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An atomically detailed study of the folding pathways of protein A with the stochastic difference equation.

An algorithm is applied here to compute folding pathways of staphylococcal protein A, fragment B. Emphasis is on studies of the complete process, starting from an ensemble of fully denatured conformations and ending at the folded state. The stochastic difference equation algorithm is based on optimization of an action that makes it possible to use a large integration step. Motions with typical displacements that change rapidly on the size scale of the step are filtered out, providing numerically stable and approximate solutions. The present approach is unique in maintaining an atomically detailed picture while providing a systematic, controlled approximation to the classical equations of motion. Analysis of 130 trajectories suggests the following folding mechanism for protein A: At an early precollapse phase of the process, a few native hydrogen bonds form near the C terminus of the protein. The hydrogen bonds are formed mostly within the third helix. The next step is chain collapse that occurs in parallel to additional growth of secondary structure seeds. Therefore, the present study does not support a pure hydrophobic collapse, or substantial early formation of secondary structure. At the last step, native tertiary contacts are formed at the same time as the completion of the secondary structure elements. To a large extent, the process is parallel and not sequential. The early formation of the third helix of protein A, fragment B (in the calculation), is consistent with experimental data.

Algorithms↗

Monte Carlo-based treatment planning for a spoiler system with experimental validation using plane-parallel ionization chambers.

A beam spoiler is often used to increase the build-up dose near the surface for treatment of superficial treatment areas. Photon-beam spoilers produce a large amount of contaminant electrons, conditions for which standard, commercial treatment-planning system dose-calculation algorithms are inadequate for producing accurate dose calculations. In this study, we implemented a Monte Carlo (MC) dose-calculation algorithm for this spoiler system. With and without a spoiler of 1 cm Lucite, depth doses and transverse profiles in the build-up region were measured for field sizes of 5 x 5 cm2 and 10 x 10 cm2 at the spoiler-to-surface distances (STSDs) of 6, 10 and 15 cm. An Attix chamber and a Markus chamber were used for depth doses, whereas a diode detector was used for transverse profiles. An MC simulation using BEAM/DOSXYZ was used to compare the calculated and the measured data. The MC calculations agreed with the Attix chamber measurements within 2% for all STSDs and field sizes, whereas the Markus data--even with corrections made-showed a discrepancy of about 3.5% with a maximum difference of 7.3% for a field size of 10 x 10 cm2 at an STSD of 6 cm. The MC treatment-planning system was successfully applied to a head-and-neck case using 6 MV photon beams with a beam spoiler.

Algorithms↗

A new hierarchical parallelization scheme: generalized distributed data interface (GDDI), and an application to the fragment molecular orbital method (FMO).

A two-level hierarchical scheme, generalized distributed data interface (GDDI), implemented into GAMESS is presented. Parallelization is accomplished first at the upper level by assigning computational tasks to groups. Then each group does parallelization at the lower level, by dividing its task into smaller work loads. The types of computations that can be used with this scheme are limited to those for which nearly independent tasks and subtasks can be assigned. Typical examples implemented, tested, and analyzed in this work are numeric derivatives and the fragment molecular orbital method (FMO) that is used to compute large molecules quantum mechanically by dividing them into fragments. Numeric derivatives can be used for algorithms based on them, such as geometry optimizations, saddle-point searches, frequency analyses, etc. This new hierarchical scheme is found to be a flexible tool easily utilizing network topology and delivering excellent performance even on slow networks. In one of the typical tests, on 16 nodes the scalability of GDDI is 1.7 times better than that of the standard parallelization scheme DDI and on 128 nodes GDDI is 93 times faster than DDI (on a multihub Fast Ethernet network). FMO delivered scalability of 80-90% on 128 nodes, depending on the molecular system (water clusters and a protein). A numerical gradient calculation for a water cluster achieved a scalability of 70% on 128 nodes. It is expected that GDDI will become a preferred tool on massively parallel computers for appropriate computational tasks.

Journal Article↗

A theoretical evaluation of the assessment of effective dose using multiple personnel dosimeters.

