SEARCH · PubMed Health

Results for “Models, Structural”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9Linked to original sources

PubMed1999

Genetically structured modeling of protein production in filamentous fungi.

A general framework for a genetically structured model is presented. The framework allows description of the interactions in a system of regulatory and structural genes. The model assumes equilibrium kinetics for the binding of regulatory proteins to the promoter regions of the genes and includes the possible activation of proteins following their synthesis. The model is evaluated by simulating the alcA-expression (alcohol dehydrogenase I) in Aspergillus nidulans which is an inducible system subject to glucose repression. The intracellular enzyme levels in strains with different regulatory mutations are simulated during various growth conditions. The model gives a good description of the experimental data with changes in only a few parameter values which have a mechanistic interpretation.

Alcohol Dehydrogenase↗

PubMed2001

The X-ray structure of Aspergillus aculeatus polygalacturonase and a modeled structure of the polygalacturonase-octagalacturonate complex.

Polygalacturonases hydrolyze the alpha-(1-4) glycosidic bonds of de-esterified pectate in the smooth region of the plant cell wall. Crystal structures of polygalacturonase from Aspergillus aculeatus were determined at pH 4.5 and 8.5 both to 2.0 A resolution. A. aculeatus polygalacturonase is a glycoprotein with one N and ten O-glycosylation sites and folds into a right-handed parallel beta-helix. The structures of the three independent molecules are essentially the same, showing no dependency on pH or crystal packing, and are very similar to that of Aspergillus niger polygalacturonase. However, the structures of the long T1 loop containing a catalytic tyrosine residue are significantly different in the two proteins. A three-dimensional model showing the substrate binding mode for a family 28 hydrolase was obtained by a combined approach of flexible docking, molecular dynamics simulations, and energy minimization. The octagalacturonate substrate was modeled as an unbent irregular helix with the -1 ring in a half-chair ((4)H(3)) form that approaches the transition state conformation. A comparative modeling of the three polygalacturonases with known structure shows that six subsites ranging from -4 to +2 are clearly defined but subsites -5 and +3 may or may not be shaped depending on the nearby amino acid residues. Both distal subsites are mostly exposed to the solvent region and have weak binding affinity even if they exist. The complex model provides a clear explanation for the functions, either in catalysis or in substrate binding, of all conserved amino acid residues in the polygalacturonase family of proteins. Modeling suggests that the role of the conserved Asn157 and Tyr270, which had previously been unidentified, may be in transition state stabilization. In A. niger polygalacturonase, the long T1 loop may have to undergo conformational change upon binding of the substrate to bring the tyrosine residue close to subsite -1.

Amino Acid Sequence↗

PubMed1991

A three-dimensional motion model of loads on the lumbar spine: I. Model structure.

Traditionally most biomechanical models that are used to estimate the loading experienced by the spine during work focus on static, two-dimensional representations of the work. However, most work tasks impose loads on the lumbar spine under dynamic, three-dimensional conditions. The objective of this study was to describe the structure and logic of a model that is capable of producing estimates of spine loading under three-dimensional motion conditions. This model is intended for use primarily under laboratory conditions. The model was designed initially for workplace simulation in which the trunk is moving under symmetric and asymmetric constant velocity lifting conditions. Future embellishments may enable the model to be used under free dynamic conditions. The model predicts lumbar spine compression, shear, and torsional forces as well as trunk torque production continuously throughout the exertion. This information may be compared with spine tolerance limits so that the risk of causing a vertebral end-plate microfracture by workplace requirements could be determined.

Biomechanical Phenomena↗

PubMed1992

Structural models for the metal centers in the nitrogenase molybdenum-iron protein.

Structural models for the nitrogenase FeMo-cofactor and P-clusters are proposed based on crystallographic analysis of the nitrogenase molybdenum-iron (MoFe)-protein from Azotobacter vinelandii at 2.7 angstrom resolution. Each center consists of two bridged clusters; the FeMo-cofactor has 4Fe:3S and 1Mo:3Fe:3S clusters bridged by three non-protein ligands, and the P-clusters contain two 4Fe:4S clusters bridged by two cysteine thiol ligands. Six of the seven Fe sites in the FeMo-cofactor appear to have trigonal coordination geometry, including one ligand provided by a bridging group. The remaining Fe site has tetrahedral geometry and is liganded to the side chain of Cys alpha 275. The Mo site exhibits approximate octahedral coordination geometry and is liganded by three sulfurs in the cofactor, two oxygens from homocitrate, and the imidazole side chain of His alpha 442. The P-clusters are liganded by six cysteine thiol groups, two which bridge the two clusters, alpha 88 and beta 95, and four which singly coordinate the remaining Fe sites, alpha 62, alpha 154, beta 70, and beta 153. The side chain of Ser beta 188 may also coordinate one iron. The polypeptide folds of the homologous alpha and beta subunits surrounding the P-clusters are approximately related by a twofold rotation that may be utilized in the binding interactions between the MoFe-protein and the nitrogenase Fe-protein. Neither the FeMo-cofactor nor the P-clusters are exposed to the surface, suggesting that substrate entry, electron transfer, and product release must involve a carefully regulated sequence of interactions between the MoFe-protein and Fe-protein of nitrogenase.

