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At least 73 records · Page 4Linked to original sources

PubMed1999

A computational model of the nicotinic acetylcholine binding site.

We have derived a model of the nicotinic acetylcholine binding site. This was accomplished by using three known agonists (acetylcholine, nicotine and epibatidine) as templates around which polypeptide side chains, found to be part of the receptor cavity from published molecular biology studies, are allowed to flow freely in molecular dynamics simulations and mold themselves around these templates. The resulting supramolecular complex should thus be a complement, both in terms of steric effects as well as electronic effects, to the agonists and it should be a good estimation of the true receptor cavity structure. The shapes of those minireceptor cavities equilibrated rapidly on the simulation time scale and their structural congruence is very high, implying that a satisfactory model of the nicotinic acetylcholine binding site has been achieved. The computational methodology was internally tested against two rigid and specific antagonists (dihydro-beta-erytroidine and erysoidine), that are expected to give rise to a somewhat differently shaped binding site compared to that derived from the agonists. Using these antagonists as templates there were structural reorganizations of the initial receptor cavities leading to distinctly different cavities compared to agonists. This indicates that adequate times and temperatures were used in our computational protocols to achieve equilibrium structures for the agonists. Overall, both minireceptor geometries for agonists and antagonists are similar with the exception of one amino acid (ARG209).

Acetylcholine↗

PubMedDate not supplied

Evaluation of an automated wavelet-based system dedicated to the detection of clustered microcalcifications in digital mammograms.

Mammographic screening programs are delivering reductions in breast cancer mortality. However, breast cancer screening will be cost effective and will provide a real profit only when both high sensitivity and specificity levels are reached. To date, due to human or technical factors, a significant number of breast cancers are still missed or misinterpreted on the mammograms. Computer methodologies, developed to assist radiologists, could represent further amelioration by increasing diagnostic accuracy in the screening programs. We have tested a computerized scheme to detect clustered microcalcifications in digital mammograms, employing 360 mammograms that were randomly selected from the mammographic screening program, currently undergoing at the Galicia Community (Spain). After the digitization process, the breast border was initially determined. A wavelet-based algorithm was employed to detect the clusters of microcalcifications. The performance of the automated system over the test set was evaluated employing Free-response Receiver Operating Characteristic (FROC) methodology. The sensitivity achieved was 74% at a false positive detection rate of 1.83. The corresponding area under the Alternative FROC (AFROC) curve was A1=0.667 +/-0.09.

Algorithms↗

PubMed2000

Discovery and modeling of transcriptional regulatory regions.

A complex network of regulatory controls governs the patterns of gene expression. Enabled by the tools of molecular cloning, initial experimental queries into the gene regulatory network elucidated a wide array of transcription factors and their cognate binding sites from hundreds of genes. The recent fusion of genome-scale experimental tools, a more comprehensive gene catalog, and concomitant advances in computational methodology, has extended the range of questions being posed. The potential to further our understanding of the biochemical mechanisms of transcriptional regulation and to accelerate the delineation of regulatory control regions in the human genome is enormous.

Animals↗

PubMed1996

Impact of the mass media on calls to the CDC National AIDS Hotline.

This paper considers new computer methodologies for assessing the impact of different types of public health information. The example used public service announcements (PSAs) and mass media news to predict the volume of attempts to call the CDC National AIDS Hotline from December 1992 through to the end of 1993. The analysis relied solely on data from electronic databases. Newspaper stories and television news transcripts were obtained from the NEXIS electronic database and were scored by machine for AIDS coverage. The PSA database was generated by computer monitoring of advertising distributed by the Centers for Disease Control and Prevention (CDC) and by others. The volume of call attempts was collected automatically by the public branch exchange (PBX) of the Hotline telephone system. The call attempts, the PSAs and the news story data were related to each other using both a standard time series method and the statistical model of ideodynamics. The analysis indicated that the only significant explanatory variable for the call attempts was PSAs produced by the CDC. One possible explanation was that these commercials all included the Hotline telephone number while the other information sources did not.

Acquired Immunodeficiency Syndrome↗

PubMed1996

Synthesis and conformational analysis by 1H NMR and restrained molecular dynamics simulations of the cyclic decapeptide [Ser-Tyr-Ser-Met-Glu-His-Phe-Arg-Trp-Gly].

