Predicting heterocyclic ring coupling constants through a conformational search of tetra-o-methyl-(+)-catechin

Treesearch

Fred L. Tobiason; Richard w. Hemingway

1994-01-01

A GMMXe conformational search routine gives a family a conformations that reflects the boltzmann-averaged heterocyclic ring conformation as evidence by accurate prediction of all three coupling constants observed for tetra-O-methyl-(+)-catechin.

DockRank: Ranking docked conformations using partner-specific sequence homology-based protein interface prediction

PubMed Central

Xue, Li C.; Jordan, Rafael A.; EL-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

2015-01-01

Selecting near-native conformations from the immense number of conformations generated by docking programs remains a major challenge in molecular docking. We introduce DockRank, a novel approach to scoring docked conformations based on the degree to which the interface residues of the docked conformation match a set of predicted interface residues. Dock-Rank uses interface residues predicted by partner-specific sequence homology-based protein–protein interface predictor (PS-HomPPI), which predicts the interface residues of a query protein with a specific interaction partner. We compared the performance of DockRank with several state-of-the-art docking scoring functions using Success Rate (the percentage of cases that have at least one near-native conformation among the top m conformations) and Hit Rate (the percentage of near-native conformations that are included among the top m conformations). In cases where it is possible to obtain partner-specific (PS) interface predictions from PS-HomPPI, DockRank consistently outperforms both (i) ZRank and IRAD, two state-of-the-art energy-based scoring functions (improving Success Rate by up to 4-fold); and (ii) Variants of DockRank that use predicted interface residues obtained from several protein interface predictors that do not take into account the binding partner in making interface predictions (improving success rate by up to 39-fold). The latter result underscores the importance of using partner-specific interface residues in scoring docked conformations. We show that DockRank, when used to re-rank the conformations returned by ClusPro, improves upon the original ClusPro rankings in terms of both Success Rate and Hit Rate. DockRank is available as a server at http://einstein.cs.iastate.edu/DockRank/. PMID:23873600

DockRank: ranking docked conformations using partner-specific sequence homology-based protein interface prediction.

PubMed

Xue, Li C; Jordan, Rafael A; El-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

2014-02-01

Selecting near-native conformations from the immense number of conformations generated by docking programs remains a major challenge in molecular docking. We introduce DockRank, a novel approach to scoring docked conformations based on the degree to which the interface residues of the docked conformation match a set of predicted interface residues. DockRank uses interface residues predicted by partner-specific sequence homology-based protein-protein interface predictor (PS-HomPPI), which predicts the interface residues of a query protein with a specific interaction partner. We compared the performance of DockRank with several state-of-the-art docking scoring functions using Success Rate (the percentage of cases that have at least one near-native conformation among the top m conformations) and Hit Rate (the percentage of near-native conformations that are included among the top m conformations). In cases where it is possible to obtain partner-specific (PS) interface predictions from PS-HomPPI, DockRank consistently outperforms both (i) ZRank and IRAD, two state-of-the-art energy-based scoring functions (improving Success Rate by up to 4-fold); and (ii) Variants of DockRank that use predicted interface residues obtained from several protein interface predictors that do not take into account the binding partner in making interface predictions (improving success rate by up to 39-fold). The latter result underscores the importance of using partner-specific interface residues in scoring docked conformations. We show that DockRank, when used to re-rank the conformations returned by ClusPro, improves upon the original ClusPro rankings in terms of both Success Rate and Hit Rate. DockRank is available as a server at http://einstein.cs.iastate.edu/DockRank/. Copyright © 2013 Wiley Periodicals, Inc.

Predicting bioactive conformations and binding modes of macrocycles

NASA Astrophysics Data System (ADS)

Anighoro, Andrew; de la Vega de León, Antonio; Bajorath, Jürgen

2016-10-01

Macrocyclic compounds experience increasing interest in drug discovery. It is often thought that these large and chemically complex molecules provide promising candidates to address difficult targets and interfere with protein-protein interactions. From a computational viewpoint, these molecules are difficult to treat. For example, flexible docking of macrocyclic compounds is hindered by the limited ability of current docking approaches to optimize conformations of extended ring systems for pose prediction. Herein, we report predictions of bioactive conformations of macrocycles using conformational search and binding modes using docking. Conformational ensembles generated using specialized search technique of about 70 % of the tested macrocycles contained accurate bioactive conformations. However, these conformations were difficult to identify on the basis of conformational energies. Moreover, docking calculations with limited ligand flexibility starting from individual low energy conformations rarely yielded highly accurate binding modes. In about 40 % of the test cases, binding modes were approximated with reasonable accuracy. However, when conformational ensembles were subjected to rigid body docking, an increase in meaningful binding mode predictions to more than 50 % of the test cases was observed. Electrostatic effects did not contribute to these predictions in a positive or negative manner. Rather, achieving shape complementarity at macrocycle-target interfaces was a decisive factor. In summary, a combined computational protocol using pre-computed conformational ensembles of macrocycles as a starting point for docking shows promise in modeling binding modes of macrocyclic compounds.

49 CFR 599.303 - Agency disposition of dealer application for reimbursement.

Code of Federal Regulations, 2010 CFR

2010-10-01

... correct a non-conforming submission. (d) Electronic rejection. An application is automatically rejected... transaction, or identifies the vehicle identification number of a new or trade-in vehicle that was involved in...

Conformal Prediction Based on K-Nearest Neighbors for Discrimination of Ginsengs by a Home-Made Electronic Nose

PubMed Central

Sun, Xiyang; Miao, Jiacheng; Wang, You; Luo, Zhiyuan; Li, Guang

2017-01-01

An estimate on the reliability of prediction in the applications of electronic nose is essential, which has not been paid enough attention. An algorithm framework called conformal prediction is introduced in this work for discriminating different kinds of ginsengs with a home-made electronic nose instrument. Nonconformity measure based on k-nearest neighbors (KNN) is implemented separately as underlying algorithm of conformal prediction. In offline mode, the conformal predictor achieves a classification rate of 84.44% based on 1NN and 80.63% based on 3NN, which is better than that of simple KNN. In addition, it provides an estimate of reliability for each prediction. In online mode, the validity of predictions is guaranteed, which means that the error rate of region predictions never exceeds the significance level set by a user. The potential of this framework for detecting borderline examples and outliers in the application of E-nose is also investigated. The result shows that conformal prediction is a promising framework for the application of electronic nose to make predictions with reliability and validity. PMID:28805721

Residue-Specific Side-Chain Polymorphisms via Particle Belief Propagation.

PubMed

Ghoraie, Laleh Soltan; Burkowski, Forbes; Li, Shuai Cheng; Zhu, Mu

2014-01-01

Protein side chains populate diverse conformational ensembles in crystals. Despite much evidence that there is widespread conformational polymorphism in protein side chains, most of the X-ray crystallography data are modeled by single conformations in the Protein Data Bank. The ability to extract or to predict these conformational polymorphisms is of crucial importance, as it facilitates deeper understanding of protein dynamics and functionality. In this paper, we describe a computational strategy capable of predicting side-chain polymorphisms. Our approach extends a particular class of algorithms for side-chain prediction by modeling the side-chain dihedral angles more appropriately as continuous rather than discrete variables. Employing a new inferential technique known as particle belief propagation, we predict residue-specific distributions that encode information about side-chain polymorphisms. Our predicted polymorphisms are in relatively close agreement with results from a state-of-the-art approach based on X-ray crystallography data, which characterizes the conformational polymorphisms of side chains using electron density information, and has successfully discovered previously unmodeled conformations.

Numerical method for predicting flow characteristics and performance of nonaxisymmetric nozzles, theory

NASA Technical Reports Server (NTRS)

Thomas, P. D.

1979-01-01

The theoretical foundation and formulation of a numerical method for predicting the viscous flowfield in and about isolated three dimensional nozzles of geometrically complex configuration are presented. High Reynolds number turbulent flows are of primary interest for any combination of subsonic, transonic, and supersonic flow conditions inside or outside the nozzle. An alternating-direction implicit (ADI) numerical technique is employed to integrate the unsteady Navier-Stokes equations until an asymptotic steady-state solution is reached. Boundary conditions are computed with an implicit technique compatible with the ADI technique employed at interior points of the flow region. The equations are formulated and solved in a boundary-conforming curvilinear coordinate system. The curvilinear coordinate system and computational grid is generated numerically as the solution to an elliptic boundary value problem. A method is developed that automatically adjusts the elliptic system so that the interior grid spacing is controlled directly by the a priori selection of the grid spacing on the boundaries of the flow region.

The application of tailor-made force fields and molecular dynamics for NMR crystallography: a case study of free base cocaine

PubMed Central

Neumann, Marcus A.

2017-01-01

Motional averaging has been proven to be significant in predicting the chemical shifts in ab initio solid-state NMR calculations, and the applicability of motional averaging with molecular dynamics has been shown to depend on the accuracy of the molecular mechanical force field. The performance of a fully automatically generated tailor-made force field (TMFF) for the dynamic aspects of NMR crystallography is evaluated and compared with existing benchmarks, including static dispersion-corrected density functional theory calculations and the COMPASS force field. The crystal structure of free base cocaine is used as an example. The results reveal that, even though the TMFF outperforms the COMPASS force field for representing the energies and conformations of predicted structures, it does not give significant improvement in the accuracy of NMR calculations. Further studies should direct more attention to anisotropic chemical shifts and development of the method of solid-state NMR calculations. PMID:28250956

Applying Mondrian Cross-Conformal Prediction To Estimate Prediction Confidence on Large Imbalanced Bioactivity Data Sets.

PubMed

Sun, Jiangming; Carlsson, Lars; Ahlberg, Ernst; Norinder, Ulf; Engkvist, Ola; Chen, Hongming

2017-07-24

Conformal prediction has been proposed as a more rigorous way to define prediction confidence compared to other application domain concepts that have earlier been used for QSAR modeling. One main advantage of such a method is that it provides a prediction region potentially with multiple predicted labels, which contrasts to the single valued (regression) or single label (classification) output predictions by standard QSAR modeling algorithms. Standard conformal prediction might not be suitable for imbalanced data sets. Therefore, Mondrian cross-conformal prediction (MCCP) which combines the Mondrian inductive conformal prediction with cross-fold calibration sets has been introduced. In this study, the MCCP method was applied to 18 publicly available data sets that have various imbalance levels varying from 1:10 to 1:1000 (ratio of active/inactive compounds). Our results show that MCCP in general performed well on bioactivity data sets with various imbalance levels. More importantly, the method not only provides confidence of prediction and prediction regions compared to standard machine learning methods but also produces valid predictions for the minority class. In addition, a compound similarity based nonconformity measure was investigated. Our results demonstrate that although it gives valid predictions, its efficiency is much worse than that of model dependent metrics.

SU-C-BRB-02: Automatic Planning as a Potential Strategy for Dose Escalation for Pancreas SBRT?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, S; Zheng, D; Ma, R

Purpose: Stereotactic body radiation therapy (SBRT) has been suggested to provide high rates of local control for locally advanced pancreatic cancer. However, the close proximity of highly radiosensitive normal tissues usually causes the labor-intensive planning process, and may impede further escalation of the prescription dose. The present study evaluates the potential of an automatic planning system as a dose escalation strategy. Methods: Ten pancreatic cancer patients treated with SBRT were studied retrospectively. SBRT was delivered over 5 consecutive fractions with 6 ∼ 8Gy/fraction. Two plans were generated by Pinnacle Auto-Planning with the original prescription and escalated prescription, respectively. Escalated prescriptionmore » adds 1 Gy/fraction to the original prescription. Manually-created planning volumes were excluded in the optimization goals in order to assess the planning efficiency and quality simultaneously. Critical organs with closest proximity were used to determine the plan normalization to ensure the OAR sparing. Dosimetric parameters including D100, and conformity index (CI) were assessed. Results: Auto-plans directly generate acceptable plans for 70% of the cases without necessity of further improvement, and two more iterations at most are necessary for the rest of the cases. For the pancreas SBRT plans with the original prescription, autoplans resulted in favorable target coverage and PTV conformity (D100 = 96.3% ± 1.48%; CI = 0.88 ± 0.06). For the plans with the escalated prescriptions, no significant target under-dosage was observed, and PTV conformity remains reasonable (D100 = 93.3% ± 3.8%, and CI = 0.84 ± 0.05). Conclusion: Automatic planning, without substantial human-intervention process, results in reasonable PTV coverage and PTV conformity on the premise of adequate OAR sparing for the pancreas SBRT plans with escalated prescription. The results highlight the potential of autoplanning as a dose escalation strategy for pancreas SBRT treatment planning. Further investigations with a larger number of patients are necessary. The project is partially supported by Philips Medical Systems.« less

Conformation-dependent restraints for polynucleotides: I. Clustering of the geometry of the phosphodiester group

PubMed Central

Kowiel, Marcin; Brzezinski, Dariusz; Jaskolski, Mariusz

2016-01-01

The refinement of macromolecular structures is usually aided by prior stereochemical knowledge in the form of geometrical restraints. Such restraints are also used for the flexible sugar-phosphate backbones of nucleic acids. However, recent highly accurate structural studies of DNA suggest that the phosphate bond angles may have inadequate description in the existing stereochemical dictionaries. In this paper, we analyze the bonding deformations of the phosphodiester groups in the Cambridge Structural Database, cluster the studied fragments into six conformation-related categories and propose a revised set of restraints for the O-P-O bond angles and distances. The proposed restraints have been positively validated against data from the Nucleic Acid Database and an ultrahigh-resolution Z-DNA structure in the Protein Data Bank. Additionally, the manual classification of PO4 geometry is compared with geometrical clusters automatically discovered by machine learning methods. The machine learning cluster analysis provides useful insights and a practical example for general applications of clustering algorithms for automatic discovery of hidden patterns of molecular geometry. Finally, we describe the implementation and application of a public-domain web server for automatic generation of the proposed restraints. PMID:27521371

Fully automated treatment planning for head and neck radiotherapy using a voxel-based dose prediction and dose mimicking method

NASA Astrophysics Data System (ADS)

McIntosh, Chris; Welch, Mattea; McNiven, Andrea; Jaffray, David A.; Purdie, Thomas G.

2017-08-01

Recent works in automated radiotherapy treatment planning have used machine learning based on historical treatment plans to infer the spatial dose distribution for a novel patient directly from the planning image. We present a probabilistic, atlas-based approach which predicts the dose for novel patients using a set of automatically selected most similar patients (atlases). The output is a spatial dose objective, which specifies the desired dose-per-voxel, and therefore replaces the need to specify and tune dose-volume objectives. Voxel-based dose mimicking optimization then converts the predicted dose distribution to a complete treatment plan with dose calculation using a collapsed cone convolution dose engine. In this study, we investigated automated planning for right-sided oropharaynx head and neck patients treated with IMRT and VMAT. We compare four versions of our dose prediction pipeline using a database of 54 training and 12 independent testing patients by evaluating 14 clinical dose evaluation criteria. Our preliminary results are promising and demonstrate that automated methods can generate comparable dose distributions to clinical. Overall, automated plans achieved an average of 0.6% higher dose for target coverage evaluation criteria, and 2.4% lower dose at the organs at risk criteria levels evaluated compared with clinical. There was no statistically significant difference detected in high-dose conformity between automated and clinical plans as measured by the conformation number. Automated plans achieved nine more unique criteria than clinical across the 12 patients tested and automated plans scored a significantly higher dose at the evaluation limit for two high-risk target coverage criteria and a significantly lower dose in one critical organ maximum dose. The novel dose prediction method with dose mimicking can generate complete treatment plans in 12-13 min without user interaction. It is a promising approach for fully automated treatment planning and can be readily applied to different treatment sites and modalities.

Fully automated treatment planning for head and neck radiotherapy using a voxel-based dose prediction and dose mimicking method.

PubMed

McIntosh, Chris; Welch, Mattea; McNiven, Andrea; Jaffray, David A; Purdie, Thomas G

2017-07-06

Recent works in automated radiotherapy treatment planning have used machine learning based on historical treatment plans to infer the spatial dose distribution for a novel patient directly from the planning image. We present a probabilistic, atlas-based approach which predicts the dose for novel patients using a set of automatically selected most similar patients (atlases). The output is a spatial dose objective, which specifies the desired dose-per-voxel, and therefore replaces the need to specify and tune dose-volume objectives. Voxel-based dose mimicking optimization then converts the predicted dose distribution to a complete treatment plan with dose calculation using a collapsed cone convolution dose engine. In this study, we investigated automated planning for right-sided oropharaynx head and neck patients treated with IMRT and VMAT. We compare four versions of our dose prediction pipeline using a database of 54 training and 12 independent testing patients by evaluating 14 clinical dose evaluation criteria. Our preliminary results are promising and demonstrate that automated methods can generate comparable dose distributions to clinical. Overall, automated plans achieved an average of 0.6% higher dose for target coverage evaluation criteria, and 2.4% lower dose at the organs at risk criteria levels evaluated compared with clinical. There was no statistically significant difference detected in high-dose conformity between automated and clinical plans as measured by the conformation number. Automated plans achieved nine more unique criteria than clinical across the 12 patients tested and automated plans scored a significantly higher dose at the evaluation limit for two high-risk target coverage criteria and a significantly lower dose in one critical organ maximum dose. The novel dose prediction method with dose mimicking can generate complete treatment plans in 12-13 min without user interaction. It is a promising approach for fully automated treatment planning and can be readily applied to different treatment sites and modalities.

Conformal Regression for Quantitative Structure-Activity Relationship Modeling-Quantifying Prediction Uncertainty.

PubMed

Svensson, Fredrik; Aniceto, Natalia; Norinder, Ulf; Cortes-Ciriano, Isidro; Spjuth, Ola; Carlsson, Lars; Bender, Andreas

2018-05-29

Making predictions with an associated confidence is highly desirable as it facilitates decision making and resource prioritization. Conformal regression is a machine learning framework that allows the user to define the required confidence and delivers predictions that are guaranteed to be correct to the selected extent. In this study, we apply conformal regression to model molecular properties and bioactivity values and investigate different ways to scale the resultant prediction intervals to create as efficient (i.e., narrow) regressors as possible. Different algorithms to estimate the prediction uncertainty were used to normalize the prediction ranges, and the different approaches were evaluated on 29 publicly available data sets. Our results show that the most efficient conformal regressors are obtained when using the natural exponential of the ensemble standard deviation from the underlying random forest to scale the prediction intervals, but other approaches were almost as efficient. This approach afforded an average prediction range of 1.65 pIC50 units at the 80% confidence level when applied to bioactivity modeling. The choice of nonconformity function has a pronounced impact on the average prediction range with a difference of close to one log unit in bioactivity between the tightest and widest prediction range. Overall, conformal regression is a robust approach to generate bioactivity predictions with associated confidence.

Steric interactions determine side-chain conformations in protein cores.

PubMed

Caballero, D; Virrueta, A; O'Hern, C S; Regan, L

2016-09-01

We investigate the role of steric interactions in defining side-chain conformations in protein cores. Previously, we explored the strengths and limitations of hard-sphere dipeptide models in defining sterically allowed side-chain conformations and recapitulating key features of the side-chain dihedral angle distributions observed in high-resolution protein structures. Here, we show that modeling residues in the context of a particular protein environment, with both intra- and inter-residue steric interactions, is sufficient to specify which of the allowed side-chain conformations is adopted. This model predicts 97% of the side-chain conformations of Leu, Ile, Val, Phe, Tyr, Trp and Thr core residues to within 20°. Although the hard-sphere dipeptide model predicts the observed side-chain dihedral angle distributions for both Thr and Ser, the model including the protein environment predicts side-chain conformations to within 20° for only 60% of core Ser residues. Thus, this approach can identify the amino acids for which hard-sphere interactions alone are sufficient and those for which additional interactions are necessary to accurately predict side-chain conformations in protein cores. We also show that our approach can predict alternate side-chain conformations of core residues, which are supported by the observed electron density. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Quantifying side-chain conformational variations in protein structure

PubMed Central

Miao, Zhichao; Cao, Yang

2016-01-01

Protein side-chain conformation is closely related to their biological functions. The side-chain prediction is a key step in protein design, protein docking and structure optimization. However, side-chain polymorphism comprehensively exists in protein as various types and has been long overlooked by side-chain prediction. But such conformational variations have not been quantitatively studied and the correlations between these variations and residue features are vague. Here, we performed statistical analyses on large scale data sets and found that the side-chain conformational flexibility is closely related to the exposure to solvent, degree of freedom and hydrophilicity. These analyses allowed us to quantify different types of side-chain variabilities in PDB. The results underscore that protein side-chain conformation prediction is not a single-answer problem, leading us to reconsider the assessment approaches of side-chain prediction programs. PMID:27845406

Quantifying side-chain conformational variations in protein structure

NASA Astrophysics Data System (ADS)

Miao, Zhichao; Cao, Yang

2016-11-01

Protein side-chain conformation is closely related to their biological functions. The side-chain prediction is a key step in protein design, protein docking and structure optimization. However, side-chain polymorphism comprehensively exists in protein as various types and has been long overlooked by side-chain prediction. But such conformational variations have not been quantitatively studied and the correlations between these variations and residue features are vague. Here, we performed statistical analyses on large scale data sets and found that the side-chain conformational flexibility is closely related to the exposure to solvent, degree of freedom and hydrophilicity. These analyses allowed us to quantify different types of side-chain variabilities in PDB. The results underscore that protein side-chain conformation prediction is not a single-answer problem, leading us to reconsider the assessment approaches of side-chain prediction programs.

Quantifying side-chain conformational variations in protein structure.

PubMed

Miao, Zhichao; Cao, Yang

2016-11-15

Protein side-chain conformation is closely related to their biological functions. The side-chain prediction is a key step in protein design, protein docking and structure optimization. However, side-chain polymorphism comprehensively exists in protein as various types and has been long overlooked by side-chain prediction. But such conformational variations have not been quantitatively studied and the correlations between these variations and residue features are vague. Here, we performed statistical analyses on large scale data sets and found that the side-chain conformational flexibility is closely related to the exposure to solvent, degree of freedom and hydrophilicity. These analyses allowed us to quantify different types of side-chain variabilities in PDB. The results underscore that protein side-chain conformation prediction is not a single-answer problem, leading us to reconsider the assessment approaches of side-chain prediction programs.

Improved Modeling of Open Waveguide Aperture Radiators for use in Conformal Antenna Arrays

NASA Astrophysics Data System (ADS)

Nelson, Gregory James

Open waveguide apertures have been used as radiating elements in conformal arrays. Individual radiating element model patterns are used in constructing overall array models. The existing models for these aperture radiating elements may not accurately predict the array pattern for TEM waves which are not on boresight for each radiating element. In particular, surrounding structures can affect the far field patterns of these apertures, which ultimately affects the overall array pattern. New models of open waveguide apertures are developed here with the goal of accounting for the surrounding structure effects on the aperture far field patterns such that the new models make accurate pattern predictions. These aperture patterns (both E plane and H plane) are measured in an anechoic chamber and the manner in which they deviate from existing model patterns are studied. Using these measurements as a basis, existing models for both E and H planes are updated with new factors and terms which allow the prediction of far field open waveguide aperture patterns with improved accuracy. These new and improved individual radiator models are then used to predict overall conformal array patterns. Arrays of open waveguide apertures are constructed and measured in a similar fashion to the individual aperture measurements. These measured array patterns are compared with the newly modeled array patterns to verify the improved accuracy of the new models as compared with the performance of existing models in making array far field pattern predictions. The array pattern lobe characteristics are then studied for predicting fully circularly conformal arrays of varying radii. The lobe metrics that are tracked are angular location and magnitude as the radii of the conformal arrays are varied. A constructed, measured array that is close to conforming to a circular surface is compared with a fully circularly conformal modeled array pattern prediction, with the predicted lobe angular locations and magnitudes tracked, plotted and tabulated. The close match between the patterns of the measured array and the modeled circularly conformal array verifies the validity of the modeled circularly conformal array pattern predictions.

Predictors of Mental Health Symptoms, Automatic Thoughts, and Self-Esteem Among University Students.

PubMed

Hiçdurmaz, Duygu; İnci, Figen; Karahan, Sevilay

2017-01-01

University youth is a risk group regarding mental health, and many mental health problems are frequent in this group. Sociodemographic factors such as level of income and familial factors such as relationship with father are reported to be associated with mental health symptoms, automatic thoughts, and self-esteem. Also, there are interrelations between mental health problems, automatic thoughts, and self-esteem. The extent of predictive effect of each of these variables on automatic thoughts, self-esteem, and mental health symptoms is not known. We aimed to determine the predictive factors of mental health symptoms, automatic thoughts, and self-esteem in university students. Participants were 530 students enrolled at a university in Turkey, during 2014-2015 academic year. Data were collected using the student information form, the Brief Symptom Inventory, the Automatic Thoughts Questionnaire, and the Rosenberg Self-Esteem Scale. Mental health symptoms, self-esteem, perception of the relationship with the father, and level of income as a student significantly predicted automatic thoughts. Automatic thoughts, mental health symptoms, participation in family decisions, and age had significant predictive effects on self-esteem. Finally, automatic thoughts, self-esteem, age, and perception of the relationship with the father had significant predictive effects on mental health symptoms. The predictive factors revealed in our study provide important information to practitioners and researchers by showing the elements that need to be screened for mental health of university students and issues that need to be included in counseling activities.

Increased conformity offers diminishing returns for reducing total knee replacement wear.

PubMed

Fregly, Benjamin J; Marquez-Barrientos, Carlos; Banks, Scott A; DesJardins, John D

2010-02-01

Wear remains a significant problem limiting the lifespan of total knee replacements (TKRs). Though increased conformity between TKR components has the potential to decrease wear, the optimal amount and planes of conformity have not been investigated. Furthermore, differing conformities in the medial and lateral compartments may provide designers the opportunity to address both wear and kinematic design goals simultaneously. This study used a computational model of a Stanmore knee simulator machine and a previously validated wear model to investigate this issue for simulated gait. TKR geometries with different amounts and planes of conformity on the medial and lateral sides were created and tested in two phases. The first phase utilized a wide range of sagittal and coronal conformity combinations to blanket a physically realistic design space. The second phase performed a focused investigation of the conformity conditions from the first phase to which predicted wear volume was sensitive. For the first phase, sagittal but not coronal conformity was found to have a significant effect on predicted wear volume. For the second phase, increased sagittal conformity was found to decrease predicted wear volume in a nonlinear fashion, with reductions gradually diminishing as conformity increased. These results suggest that TKR geometric design efforts aimed at minimizing wear should focus on sagittal rather than coronal conformity and that at least moderate sagittal conformity is desirable in both compartments.

Driving photomask supplier quality through automation

NASA Astrophysics Data System (ADS)

Russell, Drew; Espenscheid, Andrew

2007-10-01

In 2005, Freescale Semiconductor's newly centralized mask data prep organization (MSO) initiated a project to develop an automated global quality validation system for photomasks delivered to Freescale Semiconductor fabs. The system handles Certificate of Conformance (CofC) quality metric collection, validation, reporting and an alert system for all photomasks shipped to Freescale fabs from all qualified global suppliers. The completed system automatically collects 30+ quality metrics for each photomask shipped. Other quality metrics are generated from the collected data and quality metric conformance is automatically validated to specifications or control limits with failure alerts emailed to fab photomask and mask data prep engineering. A quality data warehouse stores the data for future analysis, which is performed quarterly. The improved access to data provided by the system has improved Freescale engineers' ability to spot trends and opportunities for improvement with our suppliers' processes. This paper will review each phase of the project, current system capabilities and quality system benefits for both our photomask suppliers and Freescale.

Automatic Selection of Order Parameters in the Analysis of Large Scale Molecular Dynamics Simulations.

PubMed

Sultan, Mohammad M; Kiss, Gert; Shukla, Diwakar; Pande, Vijay S

2014-12-09

Given the large number of crystal structures and NMR ensembles that have been solved to date, classical molecular dynamics (MD) simulations have become powerful tools in the atomistic study of the kinetics and thermodynamics of biomolecular systems on ever increasing time scales. By virtue of the high-dimensional conformational state space that is explored, the interpretation of large-scale simulations faces difficulties not unlike those in the big data community. We address this challenge by introducing a method called clustering based feature selection (CB-FS) that employs a posterior analysis approach. It combines supervised machine learning (SML) and feature selection with Markov state models to automatically identify the relevant degrees of freedom that separate conformational states. We highlight the utility of the method in the evaluation of large-scale simulations and show that it can be used for the rapid and automated identification of relevant order parameters involved in the functional transitions of two exemplary cell-signaling proteins central to human disease states.

Pyranopterin conformation defines the function of molybdenum and tungsten enzymes.

PubMed

Rothery, Richard A; Stein, Benjamin; Solomonson, Matthew; Kirk, Martin L; Weiner, Joel H

2012-09-11

We have analyzed the conformations of 319 pyranopterins in 102 protein structures of mononuclear molybdenum and tungsten enzymes. These span a continuum between geometries anticipated for quinonoid dihydro, tetrahydro, and dihydro oxidation states. We demonstrate that pyranopterin conformation is correlated with the protein folds defining the three major mononuclear molybdenum and tungsten enzyme families, and that binding-site micro-tuning controls pyranopterin oxidation state. Enzymes belonging to the bacterial dimethyl sulfoxide reductase (DMSOR) family contain a metal-bis-pyranopterin cofactor, the two pyranopterins of which have distinct conformations, with one similar to the predicted tetrahydro form, and the other similar to the predicted dihydro form. Enzymes containing a single pyranopterin belong to either the xanthine dehydrogenase (XDH) or sulfite oxidase (SUOX) families, and these have pyranopterin conformations similar to those predicted for tetrahydro and dihydro forms, respectively. This work provides keen insight into the roles of pyranopterin conformation and oxidation state in catalysis, redox potential modulation of the metal site, and catalytic function.

