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PubMed1997

Computational approach for probing the flow through artificial heart devices.

Computational fluid dynamics (CFD) has become an indispensable part of aerospace research and design. The solution procedure for incompressible Navier-Stokes equations can be used for biofluid mechanics research. The computational approach provides detailed knowledge of the flowfield complementary to that obtained by experimental measurements. This paper illustrates the extension of CFD techniques to artificial heart flow simulation. Unsteady incompressible Navier-Stokes equations written in three-dimensional generalized curvilinear coordinates are solved iteratively at each physical time step until the incompressibility condition is satisfied. The solution method is based on the pseudocompressibility approach. It uses an implicit upwind-differencing scheme together with the Gauss-Seidel line-relaxation method. The efficiency and robustness of the time-accurate formulation of the numerical algorithm are tested by computing the flow through model geometries. A channel flow with a moving indentation is computed and validated by experimental measurements and other numerical solutions. In order to handle the geometric complexity and the moving boundary problems, a zonal method and an overlapped grid embedding scheme are employed, respectively. Steady-state solutions for the flow through a tilting-disk heart valve are compared with experimental measurements. Good agreement is obtained. Aided by experimental data, the flow through an entire Penn State artificial heart model is computed.

Algorithms↗
PubMed2003

A new computational approach for electrical analysis of biological tissues.

A new computational approach for electrical analysis especially designed for application in biological tissues is presented. It is based on the modelling of the electrical properties of the medium by means of lumped circuit elements, such as capacitance, conductance and current sources. The cell scale model is suitable for modelling the local anisotropy around cell membranes. It permits to obtain the electric potential, ionic concentrations and current densities around cells in time steps in an iterative process. The tissue scale model utilises volume-averaged values of conductivity and permittivity and models suitably the dispersive characteristic of biological tissues. It permits to obtain potential and current distributions in large volumes of tissue in the time or frequency domain. An example of analysis of skeletal muscle is presented aiming to demonstrate the features of the method.

Animals↗
PubMed2003

Inhibition and substrate recognition--a computational approach applied to HIV protease.

We have developed a computational approach in which an inhibitor's strength is determined from its interaction energy with a limited set of amino acid residues of the inhibited protein. We applied this method to HIV protease. The method uses a consensus structure built from X-ray crystallographic data. All inhibitors are docked into the consensus structure. Given that not every ligand-protein interaction causes inhibition, we implemented a genetic algorithm to determine the relevant set of residues. The algorithm optimizes the q2 between the sum of interaction energies and the observed inhibition constants. The best possible predictive model resulting has a q2 of 0.63. External validation by examining the predictivity for compounds not used in derivation of the model leads to a prediction accuracy between 0.9 and 1.5 log10 unit. Out of 198 residues in the whole protein, the best internally predictive model defines a subset of 20 residues and the best externally predictive model one of 9 residues. These residues are distributed over the subsites of the enzyme. This approach provides insight in which interactions are important for inhibiting HIV protease and it allows for quantitative prediction of inhibitor strength.

Amino Acids↗
PubMed1995

Structure-aided drug design: crystallography and computational approaches.

Ideally, a drug that effectively attacks a specific target will be efficacious with few or no side effects. Historically, drug development has relied on a structure-activity sequential (trial-and-error) approach, testing many compounds and observing their pharmacologic effects. More recently, molecular biologists have investigated a new approach to drug design: starting with a specific target, determining what types of molecules would have a desired effect on that target and then constructing molecules that fit those criteria. Structure-aided drug design is a tool used in this new approach, which involves using crystallographic data and computer processing to describe a molecule precisely--in terms of all binding, Van der Waal's and electrostatic interactions--as a computational entity. The goal of this computational approach is to determine whether a molecule will bind to a target molecule and the character of the ligand interaction.

Computer Simulation↗
PubMed2002

BEST: a novel computational approach for comparing gene expression patterns from early stages of Drosophila melanogaster development.

Embryonic gene expression patterns are an indispensable part of modern developmental biology. Currently, investigators must visually inspect numerous images containing embryonic expression patterns to identify spatially similar patterns for inferring potential genetic interactions. The lack of a computational approach to identify pattern similarities is an impediment to advancement in developmental biology research because of the rapidly increasing amount of available embryonic gene expression data. Therefore, we have developed computational approaches to automate the comparison of gene expression patterns contained in images of early stage Drosophila melanogaster embryos (prior to the beginning of germ-band elongation); similarities and differences in gene expression patterns in these early stages have extensive developmental effects. Here we describe a basic expression search tool (BEST) to retrieve best matching expression patterns for a given query expression pattern and a computational device for gene interaction inference using gene expression pattern images and information on the associated genotypes and probes. Analysis of a prototype collection of Drosophila gene expression pattern images is presented to demonstrate the utility of these methods in identifying biologically meaningful matches and inferring gene interactions by direct image content analysis. In particular, the use of BEST searches for gene expression patterns is akin to that of BLAST searches for finding similar sequences. These computational developmental biology methodologies are likely to make the great wealth of embryonic gene expression pattern data easily accessible and to accelerate the discovery of developmental networks.

