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At least 55 records · Page 3Linked to original sources
PubMed2005

A comparative study of various computational approaches in calculating the structure of pyridoxal 5'-phosphate (PLP)-dependent beta-lyase protein. The importance of protein environment.

Various computational approaches, using molecular mechanics (Amber), semiempirical (AM1), density functional (B3LYP), and various ONIOM methods, have been comparatively investigated for the structure of Escherichia coli NifS CsdB protein. The structure of the entire monomer containing 407 amino acid residues and 579 surrounding water molecules has been optimized. The full geometry optimization in the "active site-only" approach (including only active site atoms) has been found to give the largest root-mean-square (RMS) deviation from the X-ray structure; a much better agreement has been achieved by keeping the atoms leading to the backbones of some amino acids frozen in their positions in the X-ray structure. The best agreement has been attained by including the surrounding protein in the calculations using the two-layer ONIOM (B3LYP:Amber) approach. The results presented in this study conclusively demonstrate the importance of the protein/active-site interaction on the active-site structure of the enzyme. The present theoretical study represents the largest system studied at the ONIOM level to date, containing 7992 atoms, including 84 atoms in the QM region and rest in the MM region.

Binding Sites↗
PubMed2005

Computational approaches to modeling drug transporters.

Computational modeling has advanced our understanding of drug absorption, tissue distribution, excretion and toxicity profiles by providing both direct and indirect knowledge of drug-transporter interactions that would otherwise be unavailable using experimental methods. Currently, two complementary approaches are available in modeling transporters: substrate-based and transporter-based methods. The transporter-based approach directly predicts the transporter's three-dimensional structure to assist in understanding the drug transport process, whereas substrate-based models infer such information by studying a group of substrates or inhibitors with measured activities. In this review, the available strategies in both transporter-based and substrate-based approaches are explained and illustrated with applications and case studies. With increasing computational power and continuously improving modeling algorithms, computational techniques can assist in further understanding transporter-substrate interactions as well as, the optimization of transporter-directed drug design.

Algorithms↗
PubMed1996

A computational approach to prefrontal cortex, cognitive control and schizophrenia: recent developments and current challenges.

In this chapter we consider the mechanisms involved in cognitive control-from both a computational and a neurobiological perspective- and how these might be impaired in schizophrenia. By 'control', we mean the ability of the cognitive system to flexibly adapt its behaviour to the demands of particular tasks, favouring the processing of task-relevant information over other sources of competing information, and mediating task-relevant behaviour over habitual, or otherwise prepotent responses. There is a large body of evidence to suggest that the prefrontal cortex (PFC) plays a critical role in cognitive control. In previous work, we have used a computational framework to understand and develop explicit models of this function of PFC, and its impairment in schizophrenia. This work has lead to the hypothesis that PFC houses a mechanism for representing and maintaining context information. We have demonstrated that this mechanism can account for the behavioural inhibition and active memory functions commonly ascribed to PFC, and for human performance in simple attention, language and memory tasks that draw upon these functions for cognitive control. Furthermore, we have used our models to simulate detailed patterns of cognitive deficit observed in schizophrenia, an illness associated with marked disturbances in cognitive control, and well established deficits of PFC. Here, we review results of recent empirical studies that test predictions made by our models regarding schizophrenic performance in tasks designed specifically to probe the processing of context. These results showed selective schizophrenic deficits in tasks conditions that placed the greatest demands on memory and inhibition, both of which we have argued rely on the processing of context. Furthermore, we observed predicted patterns of deterioration in first episode vs multi-episode patients. We also discuss recent developments in our computational work, that have led to refinements of the models that allow us to simulate more detailed aspects of task performance, such as reaction time data and manipulations of task parameters such as interstimulus delay. These refined models make several provocative new predictions, including conditions in which schizophrenics and control subjects are expected to show similar reaction time performance, and we provide preliminary data in support of these predictions. These successes notwithstanding, our theory of PFC function and its impairment in schizophrenia is still in an early stage of development. We conclude by presenting some of the challenges to the theory in its current form, and new directions that we have begun to take to meet these challenges. In particular, we focus on refinements concerning the mechanisms underlying active maintenance of representations within PFC, and the characteristics of these representations that allow them to support the flexibility of cognitive control exhibited by normal human behaviour. Taken in toto, we believe that this work illustrates the value of a computational approach for understanding the mechanisms responsible for cognitive control, at both the neural and psychological levels, and the specific manner in which they break down in schizophrenia.

