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PubMed2004

The SWISS-MODEL Repository of annotated three-dimensional protein structure homology models.

The SWISS-MODEL Repository is a database of annotated three-dimensional comparative protein structure models generated by the fully automated homology-modelling pipeline SWISS-MODEL. The Repository currently contains about 300,000 three-dimensional models for sequences from the Swiss-Prot and TrEMBL databases. The content of the Repository is updated on a regular basis incorporating new sequences, taking advantage of new template structures becoming available and reflecting improvements in the underlying modelling algorithms. Each entry consists of one or more three-dimensional protein models, the superposed template structures, the alignments on which the models are based, a summary of the modelling process and a force field based quality assessment. The SWISS-MODEL Repository can be queried via an interactive website at http://swissmodel.expasy. org/repository/. Annotation and cross-linking of the models with other databases, e.g. Swiss-Prot on the ExPASy server, allow for seamless navigation between protein sequence and structure information. The aim of the SWISS-MODEL Repository is to provide access to an up-to-date collection of annotated three-dimensional protein models generated by automated homology modelling, bridging the gap between sequence and structure databases.

Animals↗

PubMedDate not supplied

[Model of the spatial structure of peptide T].

The spatial structure model of peptide T (AIDS reproduction inhibitor, the amino acid sequence of which corresponds to the fragment into the binding site of the virus protein gp120 with T4 receptor) is proposed. Peptide structure modelling has been carried out by the previously developed method based on joint usage of the molecular mechanics algorithms and NMR spectroscopy data. To build the model, two-dimensional nuclear Overhauser effect spectroscopy data for RNase A homologous fragment 22-26 were taken from the literature. The result of the presented work was a set consisting of six types of low-energy structures with different spatial packing of the peptide main chain. All structural types have been shown to be characterized by the lack of strict determination of the side chain conformations of the amino acid residues that can be realized in a few states providing approximately equal (within the given type) stabilization of one main chain form. At the same time, despite the definite differences, all of the selected structures were characterized by the presence of two consecutive reverse polypeptide chain turns at the C-terminal pentapeptide fragment. This site is supposed to be responsible for the peptide binding with T4 receptor and the antiviral effect.

Algorithms↗

PubMed1998

Modelling the secondary structures of slippage-prone hypervariable RNA regions: the example of the tiger beetle 18S rRNA variable region V4.

Variable regions within ribosomal RNAs frequently vary in length as a result of incorporating products of slippage. This makes constructing secondary structure models problematic because base homology is difficult or impossible to establish between species. Here, we model such a region by comparing the results of the MFOLD suboptimal folding algorithm for different species to identify conserved structures. Based on the reconstruction of base change on a phylogenetic tree of the species and comparison against null models of character change, we devise a statistical analysis to assess support of these structures from compensatory and semi-compensatory (i.e. G.C to G.U or A.U to G.U) mutations. As a model system we have used variable region V4 from cicindelid (tiger beetle) small subunit ribosomal RNAs (SSU rRNAs). This consists of a mixture of conserved and highly variable subregions and has been subject to extensive comparative analysis in the past. The model that results is similar to a previously described model of this variable region derived from a different set of species and contains a novel structure in the central, highly variable part. The method we describe may be useful in modelling other RNA regions that are subject to slippage.

Animals↗

PubMed1988

A model for the tertiary structure of the 28 residue DNA-binding motif ('zinc finger') common to many eukaryotic transcriptional regulatory proteins.

Many eukaryotic transcriptional activator proteins, including the Xenopus 5S RNA gene activator protein TFIIIA and the HeLa cell protein Sp1, have an approximately 30 amino acid repeating motif which binds to short, specific DNA sequences. Over 150 of these sequences are now known. Based on the observed distribution of amino acid residues, a series of constraints and predictions can be proposed for the structure of the motif. A compatible three-dimensional structural model has been developed by a combination of interactive model building and refinement by molecular dynamics. The model structure consists of a two-stranded beta-hairpin stabilizing a C-terminal alpha-helix by both zinc ligands and hydrophobic interactions. Four of the residue positions on the helix N-terminus and exposed face are predicted to provide base specific ligands. Further implications of the model for DNA binding are discussed.