The ability of a dose calculation algorithm, using the readings of multiple dosimeters, to accurately assess the effective dose under different photon irradiation conditions was assessed using computer simulation. The algorithm was that described in American National Standards Institute publication N13.41. Monte Carlo calculations with an anthropomorphic humanoid phantom were used to calculate the effective doses and also the expected readings of the multiple dosimeters. The irradiation geometries considered included a point source placed at several locations at a distance of 100 cm in front of the phantom, as well as an anterior-posterior plane parallel beam with a lead shield interposed between the phantom and the source. The point source energies considered were 0.05, 0.6, and 2 MeV, and the beam energy was varied between 0.03 and 10 MeV. Also considered were the estimates of effective dose based on the highest reading of the multiple dosimeters, a practice that is currently used in many work places. The results showed that use of the algorithm resulted in substantial improvements in the ability to accurately estimate effective dose. However, the results also showed that the improvements in accuracy were achievable only by using a calibration factor for the dosimetry that is different from the one obtained in current dosimetry calibration practices, and that without the use of this factor, the algorithm tended to underestimate the effective dose for nearly all the irradiation geometries considered. In addition, it appeared that this calibration factor is not constant but varies with irradiation conditions. There thus appears to be a problem of proper dosimetry calibration for use with the algorithm. This work considered only anterior posterior irradiations, and additional work is needed to assess the performance of the algorithm in other non-uniform irradiation geometries.

Algorithms↗

Visual and auditory association areas of the cat's posterior ectosylvian gyrus: thalamic afferents.

The feline posterior ectosylvian gyrus contains a broad band of association cortex that is bounded anteriorly by tonotopic auditory areas and posteriorly by retinotopic visual areas. To characterize the possible functions of this cortex and to throw light on its pattern of internal divisions, we have carried out an analysis of its thalamic afferents. Deposits of differentiable retrograde tracers were placed at 17 cortical sites in nine cats. The deposit sites spanned the crown of the posterior ectosylvian gyrus and adjacent cortex in the suprasylvian sulcus. We compiled counts of retrogradely labeled neurons in 12 thalamic nuclei delineated by use of Nissl and acetylcholinesterase stains. We then employed a statistical clustering algorithm to identify groups of injections that gave rise to similar patterns of thalamic labeling. The results suggest that the posterior ectosylvian gyrus contains 3 fundamentally different cortical districts that have the form of parallel vertical bands. Very anterior cortex, overlapping previously identified tonotopic auditory areas (AI, P and VP) receives a dense projection from the laminated division of the medial geniculate body (MGl). An intermediate strip, to which we refer as the auditory belt, is innervated by axons from nontonotopic divisions of the medial geniculate body (MGds, MGvl, MGm, and MGd), from the lateral division of the posterior group (Pol), and from the posterior suprageniculate nucleus (SGp). A posterior strip, to which we refer as EPp, receives strong projections from the LM-SG complex (LM-SGa and LMp), and lighter projections from the intralaminar and lateroposterior (LPm and LPl) nuclei. On grounds of thalamic connectivity, EPp is not obviously distinguishable from adjacent retinotopic visual areas (PLLS, DLS, and VLS), and may be regarded as forming, together with these areas, a connectionally homogeneous visual belt.

Animals↗

Identification of a novel class in the alpha/beta hydrolase fold superfamily: the N-myc differentiation-related proteins.

The alpha/beta hydrolases constitute a large protein superfamily that mainly consists of enzymes that catalyze a diverse range of reactions. These proteins exhibit the alpha/beta hydrolase fold, the essential features of which have recently been delineated: the presence of at least five parallel beta-strands, a catalytic triad in a specific order (nucleophile-acid-histidine), and a nucleophilic elbow. Because of the difficulties experimentally in identifying protein structures, we have used a Bayesian computational algorithm (PROBE) to identify the members of this superfamily based on distant sequence relationships. We found that the presence of five sequence motifs, which contain residues important for substrate binding and stabilization of the fold, are required for membership in this superfamily. The superfamily consists of at least 909 members, including the N-myc downstream regulated proteins, which are believed to be involved in cell differentiation. Unlike most of the other superfamily members, the N-myc downstream regulated proteins have never been proposed to possess the alpha/beta hydrolase fold and do not appear to be hydrolases.

Amino Acid Motifs↗

Hardware-accelerated protein identification for mass spectrometry.

