithms returned estimates of the apparent diffusion coefficients, D(r,t), that were very low at the onset of diffusion (∼10(-10) cm(2) s(-1)) but increased with time as cytosolic protein density, which was initially high, decreased. D(r,t) at later times ranged from 2.11 × 10(-7) cm(2) s(-1) (parvalbumin) to 0.20 × 10(-7) cm(2) s(-1) (phosphofructose kinase), values that are 3.6- to 12.3-fold lower than those predicted in bulk water. The low initial values are consistent with the presence of complexes in situ; the higher later values are consistent with molecular sieving and transient binding of dissociated proteins. Channeling of metabolic intermediates via enzyme complexes may enhance production of adenosine triphosphate at rates beyond that possible with randomly and/or sparsely distributed enzymes, thereby matching supply with demand.
| S-EPMC3944625 | biostudies-literature
Project description:The formation of biomimetic lipid membranes has the potential to provide insights into cellular lipid membrane dynamics. The construction of such membranes necessitates not only the utilization of appropriate lipids, but also physiologically relevant substrate/support materials. The substrate materials employed have been shown to have demonstrable effects on the behavior of the overlying lipid membrane, and thus must be studied before use as a model cushion support. To our knowledge, we report the formation and investigation of a novel actin protein-supported lipid membrane. Specifically, inner leaflet lateral mobility of globular actin-supported DMPC (1,2-dimyristoyl-sn-glycero-3-phosphocholine) bilayers, deposited via the Langmuir-Blodgett/Langmuir Schaefer methodology, was investigated by z-scan fluorescence correlation spectroscopy across a temperature range of 20-44°C. The actin substrate was found to decrease the diffusion coefficient when compared to an identical membrane supported on glass. The depression of the diffusion coefficient occurred across all measured temperatures. These results indicated that the actin substrate exerted a direct effect on the fluidity of the lipid membrane and highlighted the fact that the choice of substrate/support is critical in studies of model lipid membranes.
| S-EPMC4407249 | biostudies-literature
Project description:Molecular dynamics simulations were performed for the prediction of the finite-size effects of Maxwell-Stefan diffusion coefficients of molecular mixtures and a wide variety of binary Lennard-Jones systems. A strong dependency of computed diffusivities on the system size was observed. Computed diffusivities were found to increase with the number of molecules. We propose a correction for the extrapolation of Maxwell-Stefan diffusion coefficients to the thermodynamic limit, based on the study by Yeh and Hummer ( J. Phys. Chem. B , 2004 , 108 , 15873 - 15879 ). The proposed correction is a function of the viscosity of the system, the size of the simulation box, and the thermodynamic factor, which is a measure for the nonideality of the mixture. Verification is carried out for more than 200 distinct binary Lennard-Jones systems, as well as 9 binary systems of methanol, water, ethanol, acetone, methylamine, and carbon tetrachloride. Significant deviations between finite-size Maxwell-Stefan diffusivities and the corresponding diffusivities at the thermodynamic limit were found for mixtures close to demixing. In these cases, the finite-size correction can be even larger than the simulated (finite-size) Maxwell-Stefan diffusivity. Our results show that considering these finite-size effects is crucial and that the suggested correction allows for reliable computations.
| S-EPMC5943679 | biostudies-literature
Project description:To investigate whether variability in reported renal apparent diffusion coefficient (ADC) values in literature can be explained by the use of different diffusion weightings (b values) and the use of a monoexponential model to calculate ADC.This prospective study was approved by institutional review board and was HIPAA-compliant, and all subjects gave written informed consent. Diffusion-weighted (DW) imaging of the kidneys was performed in three healthy volunteers to generate reference diffusion decay curves. In a literature meta-analysis, the authors resampled the reference curves at the various b values used in 19 published studies of normal kidneys (reported ADC = [2.0-4.1] x 10(-3) mm(2) / sec for cortex and [1.9-5.1] x 10(-3) mm(2) / sec for medulla) and then fitted the resampled signals by monoexponential model to produce "predicted" ADC. Correlation plots were used to compare the predicted ADC values with the published values obtained with the same b values.Significant correlation was found between the reported and predicted ADC values for whole renal parenchyma (R(2) = 0.50, P = .002), cortex (R(2) = 0.87, P = .0002), and medulla (R(2) = 0.61, P = .0129), indicating that most of the variability in reported ADC values arises from limitations of a monoexponential model and use of different b values.The use of a monoexponential function for DW imaging analysis and variably sampled diffusion weighting plays a substantial role in causing the variability in ADC of healthy kidneys. For maximum reliability in renal apparent diffusion coefficient quantification, data for monoexponential analysis should be acquired at a fixed set of b values or a biexponential model should be used. (c) RSNA, 2010.
| S-EPMC2851010 | biostudies-other
Project description:The activity coefficient is largely considered an empirical parameter that was traditionally introduced to correct the non-ideality observed in thermodynamic systems such as osmotic pressure. Here, the activity coefficient of free-solvent is related to physically realistic parameters and a mathematical expression is developed to directly predict the activity coefficients of free-solvent, for aqueous protein solutions up to near-saturation concentrations. The model is based on the free-solvent model, which has previously been shown to provide excellent prediction of the osmotic pressure of concentrated and crowded globular proteins in aqueous solutions up to near-saturation concentrations. Thus, this model uses only the independently determined, physically realizable quantities: mole fraction, solvent accessible surface area, and ion binding, in its prediction. Predictions are presented for the activity coefficients of free-solvent for near-saturated protein solutions containing either bovine serum albumin or hemoglobin. As a verification step, the predictability of the model for the activity coefficient of sucrose solutions was evaluated. The predicted activity coefficients of free-solvent are compared to the calculated activity coefficients of free-solvent based on osmotic pressure data. It is observed that the predicted activity coefficients are increasingly dependent on the solute-solvent parameters as the protein concentration increases to near-saturation concentrations.
| S-EPMC3852980 | biostudies-literature