Guiding Conformation Space Search with an All-Atom Energy Potential

PubMed Central

Brunette, TJ; Brock, Oliver

2009-01-01

The most significant impediment for protein structure prediction is the inadequacy of conformation space search. Conformation space is too large and the energy landscape too rugged for existing search methods to consistently find near-optimal minima. To alleviate this problem, we present model-based search, a novel conformation space search method. Model-based search uses highly accurate information obtained during search to build an approximate, partial model of the energy landscape. Model-based search aggregates information in the model as it progresses, and in turn uses this information to guide exploration towards regions most likely to contain a near-optimal minimum. We validate our method by predicting the structure of 32 proteins, ranging in length from 49 to 213 amino acids. Our results demonstrate that model-based search is more effective at finding low-energy conformations in high-dimensional conformation spaces than existing search methods. The reduction in energy translates into structure predictions of increased accuracy. PMID:18536015

De novo protein structure prediction by dynamic fragment assembly and conformational space annealing.

PubMed

Lee, Juyong; Lee, Jinhyuk; Sasaki, Takeshi N; Sasai, Masaki; Seok, Chaok; Lee, Jooyoung

2011-08-01

Ab initio protein structure prediction is a challenging problem that requires both an accurate energetic representation of a protein structure and an efficient conformational sampling method for successful protein modeling. In this article, we present an ab initio structure prediction method which combines a recently suggested novel way of fragment assembly, dynamic fragment assembly (DFA) and conformational space annealing (CSA) algorithm. In DFA, model structures are scored by continuous functions constructed based on short- and long-range structural restraint information from a fragment library. Here, DFA is represented by the full-atom model by CHARMM with the addition of the empirical potential of DFIRE. The relative contributions between various energy terms are optimized using linear programming. The conformational sampling was carried out with CSA algorithm, which can find low energy conformations more efficiently than simulated annealing used in the existing DFA study. The newly introduced DFA energy function and CSA sampling algorithm are implemented into CHARMM. Test results on 30 small single-domain proteins and 13 template-free modeling targets of the 8th Critical Assessment of protein Structure Prediction show that the current method provides comparable and complementary prediction results to existing top methods. Copyright © 2011 Wiley-Liss, Inc.

Recent technical advances in general purpose mobile Satcom aviation terminals

NASA Technical Reports Server (NTRS)

Sydor, John T.

1990-01-01

A second general aviation amplitude companded single sideband (ACSSB) aeronautical terminal was developed for use with the Ontario Air Ambulance Service (OAAS). This terminal is designed to have automatic call set up and take down and to interface with the Public Service Telephone Network (PSTN) through a ground earth station hub controller. The terminal has integrated RF and microprocessor hardware which allows such functions as beam steering and automatic frequency control to be software controlled. The terminal uses a conformal patch array system to provide almost full azimuthal coverage. Antenna beam steering is executed without relying on aircraft supplied orientation information.

Maintaining and Enhancing Diversity of Sampled Protein Conformations in Robotics-Inspired Methods.

PubMed

Abella, Jayvee R; Moll, Mark; Kavraki, Lydia E

2018-01-01

The ability to efficiently sample structurally diverse protein conformations allows one to gain a high-level view of a protein's energy landscape. Algorithms from robot motion planning have been used for conformational sampling, and several of these algorithms promote diversity by keeping track of "coverage" in conformational space based on the local sampling density. However, large proteins present special challenges. In particular, larger systems require running many concurrent instances of these algorithms, but these algorithms can quickly become memory intensive because they typically keep previously sampled conformations in memory to maintain coverage estimates. In addition, robotics-inspired algorithms depend on defining useful perturbation strategies for exploring the conformational space, which is a difficult task for large proteins because such systems are typically more constrained and exhibit complex motions. In this article, we introduce two methodologies for maintaining and enhancing diversity in robotics-inspired conformational sampling. The first method addresses algorithms based on coverage estimates and leverages the use of a low-dimensional projection to define a global coverage grid that maintains coverage across concurrent runs of sampling. The second method is an automatic definition of a perturbation strategy through readily available flexibility information derived from B-factors, secondary structure, and rigidity analysis. Our results show a significant increase in the diversity of the conformations sampled for proteins consisting of up to 500 residues when applied to a specific robotics-inspired algorithm for conformational sampling. The methodologies presented in this article may be vital components for the scalability of robotics-inspired approaches.

Discriminating the structure of exo-2-aminonorbornane using nuclear quadrupole coupling interactions.

PubMed

Écija, Patricia; Cocinero, Emilio J; Lesarri, Alberto; Millán, Judith; Basterretxea, Francisco; Fernández, José A; Castaño, Fernando

2011-04-28

The intrinsic conformational and structural properties of the bicycle exo-2-aminonorbornane have been probed in a supersonic jet expansion using Fourier-transform microwave (FT-MW) spectroscopy and quantum chemical calculations. The rotational spectrum revealed two different conformers arising from the internal rotation of the amino group, exhibiting small (MHz) hyperfine patterns originated by the (14)N nuclear quadrupole coupling interaction. Complementary ab initio (MP2) and DFT (B3LYP and M05-2X) calculations provided comparative predictions for the structural properties, rotational and centrifugal distortion data, hyperfine parameters, and isomerization barriers. Due to the similarity of the rotational constants, the structural assignment of the observed rotamers and the calculation of the torsion angles of the amino group were based on the conformational dependence of the (14)N nuclear quadrupole coupling hyperfine tensor. In the most stable conformation (ss), the two amino N-H bonds are staggered with respect to the adjacent C-H bond. In the second conformer (st), only one of the N-H bonds is staggered and the other is trans. A third predicted conformer (ts) was not detected, consistent with a predicted conformational relaxation to conformer ss through a low barrier of 5.2 kJ mol(-1).

Synergistic use of compound properties and docking scores in neural network modeling of CYP2D6 binding: predicting affinity and conformational sampling.

PubMed

Bazeley, Peter S; Prithivi, Sridevi; Struble, Craig A; Povinelli, Richard J; Sem, Daniel S

2006-01-01

Cytochrome P450 2D6 (CYP2D6) is used to develop an approach for predicting affinity and relevant binding conformation(s) for highly flexible binding sites. The approach combines the use of docking scores and compound properties as attributes in building a neural network (NN) model. It begins by identifying segments of CYP2D6 that are important for binding specificity, based on structural variability among diverse CYP enzymes. A family of distinct, low-energy conformations of CYP2D6 are generated using simulated annealing (SA) and a collection of 82 compounds with known CYP2D6 affinities are docked. Interestingly, docking poses are observed on the backside of the heme as well as in the known active site. Docking scores for the active site binders, along with compound-specific attributes, are used to train a neural network model to properly bin compounds as strong binders, moderate binders, or nonbinders. Attribute selection is used to preselect the most important scores and compound-specific attributes for the model. A prediction accuracy of 85+/-6% is achieved. Dominant attributes include docking scores for three of the 20 conformations in the ensemble as well as the compound's formal charge, number of aromatic rings, and AlogP. Although compound properties were highly predictive attributes (12% improvement over baseline) in the NN-based prediction of CYP2D6 binders, their combined use with docking score attributes is synergistic (net increase of 23% above baseline). Beyond prediction of affinity, attribute selection provides a way to identify the most relevant protein conformation(s), in terms of binding competence. In the case of CYP2D6, three out of the ensemble of 20 SA-generated structures are found to be the most predictive for binding.

Computational prediction of the spectroscopic parameters of methanediol, an elusive molecule for interstellar detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barrientos, Carmen; Redondo, Pilar; Largo, Antonio

2014-04-01

The molecular structure of methanediol has been investigated by means of quantum chemical calculations. Two conformers, corresponding to C{sub 2} and C {sub s} symmetries, respectively, were considered. The C{sub 2} conformer is found to lie about 1.7 (at 298 K) or 2.3 (at 0 K) kcal mol{sup –1} below the C {sub s} conformer. Predictions for their rotational constants, vibrational frequencies, IR intensities, and dipole moments have been provided. The lowest-lying isomer has a very low dipole moment, around 0.03 D, whereas the C {sub s} conformer has a relatively high dipole moment, namely, 2.7 D. The barrier formore » the C {sub s} →C{sub 2} process is predicted to be around 0.7-1 kcal mol{sup –1}. Based on the energetic results the proportion of the C{sub s} conformer is likely to be negligible under low temperature conditions, such as in the interstellar medium. Therefore, it is predicted that detection by radioastronomy of methanediol would be rather unlikely.« less

Conformational free energy modeling of druglike molecules by metadynamics in the WHIM space.

PubMed

Spiwok, Vojtěch; Hlat-Glembová, Katarína; Tvaroška, Igor; Králová, Blanka

2012-03-26

Protein-ligand affinities can be significantly influenced not only by the interaction itself but also by conformational equilibrium of both binding partners, free ligand and free protein. Identification of important conformational families of a ligand and prediction of their thermodynamics is important for efficient ligand design. Here we report conformational free energy modeling of nine small-molecule drugs in explicitly modeled water by metadynamics with a bias potential applied in the space of weighted holistic invariant molecular (WHIM) descriptors. Application of metadynamics enhances conformational sampling compared to unbiased molecular dynamics simulation and allows to predict relative free energies of key conformations. Selected free energy minima and one example of transition state were tested by a series of unbiased molecular dynamics simulation. Comparison of free energy surfaces of free and target-bound Imatinib provides an estimate of free energy penalty of conformational change induced by its binding to the target. © 2012 American Chemical Society

Automatic Avoidance Tendencies for Alcohol Cues Predict Drinking After Detoxification Treatment in Alcohol Dependence

PubMed Central

2016-01-01

Alcohol dependence is characterized by conflict between approach and avoidance motivational orientations for alcohol that operate in automatic and controlled processes. This article describes the first study to investigate the predictive validity of these motivational orientations for relapse to drinking after discharge from alcohol detoxification treatment in alcohol-dependent patients. One hundred twenty alcohol-dependent patients who were nearing the end of inpatient detoxification treatment completed measures of self-reported (Approach and Avoidance of Alcohol Questionnaire; AAAQ) and automatic (modified Stimulus-Response Compatibility task) approach and avoidance motivational orientations for alcohol. Their drinking behavior was assessed via telephone follow-ups at 2, 4, and 6 months after discharge from treatment. Results indicated that, after controlling for the severity of alcohol dependence, strong automatic avoidance tendencies for alcohol cues were predictive of higher percentage of heavy drinking days (PHDD) at 4-month (β = 0.22, 95% CI [0.07, 0.43]) and 6-month (β = 0.22, 95% CI [0.01, 0.42]) follow-ups. We failed to replicate previous demonstrations of the predictive validity of approach subscales of the AAAQ for relapse to drinking, and there were no significant predictors of PHDD at 2-month follow-up. In conclusion, strong automatic avoidance tendencies predicted relapse to drinking after inpatient detoxification treatment, but automatic approach tendencies and self-reported approach and avoidance tendencies were not predictive in this study. Our results extend previous findings and help to resolve ambiguities with earlier studies that investigated the roles of automatic and controlled cognitive processes in recovery from alcohol dependence. PMID:27935726

Handling Trajectory Uncertainties for Airborne Conflict Management

NASA Technical Reports Server (NTRS)

Barhydt, Richard; Doble, Nathan A.; Karr, David; Palmer, Michael T.

2005-01-01

Airborne conflict management is an enabling capability for NASA's Distributed Air-Ground Traffic Management (DAG-TM) concept. DAGTM has the goal of significantly increasing capacity within the National Airspace System, while maintaining or improving safety. Under DAG-TM, autonomous aircraft maintain separation from each other and from managed aircraft unequipped for autonomous flight. NASA Langley Research Center has developed the Autonomous Operations Planner (AOP), an onboard decision support system that provides airborne conflict management (ACM) and strategic flight planning support for autonomous aircraft pilots. The AOP performs conflict detection, prevention, and resolution from nearby traffic aircraft and area hazards. Traffic trajectory information is assumed to be provided by Automatic Dependent Surveillance Broadcast (ADS-B). Reliable trajectory prediction is a key capability for providing effective ACM functions. Trajectory uncertainties due to environmental effects, differences in aircraft systems and performance, and unknown intent information lead to prediction errors that can adversely affect AOP performance. To accommodate these uncertainties, the AOP has been enhanced to create cross-track, vertical, and along-track buffers along the predicted trajectories of both ownship and traffic aircraft. These buffers will be structured based on prediction errors noted from previous simulations such as a recent Joint Experiment between NASA Ames and Langley Research Centers and from other outside studies. Currently defined ADS-B parameters related to navigation capability, trajectory type, and path conformance will be used to support the algorithms that generate the buffers.

24 CFR 985.103 - SEMAP score and overall performance rating.

Code of Federal Regulations, 2010 CFR

2010-04-01

... indicates that the auditor is unable to provide an opinion as to whether the PHA's financial statements are presented fairly in all material respects in conformity with generally accepted accounting principals, or an... in relation to the financial statements taken as a whole, the PHA will automatically be given an...

76 FR 30322 - Notice of Availability of Government-Owned Inventions; Available for Licensing

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-25

... below are assigned to the United States Government as represented by the Secretary of the Navy. U.S... ``Automatic Clock Synchronization and Distribution Circuit for Counter Clock Flow Pipelined Systems'' issued... Flow and Metallic Conformal Coating of Conductive Templates'' issued on October 12, 2010; U.S. Patent...

Binding Site and Potency Prediction of Teixobactin and other Lipid II Ligands by Statistical Base Scoring of Conformational Space Maps.

PubMed

Lungu, Claudiu N; Diudea, Mircea V

2018-01-01

Lipid II, a peptidoglycan, is a precursor in bacterial cell synthesis. It has both hydrophilic and lipophilic properties. The molecule translocates a bacterial membrane to deliver and incorporate "building blocks" from disaccharide-pentapeptide into the peptidoglican wall. Lipid II is a valid antibiotic target. A receptor binding pocket may be occupied by a ligand in various plausible conformations, among which only few ones are energetically related to a biological activity in the physiological efficiency domain. This paper reports the mapping of the conformational space of Lipid II in its interaction with Teixobactin and other Lipid II ligands. In order to study computationally the complex between Lipid II and ligands, a docking study was first carried on. Docking site was retrieved form literature. After docking, 5 ligand conformations and further 5 complexes (denoted 00 to 04) for each molecule were taken into account. For each structure, conformational studies were performed. Statistical analysis, conformational analysis and molecular dynamics based clustering were used to predict the potency of these compounds. A score for potency prediction was developed. Appling lipid II classification according to Lipid II conformational energy, a conformation of Teixobactin proved to be energetically favorable, followed by Oritravicin, Dalbavycin, Telvanicin, Teicoplamin and Vancomycin, respectively. Scoring of molecules according to cluster band and PCA produced the same result. Molecules classified according to standard deviations showed Dalbavycin as the most favorable conformation, followed by Teicoplamin, Telvanicin, Teixobactin, Oritravicin and Vancomycin, respectively. Total score showing best energetic efficiency of complex formation shows Teixobactin to have the best conformation (a score of 15 points) followed by Dalbavycin (14 points), Oritravicin (12v points), Telvanicin (10 points), Teicoplamin (9 points), Vancomycin (3 points). Statistical analysis of conformations can be used to predict the efficiency of ligand - target interaction and consecutively to find insight regarding ligand potency and postulate about favorable conformation of ligand and binding site. In this study it was shown that Teixobactin is more efficient in binding with Lipid II compared to Vancomycin, results confirmed by experimental data reported in literature. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Self-Learning Adaptive Umbrella Sampling Method for the Determination of Free Energy Landscapes in Multiple Dimensions

PubMed Central

Wojtas-Niziurski, Wojciech; Meng, Yilin; Roux, Benoit; Bernèche, Simon

2013-01-01

The potential of mean force describing conformational changes of biomolecules is a central quantity that determines the function of biomolecular systems. Calculating an energy landscape of a process that depends on three or more reaction coordinates might require a lot of computational power, making some of multidimensional calculations practically impossible. Here, we present an efficient automatized umbrella sampling strategy for calculating multidimensional potential of mean force. The method progressively learns by itself, through a feedback mechanism, which regions of a multidimensional space are worth exploring and automatically generates a set of umbrella sampling windows that is adapted to the system. The self-learning adaptive umbrella sampling method is first explained with illustrative examples based on simplified reduced model systems, and then applied to two non-trivial situations: the conformational equilibrium of the pentapeptide Met-enkephalin in solution and ion permeation in the KcsA potassium channel. With this method, it is demonstrated that a significant smaller number of umbrella windows needs to be employed to characterize the free energy landscape over the most relevant regions without any loss in accuracy. PMID:23814508

Automatic and strategic measures as predictors of mirror gazing among individuals with body dysmorphic disorder symptoms.

PubMed

Clerkin, Elise M; Teachman, Bethany A

2009-08-01

The current study tests cognitive-behavioral models of body dysmorphic disorder (BDD) by examining the relationship between cognitive biases and correlates of mirror gazing. To provide a more comprehensive picture, we investigated both relatively strategic (i.e., available for conscious introspection) and automatic (i.e., outside conscious control) measures of cognitive biases in a sample with either high (n = 32) or low (n = 31) BDD symptoms. Specifically, we examined the extent that (1) explicit interpretations tied to appearance, as well as (2) automatic associations and (3) strategic evaluations of the importance of attractiveness predict anxiety and avoidance associated with mirror gazing. Results indicated that interpretations tied to appearance uniquely predicted self-reported desire to avoid, whereas strategic evaluations of appearance uniquely predicted peak anxiety associated with mirror gazing, and automatic appearance associations uniquely predicted behavioral avoidance. These results offer considerable support for cognitive models of BDD, and suggest a dissociation between automatic and strategic measures.

Automatic and Strategic Measures as Predictors of Mirror Gazing Among Individuals with Body Dysmorphic Disorder Symptoms

PubMed Central

Clerkin, Elise M.; Teachman, Bethany A.

2011-01-01

The current study tests cognitive-behavioral models of body dysmorphic disorder (BDD) by examining the relationship between cognitive biases and correlates of mirror gazing. To provide a more comprehensive picture, we investigated both relatively strategic (i.e., available for conscious introspection) and automatic (i.e., outside conscious control) measures of cognitive biases in a sample with either high (n=32) or low (n=31) BDD symptoms. Specifically, we examined the extent that 1) explicit interpretations tied to appearance, as well as 2) automatic associations and 3) strategic evaluations of the importance of attractiveness predict anxiety and avoidance associated with mirror gazing. Results indicated that interpretations tied to appearance uniquely predicted self-reported desire to avoid, while strategic evaluations of appearance uniquely predicted peak anxiety associated with mirror gazing, and automatic appearance associations uniquely predicted behavioral avoidance. These results offer considerable support for cognitive models of BDD, and suggest a dissociation between automatic and strategic measures. PMID:19684496

An interoperable standard system for the automatic generation and publication of the fire risk maps based on Fire Weather Index (FWI)

NASA Astrophysics Data System (ADS)

Julià Selvas, Núria; Ninyerola Casals, Miquel

2015-04-01

It has been implemented an automatic system to predict the fire risk in the Principality of Andorra, a small country located in the eastern Pyrenees mountain range, bordered by Catalonia and France, due to its location, his landscape is a set of a rugged mountains with an average elevation around 2000 meters. The system is based on the Fire Weather Index (FWI) that consists on different components, each one, measuring a different aspect of the fire danger calculated by the values of the weather variables at midday. CENMA (Centre d'Estudis de la Neu i de la Muntanya d'Andorra) has a network around 10 automatic meteorological stations, located in different places, peeks and valleys, that measure weather data like relative humidity, wind direction and speed, surface temperature, rainfall and snow cover every ten minutes; this data is sent daily and automatically to the system implemented that will be processed in the way to filter incorrect measurements and to homogenizer measurement units. Then this data is used to calculate all components of the FWI at midday and for the level of each station, creating a database with the values of the homogeneous measurements and the FWI components for each weather station. In order to extend and model this data to all Andorran territory and to obtain a continuous map, an interpolation method based on a multiple regression with spline residual interpolation has been implemented. This interpolation considerer the FWI data as well as other relevant predictors such as latitude, altitude, global solar radiation and sea distance. The obtained values (maps) are validated using a cross-validation leave-one-out method. The discrete and continuous maps are rendered in tiled raster maps and published in a web portal conform to Web Map Service (WMS) Open Geospatial Consortium (OGC) standard. Metadata and other reference maps (fuel maps, topographic maps, etc) are also available from this geoportal.

Three Dimensional Sector Design with Optimal Number of Sectors

NASA Technical Reports Server (NTRS)

Xue, Min

2010-01-01

In the national airspace system, sectors get overloaded due to high traffic demand and inefficient airspace designs. Overloads can be eliminated in some cases by redesigning sector boundaries. This paper extends the Voronoi-based sector design method by automatically selecting the number of sectors, allowing three-dimensional partitions, and enforcing traffic pattern conformance. The method was used to design sectors at Fort-Worth and Indianapolis centers for current traffic scenarios. Results show that new designs can eliminate overloaded sectors, although not in all cases, reduce the number of necessary sectors, and conform to major traffic patterns. Overall, the new methodology produces enhanced and efficient sector designs.

Automatic mental associations predict future choices of undecided decision-makers.

PubMed

Galdi, Silvia; Arcuri, Luciano; Gawronski, Bertram

2008-08-22

Common wisdom holds that choice decisions are based on conscious deliberations of the available information about choice options. On the basis of recent insights about unconscious influences on information processing, we tested whether automatic mental associations of undecided individuals bias future choices in a manner such that these choices reflect the evaluations implied by earlier automatic associations. With the use of a computer-based, speeded categorization task to assess automatic mental associations (i.e., associations that are activated unintentionally, difficult to control, and not necessarily endorsed at a conscious level) and self-report measures to assess consciously endorsed beliefs and choice preferences, automatic associations of undecided participants predicted changes in consciously reported beliefs and future choices over a period of 1 week. Conversely, for decided participants, consciously reported beliefs predicted changes in automatic associations and future choices over the same period. These results indicate that decision-makers sometimes have already made up their mind at an unconscious level, even when they consciously indicate that they are still undecided.

Automatic avoidance tendencies for alcohol cues predict drinking after detoxification treatment in alcohol dependence.

PubMed

Field, Matt; Di Lemma, Lisa; Christiansen, Paul; Dickson, Joanne

2017-03-01

Alcohol dependence is characterized by conflict between approach and avoidance motivational orientations for alcohol that operate in automatic and controlled processes. This article describes the first study to investigate the predictive validity of these motivational orientations for relapse to drinking after discharge from alcohol detoxification treatment in alcohol-dependent patients. One hundred twenty alcohol-dependent patients who were nearing the end of inpatient detoxification treatment completed measures of self-reported (Approach and Avoidance of Alcohol Questionnaire; AAAQ) and automatic (modified Stimulus-Response Compatibility task) approach and avoidance motivational orientations for alcohol. Their drinking behavior was assessed via telephone follow-ups at 2, 4, and 6 months after discharge from treatment. Results indicated that, after controlling for the severity of alcohol dependence, strong automatic avoidance tendencies for alcohol cues were predictive of higher percentage of heavy drinking days (PHDD) at 4-month (β = 0.22, 95% CI [0.07, 0.43]) and 6-month (β = 0.22, 95% CI [0.01, 0.42]) follow-ups. We failed to replicate previous demonstrations of the predictive validity of approach subscales of the AAAQ for relapse to drinking, and there were no significant predictors of PHDD at 2-month follow-up. In conclusion, strong automatic avoidance tendencies predicted relapse to drinking after inpatient detoxification treatment, but automatic approach tendencies and self-reported approach and avoidance tendencies were not predictive in this study. Our results extend previous findings and help to resolve ambiguities with earlier studies that investigated the roles of automatic and controlled cognitive processes in recovery from alcohol dependence. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Towards parsimony in habit measurement: Testing the convergent and predictive validity of an automaticity subscale of the Self-Report Habit Index

PubMed Central

2012-01-01

Background The twelve-item Self-Report Habit Index (SRHI) is the most popular measure of energy-balance related habits. This measure characterises habit by automatic activation, behavioural frequency, and relevance to self-identity. Previous empirical research suggests that the SRHI may be abbreviated with no losses in reliability or predictive utility. Drawing on recent theorising suggesting that automaticity is the ‘active ingredient’ of habit-behaviour relationships, we tested whether an automaticity-specific SRHI subscale could capture habit-based behaviour patterns in self-report data. Methods A content validity task was undertaken to identify a subset of automaticity indicators within the SRHI. The reliability, convergent validity and predictive validity of the automaticity item subset was subsequently tested in secondary analyses of all previous SRHI applications, identified via systematic review, and in primary analyses of four raw datasets relating to energy‐balance relevant behaviours (inactive travel, active travel, snacking, and alcohol consumption). Results A four-item automaticity subscale (the ‘Self-Report Behavioural Automaticity Index’; ‘SRBAI’) was found to be reliable and sensitive to two hypothesised effects of habit on behaviour: a habit-behaviour correlation, and a moderating effect of habit on the intention-behaviour relationship. Conclusion The SRBAI offers a parsimonious measure that adequately captures habitual behaviour patterns. The SRBAI may be of particular utility in predicting future behaviour and in studies tracking habit formation or disruption. PMID:22935297

Conformational stability, r(0) structural parameters, vibrational assignments and ab initio calculations of ethyldichlorophosphine.

PubMed

Darkhalil, Ikhlas D; Paquet, Charles; Waqas, Mohammad; Gounev, Todor K; Durig, James R

2015-02-05

Variable temperature (-60 to -100 °C) studies of ethyldichlorophosphine, CH3CH2PCl2, of the infrared spectra (4000-400 cm(-1)) dissolved in liquid xenon have been carried out. From these data, the two conformers have been identified and the enthalpy difference has been determined between the more stable trans conformer and the less stable gauche form to be 88±9 cm(-1) (1.04±0.11 kJ/mol). The percentage of abundance of the gauche conformer is estimated to be 57% at ambient temperature. The conformational stabilities have been predicted from ab initio calculations by utilizing many different basis sets up to aug-cc-pVTZ for both MP2(full) and density functional theory calculations by the B3LYP method. Vibrational assignments have been provided for both conformers which have been predicted by MP2(full)/6-31G(d) ab initio calculations to predict harmonic force fields, wavenumbers of the fundamentals, infrared intensities, Raman activities and depolarization ratios for both conformers. Estimated r0 structural parameters have been obtained from adjusted MP2(full)/6-311+G(d,p) calculations. The results are discussed and compared to the corresponding properties of some related molecules. Copyright © 2014 Elsevier B.V. All rights reserved.

Validation of the ICU-DaMa tool for automatically extracting variables for minimum dataset and quality indicators: The importance of data quality assessment.

PubMed

Sirgo, Gonzalo; Esteban, Federico; Gómez, Josep; Moreno, Gerard; Rodríguez, Alejandro; Blanch, Lluis; Guardiola, Juan José; Gracia, Rafael; De Haro, Lluis; Bodí, María

2018-04-01

Big data analytics promise insights into healthcare processes and management, improving outcomes while reducing costs. However, data quality is a major challenge for reliable results. Business process discovery techniques and an associated data model were used to develop data management tool, ICU-DaMa, for extracting variables essential for overseeing the quality of care in the intensive care unit (ICU). To determine the feasibility of using ICU-DaMa to automatically extract variables for the minimum dataset and ICU quality indicators from the clinical information system (CIS). The Wilcoxon signed-rank test and Fisher's exact test were used to compare the values extracted from the CIS with ICU-DaMa for 25 variables from all patients attended in a polyvalent ICU during a two-month period against the gold standard of values manually extracted by two trained physicians. Discrepancies with the gold standard were classified into plausibility, conformance, and completeness errors. Data from 149 patients were included. Although there were no significant differences between the automatic method and the manual method, we detected differences in values for five variables, including one plausibility error and two conformance and completeness errors. Plausibility: 1) Sex, ICU-DaMa incorrectly classified one male patient as female (error generated by the Hospital's Admissions Department). Conformance: 2) Reason for isolation, ICU-DaMa failed to detect a human error in which a professional misclassified a patient's isolation. 3) Brain death, ICU-DaMa failed to detect another human error in which a professional likely entered two mutually exclusive values related to the death of the patient (brain death and controlled donation after circulatory death). Completeness: 4) Destination at ICU discharge, ICU-DaMa incorrectly classified two patients due to a professional failing to fill out the patient discharge form when thepatients died. 5) Length of continuous renal replacement therapy, data were missing for one patient because the CRRT device was not connected to the CIS. Automatic generation of minimum dataset and ICU quality indicators using ICU-DaMa is feasible. The discrepancies were identified and can be corrected by improving CIS ergonomics, training healthcare professionals in the culture of the quality of information, and using tools for detecting and correcting data errors. Copyright © 2018 Elsevier B.V. All rights reserved.

Dosimetric validation for an automatic brain metastases planning software using single-isocenter dynamic conformal arcsDosimetric validation for an automatic brain metastases planning software using single-isocenter dynamic conformal arcs.