The design of enzyme mimics with therapeutic and industrial applications has interested both experimental and computational chemists for several decades. Recent advances in the computational methodology of restrained molecular dynamics, used in conjunction with data obtained from two-dimensional 1H NMR spectroscopy, make it a promising method to study peptide and protein structure and function. Several issues, however, need to be addressed in order to assess the validity of this method for its explanatory and predictive value. Among the issues addressed in this study are: the accuracy and generizability of the GROMOS peptide molecular mechanics force field; the effect of inclusion of solvent on the simulations; and the effect of different types of restraining algorithms on the computational results. The decapeptide Ser-Tyr-Ser-Met-Glu-His-Phe-Arg-Trp-Gly, which corresponds to the sequence of ACTH1-10, has been synthesized, cyclized, and studied by two-dimensional 1H NMR spectroscopy. Restrained molecular dynamics (RMD) and time-averaged restrained molecular dynamics (TARMD) simulations were carried out on four different distance-geometry starting structures in order to determine and contrast the behavior of cyclic ACTH1-10 in vacuum and in solution. For the RMD simulations, the structures did not fit the NOE data well, even at high values of the restraining potential. The TARMD simulation method, however, was able to give structures that fit the NOE data at high values of the restraining potential. In both cases, inclusion of explicit solvent molecules in the simulation had little effect on the quality of the fit, although it was found to dampen the motion of the cyclic peptide. For both simulation techniques, the number and size of the NOE violations increased as the restraining potential approached zero. This is due, presumably, to inadequacies in the force field. Additional TARMD vacuum-phase simulations, run with a larger memory length or with a larger sampling size (16 additional distance-geometry structures), yielded no significantly different results. The computed data were then analyzed to help explain the sparse NOE data and poor chymotryptic activity of the cyclic peptide. Cyclic ACTH1-10, which contains the functional moieties of the catalytic triad of chymotrypsin, was evaluated as a potential mimic of chymotrypsin by measurement of the rate of hydrolysis of esters of L- and D-phenylalanine. The poor rate of hydrolysis is attributed to the flexibility of the decapeptide, the motion of the side chains, which result in the absence of long-range NOEs, the small size of the macrocycle relative to that of the substrate, and the inappropriate orientation of the Gly, His, and Ser residues. The results demonstrate the utility of this method in computer-aided molecular design of cyclic peptides and suggest structural modifications for future work based on a larger and more rigid peptide framework.

Adrenocorticotropic Hormone↗

PubMed1996

Comparison of experimental and computational functional group mapping of an RNase A structure: implications for computer-aided drug design.

One relatively new computational approach to the drug discovery process involves calculating functional group maps of a target structure. Experimental functional group mapping techniques have also recently emerged. In this paper, the structure of RNase A with two bound formates (i.e. carboxylate functionalities) is used as a model system to test the computational methodology. Functional group maps of the RNase A structure were calculated using the Multiple Copy Simultaneous Search (MCSS) method and compared with experimentally determined formate and water positions. The calculations indicate that the protonation state of active-site histidines determines the ability of the enzyme to bind formate. The results also suggest an ordered binding mechanism for the two formates. An improved strategy for using the MCSS method to design new candidate ligands is discussed.

Animals↗

PubMedDate not supplied

Population kinetics and conditional assessment of the optimal dosage regimen using the P-PHARM software package.

The adjustment of individual dosage regimen is an adaptive control process based upon an individual response to a pharmacokinetic model. To attain this objective, it is very helpful to know the characteristics of the population to which the subject belongs, in terms of mean parameters and interindividual variability. Usually the available information consists of incomplete and sparse data. For this reason it is essential to employ a computational methodology based on non-linear mixed-effect procedures in order to obtain a population parameter estimate. A Bayesian methodology can then be applied from the population parameters to the specific data for the individual requiring a dosage adjustment (such data includes drug concentration(s) of the active drug, demographic data, etc). The result of the Bayesian calculation supplies the required individual pharmacokinetic parameters. An optimal dosage regimen can be defined on the basis of therapeutical criteria (concentration ranges) as well as practical constraints such as: the size of available unitary drug dosages, feasible drug intake times, penalties associated with expected concentrations falling outside the therapeutic concentration ranges. In this paper we present the methodology and results obtained using the P-Pharm software tool. P-Pharm implements a non-linear mixed-effect population parameter estimation algorithm based on the EM algorithm. This method allows the inclusion of explicit variables into the calculations, it implements an individual Bayesian parameter estimation procedure and also an algorithm for the conditional assessment of the optimal dosage regimen given a list of practical constraints.