Cognition↗
PubMed2006

Computational approaches to the prediction of blood-brain barrier permeability: A comparative analysis of central nervous system drugs versus secretase inhibitors for Alzheimer's disease.

This review summarizes progress made in the development of fully computational approaches to the prediction of blood-brain barrier (BBB) permeability of small molecules, with a focus on rapid computational methods suitable for the analysis of large compound sets and virtual screening. A comparative analysis using the recently developed Advanced Chemistry Development (ACD/Labs) Inc BBB permeability algorithm for the calculation of logBB values for known Alzheimer's disease medicines, selected central nervous system drugs and new secretase inhibitors for Alzheimer's disease, is presented. The trends in logBB values and the associated physiochemical properties of these agents as they relate to the potential for BBB permeability are also discussed.

Alzheimer Disease↗
PubMed2004

Insights into amyloid structural formation and assembly through computational approaches.

Amyloids are long, insoluble ordered fibers. Due to their insolubility, to date the determination of an amyloid structure with an atomic scale resolution has proven to be a difficult task. Under such circumstances, computational approaches are a preferred option, providing the means to build likely models, test their stabilities and figure out the chemistry of their prevailing interactions. Computational models can be validated by targeted experiments, such as introducing mutations and testing for amyloid formation. Computations further provide vehicles for the comprehension of the mechanisms of amyloid seed formation and oligomer toxicity. Nevertheless, computations face an immense hurdle, the outcome of the time scales involved in amyloid formation and the immense sizes of the systems. In an attempt to overcome these, we adopt a strategy that encompasses (1) bioinformatics studies of native proteins containing beta-sheet structures; (2) simulations of shorter peptides; and finally (3) construction of potential oligomeric models and tests of their stabilities. The results are correlated with experimental data where available. Here, we describe the computational methods in simple terms and present an overview of the results. The systems derive from amyloidogenic, disease-related proteins, including gelsolin, beta2-microglobulin, and peptides derived from the prion, Alzheimer's Abeta, IAPP and human calcitonin. Ultimately, obtaining molecular structures should facilitate efforts to therapy and drug design.

Amyloid↗
PubMed2005

A computational approach for identifying pathogenicity islands in prokaryotic genomes.

BACKGROUND: Pathogenicity islands (PAIs), distinct genomic segments of pathogens encoding virulence factors, represent a subgroup of genomic islands (GIs) that have been acquired by horizontal gene transfer event. Up to now, computational approaches for identifying PAIs have been focused on the detection of genomic regions which only differ from the rest of the genome in their base composition and codon usage. These approaches often lead to the identification of genomic islands, rather than PAIs. RESULTS: We present a computational method for detecting potential PAIs in complete prokaryotic genomes by combining sequence similarities and abnormalities in genomic composition. We first collected 207 GenBank accessions containing either part or all of the reported PAI loci. In sequenced genomes, strips of PAI-homologs were defined based on the proximity of the homologs of genes in the same PAI accession. An algorithm reminiscent of sequence-assembly procedure was then devised to merge overlapping or adjacent genomic strips into a large genomic region. Among the defined genomic regions, PAI-like regions were identified by the presence of homolog(s) of virulence genes. Also, GIs were postulated by calculating G+C content anomalies and codon usage bias. Of 148 prokaryotic genomes examined, 23 pathogenic and 6 non-pathogenic bacteria contained 77 candidate PAIs that partly or entirely overlap GIs. CONCLUSION: Supporting the validity of our method, included in the list of candidate PAIs were thirty four PAIs previously identified from genome sequencing papers. Furthermore, in some instances, our method was able to detect entire PAIs for those only partial sequences are available. Our method was proven to be an efficient method for demarcating the potential PAIs in our study. Also, the function(s) and origin(s) of a candidate PAI can be inferred by investigating the PAI queries comprising it. Identification and analysis of potential PAIs in prokaryotic genomes will broaden our knowledge on the structure and properties of PAIs and the evolution of bacterial pathogenesis.