Azotobacter vinelandii↗

PubMed2000

Marginal structural models and causal inference in epidemiology.

In observational studies with exposures or treatments that vary over time, standard approaches for adjustment of confounding are biased when there exist time-dependent confounders that are also affected by previous treatment. This paper introduces marginal structural models, a new class of causal models that allow for improved adjustment of confounding in those situations. The parameters of a marginal structural model can be consistently estimated using a new class of estimators, the inverse-probability-of-treatment weighted estimators.

Anti-HIV Agents↗

PubMed2000

Influence of parasitized adult reproduction on host-parasitoid dynamics: an age-structured model.

In this work, we develop an age-structured model (based on delay-differential equations) to investigate the dynamics of host-parasitoid systems in which adults are the target of parasitism. The rare previous work dealing with such interactions assumes that hosts are functionally dead as soon as they are attacked. We relax this assumption and show that low reproduction rates of parasitized hosts can promote stability at the expense of cyclic behavior (either long term or generation cycles). Higher reproduction rates make the regulation of the host population by parasitoids impossible. As it is the case in models in which adults are subjected to attacks but do not reproduce, our model generates generation cycles for a larger set of parameter values than in models in which juveniles are attacked.

Aging↗

PubMed1993

The use of causal indicators in covariance structure models: some practical issues.

In conventional representations of covariance structure models, indicators are defined as linear functions of latent variables, plus error. In an alternative representation, constructs can be defined as linear functions of their indicators, called causal indicators, plus an error term. Such constructs are not latent variables but composite variables, and they have no indicators in the conventional sense. The presence of composite variables in a model can, in some situations, result in problems with identification of model parameters. Also, the use of causal indicators can produce models that imply zero correlation among many measured variables, a problem resolved only by the inclusion of a potentially large number of additional parameters. These phenomena are demonstrated with an example, and general principles underlying them are discussed. Remedies are described so as to allow for the evaluation of models that contain causal indicators.

Analysis of Variance↗

PubMed1982

Sequences of three molluscan 5 S ribosomal RNAs confirm the validity of a dynamic secondary structure model.

The collection of known 5 S rRNA primary structures is enriched with the sequences from three mollusca, the snails Helix pomatia and Arion rufus, and the mussel Mytilus edulis. The three sequences can be fitted in a five-helix secondary structure model previously shown (De Wachter et al. (1982) Biochimie 64, 311-329) to apply to all 5 S RNAs regardless of their origin. One of the helices in this model can undergo a bulge-internal loop transition. Within the metazoan kingdom, the dimensions of each helix and loop are rigidly conserved, except for one helix which can comprise either 6 or 7 base pairs.

Animals↗

PubMed1999

A physiological model for tert-amyl methyl ether and tert-amyl alcohol: hypothesis testing of model structures.

The oxygenate tert-amyl methyl ether (TAME) is a gasoline fuel additive used to reduce carbon monoxide in automobile emissions. To evaluate the relative health risk of TAME as a gasoline additive, information is needed on its pharmacokinetics and toxicity. The objective of this study was to use a physiologically-based pharmacokinetic (PBPK) model to describe the disposition of TAME and its major metabolite, tert-amyl alcohol (TAA), in male Fischer-344 rats. The model compartments for TAME and TAA were flow-limited. The TAME physiological model had 6 compartments: lung, liver, rapidly perfused tissues, slowly perfused tissues, fat, and kidney. The TAA model had 3 compartments: lung, liver, and total-body water. The 2 models were linked through metabolism of TAME to TAA in the liver. Model simulations were compared with data on blood concentrations of TAME and TAA taken from male Fischer-344 rats during and after a 6-hour inhalation exposure to 2500, 500, or 100 ppm TAME. The PBPK model predicted TAME pharmacokinetics when 2 saturable pathways for TAME oxidation were included. The TAA model, which included pathways for oxidation and glucuronide conjugation of TAA, underpredicted the experimental data collected at later times postexposure. To account for biological processes occurring during this time, three hypotheses were developed: nonspecific binding of TAA, diffusion-limited transport of TAA, and enterohepatic circulation of TAA glucuronide. These hypotheses were tested using three different model structures. Visual inspection and statistical evaluation involving maximum likelihood techniques indicated that the model incorporating nonspecific binding of TAA provided the best fit to the data. A correct model structure, based upon experimental data, statistical analyses, and biological interpretation, will allow a more accurate extrapolation to humans and, consequently, a greater understanding of human risk from exposure to TAME.