PubMed

Liu, Haisong; Li, Jun; Pappas, Evangelos; Andrews, David; Evans, James; Werner-Wasik, Maria; Yu, Yan; Dicker, Adam; Shi, Wenyin

2016-09-08

An automatic brain-metastases planning (ABMP) software has been installed in our institution. It is dedicated for treating multiple brain metastases with radiosurgery on linear accelerators (linacs) using a single-setup isocenter with noncoplanar dynamic conformal arcs. This study is to validate the calculated absolute dose and dose distribution of ABMP. Three types of measurements were performed to validate the planning software: 1, dual micro ion chambers were used with an acrylic phantom to measure the absolute dose; 2, a 3D cylindrical phantom with dual diode array was used to evaluate 2D dose distribution and point dose for smaller targets; and 3, a 3D pseudo-in vivo patient-specific phantom filled with polymer gels was used to evaluate the accuracy of 3D dose distribution and radia-tion delivery. Micro chamber measurement of two targets (volumes of 1.2 cc and 0.9 cc, respectively) showed that the percentage differences of the absolute dose at both targets were less than 1%. Averaged GI passing rate of five different plans measured with the diode array phantom was above 98%, using criteria of 3% dose difference, 1 mm distance to agreement (DTA), and 10% low-dose threshold. 3D gel phantom measurement results demonstrated a 3D displacement of nine targets of 0.7 ± 0.4 mm (range 0.2 ~ 1.1 mm). The averaged two-dimensional (2D) GI passing rate for several region of interests (ROI) on axial slices that encompass each one of the nine targets was above 98% (5% dose difference, 2 mm DTA, and 10% low-dose threshold). Measured D95, the minimum dose that covers 95% of the target volume, of the nine targets was 0.7% less than the calculated D95. Three different types of dosimetric verification methods were used and proved the dose calculation of the new automatic brain metastases planning (ABMP) software was clinical acceptable. The 3D pseudo-in vivo patient-specific gel phantom test also served as an end-to-end test for validating not only the dose calculation, but the treatment delivery accuracy as well. © 2016 The Authors.

40 CFR 1045.320 - What happens if one of my production-line engines fails to meet emission standards?

Code of Federal Regulations, 2012 CFR

2012-07-01

...-line engines fails to meet emission standards? 1045.320 Section 1045.320 Protection of Environment... production-line engines fails to meet emission standards? (a) If you have a production-line engine with final... conformity is automatically suspended for that failing engine. You must take the following actions before...

40 CFR 1045.320 - What happens if one of my production-line engines fails to meet emission standards?

Code of Federal Regulations, 2010 CFR

2010-07-01

...-line engines fails to meet emission standards? 1045.320 Section 1045.320 Protection of Environment... production-line engines fails to meet emission standards? (a) If you have a production-line engine with final... conformity is automatically suspended for that failing engine. You must take the following actions before...

40 CFR 1042.320 - What happens if one of my production-line engines fails to meet emission standards?

Code of Federal Regulations, 2012 CFR

2012-07-01

...-line engines fails to meet emission standards? 1042.320 Section 1042.320 Protection of Environment... if one of my production-line engines fails to meet emission standards? (a) If you have a production....315(a)), the certificate of conformity is automatically suspended for that failing engine. You must...

40 CFR 1042.320 - What happens if one of my production-line engines fails to meet emission standards?

Code of Federal Regulations, 2011 CFR

2011-07-01

...-line engines fails to meet emission standards? 1042.320 Section 1042.320 Protection of Environment... if one of my production-line engines fails to meet emission standards? (a) If you have a production....315(a)), the certificate of conformity is automatically suspended for that failing engine. You must...

40 CFR 1048.320 - What happens if one of my production-line engines fails to meet emission standards?

Code of Federal Regulations, 2012 CFR

2012-07-01

...-line engines fails to meet emission standards? 1048.320 Section 1048.320 Protection of Environment...-line engines fails to meet emission standards? If you have a production-line engine with final... conformity is automatically suspended for that failing engine. You must take the following actions before...

40 CFR 1054.320 - What happens if one of my production-line engines fails to meet emission standards?

Code of Federal Regulations, 2011 CFR

2011-07-01

...-line engines fails to meet emission standards? 1054.320 Section 1054.320 Protection of Environment... production-line engines fails to meet emission standards? (a) If you have a production-line engine with final... conformity is automatically suspended for that failing engine. You must take the following actions before...

40 CFR 1045.320 - What happens if one of my production-line engines fails to meet emission standards?

Code of Federal Regulations, 2011 CFR

2011-07-01

...-line engines fails to meet emission standards? 1045.320 Section 1045.320 Protection of Environment... production-line engines fails to meet emission standards? (a) If you have a production-line engine with final... conformity is automatically suspended for that failing engine. You must take the following actions before...

40 CFR 1048.320 - What happens if one of my production-line engines fails to meet emission standards?

Code of Federal Regulations, 2010 CFR

2010-07-01

...-line engines fails to meet emission standards? 1048.320 Section 1048.320 Protection of Environment...-line engines fails to meet emission standards? If you have a production-line engine with final... conformity is automatically suspended for that failing engine. You must take the following actions before...

40 CFR 1048.320 - What happens if one of my production-line engines fails to meet emission standards?

Code of Federal Regulations, 2011 CFR

2011-07-01

...-line engines fails to meet emission standards? 1048.320 Section 1048.320 Protection of Environment...-line engines fails to meet emission standards? If you have a production-line engine with final... conformity is automatically suspended for that failing engine. You must take the following actions before...

40 CFR 1042.320 - What happens if one of my production-line engines fails to meet emission standards?

Code of Federal Regulations, 2010 CFR

2010-07-01

...-line engines fails to meet emission standards? 1042.320 Section 1042.320 Protection of Environment... if one of my production-line engines fails to meet emission standards? (a) If you have a production....315(a)), the certificate of conformity is automatically suspended for that failing engine. You must...

40 CFR 1054.320 - What happens if one of my production-line engines fails to meet emission standards?

Code of Federal Regulations, 2012 CFR

2012-07-01

...-line engines fails to meet emission standards? 1054.320 Section 1054.320 Protection of Environment... production-line engines fails to meet emission standards? (a) If you have a production-line engine with final... conformity is automatically suspended for that failing engine. You must take the following actions before...

76 FR 20412 - Self-Regulatory Organizations; National Stock Exchange, Inc.; Notice of Filing and Immediate...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-12

... least one dollar. With respect to the rebate for Zero Display Orders that add liquidity in AutoEx that... in the Automatic Execution Mode of order interaction (``AutoEx'') \\3\\ priced at least one dollar. Certain conforming changes are also proposed for rebates for liquidity adding Zero Display Orders \\4\\ in...

29 CFR 1910.126 - Additional requirements for special dipping and coating operations.

Code of Federal Regulations, 2011 CFR

2011-07-01

... sprinklers; or (ii) An automatic fire-extinguishing system conforming to the requirements of subpart L of... the alarm set point, you must equip the tank with a circulating cooling system. (5) If the tank has a bottom drain, the bottom drain may be combined with the oil-circulating system. (6) You must not use air...

29 CFR 1910.126 - Additional requirements for special dipping and coating operations.

Code of Federal Regulations, 2010 CFR

2010-07-01

... sprinklers; or (ii) An automatic fire-extinguishing system conforming to the requirements of subpart L of... the alarm set point, you must equip the tank with a circulating cooling system. (5) If the tank has a bottom drain, the bottom drain may be combined with the oil-circulating system. (6) You must not use air...

Conformational analysis and circular dichroism of bilirubin, the yellow pigment of jaundice

NASA Astrophysics Data System (ADS)

Lightner, David A.; Person, Richard; Peterson, Blake; Puzicha, Gisbert; Pu, Yu-Ming; Bojadziev, Stefan

1991-06-01

Conformational analysis of (4Z, 15Z)-bilirubin-IX(alpha) by molecular mechanics computations reveals a global energy minimum folded conformation. Powerful added stabilization is achieved through intramolecular hydrogen bonding. Theoretical treatment of bilirubin as a molecular exciton predicts an intense bisignate circular dichroism spectrum for the folded conformation: (Delta) (epsilon) is congruent to 270 L (DOT) mole-1 (DOT) cm-1 for the $OM450 nm electronic transition(s). Synthesis of bilirubin analogs with propionic acid groups methylated at the (alpha) or (beta) position introduces an allosteric effect that allows for an optical resolution of the pigments, with enantiomers exhibiting the theoretically predicted circular dichroism.

Automatic detection of adverse events to predict drug label changes using text and data mining techniques.

PubMed

Gurulingappa, Harsha; Toldo, Luca; Rajput, Abdul Mateen; Kors, Jan A; Taweel, Adel; Tayrouz, Yorki

2013-11-01

The aim of this study was to assess the impact of automatically detected adverse event signals from text and open-source data on the prediction of drug label changes. Open-source adverse effect data were collected from FAERS, Yellow Cards and SIDER databases. A shallow linguistic relation extraction system (JSRE) was applied for extraction of adverse effects from MEDLINE case reports. Statistical approach was applied on the extracted datasets for signal detection and subsequent prediction of label changes issued for 29 drugs by the UK Regulatory Authority in 2009. 76% of drug label changes were automatically predicted. Out of these, 6% of drug label changes were detected only by text mining. JSRE enabled precise identification of four adverse drug events from MEDLINE that were undetectable otherwise. Changes in drug labels can be predicted automatically using data and text mining techniques. Text mining technology is mature and well-placed to support the pharmacovigilance tasks. Copyright © 2013 John Wiley & Sons, Ltd.

Side-chain conformational space analysis (SCSA): A multi conformation-based QSAR approach for modeling and prediction of protein-peptide binding affinities

NASA Astrophysics Data System (ADS)

Zhou, Peng; Chen, Xiang; Shang, Zhicai

2009-03-01

In this article, the concept of multi conformation-based quantitative structure-activity relationship (MCB-QSAR) is proposed, and based upon that, we describe a new approach called the side-chain conformational space analysis (SCSA) to model and predict protein-peptide binding affinities. In SCSA, multi-conformations (rather than traditional single-conformation) have received much attention, and the statistical average information on multi-conformations of side chains is determined using self-consistent mean field theory based upon side chain rotamer library. Thereby, enthalpy contributions (including electrostatic, steric, hydrophobic interaction and hydrogen bond) and conformational entropy effects to the binding are investigated in terms of occurrence probability of residue rotamers. Then, SCSA was applied into the dataset of 419 HLA-A*0201 binding peptides, and nonbonding contributions of each position in peptide ligands are well determined. For the peptides, the hydrogen bond and electrostatic interactions of the two ends are essential to the binding specificity, van der Waals and hydrophobic interactions of all the positions ensure strong binding affinity, and the loss of conformational entropy at anchor positions partially counteracts other favorable nonbonding effects.

Automatic intraaortic balloon pump timing using an intrabeat dicrotic notch prediction algorithm.

PubMed

Schreuder, Jan J; Castiglioni, Alessandro; Donelli, Andrea; Maisano, Francesco; Jansen, Jos R C; Hanania, Ramzi; Hanlon, Pat; Bovelander, Jan; Alfieri, Ottavio

2005-03-01

The efficacy of intraaortic balloon counterpulsation (IABP) during arrhythmic episodes is questionable. A novel algorithm for intrabeat prediction of the dicrotic notch was used for real time IABP inflation timing control. A windkessel model algorithm was used to calculate real-time aortic flow from aortic pressure. The dicrotic notch was predicted using a percentage of calculated peak flow. Automatic inflation timing was set at intrabeat predicted dicrotic notch and was combined with automatic IAB deflation. Prophylactic IABP was applied in 27 patients with low ejection fraction (< 35%) undergoing cardiac surgery. Analysis of IABP at a 1:4 ratio revealed that IAB inflation occurred at a mean of 0.6 +/- 5 ms from the dicrotic notch. In all patients accurate automatic timing at a 1:1 assist ratio was performed. Seventeen patients had episodes of severe arrhythmia, the novel IABP inflation algorithm accurately assisted 318 of 320 arrhythmic beats at a 1:1 ratio. The novel real-time intrabeat IABP inflation timing algorithm performed accurately in all patients during both regular rhythms and severe arrhythmia, allowing fully automatic intrabeat IABP timing.

Using 1H and 13C NMR chemical shifts to determine cyclic peptide conformations: a combined molecular dynamics and quantum mechanics approach.

PubMed

Nguyen, Q Nhu N; Schwochert, Joshua; Tantillo, Dean J; Lokey, R Scott

2018-05-10

Solving conformations of cyclic peptides can provide insight into structure-activity and structure-property relationships, which can help in the design of compounds with improved bioactivity and/or ADME characteristics. The most common approaches for determining the structures of cyclic peptides are based on NMR-derived distance restraints obtained from NOESY or ROESY cross-peak intensities, and 3J-based dihedral restraints using the Karplus relationship. Unfortunately, these observables are often too weak, sparse, or degenerate to provide unequivocal, high-confidence solution structures, prompting us to investigate an alternative approach that relies only on 1H and 13C chemical shifts as experimental observables. This method, which we call conformational analysis from NMR and density-functional prediction of low-energy ensembles (CANDLE), uses molecular dynamics (MD) simulations to generate conformer families and density functional theory (DFT) calculations to predict their 1H and 13C chemical shifts. Iterative conformer searches and DFT energy calculations on a cyclic peptide-peptoid hybrid yielded Boltzmann ensembles whose predicted chemical shifts matched the experimental values better than any single conformer. For these compounds, CANDLE outperformed the classic NOE- and 3J-coupling-based approach by disambiguating similar β-turn types and also enabled the structural elucidation of the minor conformer. Through the use of chemical shifts, in conjunction with DFT and MD calculations, CANDLE can help illuminate conformational ensembles of cyclic peptides in solution.

MARZ: Manual and automatic redshifting software

NASA Astrophysics Data System (ADS)

Hinton, S. R.; Davis, Tamara M.; Lidman, C.; Glazebrook, K.; Lewis, G. F.

2016-04-01

The Australian Dark Energy Survey (OzDES) is a 100-night spectroscopic survey underway on the Anglo-Australian Telescope using the fibre-fed 2-degree-field (2dF) spectrograph. We have developed a new redshifting application MARZ with greater usability, flexibility, and the capacity to analyse a wider range of object types than the RUNZ software package previously used for redshifting spectra from 2dF. MARZ is an open-source, client-based, Javascript web-application which provides an intuitive interface and powerful automatic matching capabilities on spectra generated from the AAOmega spectrograph to produce high quality spectroscopic redshift measurements. The software can be run interactively or via the command line, and is easily adaptable to other instruments and pipelines if conforming to the current FITS file standard is not possible. Behind the scenes, a modified version of the AUTOZ cross-correlation algorithm is used to match input spectra against a variety of stellar and galaxy templates, and automatic matching performance for OzDES spectra has increased from 54% (RUNZ) to 91% (MARZ). Spectra not matched correctly by the automatic algorithm can be easily redshifted manually by cycling automatic results, manual template comparison, or marking spectral features.

Assessment of Protein Side-Chain Conformation Prediction Methods in Different Residue Environments

PubMed Central

Peterson, Lenna X.; Kang, Xuejiao; Kihara, Daisuke

2016-01-01

Computational prediction of side-chain conformation is an important component of protein structure prediction. Accurate side-chain prediction is crucial for practical applications of protein structure models that need atomic detailed resolution such as protein and ligand design. We evaluated the accuracy of eight side-chain prediction methods in reproducing the side-chain conformations of experimentally solved structures deposited to the Protein Data Bank. Prediction accuracy was evaluated for a total of four different structural environments (buried, surface, interface, and membrane-spanning) in three different protein types (monomeric, multimeric, and membrane). Overall, the highest accuracy was observed for buried residues in monomeric and multimeric proteins. Notably, side-chains at protein interfaces and membrane-spanning regions were better predicted than surface residues even though the methods did not all use multimeric and membrane proteins for training. Thus, we conclude that the current methods are as practically useful for modeling protein docking interfaces and membrane-spanning regions as for modeling monomers. PMID:24619909

First experiences with the LHC BLM sanity checks

NASA Astrophysics Data System (ADS)

Emery, J.; Dehning, B.; Effinger, E.; Nordt, A.; Sapinski, M. G.; Zamantzas, C.

2010-12-01

The reliability concerns have driven the design of the Large Hardron Collider (LHC) Beam Loss Monitoring (BLM) system from the early stage of the studies up to the present commissioning and the latest development of diagnostic tools. To protect the system against non-conformities, new ways of automatic checking have been developed and implemented. These checks are regularly and systematically executed by the LHC operation team to ensure that the system status is after each test "as good as new". The sanity checks are part of this strategy. They are testing the electrical part of the detectors (ionisation chamber or secondary emission detector), their cable connections to the front-end electronics, further connections to the back-end electronics and their ability to request a beam abort. During the installation and in the early commissioning phase, these checks have shown their ability to find also non-conformities caused by unexpected failure event scenarios. In every day operation, a non-conformity discovered by this check inhibits any further injections into the LHC until the check confirms the absence of non-conformities.

The Conforming Brain and Deontological Resolve

PubMed Central

Pincus, Melanie; LaViers, Lisa; Prietula, Michael J.; Berns, Gregory

2014-01-01

Our personal values are subject to forces of social influence. Deontological resolve captures how strongly one relies on absolute rules of right and wrong in the representation of one's personal values and may predict willingness to modify one's values in the presence of social influence. Using fMRI, we found that a neurobiological metric for deontological resolve based on relative activity in the ventrolateral prefrontal cortex (VLPFC) during the passive processing of sacred values predicted individual differences in conformity. Individuals with stronger deontological resolve, as measured by greater VLPFC activity, displayed lower levels of conformity. We also tested whether responsiveness to social reward, as measured by ventral striatal activity during social feedback, predicted variability in conformist behavior across individuals but found no significant relationship. From these results we conclude that unwillingness to conform to others' values is associated with a strong neurobiological representation of social rules. PMID:25170989

Machine Learning Estimates of Natural Product Conformational Energies

PubMed Central

Rupp, Matthias; Bauer, Matthias R.; Wilcken, Rainer; Lange, Andreas; Reutlinger, Michael; Boeckler, Frank M.; Schneider, Gisbert

2014-01-01

Machine learning has been used for estimation of potential energy surfaces to speed up molecular dynamics simulations of small systems. We demonstrate that this approach is feasible for significantly larger, structurally complex molecules, taking the natural product Archazolid A, a potent inhibitor of vacuolar-type ATPase, from the myxobacterium Archangium gephyra as an example. Our model estimates energies of new conformations by exploiting information from previous calculations via Gaussian process regression. Predictive variance is used to assess whether a conformation is in the interpolation region, allowing a controlled trade-off between prediction accuracy and computational speed-up. For energies of relaxed conformations at the density functional level of theory (implicit solvent, DFT/BLYP-disp3/def2-TZVP), mean absolute errors of less than 1 kcal/mol were achieved. The study demonstrates that predictive machine learning models can be developed for structurally complex, pharmaceutically relevant compounds, potentially enabling considerable speed-ups in simulations of larger molecular structures. PMID:24453952

Modelling proteins' hidden conformations to predict antibiotic resistance

NASA Astrophysics Data System (ADS)

Hart, Kathryn M.; Ho, Chris M. W.; Dutta, Supratik; Gross, Michael L.; Bowman, Gregory R.

2016-10-01

TEM β-lactamase confers bacteria with resistance to many antibiotics and rapidly evolves activity against new drugs. However, functional changes are not easily explained by differences in crystal structures. We employ Markov state models to identify hidden conformations and explore their role in determining TEM's specificity. We integrate these models with existing drug-design tools to create a new technique, called Boltzmann docking, which better predicts TEM specificity by accounting for conformational heterogeneity. Using our MSMs, we identify hidden states whose populations correlate with activity against cefotaxime. To experimentally detect our predicted hidden states, we use rapid mass spectrometric footprinting and confirm our models' prediction that increased cefotaxime activity correlates with reduced Ω-loop flexibility. Finally, we design novel variants to stabilize the hidden cefotaximase states, and find their populations predict activity against cefotaxime in vitro and in vivo. Therefore, we expect this framework to have numerous applications in drug and protein design.

Modelling proteins’ hidden conformations to predict antibiotic resistance

PubMed Central

Hart, Kathryn M.; Ho, Chris M. W.; Dutta, Supratik; Gross, Michael L.; Bowman, Gregory R.

2016-01-01

TEM β-lactamase confers bacteria with resistance to many antibiotics and rapidly evolves activity against new drugs. However, functional changes are not easily explained by differences in crystal structures. We employ Markov state models to identify hidden conformations and explore their role in determining TEM’s specificity. We integrate these models with existing drug-design tools to create a new technique, called Boltzmann docking, which better predicts TEM specificity by accounting for conformational heterogeneity. Using our MSMs, we identify hidden states whose populations correlate with activity against cefotaxime. To experimentally detect our predicted hidden states, we use rapid mass spectrometric footprinting and confirm our models’ prediction that increased cefotaxime activity correlates with reduced Ω-loop flexibility. Finally, we design novel variants to stabilize the hidden cefotaximase states, and find their populations predict activity against cefotaxime in vitro and in vivo. Therefore, we expect this framework to have numerous applications in drug and protein design. PMID:27708258

Conformational switching upon phosphorylation: a predictive framework based on energy landscape principles.

PubMed

Lätzer, Joachim; Shen, Tongye; Wolynes, Peter G

2008-02-19

We investigate how post-translational phosphorylation modifies the global conformation of a protein by changing its free energy landscape using two test proteins, cystatin and NtrC. We first examine the changes in a free energy landscape caused by phosphorylation using a model containing information about both structural forms. For cystatin the free energy cost is fairly large indicating a low probability of sampling the phosphorylated conformation in a perfectly funneled landscape. The predicted barrier for NtrC conformational transition is several times larger than the barrier for cystatin, indicating that the switch protein NtrC most probably follows a partial unfolding mechanism to move from one basin to the other. Principal component analysis and linear response theory show how the naturally occurring conformational changes in unmodified proteins are captured and stabilized by the change of interaction potential. We also develop a partially guided structure prediction Hamiltonian which is capable of predicting the global structure of a phosphorylated protein using only knowledge of the structure of the unphosphorylated protein or vice versa. This algorithm makes use of a generic transferable long-range residue contact potential along with details of structure short range in sequence. By comparing the results obtained with this guided transferable potential to those from the native-only, perfectly funneled Hamiltonians, we show that the transferable Hamiltonian correctly captures the nature of the global conformational changes induced by phosphorylation and can sample substantially correct structures for the modified protein with high probability.

Conformational Heterogeneity of Unbound Proteins Enhances Recognition in Protein-Protein Encounters.

PubMed

Pallara, Chiara; Rueda, Manuel; Abagyan, Ruben; Fernández-Recio, Juan

2016-07-12

To understand cellular processes at the molecular level we need to improve our knowledge of protein-protein interactions, from a structural, mechanistic, and energetic point of view. Current theoretical studies and computational docking simulations show that protein dynamics plays a key role in protein association and support the need for including protein flexibility in modeling protein interactions. Assuming the conformational selection binding mechanism, in which the unbound state can sample bound conformers, one possible strategy to include flexibility in docking predictions would be the use of conformational ensembles originated from unbound protein structures. Here we present an exhaustive computational study about the use of precomputed unbound ensembles in the context of protein docking, performed on a set of 124 cases of the Protein-Protein Docking Benchmark 3.0. Conformational ensembles were generated by conformational optimization and refinement with MODELLER and by short molecular dynamics trajectories with AMBER. We identified those conformers providing optimal binding and investigated the role of protein conformational heterogeneity in protein-protein recognition. Our results show that a restricted conformational refinement can generate conformers with better binding properties and improve docking encounters in medium-flexible cases. For more flexible cases, a more extended conformational sampling based on Normal Mode Analysis was proven helpful. We found that successful conformers provide better energetic complementarity to the docking partners, which is compatible with recent views of binding association. In addition to the mechanistic considerations, these findings could be exploited for practical docking predictions of improved efficiency.

Developing hybrid approaches to predict pKa values of ionizable groups

PubMed Central

Witham, Shawn; Talley, Kemper; Wang, Lin; Zhang, Zhe; Sarkar, Subhra; Gao, Daquan; Yang, Wei

2011-01-01

Accurate predictions of pKa values of titratable groups require taking into account all relevant processes associated with the ionization/deionization. Frequently, however, the ionization does not involve significant structural changes and the dominating effects are purely electrostatic in origin allowing accurate predictions to be made based on the electrostatic energy difference between ionized and neutral forms alone using a static structure. On another hand, if the change of the charge state is accompanied by a structural reorganization of the target protein, then the relevant conformational changes have to be taken into account in the pKa calculations. Here we report a hybrid approach that first predicts the titratable groups, which ionization is expected to cause conformational changes, termed “problematic” residues, then applies a special protocol on them, while the rest of the pKa’s are predicted with rigid backbone approach as implemented in multi-conformation continuum electrostatics (MCCE) method. The backbone representative conformations for “problematic” groups are generated with either molecular dynamics simulations with charged and uncharged amino acid or with ab-initio local segment modeling. The corresponding ensembles are then used to calculate the pKa of the “problematic” residues and then the results are averaged. PMID:21744395

40 CFR 1051.320 - What happens if one of my production-line vehicles or engines fails to meet emission standards?

Code of Federal Regulations, 2012 CFR

2012-07-01

...-line vehicles or engines fails to meet emission standards? 1051.320 Section 1051.320 Protection of... of my production-line vehicles or engines fails to meet emission standards? (a) If you have a... standards (see § 1051.315(a)), the certificate of conformity is automatically suspended for that failing...

40 CFR 1051.320 - What happens if one of my production-line vehicles or engines fails to meet emission standards?

Code of Federal Regulations, 2011 CFR

2011-07-01

...-line vehicles or engines fails to meet emission standards? 1051.320 Section 1051.320 Protection of... of my production-line vehicles or engines fails to meet emission standards? (a) If you have a... standards (see § 1051.315(a)), the certificate of conformity is automatically suspended for that failing...

46 CFR 160.170-13 - Approval inspections and tests for prototype automatic release mechanisms.

Code of Federal Regulations, 2014 CFR

2014-10-01

... as built. The plans must include, in triplicate, the instructions for training and maintenance... determine that the prototype— (A) Conforms with the plans reviewed under § 160.170-9 of this subpart; (B) Is constructed by the methods and with the materials specified in the plans reviewed under § 160.170-9 of this...

46 CFR 160.170-13 - Approval inspections and tests for prototype automatic release mechanisms.

Code of Federal Regulations, 2013 CFR

2013-10-01

... as built. The plans must include, in triplicate, the instructions for training and maintenance... determine that the prototype— (A) Conforms with the plans reviewed under § 160.170-9 of this subpart; (B) Is constructed by the methods and with the materials specified in the plans reviewed under § 160.170-9 of this...

46 CFR 160.170-13 - Approval inspections and tests for prototype automatic release mechanisms.

Code of Federal Regulations, 2012 CFR

2012-10-01

... as built. The plans must include, in triplicate, the instructions for training and maintenance... determine that the prototype— (A) Conforms with the plans reviewed under § 160.170-9 of this subpart; (B) Is constructed by the methods and with the materials specified in the plans reviewed under § 160.170-9 of this...

Toward accurate prediction of pKa values for internal protein residues: the importance of conformational relaxation and desolvation energy.

PubMed

Wallace, Jason A; Wang, Yuhang; Shi, Chuanyin; Pastoor, Kevin J; Nguyen, Bao-Linh; Xia, Kai; Shen, Jana K

2011-12-01

Proton uptake or release controls many important biological processes, such as energy transduction, virus replication, and catalysis. Accurate pK(a) prediction informs about proton pathways, thereby revealing detailed acid-base mechanisms. Physics-based methods in the framework of molecular dynamics simulations not only offer pK(a) predictions but also inform about the physical origins of pK(a) shifts and provide details of ionization-induced conformational relaxation and large-scale transitions. One such method is the recently developed continuous constant pH molecular dynamics (CPHMD) method, which has been shown to be an accurate and robust pK(a) prediction tool for naturally occurring titratable residues. To further examine the accuracy and limitations of CPHMD, we blindly predicted the pK(a) values for 87 titratable residues introduced in various hydrophobic regions of staphylococcal nuclease and variants. The predictions gave a root-mean-square deviation of 1.69 pK units from experiment, and there were only two pK(a)'s with errors greater than 3.5 pK units. Analysis of the conformational fluctuation of titrating side-chains in the context of the errors of calculated pK(a) values indicate that explicit treatment of conformational flexibility and the associated dielectric relaxation gives CPHMD a distinct advantage. Analysis of the sources of errors suggests that more accurate pK(a) predictions can be obtained for the most deeply buried residues by improving the accuracy in calculating desolvation energies. Furthermore, it is found that the generalized Born implicit-solvent model underlying the current CPHMD implementation slightly distorts the local conformational environment such that the inclusion of an explicit-solvent representation may offer improvement of accuracy. Copyright © 2011 Wiley-Liss, Inc.

Chirality recognition in the glycidol···propylene oxide complex: a rotational spectroscopic study.

PubMed

Thomas, Javix; Sunahori, Fumie X; Borho, Nicole; Xu, Yunjie

2011-04-11

Chirality recognition in the hydrogen-bonded glycidol···propylene oxide complex has been studied by using rotational spectroscopy and ab initio calculations. An extensive conformational search has been performed for this binary adduct at the MP2/6-311++G(d,p) level of theory and a total of 28 homo- and heterochiral conformers were identified. The eight binary conformers, built of the two dominant glycidol monomeric conformers, g-G+ and g+G-, were predicted to be the most stable ones. Jet-cooled rotational spectra of six out of the eight conformers were observed and unambiguously assigned for the first time. The experimental stability ordering has been obtained and compared with the ab initio predictions. The relative stability of the two dominant glycidol monomeric conformers is reversed in some cases when binding to propylene oxide. The contributions of monomeric energy, deformation energy, and binary intermolecular interaction energy to the relative stability of the binary conformers are discussed. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

What Automaticity Deficit? Activation of Lexical Information by Readers with Dyslexia in a Rapid Automatized Naming Stroop-Switch Task

ERIC Educational Resources Information Center

Jones, Manon W.; Snowling, Margaret J.; Moll, Kristina

2016-01-01

Reading fluency is often predicted by rapid automatized naming (RAN) speed, which as the name implies, measures the automaticity with which familiar stimuli (e.g., letters) can be retrieved and named. Readers with dyslexia are considered to have less "automatized" access to lexical information, reflected in longer RAN times compared with…

Automated Transformation of CDISC ODM to OpenClinica.