Algorithms↗

PubMedDate not supplied

Touch-screen computerized education for patients with brain injuries.

The use of computer technology for patient education has increased in recent years. This article describes a study that measures the attitudes and perceptions of healthcare professionals and laypeople regarding the effectiveness of a multimedia computer, the Brain Injury Resource Center (BIRC), as an educational tool. The study focused on three major themes: (a) usefulness of the information presented, (b) effectiveness of the multimedia touch-screen computer methodology, and (c) the appropriate time for making this resource available. This prospective study, conducted in an acute care medical center, obtained healthcare professionals' evaluations using a written survey and responses from patients with brain injury and their families during interviews. The findings have yielded excellent ratings as to the ease of understanding and usefulness of the BIRC. By using sight, sound, and touch, such a multimedia learning center has the potential to simplify patient and family education.

Attitude of Health Personnel↗

PubMed2001

Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings.

Experimental and computational approaches to estimate solubility and permeability in discovery and development settings are described. In the discovery setting 'the rule of 5' predicts that poor absorption or permeation is more likely when there are more than 5 H-bond donors, 10 H-bond acceptors, the molecular weight (MWT) is greater than 500 and the calculated Log P (CLogP) is greater than 5 (or MlogP > 4.15). Computational methodology for the rule-based Moriguchi Log P (MLogP) calculation is described. Turbidimetric solubility measurement is described and applied to known drugs. High throughput screening (HTS) leads tend to have higher MWT and Log P and lower turbidimetric solubility than leads in the pre-HTS era. In the development setting, solubility calculations focus on exact value prediction and are difficult because of polymorphism. Recent work on linear free energy relationships and Log P approaches are critically reviewed. Useful predictions are possible in closely related analog series when coupled with experimental thermodynamic solubility measurements.

Adsorption↗

PubMed1996

Thermomechanical analysis of shape memory devices.

Shape memory alloys (SMA) are being increasingly used in various industrial applications as actuators, connectors, or damping materials. In the medical field, superelastic devices such as eyeglass frames, stents or guide catheters have come to market in the recent years. The design of SMA devices has usually been based on trial and error, since until recently no general simulation model was available to assist application engineers. The purpose of this article is to describe the computational methodology developed, validated and used for several industrial projects at Ecole Polytechnique of Montréal to simulate the thermomechanical behavior of shape memory materials. This new approach includes three main stages: experimental characterization, construction of a nonlinear material law based on dual kriging interpolation and finally, calculation of the thermomechanical response of SMA devices. For complex geometry, finite element analysis is used, but for simple devices such as springs or electrically activated SMA wires, simplified calculation methods are satisfactory. Validation results recently obtained will also be presented, and examples of industrial applications briefly reviewed.

Algorithms↗

PubMed1998

Combining data sets with different phylogenetic histories.

The possibility that two data sets may have different underlying phylogenetic histories (such as gene trees that deviate from species trees) has become an important argument against combining data in phylogenetic analysis. However, two data sets sampled for a large number of taxa may differ in only part of their histories. This is a realistic scenario and one in which the relative advantages of combined, separate, and consensus analysis become much less clear. I propose a simple methodology for dealing with this situation that involves (1) partitioning the available data to maximize detection of different histories, (2) performing separate analyses of the data sets, and (3) combining the data but considering questionable or unresolved those parts of the combined tree that are strongly contested in the separate analyses (and which therefore may have different histories) until a majority of unlinked data sets support one resolution over another. In support of this methodology, computer simulations suggest that (1) the accuracy of combined analysis for recovering the true species phylogeny may exceed that of either of two separately analyzed data sets under some conditions, particularly when the mismatch between phylogenetic histories is small and the estimates of the underlying histories are imperfect (few characters, high homoplasy, or both) and (2) combined analysis provides a poor estimate of the species tree in areas of the phylogenies with different histories but gives an improved estimate in regions that share the same history. Thus, when there is a localized mismatch between the histories of two data sets, the separate, consensus, and combined analyses may all give unsatisfactory results in certain parts of the phylogeny. Similarly, approaches that allow data combination only after a global test of heterogeneity will suffer from the potential failings of either separate or combined analysis, depending on the outcome of the test. Excision of conflicting taxa is also problematic, in that doing so may obfuscate the position of conflicting taxa within a larger tree, even when their placement is congruent between data sets. Application of the proposed methodology to molecular and morphological data sets for Sceloporus lizards is discussed.