Administration, Inhalation↗

PubMed2001

A tertiary structure model of the internal ribosome entry site (IRES) for methionine-independent initiation of translation.

Cricket paralysis-like viruses have a dicistronic positive-strand RNA genome. These viruses produce capsid proteins through internal ribosome entry site (IRES)-mediated translation. The IRES element of one of these viruses, Plautia stall intestine virus (PSIV), forms a pseudoknot immediately upstream from the capsid coding sequence, and initiates translation from other than methionine. Previously, we estimated that the IRES element of PSIV consists of seven stem-loops using the program MFOLD; however, experimental evidence of the predicted structures was not shown, except for stem-loop VI, which was responsible for formation of the pseudoknot. To determine the whole structure of the PSIV-IRES element, we introduced compensatory mutations into the upstream MFOLD-predicted helical segments. Mutation analysis showed that stem-loop V exists as predicted, but stem-loop IV is shorter than predicted. The structure of stem-loop III is different from predicted, and stem-loops I and II are not necessary for IRES activity. In addition, we identified two new pseudoknots in the IRES element of PSIV. The complementary sequence segments that are responsible for formation of the two pseudoknots are also observed in cricket paralysis virus (CrPV) and CrPV-like viruses such as Drosophila C virus (DCV), Rhopalosiphum padi virus (RhPV), himetobi P virus (HiPV), Triatoma virus (TrV), and black queen-cell virus (BQCV), although each sequence is distinct in each virus. Considering the three pseudoknots, we constructed a tertiary structure model of the PSIV-IRES element. This structural model is applicable to other CrPV-like viruses, indicating that other CrPV-like viruses can also initiate translation from other than methionine.

Base Pairing↗

PubMed2000

A structural model of the orthorhombic Ga7Mn5 derived from its HREM image

The base-centered orthorhombic approximant Ga7Mn5 (a = 4.547(6) nm, b = 1.256(9) nm, c = 1.482(1) nm) consisting of flattened hexagon and concave octagon (called "crown" in this paper) subunits shown by high-resolution electron microscopy (HREM) was found to coexist with the Ga-Mn decagonal quasicrystal in the Ga58Mn42 alloy. The atomic sites in the flattened hexagon subunit have been deduced recently from a structural study of the orthorhombic Ga-Mn (1/1,1/1) approximant that consists only of the hexagon subunits. Similarly, the atomic sites in the crown subunit have been deduced from another orthorhombic Ga-Mn (2/1,1/1) approximant consisting only of the crown subunits. A structural model of the orthorhombic Ga7Mn5 can thus be constructed from these structural subunits. There are 332 Ga atoms and 232 Mn atoms in a unit cell, with a composition of Mn41.2Ga58.8, satisfying the symmetry of the space group Bmm2. The simulated electron diffraction patterns, [010] HREM images, and X-ray powder diffraction pattern based on this structural model agrees mainly with the experimental observations.

Journal Article↗

PubMed1999

A simulation study of the effects of assignment of prior identity-by-descent probabilities to unselected sib pairs, in covariance-structure modeling of a quantitative-trait locus.

Sib pair-selection strategies, designed to identify the most informative sib pairs in order to detect a quantitative-trait locus (QTL), give rise to a missing-data problem in genetic covariance-structure modeling of QTL effects. After selection, phenotypic data are available for all sibs, but marker data-and, consequently, the identity-by-descent (IBD) probabilities-are available only in selected sib pairs. One possible solution to this missing-data problem is to assign prior IBD probabilities (i.e., expected values) to the unselected sib pairs. The effect of this assignment in genetic covariance-structure modeling is investigated in the present paper. Two maximum-likelihood approaches to estimation are considered, the pi-hat approach and the IBD-mixture approach. In the simulations, sample size, selection criteria, QTL-increaser allele frequency, and gene action are manipulated. The results indicate that the assignment of prior IBD probabilities results in serious estimation bias in the pi-hat approach. Bias is also present in the IBD-mixture approach, although here the bias is generally much smaller. The null distribution of the log-likelihood ratio (i.e., in absence of any QTL effect) does not follow the expected null distribution in the pi-hat approach after selection. In the IBD-mixture approach, the null distribution does agree with expectation.

