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At least 109 records · Page 6Linked to original sources
PubMed2002

Modeling the structure of agitoxin in complex with the Shaker K+ channel: a computational approach based on experimental distance restraints extracted from thermodynamic mutant cycles.

Computational methods are used to determine the three-dimensional structure of the Agitoxin (AgTx2)-Shaker complex. In a first stage, a large number of models of the complex are generated using high temperature molecular dynamics, accounting for side chain flexibility with distance restraints deduced from thermodynamic analysis of double mutant cycles. Four plausible binding mode candidates are found using this procedure. In a second stage, the quality and validity of the resulting complexes is assessed by examining the stability of the binding modes during molecular dynamics simulations with explicit water molecules and by calculating the binding free energies of mutant proteins using a continuum solvent representation and comparing with experimental data. The docking protocol and the continuum solvent model are validated using the Barstar-Barnase and the lysozyme-antibody D1.2 complexes, for which there are high-resolution structures as well as double mutant data. This combination of computational methods permits the identification of two possible structural models of AgTx2 in complex with the Shaker K+ channel, additional structural analysis providing further evidence in favor of a single model. In this final complex, the toxin is bound to the extracellular entrance of the channel along the pore axis via a combination of hydrophobic, hydrogen bonding, and electrostatic interactions. The magnitude of the buried solvent accessible area corresponding to the protein-protein contact is on the order of 1000 A with roughly similar contributions from each of the four subunits. Some side chains of the toxin adopt different conformation than in the experimental solution structure, indicating the importance of an induced-fit upon the formation of the complex. In particular, the side chain of Lys-27, a residue highly conserved among scorpion toxins, points deep into the pore with its positively charge amino group positioned at the outer binding site for K+. Specific site-directed mutagenesis experiments are suggested to verify and confirm the structure of the toxin-channel complex.

Animals↗
PubMed2003

Reagent-based and product-based computational approaches in library design.

The design of combinatorial libraries involves the consideration of all synthesizable compounds (the virtual library), followed by the selection of a suitably sized subset for actual synthesis and experimentation. Several approaches to this task can be envisaged, involving either reagent-based or product-based considerations. Reagent-based design considers the properties of the building blocks rather than those of the final products. Although popular with chemists, this approach overlooks the extent of chemical transformations involved in generating products. In effect, several important properties cannot be derived from building blocks alone and require access to product structures. Several studies have demonstrated the superiority of product-based designs in yielding diverse and representative subsets. Although more computationally intensive, the latter approach provides a basis for more sophisticated designs where reagent-based and product based considerations can be combined for a best-of-breed approach.

Computational Biology↗
PubMed1989

Children and computers. Approaching the twenty-first century.

The "effects" that various forms of "computer" use are likely to have on different children's learning, motivation, and social behavior have been a source of heated debate and continuing controversy. In this article, various aspects of this controversy are characterized, and sources of disagreement concerning educational computing are examined. Difficulties in the current state of empirical research in this area are then considered, and recommendations regarding directions for future research are proposed.

Attitude to Computers↗
PubMed2006

Analysis of computational approaches for motif discovery.

Recently, we performed an assessment of 13 popular computational tools for discovery of transcription factor binding sites (M. Tompa, N. Li, et al., "Assessing Computational Tools for the Discovery of Transcription Factor Binding Sites", Nature Biotechnology, Jan. 2005). This paper contains follow-up analysis of the assessment results, and raises and discusses some important issues concerning the state of the art in motif discovery methods: 1. We categorize the objective functions used by existing tools, and design experiments to evaluate whether any of these objective functions is the right one to optimize. 2. We examine various features of the data sets that were used in the assessment, such as sequence length and motif degeneracy, and identify which features make data sets hard for current motif discovery tools. 3. We identify an important feature that has not yet been used by existing tools and propose a new objective function that incorporates this feature.

Journal Article↗
PubMed2006

An imaging-based computational approach to model ventilation distribution and soft-tissue deformation in the ovine lung.