PubMed

Gessner, Sophia; Storck, Michael; Hegselmann, Stefan; Dugas, Martin; Soto-Rey, Iñaki

2017-01-01

Due to the increasing use of electronic data capture systems for clinical research, the interest in saving resources by automatically generating and reusing case report forms in clinical studies is growing. OpenClinica, an open-source electronic data capture system enables the reuse of metadata in its own Excel import template, hampering the reuse of metadata defined in other standard formats. One of these standard formats is the Operational Data Model for metadata, administrative and clinical data in clinical studies. This work suggests a mapping from Operational Data Model to OpenClinica and describes the implementation of a converter to automatically generate OpenClinica conform case report forms based upon metadata in the Operational Data Model.

An automated approach to the segmentation of HEp-2 cells for the indirect immunofluorescence ANA test.

PubMed

Tonti, Simone; Di Cataldo, Santa; Bottino, Andrea; Ficarra, Elisa

2015-03-01

The automatization of the analysis of Indirect Immunofluorescence (IIF) images is of paramount importance for the diagnosis of autoimmune diseases. This paper proposes a solution to one of the most challenging steps of this process, the segmentation of HEp-2 cells, through an adaptive marker-controlled watershed approach. Our algorithm automatically conforms the marker selection pipeline to the peculiar characteristics of the input image, hence it is able to cope with different fluorescent intensities and staining patterns without any a priori knowledge. Furthermore, it shows a reduced sensitivity to over-segmentation errors and uneven illumination, that are typical issues of IIF imaging. Copyright © 2015 Elsevier Ltd. All rights reserved.

Conformations of organophosphine oxides

DOE PAGES

De Silva, Nuwan; Zahariev, Federico; Hay, Benjamin P.; ...

2015-07-17

The conformations of a series of organophosphine oxides, OP(CH 3) 2R, where R = methyl, ethyl, isopropyl, tert-butyl, vinyl, and phenyl, are predicted using the MP2/cc-pVTZ level of theory. Comparison of potential energy surfaces for rotation about P–C bonds with crystal structure data reveals a strong correlation between predicted location and energetics of minima and histograms of dihedral angle distributions observed in the solid state. In addition, the most stable conformers are those that minimize the extent of steric repulsion between adjacent rotor substituents, and the torsional barriers tend to increase with the steric bulk of the rotating alkyl group.more » MM3 force field parameters were adjusted to fit the MP2 results, providing a fast and accurate model for predicting organophosphine oxides shapes—an essential part of understanding the chemistry of these compounds. As a result, the predictive power of the modified MM3 model was tested against MP2/cc-pVTZ conformations for triethylphosphine oxide, OP(CH 2CH 3) 3, and triphenylphosphine oxide, OP(Ph) 3.« less

Structure Prediction of the Second Extracellular Loop in G-Protein-Coupled Receptors

PubMed Central

Kmiecik, Sebastian; Jamroz, Michal; Kolinski, Michal

2014-01-01

G-protein-coupled receptors (GPCRs) play key roles in living organisms. Therefore, it is important to determine their functional structures. The second extracellular loop (ECL2) is a functionally important region of GPCRs, which poses significant challenge for computational structure prediction methods. In this work, we evaluated CABS, a well-established protein modeling tool for predicting ECL2 structure in 13 GPCRs. The ECL2s (with between 13 and 34 residues) are predicted in an environment of other extracellular loops being fully flexible and the transmembrane domain fixed in its x-ray conformation. The modeling procedure used theoretical predictions of ECL2 secondary structure and experimental constraints on disulfide bridges. Our approach yielded ensembles of low-energy conformers and the most populated conformers that contained models close to the available x-ray structures. The level of similarity between the predicted models and x-ray structures is comparable to that of other state-of-the-art computational methods. Our results extend other studies by including newly crystallized GPCRs. PMID:24896119

Interactions in the ionic liquid [EMIM][FAP]: a coupled experimental and computational analysis.

PubMed

Voroshylova, Iuliia V; Teixeira, Filipe; Costa, Renata; Pereira, Carlos M; Cordeiro, M Natália D S

2016-01-28

Gas-phase electronic and structural properties of the room temperature ionic liquid 1-ethyl-3-methylimidazolium tris(perfluoroethyl)trifluorophosphate ([EMIM][FAP]) were studied using density functional theory, and confirmed with results from infrared spectroscopy. A conformational analysis allowed the identification of several plausible conformers of the ion pairs. For the detected conformers, the infrared spectra were predicted and their thermodynamic properties were evaluated. The topology of the electronic density of the most stable conformers of [EMIM][FAP] ion pairs were characterised using the quantum theory of atoms in molecules. A number of possible hydrogen bonds between the cations and anions of the ionic liquid were identified. Excellent correspondence was found between the predicted spectra of gas-phase [EMIM][FAP] conformers and the experimental infrared spectrum, which in turn allowed a clear attribution of the vibration modes of [EMIM][FAP]. Finally, the contribution of the various conformers of both isomers of the [FAP](-) anion to the ionic liquid macro-properties is shown.

Conformational Transitions upon Ligand Binding: Holo-Structure Prediction from Apo Conformations

PubMed Central

Seeliger, Daniel; de Groot, Bert L.

2010-01-01

Biological function of proteins is frequently associated with the formation of complexes with small-molecule ligands. Experimental structure determination of such complexes at atomic resolution, however, can be time-consuming and costly. Computational methods for structure prediction of protein/ligand complexes, particularly docking, are as yet restricted by their limited consideration of receptor flexibility, rendering them not applicable for predicting protein/ligand complexes if large conformational changes of the receptor upon ligand binding are involved. Accurate receptor models in the ligand-bound state (holo structures), however, are a prerequisite for successful structure-based drug design. Hence, if only an unbound (apo) structure is available distinct from the ligand-bound conformation, structure-based drug design is severely limited. We present a method to predict the structure of protein/ligand complexes based solely on the apo structure, the ligand and the radius of gyration of the holo structure. The method is applied to ten cases in which proteins undergo structural rearrangements of up to 7.1 Å backbone RMSD upon ligand binding. In all cases, receptor models within 1.6 Å backbone RMSD to the target were predicted and close-to-native ligand binding poses were obtained for 8 of 10 cases in the top-ranked complex models. A protocol is presented that is expected to enable structure modeling of protein/ligand complexes and structure-based drug design for cases where crystal structures of ligand-bound conformations are not available. PMID:20066034

Effortful versus automatic emotional processing in schizophrenia: Insights from a face-vignette task.

PubMed

Patrick, Regan E; Rastogi, Anuj; Christensen, Bruce K

2015-01-01

Adaptive emotional responding relies on dual automatic and effortful processing streams. Dual-stream models of schizophrenia (SCZ) posit a selective deficit in neural circuits that govern goal-directed, effortful processes versus reactive, automatic processes. This imbalance suggests that when patients are confronted with competing automatic and effortful emotional response cues, they will exhibit diminished effortful responding and intact, possibly elevated, automatic responding compared to controls. This prediction was evaluated using a modified version of the face-vignette task (FVT). Participants viewed emotional faces (automatic response cue) paired with vignettes (effortful response cue) that signalled a different emotion category and were instructed to discriminate the manifest emotion. Patients made less vignette and more face responses than controls. However, the relationship between group and FVT responding was moderated by IQ and reading comprehension ability. These results replicate and extend previous research and provide tentative support for abnormal conflict resolution between automatic and effortful emotional processing predicted by dual-stream models of SCZ.

Protein side chain conformation predictions with an MMGBSA energy function.

PubMed

Gaillard, Thomas; Panel, Nicolas; Simonson, Thomas

2016-06-01

The prediction of protein side chain conformations from backbone coordinates is an important task in structural biology, with applications in structure prediction and protein design. It is a difficult problem due to its combinatorial nature. We study the performance of an "MMGBSA" energy function, implemented in our protein design program Proteus, which combines molecular mechanics terms, a Generalized Born and Surface Area (GBSA) solvent model, with approximations that make the model pairwise additive. Proteus is not a competitor to specialized side chain prediction programs due to its cost, but it allows protein design applications, where side chain prediction is an important step and MMGBSA an effective energy model. We predict the side chain conformations for 18 proteins. The side chains are first predicted individually, with the rest of the protein in its crystallographic conformation. Next, all side chains are predicted together. The contributions of individual energy terms are evaluated and various parameterizations are compared. We find that the GB and SA terms, with an appropriate choice of the dielectric constant and surface energy coefficients, are beneficial for single side chain predictions. For the prediction of all side chains, however, errors due to the pairwise additive approximation overcome the improvement brought by these terms. We also show the crucial contribution of side chain minimization to alleviate the rigid rotamer approximation. Even without GB and SA terms, we obtain accuracies comparable to SCWRL4, a specialized side chain prediction program. In particular, we obtain a better RMSD than SCWRL4 for core residues (at a higher cost), despite our simpler rotamer library. Proteins 2016; 84:803-819. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Prediction of protein loop conformations using multiscale modeling methods with physical energy scoring functions.

PubMed

Olson, Mark A; Feig, Michael; Brooks, Charles L

2008-04-15

This article examines ab initio methods for the prediction of protein loops by a computational strategy of multiscale conformational sampling and physical energy scoring functions. Our approach consists of initial sampling of loop conformations from lattice-based low-resolution models followed by refinement using all-atom simulations. To allow enhanced conformational sampling, the replica exchange method was implemented. Physical energy functions based on CHARMM19 and CHARMM22 parameterizations with generalized Born (GB) solvent models were applied in scoring loop conformations extracted from the lattice simulations and, in the case of all-atom simulations, the ensemble of conformations were generated and scored with these models. Predictions are reported for 25 loop segments, each eight residues long and taken from a diverse set of 22 protein structures. We find that the simulations generally sampled conformations with low global root-mean-square-deviation (RMSD) for loop backbone coordinates from the known structures, whereas clustering conformations in RMSD space and scoring detected less favorable loop structures. Specifically, the lattice simulations sampled basins that exhibited an average global RMSD of 2.21 +/- 1.42 A, whereas clustering and scoring the loop conformations determined an RMSD of 3.72 +/- 1.91 A. Using CHARMM19/GB to refine the lattice conformations improved the sampling RMSD to 1.57 +/- 0.98 A and detection to 2.58 +/- 1.48 A. We found that further improvement could be gained from extending the upper temperature in the all-atom refinement from 400 to 800 K, where the results typically yield a reduction of approximately 1 A or greater in the RMSD of the detected loop. Overall, CHARMM19 with a simple pairwise GB solvent model is more efficient at sampling low-RMSD loop basins than CHARMM22 with a higher-resolution modified analytical GB model; however, the latter simulation method provides a more accurate description of the all-atom energy surface, yet demands a much greater computational cost. (c) 2007 Wiley Periodicals, Inc.

Impact of mutations on the allosteric conformational equilibrium

PubMed Central

Weinkam, Patrick; Chen, Yao Chi; Pons, Jaume; Sali, Andrej

2012-01-01

Allostery in a protein involves effector binding at an allosteric site that changes the structure and/or dynamics at a distant, functional site. In addition to the chemical equilibrium of ligand binding, allostery involves a conformational equilibrium between one protein substate that binds the effector and a second substate that less strongly binds the effector. We run molecular dynamics simulations using simple, smooth energy landscapes to sample specific ligand-induced conformational transitions, as defined by the effector-bound and unbound protein structures. These simulations can be performed using our web server: http://salilab.org/allosmod/. We then develop a set of features to analyze the simulations and capture the relevant thermodynamic properties of the allosteric conformational equilibrium. These features are based on molecular mechanics energy functions, stereochemical effects, and structural/dynamic coupling between sites. Using a machine-learning algorithm on a dataset of 10 proteins and 179 mutations, we predict both the magnitude and sign of the allosteric conformational equilibrium shift by the mutation; the impact of a large identifiable fraction of the mutations can be predicted with an average unsigned error of 1 kBT. With similar accuracy, we predict the mutation effects for an 11th protein that was omitted from the initial training and testing of the machine-learning algorithm. We also assess which calculated thermodynamic properties contribute most to the accuracy of the prediction. PMID:23228330

SIMS: A Hybrid Method for Rapid Conformational Analysis

PubMed Central

Gipson, Bryant; Moll, Mark; Kavraki, Lydia E.

2013-01-01

Proteins are at the root of many biological functions, often performing complex tasks as the result of large changes in their structure. Describing the exact details of these conformational changes, however, remains a central challenge for computational biology due the enormous computational requirements of the problem. This has engendered the development of a rich variety of useful methods designed to answer specific questions at different levels of spatial, temporal, and energetic resolution. These methods fall largely into two classes: physically accurate, but computationally demanding methods and fast, approximate methods. We introduce here a new hybrid modeling tool, the Structured Intuitive Move Selector (sims), designed to bridge the divide between these two classes, while allowing the benefits of both to be seamlessly integrated into a single framework. This is achieved by applying a modern motion planning algorithm, borrowed from the field of robotics, in tandem with a well-established protein modeling library. sims can combine precise energy calculations with approximate or specialized conformational sampling routines to produce rapid, yet accurate, analysis of the large-scale conformational variability of protein systems. Several key advancements are shown, including the abstract use of generically defined moves (conformational sampling methods) and an expansive probabilistic conformational exploration. We present three example problems that sims is applied to and demonstrate a rapid solution for each. These include the automatic determination of “active” residues for the hinge-based system Cyanovirin-N, exploring conformational changes involving long-range coordinated motion between non-sequential residues in Ribose-Binding Protein, and the rapid discovery of a transient conformational state of Maltose-Binding Protein, previously only determined by Molecular Dynamics. For all cases we provide energetic validations using well-established energy fields, demonstrating this framework as a fast and accurate tool for the analysis of a wide range of protein flexibility problems. PMID:23935893

Sphinx: merging knowledge-based and ab initio approaches to improve protein loop prediction

PubMed Central

Marks, Claire; Nowak, Jaroslaw; Klostermann, Stefan; Georges, Guy; Dunbar, James; Shi, Jiye; Kelm, Sebastian

2017-01-01

Abstract Motivation: Loops are often vital for protein function, however, their irregular structures make them difficult to model accurately. Current loop modelling algorithms can mostly be divided into two categories: knowledge-based, where databases of fragments are searched to find suitable conformations and ab initio, where conformations are generated computationally. Existing knowledge-based methods only use fragments that are the same length as the target, even though loops of slightly different lengths may adopt similar conformations. Here, we present a novel method, Sphinx, which combines ab initio techniques with the potential extra structural information contained within loops of a different length to improve structure prediction. Results: We show that Sphinx is able to generate high-accuracy predictions and decoy sets enriched with near-native loop conformations, performing better than the ab initio algorithm on which it is based. In addition, it is able to provide predictions for every target, unlike some knowledge-based methods. Sphinx can be used successfully for the difficult problem of antibody H3 prediction, outperforming RosettaAntibody, one of the leading H3-specific ab initio methods, both in accuracy and speed. Availability and Implementation: Sphinx is available at http://opig.stats.ox.ac.uk/webapps/sphinx. Contact: deane@stats.ox.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28453681

Sphinx: merging knowledge-based and ab initio approaches to improve protein loop prediction.

PubMed

Marks, Claire; Nowak, Jaroslaw; Klostermann, Stefan; Georges, Guy; Dunbar, James; Shi, Jiye; Kelm, Sebastian; Deane, Charlotte M

2017-05-01

Loops are often vital for protein function, however, their irregular structures make them difficult to model accurately. Current loop modelling algorithms can mostly be divided into two categories: knowledge-based, where databases of fragments are searched to find suitable conformations and ab initio, where conformations are generated computationally. Existing knowledge-based methods only use fragments that are the same length as the target, even though loops of slightly different lengths may adopt similar conformations. Here, we present a novel method, Sphinx, which combines ab initio techniques with the potential extra structural information contained within loops of a different length to improve structure prediction. We show that Sphinx is able to generate high-accuracy predictions and decoy sets enriched with near-native loop conformations, performing better than the ab initio algorithm on which it is based. In addition, it is able to provide predictions for every target, unlike some knowledge-based methods. Sphinx can be used successfully for the difficult problem of antibody H3 prediction, outperforming RosettaAntibody, one of the leading H3-specific ab initio methods, both in accuracy and speed. Sphinx is available at http://opig.stats.ox.ac.uk/webapps/sphinx. deane@stats.ox.ac.uk. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press.

Do Judgments of Learning Predict Automatic Influences of Memory?

ERIC Educational Resources Information Center

Undorf, Monika; Böhm, Simon; Cüpper, Lutz

2016-01-01

Current memory theories generally assume that memory performance reflects both recollection and automatic influences of memory. Research on people's predictions about the likelihood of remembering recently studied information on a memory test, that is, on judgments of learning (JOLs), suggests that both magnitude and resolution of JOLs are linked…

Prelude and Fugue, predicting local protein structure, early folding regions and structural weaknesses.

PubMed

Kwasigroch, Jean Marc; Rooman, Marianne

2006-07-15

Prelude&Fugue are bioinformatics tools aiming at predicting the local 3D structure of a protein from its amino acid sequence in terms of seven backbone torsion angle domains, using database-derived potentials. Prelude(&Fugue) computes all lowest free energy conformations of a protein or protein region, ranked by increasing energy, and possibly satisfying some interresidue distance constraints specified by the user. (Prelude&)Fugue detects sequence regions whose predicted structure is significantly preferred relative to other conformations in the absence of tertiary interactions. These programs can be used for predicting secondary structure, tertiary structure of short peptides, flickering early folding sequences and peptides that adopt a preferred conformation in solution. They can also be used for detecting structural weaknesses, i.e. sequence regions that are not optimal with respect to the tertiary fold. http://babylone.ulb.ac.be/Prelude_and_Fugue.

Conformational Entropy of Intrinsically Disordered Proteins from Amino Acid Triads

PubMed Central

Baruah, Anupaul; Rani, Pooja; Biswas, Parbati

2015-01-01

This work quantitatively characterizes intrinsic disorder in proteins in terms of sequence composition and backbone conformational entropy. Analysis of the normalized relative composition of the amino acid triads highlights a distinct boundary between globular and disordered proteins. The conformational entropy is calculated from the dihedral angles of the middle amino acid in the amino acid triad for the conformational ensemble of the globular, partially and completely disordered proteins relative to the non-redundant database. Both Monte Carlo (MC) and Molecular Dynamics (MD) simulations are used to characterize the conformational ensemble of the representative proteins of each group. The results show that the globular proteins span approximately half of the allowed conformational states in the Ramachandran space, while the amino acid triads in disordered proteins sample the entire range of the allowed dihedral angle space following Flory’s isolated-pair hypothesis. Therefore, only the sequence information in terms of the relative amino acid triad composition may be sufficient to predict protein disorder and the backbone conformational entropy, even in the absence of well-defined structure. The predicted entropies are found to agree with those calculated using mutual information expansion and the histogram method. PMID:26138206

Use of Crystal Structure Informatics for Defining the Conformational Space Needed for Predicting Crystal Structures of Pharmaceutical Molecules.

PubMed

Iuzzolino, Luca; Reilly, Anthony M; McCabe, Patrick; Price, Sarah L

2017-10-10

Determining the range of conformations that a flexible pharmaceutical-like molecule could plausibly adopt in a crystal structure is a key to successful crystal structure prediction (CSP) studies. We aim to use conformational information from the crystal structures in the Cambridge Structural Database (CSD) to facilitate this task. The conformations produced by the CSD Conformer Generator are reduced in number by considering the underlying rotamer distributions, an analysis of changes in molecular shape, and a minimal number of molecular ab initio calculations. This method is tested for five pharmaceutical-like molecules where an extensive CSP study has already been performed. The CSD informatics-derived set of crystal structure searches generates almost all the low-energy crystal structures previously found, including all experimental structures. The workflow effectively combines information on individual torsion angles and then eliminates the combinations that are too high in energy to be found in the solid state, reducing the resources needed to cover the solid-state conformational space of a molecule. This provides insights into how the low-energy solid-state and isolated-molecule conformations are related to the properties of the individual flexible torsion angles.

Analysis of factors influencing hydration site prediction based on molecular dynamics simulations.

PubMed

Yang, Ying; Hu, Bingjie; Lill, Markus A

2014-10-27

Water contributes significantly to the binding of small molecules to proteins in biochemical systems. Molecular dynamics (MD) simulation based programs such as WaterMap and WATsite have been used to probe the locations and thermodynamic properties of hydration sites at the surface or in the binding site of proteins generating important information for structure-based drug design. However, questions associated with the influence of the simulation protocol on hydration site analysis remain. In this study, we use WATsite to investigate the influence of factors such as simulation length and variations in initial protein conformations on hydration site prediction. We find that 4 ns MD simulation is appropriate to obtain a reliable prediction of the locations and thermodynamic properties of hydration sites. In addition, hydration site prediction can be largely affected by the initial protein conformations used for MD simulations. Here, we provide a first quantification of this effect and further indicate that similar conformations of binding site residues (RMSD < 0.5 Å) are required to obtain consistent hydration site predictions.

Molecular structure and interactions in the ionic liquid 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide.

PubMed

Dhumal, Nilesh R; Noack, Kristina; Kiefer, Johannes; Kim, Hyung J

2014-04-03

Electronic structure theory (density functional and Møller-Plesset perturbation theory) and vibrational spectroscopy (FT-IR and Raman) are employed to study molecular interactions in the room-temperature ionic liquid 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide. Different conformers of a cation-anion pair based on their molecular interactions are simulated in the gas phase and in a dielectric continuum solvent environment. Although the ordering of conformers in energy varies with theoretical methods, their predictions for three lowest energy conformers in the gas phase are similar. Strong C-H---N interactions between the acidic hydrogen atom of the cation imidazole ring and the nitrogen atom of the anion are predicted for either the lowest or second lowest energy conformer. In a continuum solvent, different theoretical methods yield the same ion-pair conformation for the lowest energy state. In both phases, the density functional method predicts that the anion is in a trans conformation in the lowest energy ion pair state. The theoretical results are compared with experimental observations from Raman scattering and IR absorption spectroscopies and manifestations of the molecular interactions in the vibrational spectra are discussed. The directions of the frequency shifts of the characteristic vibrations relative to the free anion and cation are explained by calculating the difference electron density coupled with electron density topography.

Conformity and dietary disinhibition: a test of the ego-strength model of self-regulation.

PubMed

Kahan, Dana; Polivy, Janet; Herman, C Peter

2003-03-01

Ego-strength depletion was examined as an explanation for dietary disinhibition in restrained eaters. We predicted that the depletion of ego strength resulting from having to choose whether to conform would undermine dietary restraint. Participants completed an Asch-type conformity task, after which they completed a taste-rating task in which food intake was measured. As predicted, restrained eaters who repeatedly exercised choice ate significantly more than did restrained eaters who did not exercise choice. An ego-strength model of dietary restraint is discussed. Copyright 2003 by Wiley Periodicals, Inc.

Prediction of conformationally dependent atomic multipole moments in carbohydrates

PubMed Central

Cardamone, Salvatore

2015-01-01

The conformational flexibility of carbohydrates is challenging within the field of computational chemistry. This flexibility causes the electron density to change, which leads to fluctuating atomic multipole moments. Quantum Chemical Topology (QCT) allows for the partitioning of an “atom in a molecule,” thus localizing electron density to finite atomic domains, which permits the unambiguous evaluation of atomic multipole moments. By selecting an ensemble of physically realistic conformers of a chemical system, one evaluates the various multipole moments at defined points in configuration space. The subsequent implementation of the machine learning method kriging delivers the evaluation of an analytical function, which smoothly interpolates between these points. This allows for the prediction of atomic multipole moments at new points in conformational space, not trained for but within prediction range. In this work, we demonstrate that the carbohydrates erythrose and threose are amenable to the above methodology. We investigate how kriging models respond when the training ensemble incorporating multiple energy minima and their environment in conformational space. Additionally, we evaluate the gains in predictive capacity of our models as the size of the training ensemble increases. We believe this approach to be entirely novel within the field of carbohydrates. For a modest training set size of 600, more than 90% of the external test configurations have an error in the total (predicted) electrostatic energy (relative to ab initio) of maximum 1 kJ mol−1 for open chains and just over 90% an error of maximum 4 kJ mol−1 for rings. © 2015 Wiley Periodicals, Inc. PMID:26547500

Prediction of conformationally dependent atomic multipole moments in carbohydrates.

PubMed

Cardamone, Salvatore; Popelier, Paul L A

2015-12-15

The conformational flexibility of carbohydrates is challenging within the field of computational chemistry. This flexibility causes the electron density to change, which leads to fluctuating atomic multipole moments. Quantum Chemical Topology (QCT) allows for the partitioning of an "atom in a molecule," thus localizing electron density to finite atomic domains, which permits the unambiguous evaluation of atomic multipole moments. By selecting an ensemble of physically realistic conformers of a chemical system, one evaluates the various multipole moments at defined points in configuration space. The subsequent implementation of the machine learning method kriging delivers the evaluation of an analytical function, which smoothly interpolates between these points. This allows for the prediction of atomic multipole moments at new points in conformational space, not trained for but within prediction range. In this work, we demonstrate that the carbohydrates erythrose and threose are amenable to the above methodology. We investigate how kriging models respond when the training ensemble incorporating multiple energy minima and their environment in conformational space. Additionally, we evaluate the gains in predictive capacity of our models as the size of the training ensemble increases. We believe this approach to be entirely novel within the field of carbohydrates. For a modest training set size of 600, more than 90% of the external test configurations have an error in the total (predicted) electrostatic energy (relative to ab initio) of maximum 1 kJ mol(-1) for open chains and just over 90% an error of maximum 4 kJ mol(-1) for rings. © 2015 Wiley Periodicals, Inc.

Modeling side-chains using molecular dynamics improve recognition of binding region in CAPRI targets.

PubMed

Camacho, Carlos J

2005-08-01

The CAPRI-II experiment added an extra level of complexity to the problem of predicting protein-protein interactions by including 5 targets for which participants had to build or complete the 3-dimensional (3D) structure of either the receptor or ligand based on the structure of a close homolog. In this article, we describe how modeling key side-chains using molecular dynamics (MD) in explicit solvent improved the recognition of the binding region of a free energy- based computational docking method. In particular, we show that MD is able to predict with relatively high accuracy the rotamer conformation of the anchor side-chains important for molecular recognition as suggested by Rajamani et al. (Proc Natl Acad Sci USA 2004;101:11287-11292). As expected, the conformations are some of the most common rotamers for the given residue, while latch side-chains that undergo induced fit upon binding are forced into less common conformations. Using these models as starting conformations in conjunction with the rigid-body docking server ClusPro and the flexible docking algorithm SmoothDock, we produced valuable predictions for 6 of the 9 targets in CAPRI-II, missing only the 3 targets that underwent significant structural rearrangements upon binding. We also show that our free energy- based scoring function, consisting of the sum of van der Waals, Coulombic electrostatic with a distance-dependent dielectric, and desolvation free energy successfully discriminates the nativelike conformation of our submitted predictions. The latter emphasizes the critical role that thermodynamics plays on our methodology, and validates the generality of the algorithm to predict protein interactions.

TTCN-3 Based Conformance Testing of Mobile Broadcast Business Management System in 3G Networks

NASA Astrophysics Data System (ADS)

Wang, Zhiliang; Yin, Xia; Xiang, Yang; Zhu, Ruiping; Gao, Shirui; Wu, Xin; Liu, Shijian; Gao, Song; Zhou, Li; Li, Peng

Mobile broadcast service is one of the emerging most important new services in 3G networks. To better operate and manage mobile broadcast services, mobile broadcast business management system (MBBMS) should be designed and developed. Such a system, with its distributed nature, complicated XML data and security mechanism, faces many challenges in testing technology. In this paper, we study the conformance testing methodology of MBBMS, and design and implement a MBBMS protocol conformance testing tool based on TTCN-3, a standardized test description language that can be used in black-box testing of reactive and distributed system. In this methodology and testing tool, we present a semi-automatic XML test data generation method of TTCN-3 test suite and use HMSC model to help the design of test suite. In addition, we also propose an integrated testing method for hierarchical MBBMS security architecture. This testing tool has been used in industrial level’s testing.

Brain Surface Conformal Parameterization Using Riemann Surface Structure

PubMed Central

Wang, Yalin; Lui, Lok Ming; Gu, Xianfeng; Hayashi, Kiralee M.; Chan, Tony F.; Toga, Arthur W.; Thompson, Paul M.; Yau, Shing-Tung

2011-01-01

In medical imaging, parameterized 3-D surface models are useful for anatomical modeling and visualization, statistical comparisons of anatomy, and surface-based registration and signal processing. Here we introduce a parameterization method based on Riemann surface structure, which uses a special curvilinear net structure (conformal net) to partition the surface into a set of patches that can each be conformally mapped to a parallelogram. The resulting surface subdivision and the parameterizations of the components are intrinsic and stable (their solutions tend to be smooth functions and the boundary conditions of the Dirichlet problem can be enforced). Conformal parameterization also helps transform partial differential equations (PDEs) that may be defined on 3-D brain surface manifolds to modified PDEs on a two-dimensional parameter domain. Since the Jacobian matrix of a conformal parameterization is diagonal, the modified PDE on the parameter domain is readily solved. To illustrate our techniques, we computed parameterizations for several types of anatomical surfaces in 3-D magnetic resonance imaging scans of the brain, including the cerebral cortex, hippocampi, and lateral ventricles. For surfaces that are topologically homeomorphic to each other and have similar geometrical structures, we show that the parameterization results are consistent and the subdivided surfaces can be matched to each other. Finally, we present an automatic sulcal landmark location algorithm by solving PDEs on cortical surfaces. The landmark detection results are used as constraints for building conformal maps between surfaces that also match explicitly defined landmarks. PMID:17679336

Structure prediction of the second extracellular loop in G-protein-coupled receptors.