An ongoing issue in mass spectrometry is the time it takes to search DNA sequences with MS/MS peptide fragments (see, e.g., Choudary et al., Proteomics 2001; 1: 651-667.) Search times are far longer than spectra acquisition time, and parallelization of search software on clusters requires doubling the size of a conventional computing cluster to cut the search time in half. Field programmable gate arrays (FPGAs) are used to create hardware-accelerated algorithms that reduce operating costs and improve search speed compared to large clusters. We present a novel hardware design that takes full spectra and computes 6-frame translation word searches on DNA databases at a rate of approximately 3 billion base pairs per second, with queries of up to 10 amino acids in length and arbitrary wildcard positions. Hardware post-processing identifies in silico tryptic peptides and scores them using a variety of techniques including mass frequency expected values. With faster FPGAs protein identifications from the human genome can be achieved in less than a second, and this makes it an ideal solution for a number of proteome-scale applications.

Equipment Design↗

A dosimetric comparison of three compensator design methods for the mantle field.

The mid-plane dose was measured in an anthropomorphic phantom for parallel opposed mantle fields as typically used in the treatment of Hodgkin's Disease. Doses were measured for four cases: no compensator, a compensator designed by a three-dimensional CT based treatment planning algorithm, a compensator designed from a port film, and a compensator designed from surface topography. The results showed all three compensators gave a significant better dose distribution than using no compensator at all. Without a compensator, doses varied from 92 percent to 131 percent, with a standard deviation of 10.9 percent for 65 measured points. The treatment planning algorithm gave the best performance with a standard deviation of 3.2 percent with all points but three within 5 percent out of the 65 points measured, and no points outside of 10 percent. The port film compensator was next best with a standard deviation of 4.4 percent, with 19 points outside of 5 percent, and doses from 88 to 106 percent. The surface topography compensator had a standard deviation of 6.1 percent with 31 points outside of 5% and doses from 89 to 114 percent.

Hodgkin Disease↗

Detection of Mycobacterium tuberculosis (TB) in vitro and in situ using an electronic nose in combination with a neural network system.

The use of volatile production patterns produced by Mycobacterium tuberculosis and associated bacterial infections from sputum samples were examined in vitro and in situ using an electronic nose based on a 14 sensor conducting polymer array. In vitro, it was possible to successfully discriminate between M. tuberculosis (TB) and control media, and between M. tuberculosis and M. avium, M. scrofulaceum and Pseudomonas aeruginosa cultures in the stationary phase after 5-6h incubation at 37 degrees C based on 35 samples. Using neural network (NN) analysis and cross-validation it was possible to successfully identify 100% of the TB cultures from others. A second in vitro study with 61 samples all four groups were successfully discriminated with 14 of 15 unknowns within each of the four groups successfully identified using cross-validation and discriminant function analysis. Subsequently, lipase enzymes were added to 46 sputum samples directly obtained from patients and the head space analysed. Parallel measurements of bacterial contamination were also carried out for confirmation using agar media. NN analysis was carried out using some of the samples as a training set. Based on the NN and genetic algorithms of up to 10 generations it was possible to successfully cross-validate 9 of 10 unknown samples. PCA was able to discriminate between TB infection alone, the controls, M. avium, P. aeruginosa and a mixed infection. These findings will have significant implications for the development of rapid qualitative systems for screening of patient samples and clinical diagnosis of tuberculosis.

Algorithms↗

Quantitative classification and natural clustering of Caenorhabditis elegans behavioral phenotypes.

Genetic analysis of nervous system function relies on the rigorous description of behavioral phenotypes. However, standard methods for classifying the behavioral patterns of mutant Caenorhabditis elegans rely on human observation and are therefore subjective and imprecise. Here we describe the application of machine learning to quantitatively define and classify the behavioral patterns of C. elegans nervous system mutants. We have used an automated tracking and image processing system to obtain measurements of a wide range of morphological and behavioral features from recordings of representative mutant types. Using principal component analysis, we represented the behavioral patterns of eight mutant types as data clouds distributed in multidimensional feature space. Cluster analysis using the k-means algorithm made it possible to quantitatively assess the relative similarities between different behavioral phenotypes and to identify natural phenotypic clusters among the data. Since the patterns of phenotypic similarity identified in this study closely paralleled the functional similarities of the mutant gene products, the complex phenotypic signatures obtained from these image data appeared to represent an effective diagnostic of the mutants' underlying molecular defects.