RATIONALE AND OBJECTIVES: A computational modeling framework of soft-tissue mechanics and air flow has been developed toward the aim of linking computed tomography measures of ventilation distribution to subject-specific predictions in imaging-based geometric models of the lung. The aim of this approach is to enable predictions of the effect of perturbations in geometry or functional parameters on imaged function of the lung. MATERIALS AND METHODS: Computational techniques that can deal with anatomic detail and spatially distributed nonlinear material properties are used to model parenchymal soft-tissue mechanics in a physically realistic model of the ovine lung. The lung is modeled as a homogeneous, compressible, nonlinearly elastic body. Using equations for large deformation mechanics, change in geometry of the lung is simulated at static inflation pressures from 25 cm H2O to 0 cm H2O. Multidetector row computed tomography imaging defines the model geometry, the movement of the model lung surface during inflation, and displacement of airway bifurcations for comparison with predicted internal displacements of the model. RESULTS: A novel modeling framework has been formulated that links equations for large deformation of the lung tissue to equations for airway flow and pressure. This preliminary model predicts airway displacements that are in good agreement with imaged displacements (total root mean square [RMS] error < 4 mm from 25 to 0 cm H2O). CONCLUSIONS: State-of-the-art computed tomography imaging is interpreted using a modeling framework to predict ventilation distribution and changes in the geometry of the lung during increments in inflation pressure. Further development will provide a predictive link between subject-specific anatomy and function.

Algorithms↗
PubMed2006

Computational approaches to analysis of DNA microarray data.

OBJECTIVES: To review the current state of the art in computational methods for the analysis of DNA microarray data. METHODS: The review considers methods of microarray data collection, transformation and representation, comparisons and predictions of gene expression from the data, their mechanistic analysis, related systems biology, and the application of clustering techniques. RESULTS: Functional genomics approaches have greatly increased the rate at which data on biological systems is generated, leading to corresponding challenges in analyzing the data through advanced computational techniques. The paper compares and contrasts the application of computational clustering for discovery, comparison, and prediction of gene expression classes, together with their evaluation and relation to mechanistic analyses of biological systems. CONCLUSION: Methods for assaying gene expression levels by DNA microarray experiments produce considerably more data than other techniques, and require a wide variety of computational techniques for identifying patterns of expression that may be biologically significant. These will have to be verified and validated by comparison to results from other methods, integrated with other systems data, and provide the feedback for further experimentation for testing mechanistic or other biological hypotheses.

Computational Biology↗
PubMedDate not supplied

Toward a greater appreciation of noncovalent chemical/DNA interactions: application of biological and computational approaches.

Noncovalent DNA interactions, e.g., DNA intercalation and DNA groove-binding, have not been well studied relative to covalent interactions largely due to the inability of predicting and detecting such events in intact cells. We have adapted an in vitro bleomycin amplification method for DNA intercalation for use in cultured V79 Chinese hamster cells and have validated this approach through the use of a three-dimensional DNA computational docking model that quantifies potential strength of DNA intercalative binding based on electrostatics and hydrogen bonding. For many structural classes of molecules, DNA intercalation is necessary but not sufficient for genotoxicity. The present article reviews our progress to date in predicting and confirming noncovalent binding of drugs and other chemicals and in understanding the mechanistic relationship between intercalation and genotoxicity.

Animals↗
PubMed2006

Modern computational approaches for analysing molecular genetic variation data.

An explosive growth is occurring in the quantity, quality and complexity of molecular variation data that are being collected. Historically, such data have been analysed by using model-based methods. Models are useful for sharpening intuition, for explanation and for prediction: they add to our understanding of how the data were formed, and they can provide quantitative answers to questions of interest. We outline some of these model-based approaches, including the coalescent, and discuss the applicability of the computational methods that are necessary given the highly complex nature of current and future data sets.

Computational Biology↗
PubMed1993

Behaviorally based modeling and computational approaches to neuroscience.

The almost incredible advances that have recently occurred in the power of computers available to scientists in all disciplines have encouraged an explosion of neural network and behavioral models. Some of these have been constrained more by the imagination of the programmer than by rude biological facts. Their relevance for the experimental neuroscientist thus varies from case to case. Some models (e.g. Grillner's model of lamprey swimming movements) are so closely based on known neuroanatomy and neurophysiology that it becomes possible to generate and test precise experimental predictions. Other models (such as MURPHY and NOMAD) use neurobiological principles in their architectures, but do not portray any particular organism. Although it is harder to relate the study of these models of the study of real animals, they fulfill an important explanatory role. They make possible insights into how behavior is controlled by neuronal activity that would be unobtainable in real animals using present methods. Thus, even the excesses of neural modeling have provided a useful impetus to what is undoubtedly a most promising approach to integrating data from the various disciplines concerned with behavior and the mind. The problems have been pointed out by many authors (see citations in our introduction), and a phase of more critical evaluation appears to have begun. We hope that our brief survey of models based on widely different theoretical approaches, but all aimed at explaining behavior, will encourage critical comparisons to be made. As in more mature fields, such as thermodynamics, we can expect that more complete models will force an evaluation of theoretical hypotheses against the entire body of available evidence, rather than just a few pertinent test cases. Such evaluation will make possible a much more rigorous exclusion of invalid or inconsistent theoretical ideas. From such studies, a much smaller, but more robust, set of basic principles can be expected to emerge. From the perspective afforded by our own modeling studies, it appears essential that modeling be informed by a general theory of brain function. In this work, the theory of neuronal group selection provides a useful basis for further work by virtue of its consistency with basic evolutionary and physiological principles and the power of the selection paradigm to shape neural networks in behaviorally adaptive directions.