PubMed

Kmiecik, Sebastian; Jamroz, Michal; Kolinski, Michal

2014-06-03

G-protein-coupled receptors (GPCRs) play key roles in living organisms. Therefore, it is important to determine their functional structures. The second extracellular loop (ECL2) is a functionally important region of GPCRs, which poses significant challenge for computational structure prediction methods. In this work, we evaluated CABS, a well-established protein modeling tool for predicting ECL2 structure in 13 GPCRs. The ECL2s (with between 13 and 34 residues) are predicted in an environment of other extracellular loops being fully flexible and the transmembrane domain fixed in its x-ray conformation. The modeling procedure used theoretical predictions of ECL2 secondary structure and experimental constraints on disulfide bridges. Our approach yielded ensembles of low-energy conformers and the most populated conformers that contained models close to the available x-ray structures. The level of similarity between the predicted models and x-ray structures is comparable to that of other state-of-the-art computational methods. Our results extend other studies by including newly crystallized GPCRs. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Conformational and Structural Studies of Isopropylamine from Temperature Dependent Raman Spectra of Xenon Solutions and {AB INITIO} Calculations

NASA Astrophysics Data System (ADS)

Klaassen, Joshua J.; Darkhalil, Ikhlas D.; Durig, James R.

2012-06-01

The Raman and infrared spectra (4000 to 50 cm-1) of the gas, liquid or solution, and solid have been recorded of isopropylamine, (CH3)2CHNH2. Variable temperature (-50 to -100oC) studies of the Raman spectra (3500 to 100 cm-1) dissolved in liquid xenon have been carried out. From these data, both the {trans} and {gauche} conformers have been identified and their relative stability obtained. The enthalpy difference has been determined from 20 band pairs at 6 temperatures to be 113 +/- 11 cm-1 (1.35 +/- 0.13 kJ mol-1) with the {trans} conformer the more stable form. The percentage of the {gauche} conformer is estimated to be 54 +/- 1 percent at ambient temperature. The conformational stabilities have been predicted from {ab initio} calculations utilizing several different basis sets up to aug-cc-pVTZ from both MP2(full) and density functional theory calculations by the B3LYP method. By utilizing previously reported microwave rotational constants along with {ab initio} MP2(full)/6-311+G(d,p) predicted structural values, adjusted r0 parameters have been obtained for the {trans} conformer. The determined heavy atom and NH2 distances in angstroms are C-C = 1.530(3), C-N = 1.465(3), N-H = 1.019(3) and angles in degrees NCC = 108.9(5), CCC = 111.0(5), HNC = 110.3(5). The structural parameters for the {gauche} conformer were estimated by using the same adjustment differences to the {gauche} form as those obtained for the corresponding {trans} parameters. Vibrational assignments have been provided for the observed bands for both conformers which are supported by MP2(full)/6-31G(d) {ab initio} calculations to predict harmonic force constants, wavenumbers, infrared intensities, Raman activities and depolarization ratios for both conformers. The results are discussed and compared to the corresponding properties of some related molecules.

ADVANCED SURVEILLANCE OF ENVIROMENTAL RADIATION IN AUTOMATIC NETWORKS.

PubMed

Benito, G; Sáez, J C; Blázquez, J B; Quiñones, J

2018-06-01

The objective of this study is the verification of the operation of a radiation monitoring network conformed by several sensors. The malfunction of a surveillance network has security and economic consequences, which derive from its maintenance and could be avoided with an early detection. The proposed method is based on a kind of multivariate distance, and the verification for the methodology has been tested at CIEMAT's local radiological early warning network.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Callear, Samantha K.; Imberti, Silvia; Johnston, Andrew

The aqueous solution of dopamine hydrochloride has been investigated using neutron and X-ray total scattering data together with Monte-Carlo based modelling using Empirical Potential Structure Refinement. The conformation of the protonated dopamine molecule is presented and the results compared to the conformations found in crystal structures, dopamine-complexed protein crystal structures and predicted from theoretical calculations and pharmacophoric models. It is found that protonated dopamine adopts a range of conformations in solution, highlighting the low rotational energy barrier between different conformations, with the preferred conformation being trans-perpendicular. The interactions between each of the species present (protonated dopamine molecules, water molecules, andmore » chloride anions) have been determined and are discussed with reference to interactions observed in similar systems both in the liquid and crystalline state, and predicted from theoretical calculations. The expected strong hydrogen bonds between the strong hydrogen bond donors and acceptors are observed, together with evidence of weaker CH hydrogen bonds and π interactions also playing a significant role in determining the arrangement of adjacent molecules.« less

Engineering a hyper-catalytic enzyme by photo-activated conformation modulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Agarwal, Pratul K

2012-01-01

Enzyme engineering for improved catalysis has wide implications. We describe a novel chemical modification of Candida antarctica lipase B that allows modulation of the enzyme conformation to promote catalysis. Computational modeling was used to identify dynamical enzyme regions that impact the catalytic mechanism. Surface loop regions located distal to active site but showing dynamical coupling to the reaction were connected by a chemical bridge between Lys136 and Pro192, containing a derivative of azobenzene. The conformational modulation of the enzyme was achieved using two sources of light that alternated the azobenzene moiety in cis and trans conformations. Computational model predicted thatmore » mechanical energy from the conformational fluctuations facilitate the reaction in the active-site. The results were consistent with predictions as the activity of the engineered enzyme was found to be enhanced with photoactivation. Preliminary estimations indicate that the engineered enzyme achieved 8-52 fold better catalytic activity than the unmodulated enzyme.« less

Exploring protein kinase conformation using swarm-enhanced sampling molecular dynamics.

PubMed

Atzori, Alessio; Bruce, Neil J; Burusco, Kepa K; Wroblowski, Berthold; Bonnet, Pascal; Bryce, Richard A

2014-10-27

Protein plasticity, while often linked to biological function, also provides opportunities for rational design of selective and potent inhibitors of their function. The application of computational methods to the prediction of concealed protein concavities is challenging, as the motions involved can be significant and occur over long time scales. Here we introduce the swarm-enhanced sampling molecular dynamics (sesMD) method as a tool to improve sampling of conformational landscapes. In this approach, a swarm of replica simulations interact cooperatively via a set of pairwise potentials incorporating attractive and repulsive components. We apply the sesMD approach to explore the conformations of the DFG motif in the protein p38α mitogen-activated protein kinase. In contrast to multiple MD simulations, sesMD trajectories sample a range of DFG conformations, some of which map onto existing crystal structures. Simulated structures intermediate between the DFG-in and DFG-out conformations are predicted to have druggable pockets of interest for structure-based ligand design.

3D QSAR studies on protein tyrosine phosphatase 1B inhibitors: comparison of the quality and predictivity among 3D QSAR models obtained from different conformer-based alignments.

PubMed

Pandey, Gyanendra; Saxena, Anil K

2006-01-01

A set of 65 flexible peptidomimetic competitive inhibitors (52 in the training set and 13 in the test set) of protein tyrosine phosphatase 1B (PTP1B) has been used to compare the quality and predictive power of 3D quantitative structure-activity relationship (QSAR) comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models for the three most commonly used conformer-based alignments, namely, cocrystallized conformer-based alignment (CCBA), docked conformer-based alignment (DCBA), and global minima energy conformer-based alignment (GMCBA). These three conformers of 5-[(2S)-2-({(2S)-2-[(tert-butoxycarbonyl)amino]-3-phenylpropanoyl}amino)3-oxo-3-pentylamino)propyl]-2-(carboxymethoxy)benzoic acid (compound number 66) were obtained from the X-ray structure of its cocrystallized complex with PTP1B (PDB ID: 1JF7), its docking studies, and its global minima by simulated annealing. Among the 3D QSAR models developed using the above three alignments, the CCBA provided the optimal predictive CoMFA model for the training set with cross-validated r2 (q2)=0.708, non-cross-validated r2=0.902, standard error of estimate (s)=0.165, and F=202.553 and the optimal CoMSIA model with q2=0.440, r2=0.799, s=0.192, and F=117.782. These models also showed the best test set prediction for the 13 compounds with predictive r2 values of 0.706 and 0.683, respectively. Though the QSAR models derived using the other two alignments also produced statistically acceptable models in the order DCBA>GMCBA in terms of the values of q2, r2, and predictive r2, they were inferior to the corresponding models derived using CCBA. Thus, the order of preference for the alignment selection for 3D QSAR model development may be CCBA>DCBA>GMCBA, and the information obtained from the CoMFA and CoMSIA contour maps may be useful in designing specific PTP1B inhibitors.

Exploration of the relationship between topology and designability of conformations

NASA Astrophysics Data System (ADS)

Leelananda, Sumudu P.; Towfic, Fadi; Jernigan, Robert L.; Kloczkowski, Andrzej

2011-06-01

Protein structures are evolutionarily more conserved than sequences, and sequences with very low sequence identity frequently share the same fold. This leads to the concept of protein designability. Some folds are more designable and lots of sequences can assume that fold. Elucidating the relationship between protein sequence and the three-dimensional (3D) structure that the sequence folds into is an important problem in computational structural biology. Lattice models have been utilized in numerous studies to model protein folds and predict the designability of certain folds. In this study, all possible compact conformations within a set of two-dimensional and 3D lattice spaces are explored. Complementary interaction graphs are then generated for each conformation and are described using a set of graph features. The full HP sequence space for each lattice model is generated and contact energies are calculated by threading each sequence onto all the possible conformations. Unique conformation giving minimum energy is identified for each sequence and the number of sequences folding to each conformation (designability) is obtained. Machine learning algorithms are used to predict the designability of each conformation. We find that the highly designable structures can be distinguished from other non-designable conformations based on certain graphical geometric features of the interactions. This finding confirms the fact that the topology of a conformation is an important determinant of the extent of its designability and suggests that the interactions themselves are important for determining the designability.

A Smart Unconscious? Procedural Origins of Automatic Partner Attitudes in Marriage

PubMed Central

Murray, Sandra L.; Holmes, John G.; Pinkus, Rebecca T.

2010-01-01

The paper examines potential origins of automatic (i.e., unconscious) attitudes toward one’s marital partner. It tests the hypothesis that early experiences in conflict-of-interest situations predict one’s later automatic inclination to approach (or avoid) the partner. A longitudinal study linked daily experiences in conflict-of-interest situations in the initial months of new marriages to automatic evaluations of the partner assessed four years later using the Implicit Associations Test. The results revealed that partners who were initially (1) treated less responsively and (2) evidenced more self-protective and less connectedness-promoting “if-then” contingencies in their thoughts and behavior later evidenced less positive automatic partner attitudes. However, these factors did not predict changes in love, satisfaction, or explicit beliefs about the partner. The findings hint at the existence of a “smart” relationship unconscious that captures behavioral realities conscious reflection can miss. PMID:20526450

Automatic speech recognition using a predictive echo state network classifier.

PubMed

Skowronski, Mark D; Harris, John G

2007-04-01

We have combined an echo state network (ESN) with a competitive state machine framework to create a classification engine called the predictive ESN classifier. We derive the expressions for training the predictive ESN classifier and show that the model was significantly more noise robust compared to a hidden Markov model in noisy speech classification experiments by 8+/-1 dB signal-to-noise ratio. The simple training algorithm and noise robustness of the predictive ESN classifier make it an attractive classification engine for automatic speech recognition.

Solution conformation of a peptide fragment representing a proposed RNA-binding site of a viral coat protein studied by two-dimensional NMR

DOE Office of Scientific and Technical Information (OSTI.GOV)

van der Graaf, M.; van Mierlo, C.P.M.; Hemminga, M.A.

1991-06-11

The first 25 amino acids of the coat protein of cowpea chlorotic mottle virus are essential for binding the encapsidated RNA. Although an {alpha}-helical conformation has been predicted for this highly positively charged N-terminal region. No experimental evidence for this conformation has been presented so far. In this study, two-dimensional proton NMR experiments were performed on a chemically synthesized pentacosapeptide containing the first 25 amino acids of this coat protein. All resonances could be assigned by a combined use of two-dimensional correlated spectroscopy and nuclear Overhauser enhancement spectroscopy carried out at four different temperatures. Various NMR parameters indicate the presencemore » of a conformational ensemble consisting of helical structures rapidly converting into more extended states. Differences in chemical shifts and nuclear Overhauser effects indicate that lowering the temperature induces a shift of the dynamic equilibrium toward more helical structures. At 10{degrees}C, a perceptible fraction of the conformational ensemble consists of structures with an {alpha}-helical conformation between residues 9 and 17, likely starting with a turnlike structure around Thr9 and Arg10. Both the conformation and the position of this helical region agree well with the secondary structure predictions mentioned above.« less

Conformational equilibria of alkanes in aqueous solution: relationship to water structure near hydrophobic solutes.

PubMed Central

Ashbaugh, H S; Garde, S; Hummer, G; Kaler, E W; Paulaitis, M E

1999-01-01

Conformational free energies of butane, pentane, and hexane in water are calculated from molecular simulations with explicit waters and from a simple molecular theory in which the local hydration structure is estimated based on a proximity approximation. This proximity approximation uses only the two nearest carbon atoms on the alkane to predict the local water density at a given point in space. Conformational free energies of hydration are subsequently calculated using a free energy perturbation method. Quantitative agreement is found between the free energies obtained from simulations and theory. Moreover, free energy calculations using this proximity approximation are approximately four orders of magnitude faster than those based on explicit water simulations. Our results demonstrate the accuracy and utility of the proximity approximation for predicting water structure as the basis for a quantitative description of n-alkane conformational equilibria in water. In addition, the proximity approximation provides a molecular foundation for extending predictions of water structure and hydration thermodynamic properties of simple hydrophobic solutes to larger clusters or assemblies of hydrophobic solutes. PMID:10423414

Kinetic rate constant prediction supports the conformational selection mechanism of protein binding.

PubMed

Moal, Iain H; Bates, Paul A

2012-01-01

The prediction of protein-protein kinetic rate constants provides a fundamental test of our understanding of molecular recognition, and will play an important role in the modeling of complex biological systems. In this paper, a feature selection and regression algorithm is applied to mine a large set of molecular descriptors and construct simple models for association and dissociation rate constants using empirical data. Using separate test data for validation, the predicted rate constants can be combined to calculate binding affinity with accuracy matching that of state of the art empirical free energy functions. The models show that the rate of association is linearly related to the proportion of unbound proteins in the bound conformational ensemble relative to the unbound conformational ensemble, indicating that the binding partners must adopt a geometry near to that of the bound prior to binding. Mirroring the conformational selection and population shift mechanism of protein binding, the models provide a strong separate line of evidence for the preponderance of this mechanism in protein-protein binding, complementing structural and theoretical studies.

Automatic Item Generation of Probability Word Problems

ERIC Educational Resources Information Center

Holling, Heinz; Bertling, Jonas P.; Zeuch, Nina

2009-01-01

Mathematical word problems represent a common item format for assessing student competencies. Automatic item generation (AIG) is an effective way of constructing many items with predictable difficulties, based on a set of predefined task parameters. The current study presents a framework for the automatic generation of probability word problems…

A Novel Method Using Abstract Convex Underestimation in Ab-Initio Protein Structure Prediction for Guiding Search in Conformational Feature Space.

PubMed

Hao, Xiao-Hu; Zhang, Gui-Jun; Zhou, Xiao-Gen; Yu, Xu-Feng

2016-01-01

To address the searching problem of protein conformational space in ab-initio protein structure prediction, a novel method using abstract convex underestimation (ACUE) based on the framework of evolutionary algorithm was proposed. Computing such conformations, essential to associate structural and functional information with gene sequences, is challenging due to the high-dimensionality and rugged energy surface of the protein conformational space. As a consequence, the dimension of protein conformational space should be reduced to a proper level. In this paper, the high-dimensionality original conformational space was converted into feature space whose dimension is considerably reduced by feature extraction technique. And, the underestimate space could be constructed according to abstract convex theory. Thus, the entropy effect caused by searching in the high-dimensionality conformational space could be avoided through such conversion. The tight lower bound estimate information was obtained to guide the searching direction, and the invalid searching area in which the global optimal solution is not located could be eliminated in advance. Moreover, instead of expensively calculating the energy of conformations in the original conformational space, the estimate value is employed to judge if the conformation is worth exploring to reduce the evaluation time, thereby making computational cost lower and the searching process more efficient. Additionally, fragment assembly and the Monte Carlo method are combined to generate a series of metastable conformations by sampling in the conformational space. The proposed method provides a novel technique to solve the searching problem of protein conformational space. Twenty small-to-medium structurally diverse proteins were tested, and the proposed ACUE method was compared with It Fix, HEA, Rosetta and the developed method LEDE without underestimate information. Test results show that the ACUE method can more rapidly and more efficiently obtain the near-native protein structure.

Analysis of Factors Influencing Hydration Site Prediction Based on Molecular Dynamics Simulations

PubMed Central

2015-01-01

Water contributes significantly to the binding of small molecules to proteins in biochemical systems. Molecular dynamics (MD) simulation based programs such as WaterMap and WATsite have been used to probe the locations and thermodynamic properties of hydration sites at the surface or in the binding site of proteins generating important information for structure-based drug design. However, questions associated with the influence of the simulation protocol on hydration site analysis remain. In this study, we use WATsite to investigate the influence of factors such as simulation length and variations in initial protein conformations on hydration site prediction. We find that 4 ns MD simulation is appropriate to obtain a reliable prediction of the locations and thermodynamic properties of hydration sites. In addition, hydration site prediction can be largely affected by the initial protein conformations used for MD simulations. Here, we provide a first quantification of this effect and further indicate that similar conformations of binding site residues (RMSD < 0.5 Å) are required to obtain consistent hydration site predictions. PMID:25252619

Multiple loop conformations of peptides predicted by molecular dynamics simulations are compatible with nuclear magnetic resonance.

PubMed

Carstens, Heiko; Renner, Christian; Milbradt, Alexander G; Moroder, Luis; Tavan, Paul

2005-03-29

The affinity and selectivity of protein-protein interactions can be fine-tuned by varying the size, flexibility, and amino acid composition of involved surface loops. As a model for such surface loops, we study the conformational landscape of an octapeptide, whose flexibility is chemically steered by a covalent ring closure integrating an azobenzene dye into and by a disulfide bridge additionally constraining the peptide backbone. Because the covalently integrated azobenzene dyes can be switched by light between a bent cis state and an elongated trans state, six cyclic peptide models of strongly different flexibilities are obtained. The conformational states of these peptide models are sampled by NMR and by unconstrained molecular dynamics (MD) simulations. Prototypical conformations and the free-energy landscapes in the high-dimensional space spanned by the phi/psi angles at the peptide backbone are obtained by clustering techniques from the MD trajectories. Multiple open-loop conformations are shown to be predicted by MD particularly in the very flexible cases and are shown to comply with the NMR data despite the fact that such open-loop conformations are missing in the refined NMR structures.

Assessment of CAPRI predictions in rounds 3-5 shows progress in docking procedures.

PubMed

Méndez, Raúl; Leplae, Raphaël; Lensink, Marc F; Wodak, Shoshana J

2005-08-01

The current status of docking procedures for predicting protein-protein interactions starting from their three-dimensional (3D) structure is reassessed by evaluating blind predictions, performed during 2003-2004 as part of Rounds 3-5 of the community-wide experiment on Critical Assessment of PRedicted Interactions (CAPRI). Ten newly determined structures of protein-protein complexes were used as targets for these rounds. They comprised 2 enzyme-inhibitor complexes, 2 antigen-antibody complexes, 2 complexes involved in cellular signaling, 2 homo-oligomers, and a complex between 2 components of the bacterial cellulosome. For most targets, the predictors were given the experimental structures of 1 unbound and 1 bound component, with the latter in a random orientation. For some, the structure of the free component was derived from that of a related protein, requiring the use of homology modeling. In some of the targets, significant differences in conformation were displayed between the bound and unbound components, representing a major challenge for the docking procedures. For 1 target, predictions could not go to completion. In total, 1866 predictions submitted by 30 groups were evaluated. Over one-third of these groups applied completely novel docking algorithms and scoring functions, with several of them specifically addressing the challenge of dealing with side-chain and backbone flexibility. The quality of the predicted interactions was evaluated by comparison to the experimental structures of the targets, made available for the evaluation, using the well-agreed-upon criteria used previously. Twenty-four groups, which for the first time included an automatic Web server, produced predictions ranking from acceptable to highly accurate for all targets, including those where the structures of the bound and unbound forms differed substantially. These results and a brief survey of the methods used by participants of CAPRI Rounds 3-5 suggest that genuine progress in the performance of docking methods is being achieved, with CAPRI acting as the catalyst.

Density-based clustering of small peptide conformations sampled from a molecular dynamics simulation.

PubMed

Kim, Minkyoung; Choi, Seung-Hoon; Kim, Junhyoung; Choi, Kihang; Shin, Jae-Min; Kang, Sang-Kee; Choi, Yun-Jaie; Jung, Dong Hyun

2009-11-01

This study describes the application of a density-based algorithm to clustering small peptide conformations after a molecular dynamics simulation. We propose a clustering method for small peptide conformations that enables adjacent clusters to be separated more clearly on the basis of neighbor density. Neighbor density means the number of neighboring conformations, so if a conformation has too few neighboring conformations, then it is considered as noise or an outlier and is excluded from the list of cluster members. With this approach, we can easily identify clusters in which the members are densely crowded in the conformational space, and we can safely avoid misclustering individual clusters linked by noise or outliers. Consideration of neighbor density significantly improves the efficiency of clustering of small peptide conformations sampled from molecular dynamics simulations and can be used for predicting peptide structures.

Acquisition of automatic imitation is sensitive to sensorimotor contingency.

PubMed

Cook, Richard; Press, Clare; Dickinson, Anthony; Heyes, Cecilia

2010-08-01

The associative sequence learning model proposes that the development of the mirror system depends on the same mechanisms of associative learning that mediate Pavlovian and instrumental conditioning. To test this model, two experiments used the reduction of automatic imitation through incompatible sensorimotor training to assess whether mirror system plasticity is sensitive to contingency (i.e., the extent to which activation of one representation predicts activation of another). In Experiment 1, residual automatic imitation was measured following incompatible training in which the action stimulus was a perfect predictor of the response (contingent) or not at all predictive of the response (noncontingent). A contingency effect was observed: There was less automatic imitation indicative of more learning in the contingent group. Experiment 2 replicated this contingency effect and showed that, as predicted by associative learning theory, it can be abolished by signaling trials in which the response occurs in the absence of an action stimulus. These findings support the view that mirror system development depends on associative learning and indicate that this learning is not purely Hebbian. If this is correct, associative learning theory could be used to explain, predict, and intervene in mirror system development.

Predicting RNA pseudoknot folding thermodynamics

PubMed Central

Cao, Song; Chen, Shi-Jie

2006-01-01

Based on the experimentally determined atomic coordinates for RNA helices and the self-avoiding walks of the P (phosphate) and C4 (carbon) atoms in the diamond lattice for the polynucleotide loop conformations, we derive a set of conformational entropy parameters for RNA pseudoknots. Based on the entropy parameters, we develop a folding thermodynamics model that enables us to compute the sequence-specific RNA pseudoknot folding free energy landscape and thermodynamics. The model is validated through extensive experimental tests both for the native structures and for the folding thermodynamics. The model predicts strong sequence-dependent helix-loop competitions in the pseudoknot stability and the resultant conformational switches between different hairpin and pseudoknot structures. For instance, for the pseudoknot domain of human telomerase RNA, a native-like and a misfolded hairpin intermediates are found to coexist on the (equilibrium) folding pathways, and the interplay between the stabilities of these intermediates causes the conformational switch that may underlie a human telomerase disease. PMID:16709732

Theoretical study of some nitrososulfamide compounds with antitumor activity.

PubMed

Djameleddine, Khatmi; Soumeya, Seridi; Fatiha, Madi

2004-09-30

The lowest-energy conformations of four 2-chloroethylnitrososulfamides were determined using the MM+ molecular mechanics method as implemented in Hyperchem 6.0. Some of the calculated structural parameters, angles and bonds lengths were compared with the crystal structure data of N-nitroso-N-(2-chloroethyl)-N'-sulfamoyl- proline. Using MM+, AM1 and PM3 the anti conformation was predicted to be more stable than the syn conformation in each of these compounds. With these methods we found that the relative energy of the transition state (TS) was considerably higher, but with the ab initio method using RHF with minimal basic function STO-3G we found that the syn conformation is predicted to be slightly more stable. The determination of some atomic charges of a selection of atoms on the syn, anti and TS structures of the various compounds provided some details about the nature of the transition state.

Piloted Simulation Evaluation of a Model-Predictive Automatic Recovery System to Prevent Vehicle Loss of Control on Approach

NASA Technical Reports Server (NTRS)

Litt, Jonathan; Liu, Yuan; Sowers, T. Shane; Owen, A. Karl; Guo, Ten-Huei

2014-01-01

This paper describes a model-predictive automatic recovery system for aircraft on the verge of a loss-of-control situation. The system determines when it must intervene to prevent an imminent accident, resulting from a poor approach. It estimates the altitude loss that would result from a go-around maneuver at the current flight condition. If the loss is projected to violate a minimum altitude threshold, the maneuver is automatically triggered. The system deactivates to allow landing once several criteria are met. Piloted flight simulator evaluation showed the system to provide effective envelope protection during extremely unsafe landing attempts. The results demonstrate how flight and propulsion control can be integrated to recover control of the vehicle automatically and prevent a potential catastrophe.

Investigation of basic cognitive predictors of reading and spelling abilities in Tunisian third-grade primary school children.

PubMed

Batnini, Soulef; Uno, Akira

2015-06-01

This study investigated first the main cognitive abilities; phonological processing, visual cognition, automatization and receptive vocabulary in predicting reading and spelling abilities in Arabic. Second, we compared good/poor readers and spellers to detect the characteristics of cognitive predictors which contribute to identifying reading and spelling difficulties in Arabic speaking children. A sample of 116 Tunisian third-grade children was tested on their abilities to read and spell, phonological processing, visual cognition, automatization and receptive vocabulary. For reading, phonological processing and automatization uniquely predicted Arabic word reading and paragraph reading abilities. Automatization uniquely predicted Arabic non-word reading ability. For spelling, phonological processing was a unique predictor for Arabic word spelling ability. Furthermore, poor readers had significantly lower scores on the phonological processing test and slower reading times on the automatization test as compared with good readers. Additionally, poor spellers showed lower scores on the phonological processing test as compared with good spellers. Visual cognitive processing and receptive vocabulary were not significant cognitive predictors of Arabic reading and spelling abilities for Tunisian third grade children in this study. Our results are consistent with previous studies in alphabetic orthographies and demonstrate that phonological processing and automatization are the best cognitive predictors in detecting early literacy problems. We suggest including phonological processing and automatization tasks in screening tests and in intervention programs may help Tunisian children with poor literacy skills overcome reading and spelling difficulties in Arabic. Copyright © 2014 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

Experimentally assessing molecular dynamics sampling of the protein native state conformational distribution

PubMed Central

Hernández, Griselda; Anderson, Janet S.; LeMaster, David M.

2012-01-01

The acute sensitivity to conformation exhibited by amide hydrogen exchange reactivity provides a valuable test for the physical accuracy of model ensembles developed to represent the Boltzmann distribution of the protein native state. A number of molecular dynamics studies of ubiquitin have predicted a well-populated transition in the tight turn immediately preceding the primary site of proteasome-directed polyubiquitylation Lys 48. Amide exchange reactivity analysis demonstrates that this transition is 103-fold rarer than these predictions. More strikingly, for the most populated novel conformational basin predicted from a recent 1 ms MD simulation of bovine pancreatic trypsin inhibitor (at 13% of total), experimental hydrogen exchange data indicates a population below 10−6. The most sophisticated efforts to directly incorporate experimental constraints into the derivation of model protein ensembles have been applied to ubiquitin, as illustrated by three recently deposited studies (PDB codes 2NR2, 2K39 and 2KOX). Utilizing the extensive set of experimental NOE constraints, each of these three ensembles yields a modestly more accurate prediction of the exchange rates for the highly exposed amides than does a standard unconstrained molecular simulation. However, for the less frequently exposed amide hydrogens, the 2NR2 ensemble offers no improvement in rate predictions as compared to the unconstrained MD ensemble. The other two NMR-constrained ensembles performed markedly worse, either underestimating (2KOX) or overestimating (2K39) the extent of conformational diversity. PMID:22425325

Molecular structure and conformations of para-methylbenzene sulfonamide and ortho-methylbenzene sulfonamide: gas electron diffraction and quantum chemical calculations study.

PubMed

Petrov, Vjacheslav M; Girichev, Georgiy V; Oberhammer, Heinz; Petrova, Valentina N; Giricheva, Nina I; Bardina, Anna V; Ivanov, Sergey N

2008-04-03

The molecular structure and conformational properties of para-methylbenzene sulfonamide (4-MBSA) and ortho-methylbenzene sulfonamide (2-MBSA) have been studied by gas electron diffraction (GED) and quantum chemical methods (B3LYP/6-311+G** and MP2/6-31G**). Quantum chemical calculations predict the existence of two conformers for 4-MBSA with the S-N bond perpendicular to the benzene plane and the NH2 group either eclipsing or staggering the S-O bonds of the SO2 group. Both conformers possess CS symmetry. The eclipsed form is predicted to be favored by DeltaE = 0.63 kcal/mol (B3LYP) or 1.00 kcal/mol (MP2). According to the calculations, the S-N bond in 2-MBSA can possess planar direction opposite the methyl group (phi(C2C1SN) = 180 degrees ) or nonplanar direction (phi(C2C1SN) approximately 60 degrees ). In both cases, the NH2 group can adopt eclipsed or staggered orientation, resulting in a total of four stable conformers. The nonplanar eclipsed conformer (C1 symmetry) and the planar eclipsed form (CS symmetry) are predicted to be favored. According to the GED analysis, the saturated vapor over solid 4-MBSA at T = 151(3) degrees C consists as mixture of the eclipsed (78(19) %) and staggered (22(19) %) forms. The saturated vapor over solid 2-MBSA at T = 157(3) degrees C consists as a mixture of the nonplanar eclipsed (69(11) %) and planar eclipsed (31(11) %) forms.