Amino Acid Sequence↗

PubMed2006

Mobile computing acceptance factors in the healthcare industry: a structural equation model.

OBJECTIVE: This paper presents a revised technology acceptance model to examine what determines mobile healthcare systems (MHS) acceptance by healthcare professionals. METHOD: Conformation factor analysis was performed to test the reliability and validity of the measurement model. The structural equation modeling technique was used to evaluate the causal model. RESULTS: The results indicated that compatibility, perceived usefulness and perceived ease of use significantly affected healthcare professional behavioral intent. MHS self-efficacy had strong indirect impact on healthcare professional behavioral intent through the mediators of perceived usefulness and perceived ease of use. Yet, the hypotheses for technical support and training effects on the perceived usefulness and perceived ease of use were not supported. CONCLUSION: This paper provides initial insights into factors that are likely to be significant antecedents of planning and implementing mobile healthcare to enhance professionals' MHS acceptance. The proposed model variables explained 70% of the variance in behavioral intention to use MHS; further study is needed to explore extra significant antecedents of new IT/IS acceptance for mobile healthcare. Such as privacy and security issue, system and information quality, limitations of mobile devices; the above may be other interesting factors for implementing mobile healthcare and could be conducted by qualitative research.

Attitude of Health Personnel↗

PubMed1983

Teratogenesis: a statistical structure-activity model.

This structure-activity model of teratogenicity was developed to provide the ability to rank untested compounds by their probability of teratogenicity. The model is based on 430 compounds collected from various sources in the literature and scored from zero to one as to evidence of teratogenicity. A discriminant equation then separates those compounds in the extremes of this distribution. The false positive classification rate based on the compounds in the equation is approximately 8% and the false negative rate approximately 10%. Approximately 22% of the compounds are not classifiable as either teratogens or nonteratogens with this equation.

Models, Biological↗

PubMed2006

Testing effective connectivity changes with structural equation modeling: what does a bad model tell us?

Structural equation modeling (SEM) is a statistical method that can assess changes in effective connectivity across tasks or between groups. In its initial application to neuroimaging data, anatomical connectivity provided the constraints to decompose interregional covariances to estimate effective connections. There have been concerns expressed, however, with the validity of interpreting effective connections for a model that does not adequately fit the data. We sought to address this concern by creating two population networks with different patterns of effective connectivity, extracting three samples sizes (N = 100, 60, 20), and then assessing whether the ability to detect effective connectivity differences depended on absolute model fit. Four scenarios were assessed: (1) elimination of a region showing no task differences; (2) elimination of connections with no task differences; (3) elimination of connections that carried task differences, but could be expressed through alternative indirect routes; (4) elimination of connections that carried task differences, and could not be expressed through indirect routes. We were able to detect task differences in all four cases, despite poor absolute model fit. In scenario 3, total effects captured the overall task differences even though the direct effect was no longer present. In scenario 4, task differences that were included in the model remained, but the missing effect was not expressed. In conclusion, it seems that when independent information (e.g., anatomical connectivity) is used to define the causal structure in SEM, inferences about task- or group-dependent changes are valid regardless of absolute model fit.

Algorithms↗

PubMed1987

Molecular dynamics simulations of cyclosporin A: the crystal structure and dynamic modelling of a structure in apolar solution based on NMR data.

The conformation of the immunosuppressive drug cyclosporin A (CPA), both in apolar solution and in crystalline state, has been studied by computer simulation techniques. Three molecular dynamics (MD) simulations have been performed: one modelling the crystal structure and two modelling the structure in apolar solution, using a restrained MD approach in which data from nuclear magnetic resonance (NMR) and infrared (IR) spectroscopy are taken into account. The simulation of the crystalline state (MDC) concerns a system of 4 unit cells containing 16 cyclosporin A molecules and 22 water molecules, which is simulated using crystalline periodic boundary conditions. The simulations modelling the apolar solvent conformation (MDS) concern one isolated cyclosporin A molecule. In these simulations an extra term in the interatomic potential function is used, which forces the molecule to satisfy a set of 57 atom-atom distance constraints originating from nuclear Overhauser effects (NOEs) obtained from NMR spectroscopy and one distance constraint deduced from IR spectroscopy. From a comparison of the results of the crystal simulation to those of the X-ray experiment in terms of structure, atomic fluctuations, hydrogen bond pattern, etc., it is concluded that the force field that is used yields an adequate representation of crystalline cyclosporin A. Secondly, it is shown that the dynamic modelling technique that is used to obtain a structure in a polar solution from NMR distance information works well. Starting from initial conformations which have a root mean square difference of 0.14 nm both distance restrained MD simulations converge to the same final solution structure. A comparison of the crystal structure of cyclosporin A and the one in apolar solution shows that there are significant differences. The overall difference in atomic positions is 0.09 nm for the C alpha atoms and 0.17 nm for all atoms. In apolar solution, the molecule is slightly more bent and the side chains of 1 MeBmt and 10 MeLeu adopt a different conformation.