Bacteria↗
PubMed2006

Antifungal and antimycobacterial activity of new imidazole and triazole derivatives. A combined experimental and computational approach.

OBJECTIVES: To synthesize new antimycobacterial and antifungal drugs that act by binding to sterol 14alpha-demethylase (14DM) and to characterize the drug-target protein interactions using computer-based molecular simulations. METHODS: Different series of imidazole and triazole derivatives having an azomethine linkage to pyridine 2-carboxamidrazone were designed and synthesized. Molecular dynamic simulations of the sterol 14DM (a mixed-function oxidase involved in sterol synthesis in eukaryotic and prokaryotic organisms) complexed with new azole derivatives have been performed to both qualify and quantify the protein-ligand interactions. MICs of the compounds were evaluated by reference assay and by the recently developed Microdilution Resazurin Assay (MRA). RESULTS: Halogenated derivatives showed good activity, with an MIC90 of 1 mg/L against 33 Candida spp. clinical strains; most compounds also had inhibitory activity against Mycobacterium tuberculosis reference and clinical strains, with MICs in the range 4-64 mg/L. Molecular modelling investigations showed that the active new compounds may interact at the active site of both the fungal and the mycobacterial cytochrome P450-dependent sterol-14alpha-demethylase and that the calculated binding free energy values are in agreement with the corresponding MIC values. CONCLUSIONS: The combined experimental and computational approach can be helpful in targeted drug design, thus yielding valuable information for the synthesis and prediction of activity of a second generation of inhibitors.

Antifungal Agents↗
PubMed2004

A computational approach for ordering signal transduction pathway components from genomics and proteomics Data.

BACKGROUND: Signal transduction is one of the most important biological processes by which cells convert an external signal into a response. Novel computational approaches to mapping proteins onto signaling pathways are needed to fully take advantage of the rapid accumulation of genomic and proteomics information. However, despite their importance, research on signaling pathways reconstruction utilizing large-scale genomics and proteomics information has been limited. RESULTS: We have developed an approach for predicting the order of signaling pathway components, assuming all the components on the pathways are known. Our method is built on a score function that integrates protein-protein interaction data and microarray gene expression data. Compared to the individual datasets, either protein interactions or gene transcript abundance measurements, the integrated approach leads to better identification of the order of the pathway components. CONCLUSIONS: As demonstrated in our study on the yeast MAPK signaling pathways, the integration analysis of high-throughput genomics and proteomics data can be a powerful means to infer the order of pathway components, enabling the transformation from molecular data into knowledge of cellular mechanisms.

Computational Biology↗
PubMed2006

Development and validation of an integrated computational approach for the modeling of cw-ESR spectra of free radicals in solution: p-(methylthio)phenyl nitronylnitroxide in toluene as a case study.

In this work we address the interpretation, via an ab initio integrated computational approach, of continuous wave electron spin resonance (cw-ESR) spectra of p-(methylthio)phenyl nitronylnitroxide (MTPNN) dissolved in toluene. Our approach is based on the determination of the spin Hamiltonian, averaged with respect to fast vibrational motions, with magnetic tensor parameters (Zeeman and hyperfine tensors) characterized by quantum mechanical density functional calculations. The system is then described by a stochastic Liouville equation, with inclusion of diffusive rotational dynamics. Parametrization of diffusion rotational tensor is provided by a hydrodynamic model. Cw-ESR spectra of MTPNN are simulated for a wide range of temperatures (155-292 K) with minimal resorting to fitting procedures, proving that the combination of sensitive ESR spectroscopy and sophisticated modeling can be highly helpful in providing structural and dynamic information on molecular systems.