Chiral self-recognition: direct spectroscopic detection of the homochiral and heterochiral dimers of propylene oxide in the gas phase.

PubMed

Su, Zheng; Borho, Nicole; Xu, Yunjie

2006-12-27

In this report, we describe rotational spectroscopic and high-level ab initio studies of the 1:1 chiral molecular adduct of propylene oxide dimer. The complexes are bound by weak secondary hydrogen bonds, that is, the O(epoxy)...H-C noncovalent interactions. Six homochiral and six heterochiral conformers were predicted to be the most stable configurations where each monomer acts as a proton acceptor and a donor simultaneously, forming two six- or five-membered intermolecular hydrogen-bonded rings. Rotational spectra of six, that is, three homochiral and heterochiral conformer pairs, out of the eight conformers that were predicted to have sufficiently large permanent electric dipole moments were measured and analyzed. The relative conformational stability order and the signs of the chiral recognition energies of the six conformers were determined experimentally and were compared to the ab initio computational results. The experimental observations and the ab initio calculations suggest that the concerted effort of these weak secondary hydrogen bonds can successfully lock the subunits in a particular orientation and that the overall binding strength is comparable to a classic hydrogen bond.

Fast de novo discovery of low-energy protein loop conformations.

PubMed

Wong, Samuel W K; Liu, Jun S; Kou, S C

2017-08-01

In the prediction of protein structure from amino acid sequence, loops are challenging regions for computational methods. Since loops are often located on the protein surface, they can have significant roles in determining protein functions and binding properties. Loop prediction without the aid of a structural template requires extensive conformational sampling and energy minimization, which are computationally difficult. In this article we present a new de novo loop sampling method, the Parallely filtered Energy Targeted All-atom Loop Sampler (PETALS) to rapidly locate low energy conformations. PETALS explores both backbone and side-chain positions of the loop region simultaneously according to the energy function selected by the user, and constructs a nonredundant ensemble of low energy loop conformations using filtering criteria. The method is illustrated with the DFIRE potential and DiSGro energy function for loops, and shown to be highly effective at discovering conformations with near-native (or better) energy. Using the same energy function as the DiSGro algorithm, PETALS samples conformations with both lower RMSDs and lower energies. PETALS is also useful for assessing the accuracy of different energy functions. PETALS runs rapidly, requiring an average time cost of 10 minutes for a length 12 loop on a single 3.2 GHz processor core, comparable to the fastest existing de novo methods for generating an ensemble of conformations. Proteins 2017; 85:1402-1412. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Identification of Rare Lewis Oligosaccharide Conformers in Aqueous Solution Using Enhanced Sampling Molecular Dynamics.

PubMed

Alibay, Irfan; Burusco, Kepa K; Bruce, Neil J; Bryce, Richard A

2018-03-08

Determining the conformations accessible to carbohydrate ligands in aqueous solution is important for understanding their biological action. In this work, we evaluate the conformational free-energy surfaces of Lewis oligosaccharides in explicit aqueous solvent using a multidimensional variant of the swarm-enhanced sampling molecular dynamics (msesMD) method; we compare with multi-microsecond unbiased MD simulations, umbrella sampling, and accelerated MD approaches. For the sialyl Lewis A tetrasaccharide, msesMD simulations in aqueous solution predict conformer landscapes in general agreement with the other biased methods and with triplicate unbiased 10 μs trajectories; these simulations find a predominance of closed conformer and a range of low-occupancy open forms. The msesMD simulations also suggest closed-to-open transitions in the tetrasaccharide are facilitated by changes in ring puckering of its GlcNAc residue away from the 4 C 1 form, in line with previous work. For sialyl Lewis X tetrasaccharide, msesMD simulations predict a minor population of an open form in solution corresponding to a rare lectin-bound pose observed crystallographically. Overall, from comparison with biased MD calculations, we find that triplicate 10 μs unbiased MD simulations may not be enough to fully sample glycan conformations in aqueous solution. However, the computational efficiency and intuitive approach of the msesMD method suggest potential for its application in glycomics as a tool for analysis of oligosaccharide conformation.

Variational Identification of Markovian Transition States

NASA Astrophysics Data System (ADS)

Martini, Linda; Kells, Adam; Covino, Roberto; Hummer, Gerhard; Buchete, Nicolae-Viorel; Rosta, Edina

2017-07-01

We present a method that enables the identification and analysis of conformational Markovian transition states from atomistic or coarse-grained molecular dynamics (MD) trajectories. Our algorithm is presented by using both analytical models and examples from MD simulations of the benchmark system helix-forming peptide Ala5 , and of larger, biomedically important systems: the 15-lipoxygenase-2 enzyme (15-LOX-2), the epidermal growth factor receptor (EGFR) protein, and the Mga2 fungal transcription factor. The analysis of 15-LOX-2 uses data generated exclusively from biased umbrella sampling simulations carried out at the hybrid ab initio density functional theory (DFT) quantum mechanics/molecular mechanics (QM/MM) level of theory. In all cases, our method automatically identifies the corresponding transition states and metastable conformations in a variationally optimal way, with the input of a set of relevant coordinates, by accurately reproducing the intrinsic slowest relaxation rate of each system. Our approach offers a general yet easy-to-implement analysis method that provides unique insight into the molecular mechanism and the rare but crucial (i.e., rate-limiting) transition states occurring along conformational transition paths in complex dynamical systems such as molecular trajectories.

Visualisation of variable binding pockets on protein surfaces by probabilistic analysis of related structure sets.

PubMed

Ashford, Paul; Moss, David S; Alex, Alexander; Yeap, Siew K; Povia, Alice; Nobeli, Irene; Williams, Mark A

2012-03-14

Protein structures provide a valuable resource for rational drug design. For a protein with no known ligand, computational tools can predict surface pockets that are of suitable size and shape to accommodate a complementary small-molecule drug. However, pocket prediction against single static structures may miss features of pockets that arise from proteins' dynamic behaviour. In particular, ligand-binding conformations can be observed as transiently populated states of the apo protein, so it is possible to gain insight into ligand-bound forms by considering conformational variation in apo proteins. This variation can be explored by considering sets of related structures: computationally generated conformers, solution NMR ensembles, multiple crystal structures, homologues or homology models. It is non-trivial to compare pockets, either from different programs or across sets of structures. For a single structure, difficulties arise in defining particular pocket's boundaries. For a set of conformationally distinct structures the challenge is how to make reasonable comparisons between them given that a perfect structural alignment is not possible. We have developed a computational method, Provar, that provides a consistent representation of predicted binding pockets across sets of related protein structures. The outputs are probabilities that each atom or residue of the protein borders a predicted pocket. These probabilities can be readily visualised on a protein using existing molecular graphics software. We show how Provar simplifies comparison of the outputs of different pocket prediction algorithms, of pockets across multiple simulated conformations and between homologous structures. We demonstrate the benefits of use of multiple structures for protein-ligand and protein-protein interface analysis on a set of complexes and consider three case studies in detail: i) analysis of a kinase superfamily highlights the conserved occurrence of surface pockets at the active and regulatory sites; ii) a simulated ensemble of unliganded Bcl2 structures reveals extensions of a known ligand-binding pocket not apparent in the apo crystal structure; iii) visualisations of interleukin-2 and its homologues highlight conserved pockets at the known receptor interfaces and regions whose conformation is known to change on inhibitor binding. Through post-processing of the output of a variety of pocket prediction software, Provar provides a flexible approach to the analysis and visualization of the persistence or variability of pockets in sets of related protein structures.

Conformational Map of Phenolic Acids.

PubMed

Cortijo, Vanessa; Alonso, Elena R; Mata, Santiago; Alonso, José L

2018-01-18

The benefits of vaporization by laser ablation and the high resolution and sensitivity attained by the chirped pulse Fourier transform microwave spectroscopy CP-FTMW have provided the first conformational map of the simplest phenolic acids of trans-cinnamic and p-coumaric. Two conformers of trans-cinnamic acid and four conformers of trans-p-coumaric acid have been characterized under the isolation conditions of a supersonic expansion. The spectroscopic constants derived from the analysis of the rotational spectra compared with those predicted theoretically provide an unmatched means to achieve an unambiguous identification of the observed species.

Bayesian energy landscape tilting: towards concordant models of molecular ensembles.

PubMed

Beauchamp, Kyle A; Pande, Vijay S; Das, Rhiju

2014-03-18

Predicting biological structure has remained challenging for systems such as disordered proteins that take on myriad conformations. Hybrid simulation/experiment strategies have been undermined by difficulties in evaluating errors from computational model inaccuracies and data uncertainties. Building on recent proposals from maximum entropy theory and nonequilibrium thermodynamics, we address these issues through a Bayesian energy landscape tilting (BELT) scheme for computing Bayesian hyperensembles over conformational ensembles. BELT uses Markov chain Monte Carlo to directly sample maximum-entropy conformational ensembles consistent with a set of input experimental observables. To test this framework, we apply BELT to model trialanine, starting from disagreeing simulations with the force fields ff96, ff99, ff99sbnmr-ildn, CHARMM27, and OPLS-AA. BELT incorporation of limited chemical shift and (3)J measurements gives convergent values of the peptide's α, β, and PPII conformational populations in all cases. As a test of predictive power, all five BELT hyperensembles recover set-aside measurements not used in the fitting and report accurate errors, even when starting from highly inaccurate simulations. BELT's principled framework thus enables practical predictions for complex biomolecular systems from discordant simulations and sparse data. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Probabilistic sampling of protein conformations: new hope for brute force?

PubMed

Feldman, Howard J; Hogue, Christopher W V

2002-01-01

Protein structure prediction from sequence alone by "brute force" random methods is a computationally expensive problem. Estimates have suggested that it could take all the computers in the world longer than the age of the universe to compute the structure of a single 200-residue protein. Here we investigate the use of a faster version of our FOLDTRAJ probabilistic all-atom protein-structure-sampling algorithm. We have improved the method so that it is now over twenty times faster than originally reported, and capable of rapidly sampling conformational space without lattices. It uses geometrical constraints and a Leonard-Jones type potential for self-avoidance. We have also implemented a novel method to add secondary structure-prediction information to make protein-like amounts of secondary structure in sampled structures. In a set of 100,000 probabilistic conformers of 1VII, 1ENH, and 1PMC generated, the structures with smallest Calpha RMSD from native are 3.95, 5.12, and 5.95A, respectively. Expanding this test to a set of 17 distinct protein folds, we find that all-helical structures are "hit" by brute force more frequently than beta or mixed structures. For small helical proteins or very small non-helical ones, this approach should have a "hit" close enough to detect with a good scoring function in a pool of several million conformers. By fitting the distribution of RMSDs from the native state of each of the 17 sets of conformers to the extreme value distribution, we are able to estimate the size of conformational space for each. With a 0.5A RMSD cutoff, the number of conformers is roughly 2N where N is the number of residues in the protein. This is smaller than previous estimates, indicating an average of only two possible conformations per residue when sterics are accounted for. Our method reduces the effective number of conformations available at each residue by probabilistic bias, without requiring any particular discretization of residue conformational space, and is the fastest method of its kind. With computer speeds doubling every 18 months and parallel and distributed computing becoming more practical, the brute force approach to protein structure prediction may yet have some hope in the near future. Copyright 2001 Wiley-Liss, Inc.

A population-based evolutionary search approach to the multiple minima problem in de novo protein structure prediction

PubMed Central

2013-01-01

Background Elucidating the native structure of a protein molecule from its sequence of amino acids, a problem known as de novo structure prediction, is a long standing challenge in computational structural biology. Difficulties in silico arise due to the high dimensionality of the protein conformational space and the ruggedness of the associated energy surface. The issue of multiple minima is a particularly troublesome hallmark of energy surfaces probed with current energy functions. In contrast to the true energy surface, these surfaces are weakly-funneled and rich in comparably deep minima populated by non-native structures. For this reason, many algorithms seek to be inclusive and obtain a broad view of the low-energy regions through an ensemble of low-energy (decoy) conformations. Conformational diversity in this ensemble is key to increasing the likelihood that the native structure has been captured. Methods We propose an evolutionary search approach to address the multiple-minima problem in decoy sampling for de novo structure prediction. Two population-based evolutionary search algorithms are presented that follow the basic approach of treating conformations as individuals in an evolving population. Coarse graining and molecular fragment replacement are used to efficiently obtain protein-like child conformations from parents. Potential energy is used both to bias parent selection and determine which subset of parents and children will be retained in the evolving population. The effect on the decoy ensemble of sampling minima directly is measured by additionally mapping a conformation to its nearest local minimum before considering it for retainment. The resulting memetic algorithm thus evolves not just a population of conformations but a population of local minima. Results and conclusions Results show that both algorithms are effective in terms of sampling conformations in proximity of the known native structure. The additional minimization is shown to be key to enhancing sampling capability and obtaining a diverse ensemble of decoy conformations, circumventing premature convergence to sub-optimal regions in the conformational space, and approaching the native structure with proximity that is comparable to state-of-the-art decoy sampling methods. The results are shown to be robust and valid when using two representative state-of-the-art coarse-grained energy functions. PMID:24565020

ATLAAS: an automatic decision tree-based learning algorithm for advanced image segmentation in positron emission tomography.

PubMed

Berthon, Beatrice; Marshall, Christopher; Evans, Mererid; Spezi, Emiliano

2016-07-07

Accurate and reliable tumour delineation on positron emission tomography (PET) is crucial for radiotherapy treatment planning. PET automatic segmentation (PET-AS) eliminates intra- and interobserver variability, but there is currently no consensus on the optimal method to use, as different algorithms appear to perform better for different types of tumours. This work aimed to develop a predictive segmentation model, trained to automatically select and apply the best PET-AS method, according to the tumour characteristics. ATLAAS, the automatic decision tree-based learning algorithm for advanced segmentation is based on supervised machine learning using decision trees. The model includes nine PET-AS methods and was trained on a 100 PET scans with known true contour. A decision tree was built for each PET-AS algorithm to predict its accuracy, quantified using the Dice similarity coefficient (DSC), according to the tumour volume, tumour peak to background SUV ratio and a regional texture metric. The performance of ATLAAS was evaluated for 85 PET scans obtained from fillable and printed subresolution sandwich phantoms. ATLAAS showed excellent accuracy across a wide range of phantom data and predicted the best or near-best segmentation algorithm in 93% of cases. ATLAAS outperformed all single PET-AS methods on fillable phantom data with a DSC of 0.881, while the DSC for H&N phantom data was 0.819. DSCs higher than 0.650 were achieved in all cases. ATLAAS is an advanced automatic image segmentation algorithm based on decision tree predictive modelling, which can be trained on images with known true contour, to predict the best PET-AS method when the true contour is unknown. ATLAAS provides robust and accurate image segmentation with potential applications to radiation oncology.

ATLAAS: an automatic decision tree-based learning algorithm for advanced image segmentation in positron emission tomography

NASA Astrophysics Data System (ADS)

Berthon, Beatrice; Marshall, Christopher; Evans, Mererid; Spezi, Emiliano

2016-07-01

Accurate and reliable tumour delineation on positron emission tomography (PET) is crucial for radiotherapy treatment planning. PET automatic segmentation (PET-AS) eliminates intra- and interobserver variability, but there is currently no consensus on the optimal method to use, as different algorithms appear to perform better for different types of tumours. This work aimed to develop a predictive segmentation model, trained to automatically select and apply the best PET-AS method, according to the tumour characteristics. ATLAAS, the automatic decision tree-based learning algorithm for advanced segmentation is based on supervised machine learning using decision trees. The model includes nine PET-AS methods and was trained on a 100 PET scans with known true contour. A decision tree was built for each PET-AS algorithm to predict its accuracy, quantified using the Dice similarity coefficient (DSC), according to the tumour volume, tumour peak to background SUV ratio and a regional texture metric. The performance of ATLAAS was evaluated for 85 PET scans obtained from fillable and printed subresolution sandwich phantoms. ATLAAS showed excellent accuracy across a wide range of phantom data and predicted the best or near-best segmentation algorithm in 93% of cases. ATLAAS outperformed all single PET-AS methods on fillable phantom data with a DSC of 0.881, while the DSC for H&N phantom data was 0.819. DSCs higher than 0.650 were achieved in all cases. ATLAAS is an advanced automatic image segmentation algorithm based on decision tree predictive modelling, which can be trained on images with known true contour, to predict the best PET-AS method when the true contour is unknown. ATLAAS provides robust and accurate image segmentation with potential applications to radiation oncology.

Modeling the Conformation-Specific Infrared Spectra of N-Alkylbenzenes

NASA Astrophysics Data System (ADS)

Tabor, Daniel P.; Sibert, Edwin; Hewett, Daniel M.; Korn, Joseph A.; Zwier, Timothy S.

2016-06-01

Conformation-specific UV-IR double resonance spectra are presented for n-alkylbenzenes. With the aid of a local mode Hamiltonian that includes the effects of stretch-bend Fermi coupling, the spectra of ethyl, n-propyl, and n-butylbenzene are assigned to individual conformers. These molecules allow for further development of the work on a first principles method for calculating alkyl stretch spectra. Due to the consistency of the anharmonic couplings from conformer to conformer, construction of the model Hamiltonian for a given conformer only requires a harmonic frequency calculation at the conformer's minimum geometry as an input. The model Hamiltonian can be parameterized with either density functional theory or MP2 electronic structure calculations. The relative strengths and weaknesses of these methods are evaluated, including their predictions of the relative energetics of the conformers. Finally, the IR spectra for conformers that have the alkyl chain bend back and interact with the π cloud of the benzene ring are modeled.

The mass-zero spin-two field and gravitational theory.

NASA Technical Reports Server (NTRS)

Coulter, C. A.

1972-01-01

Demonstration that the conventional theory of the mass-zero spin-two field with sources introduces extraneous nonspin-two field components in source regions and fails to be covariant under the full or restricted conformal group. A modified theory is given, expressed in terms of the physical components of mass-zero spin-two field rather than in terms of 'potentials,' which has no extraneous components inside or outside sources, and which is covariant under the full conformal group. For a proper choice of source term, this modified theory has the correct Newtonian limit and automatically implies that a symmetric second-rank source tensor has zero divergence. It is shown that possibly a generally covariant form of the spin-two theory derived here can be constructed to agree with general relativity in all currently accessible experimental situations.

Investigating the Relationship between Stable Personality Characteristics and Automatic Imitation

PubMed Central

Butler, Emily E.; Ward, Robert; Ramsey, Richard

2015-01-01

Automatic imitation is a cornerstone of nonverbal communication that fosters rapport between interaction partners. Recent research has suggested that stable dimensions of personality are antecedents to automatic imitation, but the empirical evidence linking imitation with personality traits is restricted to a few studies with modest sample sizes. Additionally, atypical imitation has been documented in autism spectrum disorders and schizophrenia, but the mechanisms underpinning these behavioural profiles remain unclear. Using a larger sample than prior studies (N=243), the current study tested whether performance on a computer-based automatic imitation task could be predicted by personality traits associated with social behaviour (extraversion and agreeableness) and with disorders of social cognition (autistic-like and schizotypal traits). Further personality traits (narcissism and empathy) were assessed in a subsample of participants (N=57). Multiple regression analyses showed that personality measures did not predict automatic imitation. In addition, using a similar analytical approach to prior studies, no differences in imitation performance emerged when only the highest and lowest 20 participants on each trait variable were compared. These data weaken support for the view that stable personality traits are antecedents to automatic imitation and that neural mechanisms thought to support automatic imitation, such as the mirror neuron system, are dysfunctional in autism spectrum disorders or schizophrenia. In sum, the impact that personality variables have on automatic imitation is less universal than initial reports suggest. PMID:26079137

Investigating the Relationship between Stable Personality Characteristics and Automatic Imitation.

PubMed

Butler, Emily E; Ward, Robert; Ramsey, Richard

2015-01-01

Automatic imitation is a cornerstone of nonverbal communication that fosters rapport between interaction partners. Recent research has suggested that stable dimensions of personality are antecedents to automatic imitation, but the empirical evidence linking imitation with personality traits is restricted to a few studies with modest sample sizes. Additionally, atypical imitation has been documented in autism spectrum disorders and schizophrenia, but the mechanisms underpinning these behavioural profiles remain unclear. Using a larger sample than prior studies (N=243), the current study tested whether performance on a computer-based automatic imitation task could be predicted by personality traits associated with social behaviour (extraversion and agreeableness) and with disorders of social cognition (autistic-like and schizotypal traits). Further personality traits (narcissism and empathy) were assessed in a subsample of participants (N=57). Multiple regression analyses showed that personality measures did not predict automatic imitation. In addition, using a similar analytical approach to prior studies, no differences in imitation performance emerged when only the highest and lowest 20 participants on each trait variable were compared. These data weaken support for the view that stable personality traits are antecedents to automatic imitation and that neural mechanisms thought to support automatic imitation, such as the mirror neuron system, are dysfunctional in autism spectrum disorders or schizophrenia. In sum, the impact that personality variables have on automatic imitation is less universal than initial reports suggest.

Supercomputer applications in molecular modeling.

PubMed

Gund, T M

1988-01-01

An overview of the functions performed by molecular modeling is given. Molecular modeling techniques benefiting from supercomputing are described, namely, conformation, search, deriving bioactive conformations, pharmacophoric pattern searching, receptor mapping, and electrostatic properties. The use of supercomputers for problems that are computationally intensive, such as protein structure prediction, protein dynamics and reactivity, protein conformations, and energetics of binding is also examined. The current status of supercomputing and supercomputer resources are discussed.

Building proteins from C alpha coordinates using the dihedral probability grid Monte Carlo method.

PubMed Central

Mathiowetz, A. M.; Goddard, W. A.

1995-01-01

Dihedral probability grid Monte Carlo (DPG-MC) is a general-purpose method of conformational sampling that can be applied to many problems in peptide and protein modeling. Here we present the DPG-MC method and apply it to predicting complete protein structures from C alpha coordinates. This is useful in such endeavors as homology modeling, protein structure prediction from lattice simulations, or fitting protein structures to X-ray crystallographic data. It also serves as an example of how DPG-MC can be applied to systems with geometric constraints. The conformational propensities for individual residues are used to guide conformational searches as the protein is built from the amino-terminus to the carboxyl-terminus. Results for a number of proteins show that both the backbone and side chain can be accurately modeled using DPG-MC. Backbone atoms are generally predicted with RMS errors of about 0.5 A (compared to X-ray crystal structure coordinates) and all atoms are predicted to an RMS error of 1.7 A or better. PMID:7549885

Correlation of chemical shifts predicted by molecular dynamics simulations for partially disordered proteins.

PubMed

Karp, Jerome M; Eryilmaz, Ertan; Erylimaz, Ertan; Cowburn, David

2015-01-01

There has been a longstanding interest in being able to accurately predict NMR chemical shifts from structural data. Recent studies have focused on using molecular dynamics (MD) simulation data as input for improved prediction. Here we examine the accuracy of chemical shift prediction for intein systems, which have regions of intrinsic disorder. We find that using MD simulation data as input for chemical shift prediction does not consistently improve prediction accuracy over use of a static X-ray crystal structure. This appears to result from the complex conformational ensemble of the disordered protein segments. We show that using accelerated molecular dynamics (aMD) simulations improves chemical shift prediction, suggesting that methods which better sample the conformational ensemble like aMD are more appropriate tools for use in chemical shift prediction for proteins with disordered regions. Moreover, our study suggests that data accurately reflecting protein dynamics must be used as input for chemical shift prediction in order to correctly predict chemical shifts in systems with disorder.

RaptorX-Angle: real-value prediction of protein backbone dihedral angles through a hybrid method of clustering and deep learning.

PubMed

Gao, Yujuan; Wang, Sheng; Deng, Minghua; Xu, Jinbo

2018-05-08

Protein dihedral angles provide a detailed description of protein local conformation. Predicted dihedral angles can be used to narrow down the conformational space of the whole polypeptide chain significantly, thus aiding protein tertiary structure prediction. However, direct angle prediction from sequence alone is challenging. In this article, we present a novel method (named RaptorX-Angle) to predict real-valued angles by combining clustering and deep learning. Tested on a subset of PDB25 and the targets in the latest two Critical Assessment of protein Structure Prediction (CASP), our method outperforms the existing state-of-art method SPIDER2 in terms of Pearson Correlation Coefficient (PCC) and Mean Absolute Error (MAE). Our result also shows approximately linear relationship between the real prediction errors and our estimated bounds. That is, the real prediction error can be well approximated by our estimated bounds. Our study provides an alternative and more accurate prediction of dihedral angles, which may facilitate protein structure prediction and functional study.

Improved assignments of the vibrational fundamental modes of ortho -, meta -, and para -xylene using gas- and liquid-phase infrared and Raman spectra combined with ab initio calculations: Quantitative gas-phase infrared spectra for detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lindenmaier, Rodica; Scharko, Nicole K.; Tonkyn, Russell G.

Xylenes contain a blend of the ortho-, meta-, and para- isomers, and all are abundant contaminants in the ground, surface waters, and air. To better characterize xylene and to better enable its detection, we report high quality quantitative vapor-phase infrared spectra of all three isomers over the 540-6500 cm -1 range. All fundamental vibrational modes are assigned based on these vapor-phase infrared spectra, liquid-phase infrared and Raman spectra, along with density functional theory (DFT), ab initio MP2 and high energy-accuracy compound theoretical model (W1BD) calculations. Both MP2 and DFT predict a single conformer with C 2v symmetry for ortho-xylene, andmore » two conformers each for meta- and para-xylene, depending on the preferred orientations of the methyl groups. For meta-xylene the two conformers have C s and C 2 symmetry, and for para-xylene these conformers have C 2v or C 2h symmetry. Since the relative population of the two conformers is approximately 50% for both isomers and predicted frequencies and intensities are very similar for each conformer, we made an arbitrary choice to discuss the C s conformer for meta-xylene and the C 2v conformer for para-xylene. We report integrated band intensities for all isomers. Using the quantitative infrared data, we determine the global warming potential values of each isomer and discuss potential bands for atmospheric monitoring.« less

Improved assignments of the vibrational fundamental modes of ortho-, meta-, and para-xylene using gas- and liquid-phase infrared and Raman spectra combined with ab initio calculations: Quantitative gas-phase infrared spectra for detection

NASA Astrophysics Data System (ADS)

Lindenmaier, Rodica; Scharko, Nicole K.; Tonkyn, Russell G.; Nguyen, Kiet T.; Williams, Stephen D.; Johnson, Timothy J.

2017-12-01

Xylenes contain a blend of the ortho-, meta-, and para- isomers, and all are abundant contaminants in the ground, surface waters, and air. To better characterize xylene and to better enable its detection, high quality quantitative vapor-phase infrared spectra of all three isomers over the 6500 - 540 cm-1 range are reported. All fundamental vibrational modes are assigned based on these vapor-phase infrared spectra, liquid-phase infrared and Raman spectra, along with density functional theory (DFT), ab initio MP2 and high energy-accuracy compound theoretical model (W1BD) calculations. Both MP2 and DFT predict a single conformer with C2v symmetry for ortho-xylene, and two conformers each for meta- and para-xylene, depending on the preferred orientations of the methyl groups. For meta-xylene the two conformers have Cs and C2 symmetry, and for para-xylene these conformers have C2v or C2h symmetry. Since the relative population of the two conformers is approximately 50% for both isomers and predicted frequencies and intensities are very similar for each conformer, an arbitrary choice to discuss the Cs conformer for meta-xylene and the C2v conformer for para-xylene is made. Integrated band intensities for all isomers are reported. Using the quantitative infrared data, the global warming potential values of each isomer are determined. Potential bands for atmospheric monitoring are also discussed.

Guiding exploration in conformational feature space with Lipschitz underestimation for ab-initio protein structure prediction.

PubMed

Hao, Xiaohu; Zhang, Guijun; Zhou, Xiaogen

2018-04-01

Computing conformations which are essential to associate structural and functional information with gene sequences, is challenging due to the high dimensionality and rugged energy surface of the protein conformational space. Consequently, the dimension of the protein conformational space should be reduced to a proper level, and an effective exploring algorithm should be proposed. In this paper, a plug-in method for guiding exploration in conformational feature space with Lipschitz underestimation (LUE) for ab-initio protein structure prediction is proposed. The conformational space is converted into ultrafast shape recognition (USR) feature space firstly. Based on the USR feature space, the conformational space can be further converted into Underestimation space according to Lipschitz estimation theory for guiding exploration. As a consequence of the use of underestimation model, the tight lower bound estimate information can be used for exploration guidance, the invalid sampling areas can be eliminated in advance, and the number of energy function evaluations can be reduced. The proposed method provides a novel technique to solve the exploring problem of protein conformational space. LUE is applied to differential evolution (DE) algorithm, and metropolis Monte Carlo(MMC) algorithm which is available in the Rosetta; When LUE is applied to DE and MMC, it will be screened by the underestimation method prior to energy calculation and selection. Further, LUE is compared with DE and MMC by testing on 15 small-to-medium structurally diverse proteins. Test results show that near-native protein structures with higher accuracy can be obtained more rapidly and efficiently with the use of LUE. Copyright © 2018 Elsevier Ltd. All rights reserved.

Automatic priming of attentional control by relevant colors.

PubMed

Ansorge, Ulrich; Becker, Stefanie I

2012-01-01

We tested whether color word cues automatically primed attentional control settings during visual search, or whether color words were used in a strategic manner for the control of attention. In Experiment 1, we used color words as cues that were informative or uninformative with respect to the target color. Regardless of the cue's informativeness, distractors similar to the color cue captured more attention. In Experiment 2, the participants either indicated their expectation about the target color or recalled the last target color, which was uncorrelated with the present target color. We observed more attentional capture by distractors that were similar to the participants' predictions and recollections, but no difference between effects of the recollected and predicted colors. In Experiment 3, we used 100%-informative word cues that were congruent with the predicted target color (e.g., the word "red" informed that the target would be red) or incongruent with the predicted target color (e.g., the word "green" informed that the target would be red) and found that informative incongruent word cues primed attention capture by a word-similar distractor. Together, the results suggest that word cues (Exps. 1 and 3) and color representations (Exp. 2) primed attention capture in an automatic manner. This indicates that color cues automatically primed temporary adjustments in attention control settings.