Algorithms↗
PubMed2006

An efficient computational approach for the evaluation of substituent constants.

Density functional theory computations at the B3LYP/6-311+G(2d,2p) and BPW91/6-311G(d,p) levels were carried out for a series of 15 monosubstituted benzene derivatives to study dependencies between electronic structure parameters and experimental reactivity constants. An efficient and accurate computational approach for the evaluation of sigma(0) substituent constants for substituted benzene systems is outlined. It is based on the excellent linear correlation between the experimental reactivity constants and the theoretical electrostatic potential values (EPN) at the carbon atoms in the para and meta positions. The results underline the usefulness of the EPN as a local reactivity descriptor. Theoretical computations to assess the influence of water solvent using the SCIPCM method showed that the solvent enhances the overall effect of polar substituents by about 30%. The results obtained indicate also that the relative values of the sigma(0) constants are predominantly determined by intramolecular influences.

Journal Article↗
PubMed2003

Inference of protein function and protein linkages in Mycobacterium tuberculosis based on prokaryotic genome organization: a combined computational approach.

The genome of Mycobacterium tuberculosis was analyzed using recently developed computational approaches to infer protein function and protein linkages. We evaluated and employed a method to infer genes likely to belong to the same operon, as judged by the nucleotide distance between genes in the same genomic orientation, and combined this method with those of the Rosetta Stone, Phylogenetic Profile and conserved Gene Neighbor computational methods for the inference of protein function.

Bacterial Proteins↗
PubMed1988

Computational approaches to the identification of suspect toxic molecules.

We have presented computational approaches that can be used for the relatively rapid identification of suspect toxigens, including carcinogens, in two different classes of compounds: (a) halogenated olefins and epoxides, and (b) substituted dibenzo-p-dioxins. A common element in these approaches is the key role played by the molecular electrostatic potential. It is applied in two different ways, however; it is used to assess the reactivity of a specific site in the case of the epoxides, and for the dibenzo-p-dioxins the focus is on the overall pattern of negative regions above the molecular plane. While we are continuing to develop and refine both types of analysis, especially that related to the dibenzo-p-dioxins, the results obtained so far are encouraging, and indicate that these can be regarded as useful screening techniques for identifying compounds that require further and more exhaustive investigation.

Carcinogens↗
PubMed2004

A computational approach to measuring coherence of gene expression in pathways.

This study uses a computational approach to analyze coherence of expression of genes in pathways. Microarray data were analyzed with respect to coherent gene expression in a group of genes defined as a pathway in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Our hypothesis is that genes in the same pathway are more likely to be coordinately regulated than a randomly selected gene set. A correlation coefficient for each pair of genes in a pathway was estimated based on gene expression in normal or tumor samples, and statistically significant correlation coefficients were identified. The coherence indicator was defined as the ratio of the number of gene pairs in the pathway whose correlation coefficients are significant, divided by the total number of gene pairs in the pathway. We defined all genes that appeared in the KEGG pathways as a reference gene set. Our analysis indicated that the mean coherence indicator of pathways is significantly larger than the mean coherence indicator of random gene sets drawn from the reference gene set. Thus, the result supports our hypothesis. The significance of each individual pathway of n genes was evaluated by comparing its coherence indicator with coherence indicators of 1000 random permutation sets of n genes chosen from the reference gene set. We analyzed three data sets: two Affymetrix microarrays and one cDNA microarray. For each of the three data sets, statistically significant pathways were identified among all KEGG pathways. Seven of 96 pathways had a significant coherence indicator in normal tissue and 14 of 96 pathways had a significant coherence indicator in tumor tissue in all three data sets. The increase in the number of pathways with significant coherence indicators may reflect the fact that tumor cells have a higher rate of metabolism than normal cells. Five pathways involved in oxidative phosphorylation, ATP synthesis, protein synthesis, or RNA synthesis were coherent in both normal and tumor tissue, demonstrating that these are essential genes, a high level of expression of which is required regardless of cell type.