Animals↗

Methacholine-induced temporal changes in airway geometry and lung density by CT.

PURPOSE: Electron-beam CT (EBCT) was utilized to assess the time course of changes in airways cross-sectional area (CSA) and lung density during methacholine-induced bronchoconstriction. MATERIALS AND METHODS: EBCT scans (200 ms, 3-mm thickness, 2 mm increments) were obtained before (baseline) and 30 s, 2 min, and 4 min after bolus IV injection of methacholine to pigs receiving mechanical ventilation. A total of seven experiments were analyzed using custom-made image analysis software. With each challenge, five different airways and 50 lung regions of interest were studied. RESULTS: The time course of lung density changes paralleled the time course for CSA changes. The maximal response to methacholine, measured in terms of both CSA and lung density changes, occurred 30 s after injection. Lung density changes were unaffected by reconstruction algorithm, normal (standard) or sharp (high resolution). Overall, there was increased air content in the lung during bronchoconstriction. This effect was significantly greater at the dependent lung regions. CONCLUSIONS: EBCT is an effective tool to assess temporal and regional changes in the lung during bronchoconstriction. Measurements of lung density during bronchoconstriction allow for assessment of peripheral changes that are beyond the CT spatial resolution of airways anatomy.

Animals↗

Five hierarchical levels of sequence-structure correlation in proteins.

This article reviews recent work towards modelling protein folding pathways using a bioinformatics approach. Statistical models have been developed for sequence-structure correlations in proteins at five levels of structural complexity: (i) short motifs; (ii) extended motifs; (iii) nonlocal pairs of motifs; (iv) 3-dimensional arrangements of multiple motifs; and (v) global structural homology. We review statistical models, including sequence profiles, hidden Markov models (HMMs) and interaction potentials, for the first four levels of structural detail. The I-sites (folding Initiation sites) Library models short local structure motifs. Each succeeding level has a statistical model, as follows: HMMSTR (HMM for STRucture) is an HMM for extended motifs; HMMSTR-CM (Contact Maps) is a model for pairwise interactions between motifs; and SCALI-HMM (HMMs for Structural Core ALIgnments) is a set of HMMs for the spatial arrangements of motifs. The parallels between the statistical models and theoretical models for folding pathways are discussed in this article; however, global sequence models are not discussed because they have been extensively reviewed elsewhere. The data used and algorithms presented in this article are available at http://www.bioinfo.rpi.edu/~bystrc/ (click on "servers" or "downloads") or by request to bystrc@rpi.edu .

Algorithms↗

Protein Threading Based on Multiple Protein Structure Alignment.

Protein threading, a method employed in protein three-dimensional (3D) structure prediction was only proposed in the early 1990's although predicting protein 3D structure from its given amino acid sequence has been around since 1970's. Here we describe a protein threading method/system that we have developed based on multiple protein structure alignment. In order to compute multiple structure alignments, we developed a similar structure search program on massive parallel computers and a program for constructing a multiple structure alignment from pairwise structure alignments, where the latter is based on the center star method for sequence alignment. A simple dynamic-programming based algorithm which uses a profile matrix obtained from the result of multiple structure alignment was also developed to compute a threading (i.e., an alignment between a target sequence and a known structure). Using this system, we participated in the threading category (category AL) of CASP3 (Third Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction). The results are discussed.

Journal Article↗

A novel method for across-chromosome phasing without relative data.