Alignment-independent technique for 3D QSAR analysis

NASA Astrophysics Data System (ADS)

Wilkes, Jon G.; Stoyanova-Slavova, Iva B.; Buzatu, Dan A.

2016-04-01

Molecular biochemistry is controlled by 3D phenomena but structure-activity models based on 3D descriptors are infrequently used for large data sets because of the computational overhead for determining molecular conformations. A diverse dataset of 146 androgen receptor binders was used to investigate how different methods for defining molecular conformations affect the performance of 3D-quantitative spectral data activity relationship models. Molecular conformations tested: (1) global minimum of molecules' potential energy surface; (2) alignment-to-templates using equal electronic and steric force field contributions; (3) alignment using contributions "Best-for-Each" template; (4) non-energy optimized, non-aligned (2D > 3D). Aggregate predictions from models were compared. Highest average coefficients of determination ranged from R Test 2 = 0.56 to 0.61. The best model using 2D > 3D (imported directly from ChemSpider) produced R Test 2 = 0.61. It was superior to energy-minimized and conformation-aligned models and was achieved in only 3-7 % of the time required using the other conformation strategies. Predictions averaged from models built on different conformations achieved a consensus R Test 2 = 0.65. The best 2D > 3D model was analyzed for underlying structure-activity relationships. For the compound strongest binding to the androgen receptor, 10 substructural features contributing to binding were flagged. Utility of 2D > 3D was compared for two other activity endpoints, each modeling a medium sized data set. Results suggested that large scale, accurate predictions using 2D > 3D SDAR descriptors may be produced for interactions involving endocrine system nuclear receptors and other data sets in which strongest activities are produced by fairly inflexible substrates.

Exposure to violent video games increases automatic aggressiveness.

PubMed

Uhlmann, Eric; Swanson, Jane

2004-02-01

The effects of exposure to violent video games on automatic associations with the self were investigated in a sample of 121 students. Playing the violent video game Doom led participants to associate themselves with aggressive traits and actions on the Implicit Association Test. In addition, self-reported prior exposure to violent video games predicted automatic aggressive self-concept, above and beyond self-reported aggression. Results suggest that playing violent video games can lead to the automatic learning of aggressive self-views.

Repeat-swap homology modeling of secondary active transporters: updated protocol and prediction of elevator-type mechanisms

PubMed Central

Vergara-Jaque, Ariela; Fenollar-Ferrer, Cristina; Kaufmann, Desirée; Forrest, Lucy R.

2015-01-01

Secondary active transporters are critical for neurotransmitter clearance and recycling during synaptic transmission and uptake of nutrients. These proteins mediate the movement of solutes against their concentration gradients, by using the energy released in the movement of ions down pre-existing concentration gradients. To achieve this, transporters conform to the so-called alternating-access hypothesis, whereby the protein adopts at least two conformations in which the substrate binding sites are exposed to one or other side of the membrane, but not both simultaneously. Structures of a bacterial homolog of neuronal glutamate transporters, GltPh, in several different conformational states have revealed that the protein structure is asymmetric in the outward- and inward-open states, and that the conformational change connecting them involves a elevator-like movement of a substrate binding domain across the membrane. The structural asymmetry is created by inverted-topology repeats, i.e., structural repeats with similar overall folds whose transmembrane topologies are related to each other by two-fold pseudo-symmetry around an axis parallel to the membrane plane. Inverted repeats have been found in around three-quarters of secondary transporter folds. Moreover, the (a)symmetry of these systems has been successfully used as a bioinformatic tool, called “repeat-swap modeling” to predict structural models of a transporter in one conformation using the known structure of the transporter in the complementary conformation as a template. Here, we describe an updated repeat-swap homology modeling protocol, and calibrate the accuracy of the method using GltPh, for which both inward- and outward-facing conformations are known. We then apply this repeat-swap homology modeling procedure to a concentrative nucleoside transporter, VcCNT, which has a three-dimensional arrangement related to that of GltPh. The repeat-swapped model of VcCNT predicts that nucleoside transport also occurs via an elevator-like mechanism. PMID:26388773

Estimation of the rotamerization constants of different conformations of N-acetylalanine: a theoretical and matrix-isolation FT-IR study.

PubMed

Boeckx, Bram; Maes, Guido

2012-02-01

The conformational landscape of N-acetylalanine has been investigated by a theoretical and matrix-isolation FT-IR study. Optimizations of N-acetylalanine structures has been conducted at successive higher levels of theory HF/3-21G, DFT(B3LYP)/6-31++G** and MP2/6-31++G**. This resulted in three stable conformations. Among these, one conformation contains an intramolecular H-bond. The vibrational properties of these conformations were calculated and used to identify the conformations in a cryogenic argon matrix. The intensities of some bands assigned to a particular conformation were used to estimate the rotamerization constants K(r12) and K(r13) for the equilibria NAA1 NAA2 and NAA1 NAA3, respectively. The obtained experimental values were in agreement with the theoretical predictions. Copyright © 2011 Elsevier B.V. All rights reserved.

Use of restrained molecular dynamics to predict the conformations of phosphorylated receiver domains in two-component signaling systems.

PubMed

Foster, Clay A; West, Ann H

2017-01-01

Two-component signaling (TCS) is the primary means by which bacteria, as well as certain plants and fungi, respond to external stimuli. Signal transduction involves stimulus-dependent autophosphorylation of a sensor histidine kinase and phosphoryl transfer to the receiver domain of a downstream response regulator. Phosphorylation acts as an allosteric switch, inducing structural and functional changes in the pathway's components. Due to their transient nature, phosphorylated receiver domains are challenging to characterize structurally. In this work, we provide a methodology for simulating receiver domain phosphorylation to predict conformations that are nearly identical to experimental structures. Using restrained molecular dynamics, phosphorylated conformations of receiver domains can be reliably sampled on nanosecond timescales. These simulations also provide data on conformational dynamics that can be used to identify regions of functional significance related to phosphorylation. We first validated this approach on several well-characterized receiver domains and then used it to compare the upstream and downstream components of the fungal Sln1 phosphorelay. Our results demonstrate that this technique provides structural insight, obtained in the absence of crystallographic or NMR information, regarding phosphorylation-induced conformational changes in receiver domains that regulate the output of their associated signaling pathway. To our knowledge, this is the first time such a protocol has been described that can be broadly applied to TCS proteins for predictive purposes. Proteins 2016; 85:155-176. © 2016 Wiley Periodicals, Inc. © 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.

Ricin, ricin agglutinin, and the ricin binding subunit structural comparison by Raman spectroscopy

NASA Astrophysics Data System (ADS)

Brandt, N. N.; Chikishev, A. Yu.; Sotnikov, A. I.; Savochkina, Yu. A.; Agapov, I. I.; Tonevitsky, A. G.

2005-02-01

Raman spectroscopy is used to study conformation-sensitive vibrational bands of the plant toxins ricin and ricin agglutinin and the ricin binding subunit in aqueous solution. The analysis of the Raman data yields the conformational state of the protein molecules differing from that predicted by the X-ray data. The differences and similarities in the conformational state of ricin, ricin agglutinin, and ricin binding subunit are discussed.

The Free Energy Profile of Tubulin Straight-Bent Conformational Changes, with Implications for Microtubule Assembly and Drug Discovery

PubMed Central

Bonomi, Massimiliano; Agard, David A.; Jacobson, Matthew P.

2014-01-01

αβ-tubulin dimers need to convert between a ‘bent’ conformation observed for free dimers in solution and a ‘straight’ conformation required for incorporation into the microtubule lattice. Here, we investigate the free energy landscape of αβ-tubulin using molecular dynamics simulations, emphasizing implications for models of assembly, and modulation of the conformational landscape by colchicine, a tubulin-binding drug that inhibits microtubule polymerization. Specifically, we performed molecular dynamics, potential-of-mean force simulations to obtain the free energy profile for unpolymerized GDP-bound tubulin as a function of the ∼12° intradimer rotation differentiating the straight and bent conformers. Our results predict that the unassembled GDP-tubulin heterodimer exists in a continuum of conformations ranging between straight and bent, but, in agreement with existing structural data, suggests that an intermediate bent state has a lower free energy (by ∼1 kcal/mol) and thus dominates in solution. In agreement with predictions of the lattice model of microtubule assembly, lateral binding of two αβ-tubulins strongly shifts the conformational equilibrium towards the straight state, which is then ∼1 kcal/mol lower in free energy than the bent state. Finally, calculations of colchicine binding to a single αβ-tubulin dimer strongly shifts the equilibrium toward the bent states, and disfavors the straight state to the extent that it is no longer thermodynamically populated. PMID:24516374

4-Methyl-1H-Indazole-5-Boronic acid: Crystal structure, vibrational spectra and DFT simulations

NASA Astrophysics Data System (ADS)

Dikmen, Gökhan

2017-12-01

Molecular structure, conformer forms, geometric parameters and vibrational assignments and properties of 4-Methyl-1H-Indazole-5-Boronic Acid (4M1HI5BA) were theoretically and experimentally studied using Raman, FT-IR, XRD spectroscopic methods and quantum chemical calculations. Raman and FT-IR spectra were examined range from 4000 to 400 cm-1. Moreover, single crystals of 4M1HI5BA were prepared in order to use in XRD experiments. Vibrational assignments were carried out using total energy distribution (TED) values. Furthermore, HOMO and LUMO were calculated for 4M1HI5BA. Four different conformations of 4M1HI5BA were calculated in only gas phase. The theoretical and experimental results show that in order to predict vibrational wavenumbers B3LYP/6-311++G(d,p) may provide acceptable results and the most stable conformer of 4M1HI5BA is predicted to be envelope conformer.

1-Methoxy-1-silacyclohexane: Synthesis, molecular structure and conformational behavior by gas electron diffraction, Raman spectroscopy and quantum chemical calculations

NASA Astrophysics Data System (ADS)

Shlykov, Sergey A.; Puchkov, Boris V.; Arnason, Ingvar; Wallevik, Sunna Ó.; Giricheva, Nina I.; Girichev, Georgiy V.; Zhabanov, Yuriy A.

2018-02-01

The synthesis and results of gas electron diffraction (GED), temperature-dependent Raman spectroscopy, along with detailed quantum chemical (QC) study of 1-methoxy-1-silacyclohexane 1 are reported. Within the series of the QC results, DFT(B3LYP, PBE0, M06, M062X), and MP2, the conformational preference predictions are rather contradictive. From the both GED and Raman experimental methods applied, the vapour and liquid phases of 1 were found to exist as a mixture of two conformers, gauche-axial and gauche-equatorial, with almost equal contributions, while the trans-forms are much less stable. In addition, theoretical calculations on the cyclohexane analog, methoxycyclohexane 2, are performed in order to compare with the conformational properties of 1. The latter is predicted not to diminish the axial/equatorial ratio, as contrasted to the expectations at switching the point of the substituent attachment from Si to C.

Holliday Junction Thermodynamics and Structure: Coarse-Grained Simulations and Experiments

NASA Astrophysics Data System (ADS)

Wang, Wujie; Nocka, Laura M.; Wiemann, Brianne Z.; Hinckley, Daniel M.; Mukerji, Ishita; Starr, Francis W.

2016-03-01

Holliday junctions play a central role in genetic recombination, DNA repair and other cellular processes. We combine simulations and experiments to evaluate the ability of the 3SPN.2 model, a coarse-grained representation designed to mimic B-DNA, to predict the properties of DNA Holliday junctions. The model reproduces many experimentally determined aspects of junction structure and stability, including the temperature dependence of melting on salt concentration, the bias between open and stacked conformations, the relative populations of conformers at high salt concentration, and the inter-duplex angle (IDA) between arms. We also obtain a close correspondence between the junction structure evaluated by all-atom and coarse-grained simulations. We predict that, for salt concentrations at physiological and higher levels, the populations of the stacked conformers are independent of salt concentration, and directly observe proposed tetrahedral intermediate sub-states implicated in conformational transitions. Our findings demonstrate that the 3SPN.2 model captures junction properties that are inaccessible to all-atom studies, opening the possibility to simulate complex aspects of junction behavior.

MRI to predict nipple-areola complex (NAC) involvement: An automatic method to compute the 3D distance between the NAC and tumor.

PubMed

Giannini, Valentina; Bianchi, Veronica; Carabalona, Silvia; Mazzetti, Simone; Maggiorotto, Furio; Kubatzki, Franziska; Regge, Daniele; Ponzone, Riccardo; Martincich, Laura

2017-12-01

To assess the role in predicting nipple-areola complex (NAC) involvement of a newly developed automatic method which computes the 3D tumor-NAC distance. Ninety-nine patients scheduled to nipple sparing mastectomy (NSM) underwent magnetic resonance (MR) examination at 1.5 T, including sagittal T2w and dynamic contrast enhanced (DCE)-MR imaging. An automatic method was developed to segment the NAC and the tumor and to compute the 3D distance between them. The automatic measurement was compared with manual axial and sagittal 2D measurements. NAC involvement was defined by the presence of invasive ductal or lobular carcinoma and/or ductal carcinoma in situ or ductal intraepithelial neoplasia (DIN1c - DIN3). Tumor-NAC distance was computed on 95/99 patients (25 NAC+), as three tumors were not correctly segmented (sensitivity = 97%), and 1 NAC was not detected (sensitivity = 99%). The automatic 3D distance reached the highest area under the receiver operating characteristic (ROC) curve (0.830) with respect to the manual axial (0.676), sagittal (0.664), and minimum distances (0.664). At the best cut-off point of 21 mm, the 3D distance obtained sensitivity = 72%, specificity = 80%, positive predictive value = 56%, and negative predictive value = 89%. This method could provide a reproducible biomarker to preoperatively select breast cancer patients candidates to NSM, thus helping surgical planning and intraoperative management of patients. © 2017 Wiley Periodicals, Inc.

BetaSCPWeb: side-chain prediction for protein structures using Voronoi diagrams and geometry prioritization

PubMed Central

Ryu, Joonghyun; Lee, Mokwon; Cha, Jehyun; Laskowski, Roman A.; Ryu, Seong Eon; Kim, Deok-Soo

2016-01-01

Many applications, such as protein design, homology modeling, flexible docking, etc. require the prediction of a protein's optimal side-chain conformations from just its amino acid sequence and backbone structure. Side-chain prediction (SCP) is an NP-hard energy minimization problem. Here, we present BetaSCPWeb which efficiently computes a conformation close to optimal using a geometry-prioritization method based on the Voronoi diagram of spherical atoms. Its outputs are visual, textual and PDB file format. The web server is free and open to all users at http://voronoi.hanyang.ac.kr/betascpweb with no login requirement. PMID:27151195

Methods in Enzymology: “Flexible backbone sampling methods to model and design protein alternative conformations”

PubMed Central

Ollikainen, Noah; Smith, Colin A.; Fraser, James S.; Kortemme, Tanja

2013-01-01

Sampling alternative conformations is key to understanding how proteins work and engineering them for new functions. However, accurately characterizing and modeling protein conformational ensembles remains experimentally and computationally challenging. These challenges must be met before protein conformational heterogeneity can be exploited in protein engineering and design. Here, as a stepping stone, we describe methods to detect alternative conformations in proteins and strategies to model these near-native conformational changes based on backrub-type Monte Carlo moves in Rosetta. We illustrate how Rosetta simulations that apply backrub moves improve modeling of point mutant side chain conformations, native side chain conformational heterogeneity, functional conformational changes, tolerated sequence space, protein interaction specificity, and amino acid co-variation across protein-protein interfaces. We include relevant Rosetta command lines and RosettaScripts to encourage the application of these types of simulations to other systems. Our work highlights that critical scoring and sampling improvements will be necessary to approximate conformational landscapes. Challenges for the future development of these methods include modeling conformational changes that propagate away from designed mutation sites and modulating backbone flexibility to predictively design functionally important conformational heterogeneity. PMID:23422426

Automated assessment of imaging biomarkers for the PanCan lung cancer risk prediction model with validation on NLST data

NASA Astrophysics Data System (ADS)

Wiemker, Rafael; Sevenster, Merlijn; MacMahon, Heber; Li, Feng; Dalal, Sandeep; Tahmasebi, Amir; Klinder, Tobias

2017-03-01

The imaging biomarkers EmphysemaPresence and NoduleSpiculation are crucial inputs for most models aiming to predict the risk of indeterminate pulmonary nodules detected at CT screening. To increase reproducibility and to accelerate screening workflow it is desirable to assess these biomarkers automatically. Validation on NLST images indicates that standard histogram measures are not sufficient to assess EmphysemaPresence in screenees. However, automatic scoring of bulla-resembling low attenuation areas can achieve agreement with experts with close to 80% sensitivity and specificity. NoduleSpiculation can be automatically assessed with similar accuracy. We find a dedicated spiculi tracing score to slightly outperform generic combinations of texture features with classifiers.

Automatic Train Operation Using Autonomic Prediction of Train Runs

NASA Astrophysics Data System (ADS)

Asuka, Masashi; Kataoka, Kenji; Komaya, Kiyotoshi; Nishida, Syogo

In this paper, we present an automatic train control method adaptable to disturbed train traffic conditions. The proposed method presumes transmission of detected time of a home track clearance to trains approaching to the station by employing equipment of Digital ATC (Automatic Train Control). Using the information, each train controls its acceleration by the method that consists of two approaches. First, by setting a designated restricted speed, the train controls its running time to arrive at the next station in accordance with predicted delay. Second, the train predicts the time at which it will reach the current braking pattern generated by Digital ATC, along with the time when the braking pattern transits ahead. By comparing them, the train correctly chooses the coasting drive mode in advance to avoid deceleration due to the current braking pattern. We evaluated the effectiveness of the proposed method regarding driving conditions, energy consumption and reduction of delays by simulation.

Fail-Safe Pressure Plug

NASA Technical Reports Server (NTRS)

Svejkovsky, Paul A.

1993-01-01

Protective plug resists slowly built-up pressure or automatically releases itself if pressure rises suddenly. Seals out moisture at pressures ranging from 50 micrometers of mercury to 200 pounds per square inch. Designed to seal throat of 38 Reaction Control Thrusters on Space Shuttle protecting internal components from corrosion. Plug conforms to contour of nozzle throat, where O-ring forms pressure seal. After plug inserted, cover attached by use of cover-fitting assembly. Modified versions useful in protecting engines, pumps, reaction vessels, and other industrial equipment during shipment and maintenance.

An object programming based environment for protein secondary structure prediction.

PubMed

Giacomini, M; Ruggiero, C; Sacile, R

1996-01-01

The most frequently used methods for protein secondary structure prediction are empirical statistical methods and rule based methods. A consensus system based on object-oriented programming is presented, which integrates the two approaches with the aim of improving the prediction quality. This system uses an object-oriented knowledge representation based on the concepts of conformation, residue and protein, where the conformation class is the basis, the residue class derives from it and the protein class derives from the residue class. The system has been tested with satisfactory results on several proteins of the Brookhaven Protein Data Bank. Its results have been compared with the results of the most widely used prediction methods, and they show a higher prediction capability and greater stability. Moreover, the system itself provides an index of the reliability of its current prediction. This system can also be regarded as a basis structure for programs of this kind.

Visual Benefits in Apparent Motion Displays: Automatically Driven Spatial and Temporal Anticipation Are Partially Dissociated

PubMed Central

Ahrens, Merle-Marie; Veniero, Domenica; Gross, Joachim; Harvey, Monika; Thut, Gregor

2015-01-01

Many behaviourally relevant sensory events such as motion stimuli and speech have an intrinsic spatio-temporal structure. This will engage intentional and most likely unintentional (automatic) prediction mechanisms enhancing the perception of upcoming stimuli in the event stream. Here we sought to probe the anticipatory processes that are automatically driven by rhythmic input streams in terms of their spatial and temporal components. To this end, we employed an apparent visual motion paradigm testing the effects of pre-target motion on lateralized visual target discrimination. The motion stimuli either moved towards or away from peripheral target positions (valid vs. invalid spatial motion cueing) at a rhythmic or arrhythmic pace (valid vs. invalid temporal motion cueing). Crucially, we emphasized automatic motion-induced anticipatory processes by rendering the motion stimuli non-predictive of upcoming target position (by design) and task-irrelevant (by instruction), and by creating instead endogenous (orthogonal) expectations using symbolic cueing. Our data revealed that the apparent motion cues automatically engaged both spatial and temporal anticipatory processes, but that these processes were dissociated. We further found evidence for lateralisation of anticipatory temporal but not spatial processes. This indicates that distinct mechanisms may drive automatic spatial and temporal extrapolation of upcoming events from rhythmic event streams. This contrasts with previous findings that instead suggest an interaction between spatial and temporal attention processes when endogenously driven. Our results further highlight the need for isolating intentional from unintentional processes for better understanding the various anticipatory mechanisms engaged in processing behaviourally relevant stimuli with predictable spatio-temporal structure such as motion and speech. PMID:26623650

Anticipating the future: Automatic prediction failures in schizophrenia

PubMed Central

Ford, Judith M.; Mathalon, Daniel H.

2011-01-01

People with schizophrenia often misperceive sensations and misinterpret experiences, perhaps contributing to psychotic symptoms. These misperceptions and misinterpretations might result from an inability to make valid predictions about expected sensations and experiences. Healthy normal people take advantage of neural mechanisms that allow them to make predictions unconsciously, facilitating processing of expected sensations and distinguishing the expected from the unexpected. In this paper, we focus on two types of automatic, unconscious mechanisms that allow us to predict our perceptions. The first involves predictions made via innate mechanisms basic to all species in the animal kingdom—the efference copy and corollary discharge mechanisms. They accompany our voluntary movements and allow us to suppress sensations resulting from our actions. We study this during talking, and show that auditory cortical response to the speech sounds during talking is reduced compared to when they are played back. This suppression is reduced in schizophrenia, suggesting a failure to predict the sensations resulting from talking. The second mechanism involves implicitly learning what to expect from the current context of events. We study this by observing the brain's response to an unexpected repetition of an event, when a change would have been predicted. That patients have a reduced response suggests they failed to predict that it was time for a change. Both types of predictions should happen automatically and effortlessly, allowing for economic processing of expected events and orientation to unexpected ones. These prediction failures characterize the diagnosis of schizophrenia rather than reflecting specific symptoms. PMID:21959054

Political Correctness and American Academe.

ERIC Educational Resources Information Center

Drucker, Peter F.

1994-01-01

Argues that today's political correctness atmosphere is a throwback to attempts made by the Nazis and Stalinists to force society into conformity. Academia, it is claimed, is being forced to conform to gain control of the institution of higher education. It is predicted that this effort will fail. (GR)

Rotational Spectroscopy and Conformational Studies of 4-PENTYNENITRILE, 4-PENTENENITRILE, and Glutaronitrile

NASA Astrophysics Data System (ADS)

Hays, Brian M.; Mehta-Hurt, Deepali; Jawad, Khadija M.; Hernandez-Castillo, Alicia O.; Abeysekera, Chamara; Zhang, Di; Zwier, Timothy S.

2017-06-01

The pure rotational spectra of 4-pentynenitrile, 4-pentenenitrile, and glutaronitrile were acquired using chirped pulse Fouirer transform microwave spectroscopy. 4-pentynenitrile and 4-pentenenitrile are the recombination products of two resonance stabilized radicals, propargyl + cyanomethyl or allyl + cyanomethyl, respectively, and are thus anticipated to be significant among the more complex nitriles in Titan's atmosphere. Indeed, these partially unsaturated alkyl cyanides have been found in laboratory analogs of tholins and are also expected to have interesting photochemistry. The optimized structures of all conformers below predicted energies of 500 \\wn were calculated for each molecule. Both of the conformers, trans and gauche, for 4-pentynenitrile have been identified and assigned. Five conformers were assigned in 4-pentenenitrile. The eclipsed conformers, with respect to the vinyl group, dominate the spectrum but some population was found in the syn conformers including the syn-gauche conformer, calculated to be 324 \\wn above the global minimum. The glutaronitrile spectrum contained only the two conformers below 500 \\wn, with reduced amount of the gauche trans conformer. The assigned spectra and structural assignments will be presented.

The relationship between parents' and children's automatic thoughts in a college student sample.

PubMed

Donnelly, Reesa; Renk, Kimberly; Sims, Valerie K; McGuire, Jack

2011-04-01

Research demonstrates the importance of early social interactions in the development of schemas and automatic thoughts. It does not appear, however, that the existing research examines intergenerational correlations in automatic thoughts. As a result, this study explores the relationship between the automatic thoughts of parents and those of their college-age children in a sample of 252 college students and their mothers and fathers. Results of this study suggest that there are significant relationships between parents' and college students' positive automatic thoughts. Different trends by gender also are noted in the relationships among variables for male and female college students with their mothers and fathers. Further, mothers' positive ATs predicted the positive ATs of their college students, with mothers' ratings of their own communication with their college students mediating partially this relationship. Finally, college students' anxiety and self-esteem is predicted significantly by their mothers' anxiety and self-esteem (respectively) as well as their own positive and negative ATs. These findings suggest the possibility that ATs play a role in the intergenerational transmission of certain domains of psychological functioning.

Combine experimental and theoretical investigation on an alkaloid-Dimethylisoborreverine

NASA Astrophysics Data System (ADS)

Singh, Swapnil; Singh, Harshita; Karthick, T.; Agarwal, Parag; Erande, Rohan D.; Dethe, Dattatraya H.; Tandon, Poonam

2016-01-01

A combined experimental (FT-IR, 1H and 13C NMR) and theoretical approach is used to study the structure and properties of antimalarial drug dimethylisoborreverine (DMIB). Conformational analysis, has been performed by plotting one dimensional potential energy curve that was computed using density functional theory (DFT) with B3LYP/6-31G method and predicted conformer A1 as the most stable conformer. After full geometry optimization, harmonic wavenumbers were computed for conformer A1 at the DFT/B3LYP/6-311++G(d,P) level. A complete vibrational assignment of all the vibrational modes have been performed on the bases of the potential energy distribution (PED) and theoretical results were found to be in good agreement with the observed data. To predict the solvent effect, the UV-Vis spectra were calculated in different solvents by polarizable continuum model using TD-DFT method. Molecular docking studies were performed to test the biological activity of the sample using SWISSDOCK web server and Hex 8.0.0 software. The molecular electrostatic potential (MESP) was plotted to identify the reactive sites of the molecule. Natural bond orbital (NBO) analysis was performed to get a deep insight of intramolecular charge transfer. Thermodynamical parameters were calculated to predict the direction of chemical reaction.

An Investigation of the Interaction Effects of Acute Self-Esteem and Perceived Competence on Conformity.

DTIC Science & Technology

1978-12-22

a demonstration of the interaction effects of acute self - esteem and perceived competence. Acute self - esteem manipulations (high, low or no) were...On the basis of previous research on conformity it was predicted that subjects who were subjected to acute self - esteem manipulations and perceived...role in conformity. The main effect of self - esteem and the interaction of self - esteem and perceived competence did not prove significant. Results were

A complete, multi-level conformational clustering of antibody complementarity-determining regions

PubMed Central

Nikoloudis, Dimitris; Pitts, Jim E.

2014-01-01

Classification of antibody complementarity-determining region (CDR) conformations is an important step that drives antibody modelling and engineering, prediction from sequence, directed mutagenesis and induced-fit studies, and allows inferences on sequence-to-structure relations. Most of the previous work performed conformational clustering on a reduced set of structures or after application of various structure pre-filtering criteria. In this study, it was judged that a clustering of every available CDR conformation would produce a complete and redundant repertoire, increase the number of sequence examples and allow better decisions on structure validity in the future. In order to cope with the potential increase in data noise, a first-level statistical clustering was performed using structure superposition Root-Mean-Square Deviation (RMSD) as a distance-criterion, coupled with second- and third-level clustering that employed Ramachandran regions for a deeper qualitative classification. The classification of a total of 12,712 CDR conformations is thus presented, along with rich annotation and cluster descriptions, and the results are compared to previous major studies. The present repertoire has procured an improved image of our current CDR Knowledge-Base, with a novel nesting of conformational sensitivity and specificity that can serve as a systematic framework for improved prediction from sequence as well as a number of future studies that would aid in knowledge-based antibody engineering such as humanisation. PMID:25071986

Conformational stability, structural parameters and vibrational assignment from variable temperature infrared spectra of krypton solutions and ab initio calculations of ethylisothiocyanate.

PubMed

Durig, James R; Zheng, Chao

2007-11-01

Variable temperature (-105 to -150 degrees C) studies of the infrared spectra (3500-400 cm(-1)) of ethylisothiocyanate, CH(3)CH(2)NCS, dissolved in liquid krypton have been recorded. Additionally the infrared spectra of the gas and solid have been re-investigated. These spectroscopic data indicate a single conformer in all physical states with a large number of molecules in the gas phase at ambient temperature in excited states of the CN torsional mode which has a very low barrier to conformational interchange. To aid in the analyses of the vibrational and rotational spectra, ab initio calculations have been carried out by the perturbation method to the second order (MP2) with valence and core electron correlation using a variety of basis sets up to 6-311+G(2df,2pd). With the smaller basis sets up to 6-311+G(d,p) and cc-PVDZ, the cis conformer is indicated as a transition state with all larger basis sets the cis conformer is the only stable form. The predicted energy difference from these calculations between the cis form and the higher energy trans conformer is about 125 cm(-1) which represents essentially the barrier to internal rotation of the NCS group (rotation around NC axis). Density functional theory calculation by the B3LYP method with the same basis sets predicts this barrier to be about 25 cm(-1). By utilizing the previously reported microwave rotational constants with the structural parameters predicted by the ab initio MP2(full)/6-311+G(d,p) calculations, adjusted r(0) structural parameters have been obtained for the cis form. The determined heavy atom parameters are: r(NC)=1.196(5), r(CS)=1.579(5), r(CN)=1.439(5), r(CC)=1.519(5)A for the distances and angles of angleCCN=112.1(5), angleCNC=146.2(5), angleNCS=174.0(5) degrees . The centrifugal distortion constants, dipole moments, conformational stability, vibrational frequencies, infrared intensities and Raman activities have been predicted from ab initio calculations and compared to experimental quantities when available. These results are compared to the corresponding quantities of some similar molecules.