Animals↗

PubMed1999

Modeling regulatory networks with weight matrices.

Systematic gene expression analyses provide comprehensive information about the transcriptional response to different environmental and developmental conditions. With enough gene expression data points, computational biologists may eventually generate predictive computer models of transcription regulation. Such models will require computational methodologies consistent with the behavior of known biological systems that remain tractable. We represent regulatory relationships between genes as linear coefficients or weights, with the "net" regulation influence on a gene's expression being the mathematical summation of the independent regulatory inputs. Test regulatory networks generated with this approach display stable and cyclically stable gene expression levels, consistent with known biological systems. We include variables to model the effect of environmental conditions on transcription regulation and observed various alterations in gene expression patterns in response to environmental input. Finally, we use a derivation of this model system to predict the regulatory network from simulated input/output data sets and find that it accurately predicts all components of the model, even with noisy expression data.

Computational Biology↗

PubMed2002

A genomic regulatory network for development.

Development of the body plan is controlled by large networks of regulatory genes. A gene regulatory network that controls the specification of endoderm and mesoderm in the sea urchin embryo is summarized here. The network was derived from large-scale perturbation analyses, in combination with computational methodologies, genomic data, cis-regulatory analysis, and molecular embryology. The network contains over 40 genes at present, and each node can be directly verified at the DNA sequence level by cis-regulatory analysis. Its architecture reveals specific and general aspects of development, such as how given cells generate their ordained fates in the embryo and why the process moves inexorably forward in developmental time.

Animals↗

PubMed2003

Computer simulation of the chemical catalysis of DNA polymerases: discriminating between alternative nucleotide insertion mechanisms for T7 DNA polymerase.

Understanding the chemical step in the catalytic reaction of DNA polymerases is essential for elucidating the molecular basis of the fidelity of DNA replication. The present work evaluates the free energy surface for the nucleotide transfer reaction of T7 polymerase by free energy perturbation/empirical valence bond (FEP/EVB) calculations. A key aspect of the enzyme simulation is a comparison of enzymatic free energy profiles with the corresponding reference reactions in water using the same computational methodology, thereby enabling a quantitative estimate for the free energy of the nucleotide insertion reaction. The reaction is driven by the FEP/EVB methodology between valence bond structures representing the reactant, pentacovalent intermediate, and the product states. This pathway corresponds to three microscopic chemical steps, deprotonation of the attacking group, a nucleophilic attack on the P(alpha) atom of the dNTP substrate, and departure of the leaving group. Three different mechanisms for the first microscopic step, the generation of the RO(-) nucleophile from the 3'-OH hydroxyl of the primer, are examined: (i) proton transfer to the bulk solvent, (ii) proton transfer to one of the ionic oxygens of the P(alpha) phosphate group, and (iii) proton transfer to the ionized Asp654 residue. The most favorable reaction mechanism in T7 pol is predicted to involve the proton transfer to Asp654. This finding sheds light on the long standing issue of the actual role of conserved aspartates. The structural preorganization that helps to catalyze the reaction is also considered and analyzed. The overall calculated mechanism consists of three subsequent steps with a similar activation free energy of about 12 kcal/mol. The similarity of the activation barriers of the three microscopic chemical steps indicates that the T7 polymerase may select against the incorrect dNTP substrate by raising any of these barriers. The relative height of these barriers comparing right and wrong dNTP substrates should therefore be a primary focus of future computational studies of the fidelity of DNA polymerases.

Aspartic Acid↗

PubMed1996

From electron density and sequence to structure: integrating protein image analysis and threading for structure determination.

This paper presents a computational methodology for integrating techniques from protein image interpretation and protein sequence threading, applied to the problem of structure determination from experimental X-ray crystallographic electron density maps. In the proposed architecture, image interpretation of an electron density map produces candidate structural segments; threading is applied to evaluate these hypothesized segments and thus to constrain the set of possible image interpretations. We present the results of experiments designed to test ability of the threading module to discriminate between correct and incorrect alignments of protein sequences onto structural models derived from protein image interpretation. The long-term goal of this research is to improve our ability to determine protein structures from crystallographic data, and to further our understanding of the underlying relationship between sequence and structure.

Algorithms↗

PubMed2002

In silico approaches to mechanistic and predictive toxicology: an introduction to bioinformatics for toxicologists.