Alleles↗

PubMed1997

Advances in comparative protein-structure modelling.

Comparative modelling of protein 3D structure can now be applied with reasonable accuracy to ten times more protein sequences than the number of experimentally determined protein structures. A protein sequence that has at least 40% identity to a known structure can be modelled automatically with an accuracy approaching that of a low resolution X-ray structure or a medium resolution NMR structure. Currently, the errors in comparative models include mistakes in the packing of sidechains, in the conformation and shifts of the core segments and loops, and, most importantly, in an incorrect alignment of the modelled sequence with related known structures. Nevertheless, the number of applications in which comparative modelling has been proven to be useful has grown rapidly.

Crystallography, X-Ray↗

PubMed1980

Bio-structural model of the human eye.

As part of a bio-engineering approach to study myopia, a structural model of the eye is proposed. The model is based on structural laws as employed by civil engineers, and on mechanical properties of the sclera and vitreous previously analyzed by the authors. The described structural behavior relates many loose clinical observations and indicates that progressive myopia should be considered a mechanical problem due to an abnormal vitreous pressure rather than an optics problem. From this bio-engineering approach, vitrectomy is suggested as the appropriate solution.

Biomechanical Phenomena↗

PubMed2002

Evolution and physics in comparative protein structure modeling.

From a physical perspective, the native structure of a protein is a consequence of physical forces acting on the protein and solvent atoms during the folding process. From a biological perspective, the native structure of proteins is a result of evolution over millions of years. Correspondingly, there are two types of protein structure prediction methods, de novo prediction and comparative modeling. We review comparative protein structure modeling and discuss the incorporation of physical considerations into the modeling process. A good starting point for achieving this aim is provided by comparative modeling by satisfaction of spatial restraints. Incorporation of physical considerations is illustrated by an inclusion of solvation effects into the modeling of loops.

Biophysical Phenomena↗

PubMed1990

Nucleotide sequence of Citrus limon 26S rRNA gene and secondary structure model of its RNA.

The complete nucleotide sequence of Citrus limon 26S rDNA has been determined. The sequence has been aligned with large ribosomal RNA (L-rRNA) sequences of Escherichia coli, Saccharomyces cerevisiae and Oryza sativa. Nine extensive expansion segments in dicot 26S rRNA relative to E. coli 23S rRNA have been identified and compared with analogous segments of monocot, yeast, amphibian and human L-rRNAs. A secondary structure model for lemon 26S rRNA has been derived based on the refined model of E. coli 23S rRNA. It has been compared with other eukaryotic L-rRNAs models in terms of location of functionally important regions. Origin and evolution of L-rRNA expansion segments are discussed.

Base Sequence↗

PubMed1993

Measurement error in dietary assessment: an investigation using covariance structure models. Part II.

In Part I we presented a covariance structure model for analysing measurement error in the assessment of nitrogen intake. In this paper we include data on urine nitrogen excretion which allows a critical assessment of the model proposed. Inclusion of urine nitrogen data produces more pessimistic estimates of the quality of dietary intake measurements and shows that previous assumptions about independence of measurement error were wrong. This underscores the need for well founded assumptions in the analysis of measurement error.

Bayes Theorem↗

PubMed1982

The sequence of the 5.8 S ribosomal RNA of the crustacean Artemia salina. With a proposal for a general secondary structure model for 5.8 S ribosomal RNA.

We report the primary structure of 5.8 S rRNA from the crustacean Artemia salina. The preparation shows length heterogeneity at the 5'-terminus, but consists of uninterrupted RNA chains, in contrast to some insect 5.8 S rRNAs, which consist of two chains of unequal length separated in the gene by a short spacer. The sequence was aligned with those of 11 other 5.8 S rRNAs and a general secondary structure model derived. It has four helical regions in common with the model of Nazar et al. (J. Biol. Chem. 250, 8591-8597 (1975)), but for a fifth helix a different base pairing scheme was found preferable, and the terminal sequences are presumed to bind to 28 S rRNA instead of binding to each other. In the case of yeast, where both the 5.8 S and 26 S rRNA sequences are known, the existence of five helices in 5.8 S rRNA is shown to be compatible with a 5.8 S - 26 S rRNA interaction model.

Animals↗