Animals↗
PubMed1989

A computational approach to the mechanism of self-cleavage of hammerhead RNA.

Extensive minimization and dynamics computational studies of the hammerhead structural domain of the virusoid of lucerne transient streak virus have been carried out. The following observations at the self-cleavage position are derived from the resulting three-dimensional structure: (i) the cytosine base is at the surface and does not interact with another base (it is free to move), and (ii) the ribose-phosphate backbone is forced to take an abrupt turn since it bridges stems I and III, and this turn points the pro-S and pro-R oxygens of the phosphate to the inward side of the hammerhead. These structural features are independent of the hammerhead being open or closed and allow an unencumbered 3'- to 2'-endo conformational change of the ribose with the resultant creation of an unusual stereochemistry that allows a direct in-line self-cleavage reaction. In the closed hammerhead structure, interactions of stems I and II create a vacancy into which the catalytic hydrated Mg(II) may be docked on labile phosphate. This opening is not present if stems I and II are shortened.

Base Sequence↗
PubMed2003

Computational approaches to motor control and their potential role for interpreting motor dysfunction.

PURPOSE OF REVIEW: Computational frameworks, notably internal models and optimal control theory, have led to rapid advances in our understanding of how the brain plans and controls movement. The purpose of this review is to provide an overview of these theoretical ideas, how they have been used to interpret motor control, as well as their potential role for interpreting motor dysfunction. RECENT FINDINGS: There are two general types of internal models, neural processes that mimic the mechanical properties of the limb (and environment). Forward internal models parallel the normal causal flow of the motor periphery and estimate limb motion from motor commands. Inverse internal models perform the reverse process by estimating motor commands from signals related to intended limb motion and/or spatial targets. This framework has led to several important behavioural observations on motor planning, control and learning, and has also been influential for interpreting neural activity in awake, behaving non-human primates. A more recent framework for interpreting motor function is optimal control theory, which recognizes that noise or errors are an inherent feature of the motor system and may influence strategies to plan and control movement. SUMMARY: Internal models and optimal feedback control both provide frameworks for interpreting motor performance, and may be of value for interpreting many motor dysfunctions associated with neurological injuries. Advanced technologies such as robots that have played a key role in these frameworks may be also of considerable value for motor assessment and rehabilitation.

Animals↗
PubMed2004

Quantitative prediction of crystal-nucleation rates for spherical colloids: a computational approach.

This review discusses the recent progress that has been made in the application of computer simulations to study crystal nucleation in colloidal systems. We discuss the concept and the numerical methods that allow for a quantitative prediction of crystal-nucleation rates. The computed nucleation rates are predicted from first principles and can be directly compared with experiments. These techniques have been applied to study crystal nucleation in hard-sphere colloids, polydisperse hard-sphere colloids, weakly charged or slightly soft colloids, and hard-sphere colloids that are confined between two-plane hard walls.

Journal Article↗
PubMed2004

Computational approaches to understand alpha-conotoxin interactions at neuronal nicotinic receptors.

Recent and increasing use of computational tools in the field of nicotinic receptors has led to the publication of several models of ligand-receptor interactions. These models are all based on the crystal structure at 2.7 A resolution of a protein related to the extracellular N-terminus of nicotinic acetylcholine receptors (nAChRs), the acetylcholine binding protein. In the absence of any X-ray or NMR information on nAChRs, this new structure has provided a reliable alternative to study the nAChR structure. We are now able to build homology models of the binding domain of any nAChR subtype and fit in different ligands using docking programs. This strategy has already been performed successfully for the docking of several nAChR agonists and antagonists. This minireview focuses on the interaction of alpha-conotoxins with neuronal nicotinic receptors in light of our new understanding of the receptor structure. Computational tools are expected to reveal the molecular recognition mechanisms that govern the interaction between alpha-conotoxins and neuronal nAChRs at the molecular level. An accurate determination of their binding modes on the neuronal nAChR may allow the rational design of alpha-conotoxin-based ligands with novel nAChR selectivity.

Amino Acid Sequence↗