Computer Simulation↗

PubMed1994

Formulating clinical research hypotheses as structural equation models: a conceptual overview.

Structural equation modeling is a comprehensive, flexible approach to research design and data analysis. Although in recent years there has been phenomenal growth in the literature on technical aspects of structural equation modeling, relatively little attention has been devoted to conceiving research hypotheses as structural equation models. The aim of this article is to provide a conceptual overview of clinical research hypotheses that invite evaluation as structural equation models. Particular attention is devoted to hypotheses that are not adequately evaluated using traditional statistical models.

Humans↗

PubMed2003

A method of moments technique for fitting interaction effects in structural equation models.

The desire to fit structural equation models containing an interaction term has received much methodological attention in the social science literature. This paper presents a technique for the cross-product structural model that utilizes factor score estimates and results in closed-form moments-type estimators. The technique, which does not require normality for the underlying factors, was originally introduced in a very general form by Wall and Amemiya (2000) for any polynomial structural model. In this paper, the practical implementation of this method, including standard error estimation, is presented specifically for the cross-product model. The procedure is applied to an example from social/behavioural epidemiology where the flexibility of the cross-product model provides a useful description of the underlying theory. A simulation study is also presented comparing the method of moments for the cross-product model with three other procedures.

Humans↗

PubMed1999

Isolation of chloroform-resistant mutants of filamentous phage: localization in models of phage structure.

Interaction of fd or M13 filamentous phage with a chloroform/water interface induces morphological change, contracting the filaments sequentially into shortened rods (I-forms), and then into spheroidal particles (S-forms). To further investigate this phage contraction, 34 and 26 chloroform-resistant isolates of fd and M13, respectively, were selected after chloroform treatment of wild-type phages at pH 8. 2 and 4 degrees C. DNA sequencing of gene VIII of the 34 fd isolates revealed five different mutants: these were D5H, M28L, V31L, I37T, and S50T. All 26 M13 isolates were I37T. These mutants exhibited variable sensitivity to chloroform, but all contracted much more slowly than wild-type phage during treatment at 4 degrees C. They all contracted like wild-type phage at 37 degrees C. Site-directed mutagenesis showed that the indicated single mutations carried the chloroform resistance. In structural models of the phage, the D5H locus is on the outside and the S50T locus is on the inside. The M28L and I37T loci are buried in a mostly hydrophobic region in the middle. Although these four mutants are spread out radially, they are localized in the axial direction into a thin disk in the model. The last mutant locus, V31L, is out of this disk, but this locus is proximal to the M28L and I37T loci and also in contact with the surface via a deep hydrophobic hole or depression. These five mutants, their locations, and their variable affects on contraction suggest that chloroform-induced contraction involves a specific mechanism rather than a generalized solvent-induced denaturation and that the critical structural changes occur in a localized level in the phage. These results add weight to suggestions that the sequential contraction of filaments-->I-forms-->S-forms mimic corresponding steps in phage penetration, and, in the reverse order, for phage assembly.

Bacteriophage M13↗

PubMed2004

Understanding tuberculosis epidemiology using structured statistical models.