Databases, Genetic↗
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↗
PubMed2005

o-Phenylene halocarbenonitrenes and o-phenylene chlorocarbenocarbene: a combined experimental and computational approach.

[reaction: see text] Computations find that o-phenylene(halo)carbenonitrenes 2-XN, X = F, Cl, Br, have quinoidal singlet biradical ground states such as the parent o-phenylenecarbenonitrene (2-HN). Compared to the parent 2-HN, halogen substitution stabilizes the A'' states relative to the A' ones. Halogen substitution also affects the barrier and exothermicity of the ring-opening reaction (to form unsaturated nitriles 4-XN, X = F, Cl, Br), but it has a smaller effect on the ring-closing reaction (to form benzo(aza)cyclobutadiene 3-XN, X = F, Cl, Br). Attempts to generate and observe the o-phenylene(halo)carbenonitrenes 2-XN, X = F, Cl, Br, using matrix isolation spectroscopy under conditions similar to those of the successful observation of 2-HN failed. Instead, the observed photoproducts were a mixture of 3-XN and 4-XN. In each case, the major product of the mixture appears to be the thermodynamically more stable one. In the case of X = Br, the observed mixture contains an additional component that is postulated to be Z-6-BrN. o-Phenylenechlorocarbenocarbene is also computed to have a quinoidal singlet biradical ground state and relatively stabilized A'' excited states. Attempts to generate the biscarbene under matrix isolation conditions led to the detection of benzochlorocyclobutadiene (3-ClC), small amounts of the ring-open product (dienediyne 4-ClC), and cycloalkyne 5-ClC. Computations suggest that the formation of 5-ClC implies the generation of Z-6-ClC, which is analogous to the formation of Z-6-BrN from 2-BrN.

Journal Article↗
PubMed2006

Sorption kinetics of toluene in humic acid: a computational approach.

Molecular dynamics, a computational technique aiming to describe the time-dependent movement of molecules, has been applied to study the sorption kinetics of volatile organic contaminants in soil organic matter. The molecular dynamics simulation results obtain reasonably accurate estimates of diffusion rates and activation energy of the penetration of a volatile organic compound molecule into a model humic substance. The sorption rate of toluene to humic acid decreases with the density of the humic acid matrix and increases with temperature. All the present results indicate that the sorption of toluene into humic acid is mainly diffusion controlled. Finally, the present studies have shown that molecular dynamics of volatile organic compounds in humic substances yields meaningful results, which help in the understanding of diffusion at the molecular level and which facilitate the problem-solving capability for removing the contaminants from the soils.

Adsorption↗
PubMed2001

An evolutionary computational approach to the phase problem in macromolecular X-ray crystallography.

The ab initio computation of the molecular envelopes of two proteins exclusively from their corresponding diffraction amplitudes demonstrates that an efficient and inherently parallel evolutionary search algorithm can assist in the direct phasing of macromolecules for which almost no a priori structural information is available. The applicability of this evolutionary computational approach is general and should not be limited to the examples described nor to extremes of data resolution, symmetry or structural size.

Algorithms↗
PubMedDate not supplied

A computational approach to medical imaging.

Notwithstanding the progress in medical imaging by means of computer-based techniques, several problems still remain unsolved in this field. In particular, a unified approach for the treatment of biological complexity and variability is lacking. Moreover, perceptive and cognitive aspects of medical vision play an important role in a computational approach to medical imaging and must be carefully considered. The recent developments of Computer Vision and Artificial Intelligence suggest that such a computational approach is feasible. As a consequence, symbolic representations of the clinical information contained in the images as well as adequate processing techniques are necessary. In this way the treatment of uncertainty and the qualitative analysis are made possible. Moreover, due to the intrinsic homogeneity of symbolic representations, the comparison of different image sources, signals and clinical data is attainable. In the paper, the basic principles of Computer Vision are summarized and the need of a specific computational theory for medical vision is emphasized. Afterwards, the main characteristics of integrated systems for computational imaging in medicine, are described. Some examples relative to the imaging of the cardiovascular system are also given. Although the development of artificial vision systems in biomedicine is still an area of research, very promising perspectives are opened by a computational approach.

Artificial Intelligence↗
PubMed2000

Virtual muscle: a computational approach to understanding the effects of muscle properties on motor control.

This paper describes a computational approach to modeling the complex mechanical properties of muscles and tendons under physiological conditions of recruitment and kinematics. It is embodied as a software package for use with Matlab and Simulink that allows the creation of realistic musculotendon elements for use in motor control simulations. The software employs graphic user interfaces (GUI) and dynamic data exchange (DDE) to facilitate building custom muscle model blocks and linking them to kinetic analyses of complete musculoskeletal systems. It is scalable in complexity and accuracy. The model is based on recently published data on muscle and tendon properties measured in feline slow- and fast-twitch muscle, and incorporates a novel approach to simulating recruitment and frequency modulation of different fiber-types in mixed muscles. This software is distributed freely over the Internet at http://ami.usc.edu/mddf/virtualmuscle.