Journal Article↗
PubMed1998

Systematic genomic screening and analysis of mRNA in untranslated regions and mRNA precursors: combining experimental and computational approaches.

MOTIVATION: The untranslated regions (UTRs) of mRNA upstream (5'UTR) and downstream (3'UTR) of the open reading frame, as well as the mRNA precursor, carry important regulatory sequences. To reveal unidentified regulatory signals, we combine information from experiments with computational approaches. Depending on available knowledge, three different strategies are employed. RESULTS: Searching with a consensus template, new RNAs with regulatory RNA elements can be identified in genomic screens. By this approach, we identify new candidate regulatory motifs resembling iron-responsive elements in the 5'UTRs of HemA, FepB and FrdB mRNA from Escherichia coli. If an RNA element is not yet defined, it may be analyzed by combining results from SELEX (selective enrichment of ligands by exponential amplification) and a search of databases from RNA or genomic sequences. A cleavage stimulating factor (CstF) binding element 3 of the polyadenylation site in the mRNA precursor serves as a test example. Alternatively, the regulatory RNA element may be found by studying different RNA foldings and their correlation with simple experimental tests. We delineate a novel instability element in the 3'UTR of the estrogen receptor mRNA in this way. AVAILABILITY: Strategy, methods and programs are available on request from T.Dandekar. CONTACT: dandekar@embl-heidelberg.de

3' Untranslated Regions↗
PubMed1999

Sodium dynamics underlying burst firing and putative mechanisms for the regulation of the firing pattern in midbrain dopamine neurons: a computational approach.

A physiologically based multicompartmental computational model of a midbrain dopamine (DA) neuron, calibrated using data from the literature, was developed and used to test the hypothesis that sodium dynamics drive the generation of a slow oscillation postulated to underlie NMDA-evoked bursting activity in a slice preparation. The full compartmental model was reduced to three compartments and ultimately to two variables, while retaining the biophysical interpretation of all parameters. A phase-plane analysis then suggested two mechanisms for the regulation of the firing pattern: (1) bursting activity is favored by manipulations that enhance the region of negative slope in the whole-cell IV curve and inhibited by those manipulations, such as increasing linear currents, that tend to dampen this region and (2) assuming a region of negative slope is present in the IV curve, the bias of the system can be altered, either enabling or disabling bursting. The model provides a coherent framework for interpreting the effects of glutamate, aspartate, NMDA, and GABA agonists and antagonists under current-clamp conditions, as well as the effects of NMDA and barium under voltage-clamp conditions.

Calibration↗
PubMed2006

Computational approaches to visual decision making.

Computational models based on diffusion processes have been proposed to account for human decision making behaviour in a variety of tasks. This study explores whether such models account for the speed and accuracy of perceptual decisions in a reaction-time random dot motion direction-discrimination task and whether they explain the decision-related activity of neurons recorded from the parietal cortex (area LIP) of monkeys performing the task. While a relatively simple diffusion model can explain the psychometric function and the mean response times, it fails to account for the response time distributions. By adding an 'urgency mechanism' to the diffusion model the psychometric function, the mean response times, and the shape of the response time distributions can be explained. Such an urgency mechanism could be implemented in different ways, but the best match between the physiological data and model predictions is provided by a diffusion process with a time-variant gain of the sensory signals. It can be shown that such a time-variant decision process allows the monkey to perform optimally (in the sense of maximizing reward rate) given the risk of aborting a trial by breaking fixation before a choice can be reported.

Animals↗
PubMed2000

The human adult skeletal muscle transcriptional profile reconstructed by a novel computational approach.

By applying a novel software tool, information on 4080 UniGene clusters was retrieved from three adult human skeletal muscle cDNA libraries, which were selected for being neither normalized nor subtracted. Reconstruction of a transcriptional profile of the corresponding tissue was attempted by a computational approach, classifying each transcript according to its level of expression. About 25% of the transcripts accounted for about 80% of the detected transcriptional activity, whereas most genes showed a low level of expression. This in silico transcriptional profile was then compared with data obtained by a SAGE study. A fairly good agreement between the two methods was observed. About 400 genes, highly expressed in skeletal muscle or putatively skeletal muscle-specific, may represent the minimal set of genes needed to determine the tissue specificity. These genes could be used as a convenient reference to monitor major changes in the transcriptional profile of adult human skeletal muscle in response to different physiological or pathological conditions, thus providing a framework for designing DNA microarrays and initiating biological studies.