Molecular epidemiological studies can provide novel insights into the transmission of infectious diseases such as tuberculosis. Typically, risk factors for transmission are identified using traditional hypothesis-driven statistical methods such as logistic regression. However, limitations become apparent in these approaches as the scope of these studies expand to include additional epidemiological and bacterial genomic data. Here we examine the use of Bayesian models to analyze tuberculosis epidemiology. We begin by exploring the use of Bayesian networks (BNs) to identify the distribution of tuberculosis patient attributes (including demographic and clinical attributes). Using existing algorithms for constructing BNs from observational data, we learned a BN from data about tuberculosis patients collected in San Francisco from 1991 to 1999. We verified that the resulting probabilistic models did in fact capture known statistical relationships. Next, we examine the use of newly introduced methods for representing and automatically constructing probabilistic models in structured domains. We use statistical relational models (SRMs) to model distributions over relational domains. SRMs are ideally suited to richly structured epidemiological data. We use a data-driven method to construct a statistical relational model directly from data stored in a relational database. The resulting model reveals the relationships between variables in the data and describes their distribution. We applied this procedure to the data on tuberculosis patients in San Francisco from 1991 to 1999, their Mycobacterium tuberculosis strains, and data on contact investigations. The resulting statistical relational model corroborated previously reported findings and revealed several novel associations. These models illustrate the potential for this approach to reveal relationships within richly structured data that may not be apparent using conventional statistical approaches. We show that Bayesian methods, in particular statistical relational models, are an important tool for understanding infectious disease epidemiology.

Adult↗

PubMedDate not supplied

Structural equation modeling and rehabilitation research.

Structural equation modeling (SEM) has been used extensively in the social sciences in the recent past to model human behavior. SEM has been less used by other disciplines, including rehabilitation medicine. This article begins by providing an introduction to structural equation modeling through the discussion of the definition and basic concepts behind SEM using a conceptual model relevant to rehabilitation medicine that describes the pathway from health to disability (the Enabling-Disabling model). The next focus is on several potential pitfalls of which the researcher needs to be aware when using SEM. After this discussion, a hypothetical example is presented using structural equation modeling to evaluate the Enabling-Disabling model. The article concludes with a review of the advantages and disadvantages of using SEM for clinical and social science research. Throughout the article, references are provided for a more detailed examination of SEM.

Humans↗

PubMed1988

Haloperidol binding to monoclonal antibodies. Predictions of three-dimensional combining site structure via computer modeling.

The amino acid sequences of five monoclonal antibodies (designated mAbs A-E) which bind to the dopaminergic D-2 antagonist, haloperidol, with a variety of affinities (Kd = 4-810 nM), have been used to build theoretical, three-dimensional, computer models of the variable region combining sites. Physiocochemical interactions which have been previously determined from in vitro binding data have been used to orient the drug molecule within the combining site model. The results indicate that hydrophobic, aromatic, and ionic amino acids are involved in specific interactions with the antagonist molecule. For example, fluorescence quenching data suggests that a tryptophan residue is intimately involved in the binding of haloperidol by mAb A. Examination of the modeled structure reveals five tryptophans within the variable fragment, only one of which (H-50) is within the classical beta-barrel binding pocket and is readily accessible to the antigen. Haloperidol's relatively electron poor fluorophenyl ring system stacks with the electron-rich tryptophan ring system at a distance of 3.3 A and in so doing, places haloperidol's positively charged piperidinyl nitrogen atom within hydrogen bond distance of the negatively charged Glu-95 and Asp-100A residues of the H3 loop (Glu-H-95 and Asp-H-100A). This type of analysis for each antibody provides an interesting profile of changes in amino acid composition and hypervariable loop length which markedly effect binding affinity and specificity for a series of proteins which have similar combining site.

Amino Acid Sequence↗

PubMed1983

[Trial modeling of acinous structures of the rat sub-mandibular gland].

The sub-mandibular glands of rats subjected to unbalanced protein diets for six months were submitted to histomorphometric study in optical light microscopy. Protein deficiency led to slower growth although an hyperprotein diet did not alter acini distribution significantly. The results allowed an acinous structure model related to the diet protein ratio to be tested.

Animals↗

PubMed2005

Using the canonical modelling approach to simplify the simulation of function in functional-structural plant models.