Animals↗
PubMed2001

A computational approach to identify genes for functional RNAs in genomic sequences.

Currently there is no successful computational approach for identification of genes encoding novel functional RNAs (fRNAs) in genomic sequences. We have developed a machine learning approach using neural networks and support vector machines to extract common features among known RNAs for prediction of new RNA genes in the unannotated regions of prokaryotic and archaeal genomes. The Escherichia coli genome was used for development, but we have applied this method to several other bacterial and archaeal genomes. Networks based on nucleotide composition were 80-90% accurate in jackknife testing experiments for bacteria and 90-99% for hyperthermophilic archaea. We also achieved a significant improvement in accuracy by combining these predictions with those obtained using a second set of parameters consisting of known RNA sequence motifs and the calculated free energy of folding. Several known fRNAs not included in the training datasets were identified as well as several hundred predicted novel RNAs. These studies indicate that there are many unidentified RNAs in simple genomes that can be predicted computationally as a precursor to experimental study. Public access to our RNA gene predictions and an interface for user predictions is available via the web.

Computational Biology↗
PubMed2002

GRID/tetrahedral intermediate computational approach to the study of selectivity of penicillin G acylase in amide bond synthesis.

Molecular modelling was used to investigate the catalytic site of penicillin G acylase (PGA) by building up a simple enzyme-ligand model able to describe and predict the enzyme selectivity. The investigation was based on a double computational approach: first, the GRID computational procedure was applied to gain a qualitative description of the chemical features of the PGA active site; second, a classical "transition state approach" was used to simulate the tetrahedral intermediates and to evaluate their energies. GRID calculations employed different probes which gave a complete description of the chemical interactions occurring upon binding of different ligands, thus indicating those structures having good affinity with the active site of the enzyme. Tetrahedral intermediates were constructed on the basis of GRID results and provided both geometrical features and energies of enzyme-substrate interaction. Such energies were compared to experimental kinetic data obtained in the enzymatic acylation of L-phenylglycine methyl ester using various methyl phenylacetate derivatives. The good agreement of computational results with experimental evidence demonstrates the validity of the model as a rapid and flexible tool to describe and predict the enzyme selectivity.

Amino Acid Sequence↗
PubMed2007

Computational approach to nuclear magnetic resonance in 1-Alkyl-3-methylimidazolium ionic liquids.

A quantum-chemical computational approach to accurately predict the nuclear magnetic resonance (NMR) properties of 1-alkyl-3-methylimidazolium ionic liquids has been performed by the gauge-including atomic orbitals method at the B3LYP/6-31++G** level using different simulated ionic liquid environments. The first molecular model chosen to describe the ionic liquid system includes the gas-phase optimized structures of ion pairs and separated ions of a series of imidazolium salts containing methyl, butyl, and octyl substituents and PF6-, BF4-, and Br- anions. In addition, a continuum polarizable model of solvation has been applied to predict the effects of the medium polarity on the molecular properties of 1,3-dimethylimidazolium hexafluorophosphate (MmimPF6). Furthermore, the specific acidic and basic solute-solvent interactions have been simulated by a discrete solvation model based on molecular clusters formed by MmimPF6 species and a discrete number of water molecules. The computational prediction of the NMR spectra allows a consistent interpretation of the dispersed experimental evidence in the literature. The following are main contributions of this work: (a) Theoretical results state the presence of a chemical equilibrium between ion-pair aggregates and solvent-separated counterions of 1-alkyl-3-methylimidazolium salts which is tuned by the solvent environment; thus, strong specific (acidic and basic) and nonspecific (polarity and polarizability) solvent interactions are predicted favoring the dissociated ionic species. (b) The calculated 1H and 13C NMR properties of these ionic liquids are revealed as highly dependent on the nature of solute-solvent interactions. Thus, the chemical shift of the hydrogen atom in position two of the imidazolium ring is deviated to high values by the specific interactions with water molecules, whereas nonspecific interaction with water (as a solvent) affects, in the opposite direction, this 1H NMR parameter. (c) Last, current calculations support the presence of hydrogen bonding between counterions, suggesting the importance of this interaction in the properties of the solvent in the 1-alkyl-3-methylimidazolium ionic liquids.

Journal Article↗