Adult↗
PubMed2006

Computational approaches to fibril structure and formation.

Assembly of normally soluble proteins into amyloid fibrils is a cause or associated symptom of numerous human disorders. Although some progress toward understanding the molecular-level details of fibril structure has been made through in vitro experiments, the insoluble nature of fibrils make them difficult to study experimentally. We describe two computational approaches used to investigate fibril formation and structure: intermediate-resolution discontinuous molecular dynamics simulations and atomistic molecular dynamics simulations. Each method has its strengths and weaknesses, but taken together the two approaches provide a useful molecular-level picture of fibril structure and formation.

Amyloid↗
PubMed2005

A computational approach for peptidomic analysis in taxonomic study of amphibian species.

Peptides in the skin secretion of frogs have been studied for some time now because they frequently possess important biological activity such as antibiotic, antimicrobial, or anticancer properties. In this paper, we present a computational approach for measuring the degree of similarity between the entire peptide complement of the skin secretion of specimens from the same or different species. The first step in the analysis is the generation of a mass spectral profile from an experimental high-performance liquid chromatography/electrosparay ionization analysis of the sample. An "overlap" between the mass spectral profiles of different specimens is then proposed as a measure of their similarity. Analysis of specimens from three species of the genus Litoria, viz., L. Aurea, L. Caerulea, and L. Infrafrenata, and Rana Capito of genus Rana shows that the degree of similarity is highest between specimens from the same species, lower for specimens from different species of the same genus, and lowest between specimens from different genera. This indicates that comparison of skin peptide profiles (i.e., mass spectral profiles of skin secretion) is potentially a useful aid in the taxonomic study of amphibian species.

Algorithms↗
PubMed1997

What represents a face? A computational approach for the integration of physiological and psychological data.

Empirical studies of face recognition suggest that faces might be stored in memory by means of a few canonical representations. The nature of these canonical representations is, however, unclear. Although psychological data show a three-quarter-view advantage, physiological studies suggest profile and frontal views are stored in memory. A computational approach to reconcile these findings is proposed. The pattern of results obtained when different views, or combinations of views, are used as the internal representation of a two-stage identification network consisting of an autoassociative memory followed by a radial-basis-function network are compared. Results show that (i) a frontal and a profile view are sufficient to reach the optimal network performance; and (ii) all the different representations produce a three-quarter view advantage, similar to that generally described for human subjects. These results indicate that although three-quarter views yield better recognition than other views, they need not be stored in memory to show this advantage.

Computer Simulation↗
PubMed2007

Computational approaches to phenotyping: high-throughput phenomics.

The recent completion of the Human Genome Project has made possible a high-throughput "systems approach" for accelerating the elucidation of molecular underpinnings of human diseases, and subsequent derivation of molecular-based strategies to more effectively prevent, diagnose, and treat these diseases. Although altered phenotypes are among the most reliable manifestations of altered gene functions, research using systematic analysis of phenotype relationships to study human biology is still in its infancy. This article focuses on the emerging field of high-throughput phenotyping (HTP) phenomics research, which aims to capitalize on novel high-throughput computation and informatics technology developments to derive genomewide molecular networks of genotype-phenotype associations, or "phenomic associations." The HTP phenomics research field faces the challenge of technological research and development to generate novel tools in computation and informatics that will allow researchers to amass, access, integrate, organize, and manage phenotypic databases across species and enable genomewide analysis to associate phenotypic information with genomic data at different scales of biology. Key state-of-the-art technological advancements critical for HTP phenomics research are covered in this review. In particular, we highlight the power of computational approaches to conduct large-scale phenomics studies.

Computational Biology↗