MOTIVATION: Across-chromosome phasing identifies which haplotypes of different chromosomes come from the same parent. This differs from within-chromosome phasing, which uses linkage disequilibrium patterns to determine which alleles were co-inherited within each chromosome but does not match haplotypes across different chromosomes. While across-chromosome phasing can be conducted using genotypes from parents or close relatives, current methods perform poorly for samples of unrelated individuals. Here, we introduce a novel approach for across-chromosome phasing that employs a window-based SNP-similarity metric, eliminating the need for data from close relatives or detection of identical-by-descent haplotypes. RESULTS: Using UK Biobank offspring with both parents genotyped as a gold standard, we evaluated the performance of our method by phasing the offspring without using parental data. In genomic data with no within-chromosome phase errors, our algorithm achieved a mean across-chromosome phasing accuracy of 95%, with 53% of individuals phased perfectly. When data was pre-phased computationally using a standard within-chromosome phasing algorithm, mean accuracy for across-chromosome phasing dropped to 83.1%. Thus, our method is limited primarily by the accuracy of within-chromosome phasing accuracy and can approach near-perfect across-chromosome phasing accuracy as within-chromosome phasing accuracy improves. AVAILABILITY AND IMPLEMENTATION: The implementation was executed within a multi-node computational environment of University of Colorado Boulder Research Computing (Blanca Cluster: https://www.colorado.edu/rc/resources/blanca), employing parallelization techniques in the C programming language. The source code has been made publicly accessible online at https://github.com/emmanuelsapin/AcrossChromosomesPhasing, thereby facilitating reproducibility of the results for researchers with authorized access to the UK Biobank dataset.

Algorithms↗

A method for analysis of encoding of stimulus separation in ensembles of afferents.

This paper describes a new method for the analysis of ensemble coding in populations of receptor afferents. The method is based on principal component analysis (PCA) combined with algorithms for calculation of stimulus separation (discrimination). It allows a quantification of the ability of ensembles of afferents to discriminate between stimuli of different intensity, and it can also be used to calculate to which extent each afferent in an ensemble contributes to the discrimination. Since the emphasis is put on discrimination of stimuli rather than on similarities between the representations of the stimulus in the ensemble response and the stimulus itself, it involves no implicit assumption about the unknown decoding mechanisms in the CNS. Examples of results obtained with analysis of and comparison of simultaneously recorded and pooled sequentially recorded populations of primary muscle spindle afferents are given. These results support some of the general arguments in favour of the ensemble coding theory, and indicate that the results of studies made on populations of simultaneously recorded receptor afferents may differ considerably from results obtained in studies on pooled sequentially recorded afferents. In contrast to when ensemble responses are based on parallel recordings, population responses constructed from sequential recordings will be distorted as a result of unavoidable temporal variations in physiological conditions.

Algorithms↗

Potential and feasibility of parallel MRI at high field.

This survey focuses on the fusion of two major lines of recent progress in MRI methodology: parallel imaging with receiver coil arrays and the transition to high and ultra-high field strength for human applications. As discussed in this paper, combining the two developments has vast potential due to multiple specific synergies. First, parallel acquisition and high field are highly complementary in terms of their individual advantages and downsides. As a consequence, the joint approach generally offers enhanced flexibility in the design of scanning strategies. Second, increasing resonance frequency changes the electrodynamics of the MR signal in such a way that parallel imaging becomes more effective in large objects. The underlying conceptual and theoretical considerations are reviewed in detail. In further sections, technical challenges and practical aspects are discussed. The feasibility of parallel MRI at ultra-high field is illustrated by current results of parallel human MRI at 7 T.

Algorithms↗

Methodological developments and strategies for a fast flexible superposition of drug-size molecules.

An alternative to experimental high through-put screening is the virtual screening of compound libraries on the computer. In absence of a detailed structure of the receptor protein, candidate molecules are compared with a known reference by mutually superimposing their skeletons and scoring their similarity. Since molecular shape highly depends on the adopted conformation, an efficient conformational screening is performed using a knowledge-based approach. A comprehensive torsion library has been compiled from crystal data stored in the Cambridge Structural Database. For molecular comparison a strategy is followed considering shape associated physicochemical properties in space such as steric occupancy, electrostatics, lipophilicity and potential hydrogen-bonding. Molecular shape is approximated by a set of Gaussian functions not necessarily located at the atomic positions. The superposition is performed in two steps: first by a global alignment search operating on multiple rigid conformations and then by conformationally relaxing the best scored hits of the global search. A normalized similarity scoring is used to allow for a comparison of molecules with rather different shape and size. The approach has been implemented on a cluster of parallel processors. As a case study, the search for ligands binding to the dopamine receptor is given.

Algorithms↗