Bioinformatics, or in silico biology, is a rapidly growing field that encompasses the theory and application of computational approaches to model, predict, and explain biological function at the molecular level. This information rich field requires new skills and new understanding of genome-scale studies in order to take advantage of the rapidly increasing amount of sequence, expression, and structure information in public and private databases. Toxicologists are poised to take advantage of the large public databases in an effort to decipher the molecular basis of toxicity. With the advent of high-throughput sequencing and computational methodologies, expressed sequences can be rapidly detected and quantitated in target tissues by database searching. Novel genes can also be isolated in silico, while their function can be predicted and characterized by virtue of sequence homology to other known proteins. Genomic DNA sequence data can be exploited to predict target genes and their modes of regulation, as well as identify susceptible genotypes based on single nucleotide polymorphism data. In addition, highly parallel gene expression profiling technologies will allow toxicologists to mine large databases of gene expression data to discover molecular biomarkers and other diagnostic and prognostic genes or expression profiles. This review serves to introduce to toxicologists the concepts of in silico biology most relevant to mechanistic and predictive toxicology, while highlighting the applicability of in silico methods using select examples.

Cluster Analysis↗

PubMed1994

Non-covalent DNA groove-binding by 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine.

The cooked meat mutagen 2-amino-1-methyl-6-phenyl-imidazo[4,5-b]pyridine (PhIP) is metabolized in vivo to electrophilic intermediates that covalently bind to DNA guanines. Here we address the mechanism of PhIP's non-covalent interaction with DNA by using spectroscopic and computational methodologies. NMR methodologies indicated that upon addition of DNA, PhIP aromatic protons underwent a small, 0.11-0.12 p.p.m. upfield shift. DNA phosphorus resonances of non-covalent PhIP-DNA complexes broadened and slightly shifted upfield, while DNA base imino proton resonances shifted slightly downfield relative to DNA alone. UV and fluorescence spectra of PhIP titrated with DNA showed no detectable shifting and hypochromism of absorbance or fluorescence bands. In the presence of DNA, PhIP fluorescence was efficiently quenched by acrylamide, but not by silver ion. Further, the NMR spectra suggest that PhIP is in fast exchange with the DNA, and is slightly specific for adenine-thymine (A-T) sequences. Finally, structural arguments based on quantum chemistry calculations suggested that PhIP and its metabolites are unlikely to intercalate into DNA. These data collectively indicate that PhIP non-covalently binds in a groove of DNA.

Computer Simulation↗

PubMed2002

MIAX: a new paradigm for modeling biomacromolecular interactions and complex formation in condensed phases.

A new paradigm is proposed for modeling biomacromolecular interactions and complex formation in solution (protein-protein interactions so far in this report) that constitutes the scaffold of the automatic system MIAX (acronym for Macromolecular Interaction Assessment X). It combines in a rational way a series of computational methodologies, the goal being the prediction of the most native-like protein complex that may be formed when two isolated (unbound) protein monomers interact in a liquid environment. The overall strategy consists of first inferring putative precomplex structures by identification of binding sites or epitopes on the proteins surfaces and a simultaneous rigid-body docking process using geometric instances alone. Precomplex configurations are defined here as all those decoys the interfaces of which comply substantially with the inferred binding sites and whose free energy values are lower. Retaining all those precomplex configurations with low energies leads to a reasonable number of decoys for which a flexible treatment is amenable. A novel algorithm is introduced here for automatically inferring binding sites in proteins given their 3-D structure. The procedure combines an unsupervised learning algorithm based on the self-organizing map or Kohonen network with a 2-D Fourier spectral analysis. To model interaction, the potential function proposed here plays a central role in the system and is constituted by empirical terms expressing well-characterized factors influencing biomacromolecular interaction processes, essentially electrostatic, van der Waals, and hydrophobic. Each of these procedures is validated by comparing results with observed instances. Finally, the more demanding process of flexible docking is performed in MIAX embedding the potential function in a simulated annealing optimization procedure. Whereas search of the entire configuration hyperspace is a major factor precluding hitherto systems from efficiently modeling macromolecular interaction modes and complex structures, the paradigm presented here may constitute a step forward in the field because it is shown that a rational treatment of the information available from the 3-D structure of the interacting monomers combined with conveniently selected computational techniques can assist to elude search of regions of low probability in configuration space and indeed lead to a highly efficient system oriented to solve this intriguing and fundamental biologic problem.

Algorithms↗