Functional-structural plant models that include detailed mechanistic representation of underlying physiological processes can be expensive to construct and the resulting models can also be extremely complicated. On the other hand, purely empirical models are not able to simulate plant adaptability and response to different conditions. In this paper, we present an intermediate approach to modelling plant function that can simulate plant response without requiring detailed knowledge of underlying physiology. Plant function is modelled using a 'canonical' modelling approach, which uses compartment models with flux functions of a standard mathematical form, while plant structure is modelled using L-systems. Two modelling examples are used to demonstrate that canonical modelling can be used in conjunction with L-systems to create functional-structural plant models where function is represented either in an accurate and descriptive way, or in a more mechanistic and explanatory way. We conclude that canonical modelling provides a useful, flexible and relatively simple approach to modelling plant function at an intermediate level of abstraction.

Computer Simulation↗

PubMed2002

Molecular modelling in structural biology.

Molecular modelling is a powerful methodology for analysing the three dimensional structure of biological macromolecules. There are many ways in which molecular modelling methods have been used to address problems in structural biology. It is not widely appreciated that modelling methods are often an integral component of structure determination by NMR spectroscopy and X-ray crystallography. In this review we consider some of the numerous ways in which modelling can be used to interpret and rationalise experimental data and in constructing hypotheses that can be tested by experiment. Genome sequencing projects are producing a vast wealth of data describing the protein coding regions of the genome under study. However, only a minority of the protein sequences thus identified will have a clear sequence homology to a known protein. In such cases valuable three-dimensional models of the protein coding sequence can be constructed by homology modelling methods. Threading methods, which used specialised schemes to relate protein sequences to a library of known structures, have been shown to be able to identify the likely protein fold even in cases where there is no clear sequence homology. The number of protein sequences that cannot be assigned to a structural class by homology or threading methods, simply because they belong to a previously unidentified protein folding class, will decrease in the future as collaborative efforts in systematic structure determination begin to develop. For this reason, modelling methods are likely to become increasingly useful in the near future. The role of the blind prediction contests, such as the Critical Assessment of techniques for protein Structure Prediction (CASP), will be briefly discussed. Methods for modelling protein-ligand and protein-protein complexes are also described and examples of their applications given.

Databases, Protein↗

PubMed1992

Modeling DNA structures.

For a molecule of biological importance, one expects a strong correlation between the three-dimensional structure and its biological function(s). Molecular simulations allow the prediction of physical properties of macromolecules. Many of these properties are closely related to the molecular structure. Model-building studies may thus supplement structurally low-resolution experimental data with detailed three-dimensional hypothetical atomic models. Such studies may give a consistent integral view of a wealth of experimental data. In most cases, such models will predict the outcome of certain experiments. Their actual results will often either confirm the model, be used for further refinement, or demand a major revision. Empirical force-fields provide a large amount of physicochemical knowledge concerning structural and other physical properties about various classes of molecules. They give reasonable bond distances and angles and prevent short van der Waals contacts. Difficulties arise for the prediction of large-scale structural elements. These are not only determined by short-range interactions, but also result from long-range electrostatic, hydration, and hydrophobic forces. In the case of the ionically driven DNA B-Z transition, the point of transition as a function of ionic strength and size can be correctly predicted (33). More must be done for a better understanding of the hydration forces (6). What type of questions will be reliably answered by a force-field? Relatively safe answers concern the local geometry of the molecules. If a conformation leads to strong distortions of bond distances or angles or to close van der Waals contacts, it can safely be rejected. Optimizing such unfavorable structures energetically may lead to structures showing how to avoid such distortions. More difficult are energetic questions: Which of two conformers is more stable, or what is the free energy of the substrate in the active site (63)? One cannot always be sure that the force-field provides the correct answers. Therefore, one should concentrate on questions that can be checked experimentally. The application of such concepts to model curved DNA (19, 60) and the DNA four-way junction (61) provides promising results. To explore the knowledge contained in the force-fields, several methods have been proposed. Taking advantage of structural symmetries may improve critically the convergence, while refining the target molecule or its building blocks. A numerically stable derivative for the torsion potential has been proposed. The optimization method of conjugated gradients (see Section II,B) is a powerful tool to find the way downhill toward a local minimum. To surmount barriers and escape local minima requires nonlocal optimization procedures.(ABSTRACT TRUNCATED AT 400 WORDS)

DNA↗