CAL3JHH: a Java program to calculate the vicinal coupling constants (3J H,H) of organic molecules.

PubMed

Aguirre-Valderrama, Alonso; Dobado, José A

2008-12-01

Here, we present a free web-accessible application, developed in the JAVA programming language for the calculation of vicinal coupling constant (3J(H,H)) of organic molecules with the H-Csp3-Csp3-H fragment. This JAVA applet is oriented to assist chemists in structural and conformational analyses, allowing the user to calculate the averaged 3J(H,H) values among conformers, according to its Boltzmann populations. Thus, the CAL3JHH program uses the Haasnoot-Leeuw-Altona equation, and, by reading the molecule geometry from a protein data bank (PDB) file format or from multiple pdb files, automatically detects all the coupled hydrogens, evaluating the data needed for this equation. Moreover, a "Graphical viewer" menu allows the display of the results on the 3D molecule structure, as well as the plotting of the Newman projection for the couplings.

Communication: Multiple atomistic force fields in a single enhanced sampling simulation

NASA Astrophysics Data System (ADS)

Hoang Viet, Man; Derreumaux, Philippe; Nguyen, Phuong H.

2015-07-01

The main concerns of biomolecular dynamics simulations are the convergence of the conformational sampling and the dependence of the results on the force fields. While the first issue can be addressed by employing enhanced sampling techniques such as simulated tempering or replica exchange molecular dynamics, repeating these simulations with different force fields is very time consuming. Here, we propose an automatic method that includes different force fields into a single advanced sampling simulation. Conformational sampling using three all-atom force fields is enhanced by simulated tempering and by formulating the weight parameters of the simulated tempering method in terms of the energy fluctuations, the system is able to perform random walk in both temperature and force field spaces. The method is first demonstrated on a 1D system and then validated by the folding of the 10-residue chignolin peptide in explicit water.

Spectroscopic study of jet-cooled indole-3-carbinol by laser desorption technique: Franck-Condon simulations and anharmonic calculations

NASA Astrophysics Data System (ADS)

Ahn, Ahreum; Min, Ahreum; Moon, Cheol Joo; Lee, Ji Hoon; Lee, Seung Jun; Warashina, Taichi; Ishiuchi, Shun-ichi; Fujii, Masaaki; Choi, Myong Yong

2015-10-01

The conformational structure of indole-3-carbinol (I3C) has been investigated in the gas phase for the first time using a laser desorption technique. A UV-UV hole-burning technique revealed the presence of a single conformer of I3C in the mass-selected resonant two-photon ionization spectrum. The assignment of the observed IR spectrum of I3C is inconclusive due to almost identically predicted IR frequencies of the two lowest energy conformers from harmonic calculations. A conclusive assignment for the conformer of I3C has been reported with an aid of performing anharmonic calculations and Franck-Condon simulations on the two lowest-energy conformers.

Multiple two-dimensional versus three-dimensional PTV definition in treatment planning for conformal radiotherapy.

PubMed

Stroom, J C; Korevaar, G A; Koper, P C; Visser, A G; Heijmen, B J

1998-06-01

To demonstrate the need for a fully three-dimensional (3D) computerized expansion of the gross tumour volume (GTV) or clinical target volume (CTV), as delineated by the radiation oncologist on CT slices, to obtain the proper planning target volume (PTV) for treatment planning according to the ICRU-50 recommendations. For 10 prostate cancer patients two PTVs have been determined by expansion of the GTV with a 1.5 cm margin, i.e. a 3D PTV and a multiple 2D PTV. The former was obtained by automatically adding the margin while accounting in 3D for GTV contour differences in neighbouring slices. The latter was generated by automatically adding the 1.5 cm margin to the GTV in each CT slice separately; the resulting PTV is a computer simulation of the PTV that a radiation oncologist would obtain with (the still common) manual contouring in CT slices. For each patient the two PTVs were compared to assess the deviations of the multiple 2D PTV from the 3D PTV. For both PTVs conformal plans were designed using a three-field technique with fixed block margins. For each patient dose-volume histograms and tumour control probabilities (TCPs) of the (correct) 3D PTV were calculated, both for the plan designed for this PTV and for the treatment plan based on the (deviating) 2D PTV. Depending on the shape of the GTV, multiple 2D PTV generation could locally result in a 1 cm underestimation of the GTV-to-PTV margin. The deviations occurred predominantly in the cranio-caudal direction at locations where the GTV contour shape varies significantly from slice to slice. This could lead to serious underdosage and to a TCP decrease of up to 15%. A full 3D GTV-to-PTV expansion should be applied in conformal radiotherapy to avoid underdosage.

Predicting human activities in sequences of actions in RGB-D videos

NASA Astrophysics Data System (ADS)

Jardim, David; Nunes, Luís.; Dias, Miguel

2017-03-01

In our daily activities we perform prediction or anticipation when interacting with other humans or with objects. Prediction of human activity made by computers has several potential applications: surveillance systems, human computer interfaces, sports video analysis, human-robot-collaboration, games and health-care. We propose a system capable of recognizing and predicting human actions using supervised classifiers trained with automatically labeled data evaluated in our human activity RGB-D dataset (recorded with a Kinect sensor) and using only the position of the main skeleton joints to extract features. Using conditional random fields (CRFs) to model the sequential nature of actions in a sequence has been used before, but where other approaches try to predict an outcome or anticipate ahead in time (seconds), we try to predict what will be the next action of a subject. Our results show an activity prediction accuracy of 89.9% using an automatically labeled dataset.

Electromagnetic Thermography Nondestructive Evaluation: Physics-based Modeling and Pattern Mining

PubMed Central

Gao, Bin; Woo, Wai Lok; Tian, Gui Yun

2016-01-01

Electromagnetic mechanism of Joule heating and thermal conduction on conductive material characterization broadens their scope for implementation in real thermography based Nondestructive testing and evaluation (NDT&E) systems by imparting sensitivity, conformability and allowing fast and imaging detection, which is necessary for efficiency. The issue of automatic material evaluation has not been fully addressed by researchers and it marks a crucial first step to analyzing the structural health of the material, which in turn sheds light on understanding the production of the defects mechanisms. In this study, we bridge the gap between the physics world and mathematical modeling world. We generate physics-mathematical modeling and mining route in the spatial-, time-, frequency-, and sparse-pattern domains. This is a significant step towards realizing the deeper insight in electromagnetic thermography (EMT) and automatic defect identification. This renders the EMT a promising candidate for the highly efficient and yet flexible NDT&E. PMID:27158061

Alternating evolutionary pressure in a genetic algorithm facilitates protein model selection

PubMed Central

Offman, Marc N; Tournier, Alexander L; Bates, Paul A

2008-01-01

Background Automatic protein modelling pipelines are becoming ever more accurate; this has come hand in hand with an increasingly complicated interplay between all components involved. Nevertheless, there are still potential improvements to be made in template selection, refinement and protein model selection. Results In the context of an automatic modelling pipeline, we analysed each step separately, revealing several non-intuitive trends and explored a new strategy for protein conformation sampling using Genetic Algorithms (GA). We apply the concept of alternating evolutionary pressure (AEP), i.e. intermediate rounds within the GA runs where unrestrained, linear growth of the model populations is allowed. Conclusion This approach improves the overall performance of the GA by allowing models to overcome local energy barriers. AEP enabled the selection of the best models in 40% of all targets; compared to 25% for a normal GA. PMID:18673557

Fragmentation of Red Blood Cells Caused Pseudothrombocytosis in a Patient.

PubMed

Tang, Wenjun; Tang, Chunhua; Zheng, Jianfeng; He, Yongling; Lu, Fangfang

2018-06-01

Pseudothrombocytopenia, caused by platelet (PLT) clumping, is often found in clinical studies [1]. However, pseudothrombocytosis resulting from the fragmentation of red blood cells (RBCs) is a very rare phenomenon. EDTA-K2 anticoagulation was used on a sample of venous blood extracted from the patient. A Symex XN9000 automatic blood analyzer was used to conduct CBC + DIFF mode and CBC + DIFF + RET mode tests, stained smear microscopy. The Symex XN9000 automatic blood analyzer was used to conduct CBC + DIFF mode test; PLTs were measured at 570 x 109/L. Stained smear microscopy revealed the number of PLTs did not conform to the instrument measured 570 x 109/L. "RET" alarm instrument, switch to CBC + DIFF + RET mode for testing. The second test result showed PLTs at 128 x 109/L, which accords with artificial microscopy. This was a case of a very rare phenomenon: the fragmentation of RBCs caused pseudothrombocytosis.

Quantum-mechanics-derived 13Cα chemical shift server (CheShift) for protein structure validation

PubMed Central

Vila, Jorge A.; Arnautova, Yelena A.; Martin, Osvaldo A.; Scheraga, Harold A.

2009-01-01

A server (CheShift) has been developed to predict 13Cα chemical shifts of protein structures. It is based on the generation of 696,916 conformations as a function of the φ, ψ, ω, χ1 and χ2 torsional angles for all 20 naturally occurring amino acids. Their 13Cα chemical shifts were computed at the DFT level of theory with a small basis set and extrapolated, with an empirically-determined linear regression formula, to reproduce the values obtained with a larger basis set. Analysis of the accuracy and sensitivity of the CheShift predictions, in terms of both the correlation coefficient R and the conformational-averaged rmsd between the observed and predicted 13Cα chemical shifts, was carried out for 3 sets of conformations: (i) 36 x-ray-derived protein structures solved at 2.3 Å or better resolution, for which sets of 13Cα chemical shifts were available; (ii) 15 pairs of x-ray and NMR-derived sets of protein conformations; and (iii) a set of decoys for 3 proteins showing an rmsd with respect to the x-ray structure from which they were derived of up to 3 Å. Comparative analysis carried out with 4 popular servers, namely SHIFTS, SHIFTX, SPARTA, and PROSHIFT, for these 3 sets of conformations demonstrated that CheShift is the most sensitive server with which to detect subtle differences between protein models and, hence, to validate protein structures determined by either x-ray or NMR methods, if the observed 13Cα chemical shifts are available. CheShift is available as a web server. PMID:19805131

A flexible docking scheme to explore the binding selectivity of PDZ domains.

PubMed

Gerek, Z Nevin; Ozkan, S Banu

2010-05-01

Modeling of protein binding site flexibility in molecular docking is still a challenging problem due to the large conformational space that needs sampling. Here, we propose a flexible receptor docking scheme: A dihedral restrained replica exchange molecular dynamics (REMD), where we incorporate the normal modes obtained by the Elastic Network Model (ENM) as dihedral restraints to speed up the search towards correct binding site conformations. To our knowledge, this is the first approach that uses ENM modes to bias REMD simulations towards binding induced fluctuations in docking studies. In our docking scheme, we first obtain the deformed structures of the unbound protein as initial conformations by moving along the binding fluctuation mode, and perform REMD using the ENM modes as dihedral restraints. Then, we generate an ensemble of multiple receptor conformations (MRCs) by clustering the lowest replica trajectory. Using ROSETTALIGAND, we dock ligands to the clustered conformations to predict the binding pose and affinity. We apply this method to postsynaptic density-95/Dlg/ZO-1 (PDZ) domains; whose dynamics govern their binding specificity. Our approach produces the lowest energy bound complexes with an average ligand root mean square deviation of 0.36 A. We further test our method on (i) homologs and (ii) mutant structures of PDZ where mutations alter the binding selectivity. In both cases, our approach succeeds to predict the correct pose and the affinity of binding peptides. Overall, with this approach, we generate an ensemble of MRCs that leads to predict the binding poses and specificities of a protein complex accurately.

A flexible docking scheme to explore the binding selectivity of PDZ domains

PubMed Central

Gerek, Z Nevin; Ozkan, S Banu

2010-01-01

Modeling of protein binding site flexibility in molecular docking is still a challenging problem due to the large conformational space that needs sampling. Here, we propose a flexible receptor docking scheme: A dihedral restrained replica exchange molecular dynamics (REMD), where we incorporate the normal modes obtained by the Elastic Network Model (ENM) as dihedral restraints to speed up the search towards correct binding site conformations. To our knowledge, this is the first approach that uses ENM modes to bias REMD simulations towards binding induced fluctuations in docking studies. In our docking scheme, we first obtain the deformed structures of the unbound protein as initial conformations by moving along the binding fluctuation mode, and perform REMD using the ENM modes as dihedral restraints. Then, we generate an ensemble of multiple receptor conformations (MRCs) by clustering the lowest replica trajectory. Using RosettaLigand, we dock ligands to the clustered conformations to predict the binding pose and affinity. We apply this method to postsynaptic density-95/Dlg/ZO-1 (PDZ) domains; whose dynamics govern their binding specificity. Our approach produces the lowest energy bound complexes with an average ligand root mean square deviation of 0.36 Å. We further test our method on (i) homologs and (ii) mutant structures of PDZ where mutations alter the binding selectivity. In both cases, our approach succeeds to predict the correct pose and the affinity of binding peptides. Overall, with this approach, we generate an ensemble of MRCs that leads to predict the binding poses and specificities of a protein complex accurately. PMID:20196074

Analysis and prediction of calcium-binding pockets from apo-protein structures exhibiting calcium-induced localized conformational changes

PubMed Central

Wang, Xue; Zhao, Kun; Kirberger, Michael; Wong, Hing; Chen, Guantao; Yang, Jenny J

2010-01-01

Calcium binding in proteins exhibits a wide range of polygonal geometries that relate directly to an equally diverse set of biological functions. The binding process stabilizes protein structures and typically results in local conformational change and/or global restructuring of the backbone. Previously, we established the MUG program, which utilized multiple geometries in the Ca2+-binding pockets of holoproteins to identify such pockets, ignoring possible Ca2+-induced conformational change. In this article, we first report our progress in the analysis of Ca2+-induced conformational changes followed by improved prediction of Ca2+-binding sites in the large group of Ca2+-binding proteins that exhibit only localized conformational changes. The MUGSR algorithm was devised to incorporate side chain torsional rotation as a predictor. The output from MUGSR presents groups of residues where each group, typically containing two to five residues, is a potential binding pocket. MUGSR was applied to both X-ray apo structures and NMR holo structures, which did not use calcium distance constraints in structure calculations. Predicted pockets were validated by comparison with homologous holo structures. Defining a “correct hit” as a group of residues containing at least two true ligand residues, the sensitivity was at least 90%; whereas for a “correct hit” defined as a group of residues containing at least three true ligand residues, the sensitivity was at least 78%. These data suggest that Ca2+-binding pockets are at least partially prepositioned to chelate the ion in the apo form of the protein. PMID:20512971

Neurotransmitters in the Gas Phase: La-Mb Studies

NASA Astrophysics Data System (ADS)

Cabezas, C.; Mata, S.; López, J. C.; Alonso, J. L.

2011-06-01

LA-MB-FTMW spectroscopy combines laser ablation with Fourier transform microwave spectroscopy in supersonic jets overcoming the problems of thermal decomposition associated with conventional heating methods. We present here the results on LA-MB-FTMW studies of some neurotransmitters. Six conformers of dopamine, four of adrenaline, five of noradrenaline and three conformers of serotonin have been characterized in the gas phase. The rotational and nuclear quadrupole coupling constants extracted from the analysis of the rotational spectrum are directly compared with those predicted by ab initio methods to achieve the conclusive identification of different conformers and the experimental characterization of the intramolecular forces at play which control conformational preferences.

BetaSCPWeb: side-chain prediction for protein structures using Voronoi diagrams and geometry prioritization.

PubMed

Ryu, Joonghyun; Lee, Mokwon; Cha, Jehyun; Laskowski, Roman A; Ryu, Seong Eon; Kim, Deok-Soo

2016-07-08

Many applications, such as protein design, homology modeling, flexible docking, etc. require the prediction of a protein's optimal side-chain conformations from just its amino acid sequence and backbone structure. Side-chain prediction (SCP) is an NP-hard energy minimization problem. Here, we present BetaSCPWeb which efficiently computes a conformation close to optimal using a geometry-prioritization method based on the Voronoi diagram of spherical atoms. Its outputs are visual, textual and PDB file format. The web server is free and open to all users at http://voronoi.hanyang.ac.kr/betascpweb with no login requirement. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

A network of molecular switches controls the activation of the two-component response regulator NtrC

NASA Astrophysics Data System (ADS)

Vanatta, Dan K.; Shukla, Diwakar; Lawrenz, Morgan; Pande, Vijay S.

2015-06-01

Recent successes in simulating protein structure and folding dynamics have demonstrated the power of molecular dynamics to predict the long timescale behaviour of proteins. Here, we extend and improve these methods to predict molecular switches that characterize conformational change pathways between the active and inactive state of nitrogen regulatory protein C (NtrC). By employing unbiased Markov state model-based molecular dynamics simulations, we construct a dynamic picture of the activation pathways of this key bacterial signalling protein that is consistent with experimental observations and predicts new mutants that could be used for validation of the mechanism. Moreover, these results suggest a novel mechanistic paradigm for conformational switching.

Game Theory and Social Psychology: Conformity Games

NASA Astrophysics Data System (ADS)

Alessio, Danielle; Kilgour, D. Marc

2011-11-01

Game models can contribute to understanding of how social biases and pressures to conform can lead to puzzling behaviour in social groups. A model of the psychological biases false uniqueness and false consensus is set out. The model predicts the phenomenon of pluralistic ignorance, which is well-studied in social psychology, showing how it arises as a result of the prevalence of false uniqueness and the desire to conform. An efficient method is developed for finding Nash equilibria of the model under certain restrictions.

Piloted Simulation of a Model-Predictive Automated Recovery System

NASA Technical Reports Server (NTRS)

Liu, James (Yuan); Litt, Jonathan; Sowers, T. Shane; Owens, A. Karl; Guo, Ten-Huei

2014-01-01

This presentation describes a model-predictive automatic recovery system for aircraft on the verge of a loss-of-control situation. The system determines when it must intervene to prevent an imminent accident, resulting from a poor approach. It estimates the altitude loss that would result from a go-around maneuver at the current flight condition. If the loss is projected to violate a minimum altitude threshold, the maneuver is automatically triggered. The system deactivates to allow landing once several criteria are met. Piloted flight simulator evaluation showed the system to provide effective envelope protection during extremely unsafe landing attempts. The results demonstrate how flight and propulsion control can be integrated to recover control of the vehicle automatically and prevent a potential catastrophe.

Evidence that Membrane Insertion of the Cytosolic Domain of Bcl-xL is Governed by an Electrostatic Mechanism

PubMed Central

Thuduppathy, Guruvasuthevan R.; Craig, Jeffrey W.; Schon, Victoria Kholodenko Arne; Hill, R. Blake

2006-01-01

Signals from different cellular networks are integrated at the mitochondria in the regulation of apoptosis. This integration is controlled by the Bcl-2 proteins, many of which change localization fromthe cytosol to the mitochondrial outer membrane in this regulation. For Bcl-xL, this change in localization reflects the ability to undergo a conformational change from a solution to integral membrane conformation. To characterize this conformational change, structural and thermodynamic measurements were performed in the absence and presence of lipid vesicles with Bcl-xL. A pH-dependent model is proposed for the solution to membrane conformational change that consists of three stable conformations: a solution conformation, a conformation similar to the solution conformation but anchored to the membrane by its C-terminal transmembrane domain, and a membrane conformation that is fully associated with the membrane. This model predicts that the solution to membrane conformational change is independent of the C-terminal trans-membrane domain, which is experimentally demonstrated. The conformational change is associated with changes in secondary and, especially, tertiary structure of the protein, as measured by far and near-UV circular dichroism spectroscopy, respectively. Membrane insertion was distinguished from peripheral association with the membrane by quenching of intrinsic tryptophan fluorescence by acrylamide and brominated lipids. For the cytosolic domain, the free energy of insertion ( ΔGox) into lipid vesicles was determined to be −6.5 k cal mol−1 at pH4.9 by vesicle binding experiments. To test whether electrostatic interactions were significant to this process, the salt dependence of this conformational change was measured and analyzed in terms of Gouy–Chapman theory to estimate an electrostatic contribution of ΔGoel ~−2.5 kcal mol−1 and a non-electrostatic contribution of ΔGonel ~−4.0 kcal mol−1 to the free energy of insertion, ΔGox. Calcium, which blocks ion channel activity of Bcl-xL, did not affect the solution to membrane conformational change more than predicted by these electrostatic considerations. The lipid cardiolipin, that is enriched at mitochondrial contact sites and reported to be important for the localization of Bcl-2 proteins, did not affect the solution to membrane conformational change of the cytosolic domain, suggesting that this lipid is not involved in the localization of Bcl-xL in vivo. Collectively, these data suggest the solution to membrane conformational change is controlled by an electrostatic mechanism. Given the distinct biological activities of these conformations, the possibility that this conformational change might be a regulatory checkpoint for apoptosis is discussed. PMID:16650855

Optimal Predictions in Everyday Cognition: The Wisdom of Individuals or Crowds?

ERIC Educational Resources Information Center

Mozer, Michael C.; Pashler, Harold; Homaei, Hadjar

2008-01-01

Griffiths and Tenenbaum (2006) asked individuals to make predictions about the duration or extent of everyday events (e.g., cake baking times), and reported that predictions were optimal, employing Bayesian inference based on veridical prior distributions. Although the predictions conformed strikingly to statistics of the world, they reflect…

GMP-conformant on-site manufacturing of a CD133+ stem cell product for cardiovascular regeneration.

PubMed

Skorska, Anna; Müller, Paula; Gaebel, Ralf; Große, Jana; Lemcke, Heiko; Lux, Cornelia A; Bastian, Manuela; Hausburg, Frauke; Zarniko, Nicole; Bubritzki, Sandra; Ruch, Ulrike; Tiedemann, Gudrun; David, Robert; Steinhoff, Gustav

2017-02-10

CD133 + stem cells represent a promising subpopulation for innovative cell-based therapies in cardiovascular regeneration. Several clinical trials have shown remarkable beneficial effects following their intramyocardial transplantation. Yet, the purification of CD133 + stem cells is typically performed in centralized clean room facilities using semi-automatic manufacturing processes based on magnetic cell sorting (MACS®). However, this requires time-consuming and cost-intensive logistics. CD133 + stem cells were purified from patient-derived sternal bone marrow using the recently developed automatic CliniMACS Prodigy® BM-133 System (Prodigy). The entire manufacturing process, as well as the subsequent quality control of the final cell product (CP), were realized on-site and in compliance with EU guidelines for Good Manufacturing Practice. The biological activity of automatically isolated CD133 + cells was evaluated and compared to manually isolated CD133 + cells via functional assays as well as immunofluorescence microscopy. In addition, the regenerative potential of purified stem cells was assessed 3 weeks after transplantation in immunodeficient mice which had been subjected to experimental myocardial infarction. We established for the first time an on-site manufacturing procedure for stem CPs intended for the treatment of ischemic heart diseases using an automatized system. On average, 0.88 × 10 6 viable CD133 + cells with a mean log 10 depletion of 3.23 ± 0.19 of non-target cells were isolated. Furthermore, we demonstrated that these automatically isolated cells bear proliferation and differentiation capacities comparable to manually isolated cells in vitro. Moreover, the automatically generated CP shows equal cardiac regeneration potential in vivo. Our results indicate that the Prodigy is a powerful system for automatic manufacturing of a CD133 + CP within few hours. Compared to conventional manufacturing processes, future clinical application of this system offers multiple benefits including stable CP quality and on-site purification under reduced clean room requirements. This will allow saving of time, reduced logistics and diminished costs.

Automated identification of functional dynamic networks from X-ray crystallography

PubMed Central

van den Bedem, Henry; Bhabha, Gira; Yang, Kun; Wright, Peter E.; Fraser, James S.

2013-01-01

Protein function often depends on the exchange between conformational substates. Allosteric ligand binding or distal mutations can stabilize specific active site conformations and consequently alter protein function. In addition to comparing independently determined X-ray crystal structures, alternative conformations observed at low levels of electron density have the potential to provide mechanistic insights into conformational dynamics. Here, we report a new multi-conformer contact network algorithm (CONTACT) that identifies networks of conformationally heterogeneous residues directly from high-resolution X-ray crystallography data. Contact networks in Escherichia coli dihydrofolate reductase (ecDHFR) predict the long-range pattern of NMR chemical shift perturbations of an allosteric mutation. A comparison of contact networks in wild type and mutant ecDHFR suggests how mutations that alter optimized networks of coordinated motions can impair catalytic function. Thus, CONTACT-guided mutagenesis will allow the structure-dynamics-function relationship to be exploited in protein engineering and design. PMID:23913260

Prospective clinical validation of independent DVH prediction for plan QA in automatic treatment planning for prostate cancer patients.

PubMed

Wang, Yibing; Heijmen, Ben J M; Petit, Steven F

2017-12-01

To prospectively investigate the use of an independent DVH prediction tool to detect outliers in the quality of fully automatically generated treatment plans for prostate cancer patients. A plan QA tool was developed to predict rectum, anus and bladder DVHs, based on overlap volume histograms and principal component analysis (PCA). The tool was trained with 22 automatically generated, clinical plans, and independently validated with 21 plans. Its use was prospectively investigated for 50 new plans by replanning in case of detected outliers. For rectum D mean , V 65Gy , V 75Gy , anus D mean , and bladder D mean , the difference between predicted and achieved was within 0.4 Gy or 0.3% (SD within 1.8 Gy or 1.3%). Thirteen detected outliers were re-planned, leading to moderate but statistically significant improvements (mean, max): rectum D mean (1.3 Gy, 3.4 Gy), V 65Gy (2.7%, 4.2%), anus D mean (1.6 Gy, 6.9 Gy), and bladder D mean (1.5 Gy, 5.1 Gy). The rectum V 75Gy of the new plans slightly increased (0.2%, p = 0.087). A high accuracy DVH prediction tool was developed and used for independent QA of automatically generated plans. In 28% of plans, minor dosimetric deviations were observed that could be improved by plan adjustments. Larger gains are expected for manually generated plans. Copyright © 2017 Elsevier B.V. All rights reserved.

Modeling and optimization of atomic layer deposition processes on vertically aligned carbon nanotubes.

PubMed

Yazdani, Nuri; Chawla, Vipin; Edwards, Eve; Wood, Vanessa; Park, Hyung Gyu; Utke, Ivo

2014-01-01

Many energy conversion and storage devices exploit structured ceramics with large interfacial surface areas. Vertically aligned carbon nanotube (VACNT) arrays have emerged as possible scaffolds to support large surface area ceramic layers. However, obtaining conformal and uniform coatings of ceramics on structures with high aspect ratio morphologies is non-trivial, even with atomic layer deposition (ALD). Here we implement a diffusion model to investigate the effect of the ALD parameters on coating kinetics and use it to develop a guideline for achieving conformal and uniform thickness coatings throughout the depth of ultra-high aspect ratio structures. We validate the model predictions with experimental data from ALD coatings of VACNT arrays. However, the approach can be applied to predict film conformality as a function of depth for any porous topology, including nanopores and nanowire arrays.

Automatically activated shame reactions and perceived legitimacy of discrimination: A longitudinal study among people with mental illness

PubMed Central

Rüsch, Nicolas; Todd, Andrew R.; Bodenhausen, Galen V.; Olschewski, Manfred; Corrigan, Patrick W.

2009-01-01

Perceived legitimacy of discrimination shapes reactions to mental illness stigma among stigmatized individuals. We assessed deliberately endorsed versus automatic shame-related reactions to mental illness as predictors of change in perceived legitimacy of discrimination over six months among 75 people with mental illness. Automatically activated shame-related associations with mental illness were measured using the Brief Implicit Association Test, deliberately endorsed beliefs via self-report. Controlling for depression and perceived stigma, stronger baseline automatic shame-related associations, but not deliberately endorsed beliefs, predicted higher perceived legitimacy of discrimination after six months. Automatically activated shame reactions may increase vulnerability to mental illness stigma. PMID:19897173

Parental Qualities as Predictors of Adolescent Conformity: Perceptions from Adolescents, Mothers, and Fathers.

ERIC Educational Resources Information Center

Henry, Carolyn S.; Peterson, Gary W.

The purpose of this study was to examine how adolescent and parental perceptions of selected parental qualities predicted adolescent conformity to parental expectations, using symbolic interaction as a conceptual foundation. Self-report questionnaire data were collected from a sample of 326 families with adolescents. Four separate multiple…

Voxel-based dose prediction with multi-patient atlas selection for automated radiotherapy treatment planning

NASA Astrophysics Data System (ADS)

McIntosh, Chris; Purdie, Thomas G.

2017-01-01

Automating the radiotherapy treatment planning process is a technically challenging problem. The majority of automated approaches have focused on customizing and inferring dose volume objectives to be used in plan optimization. In this work we outline a multi-patient atlas-based dose prediction approach that learns to predict the dose-per-voxel for a novel patient directly from the computed tomography planning scan without the requirement of specifying any objectives. Our method learns to automatically select the most effective atlases for a novel patient, and then map the dose from those atlases onto the novel patient. We extend our previous work to include a conditional random field for the optimization of a joint distribution prior that matches the complementary goals of an accurately spatially distributed dose distribution while still adhering to the desired dose volume histograms. The resulting distribution can then be used for inverse-planning with a new spatial dose objective, or to create typical dose volume objectives for the canonical optimization pipeline. We investigated six treatment sites (633 patients for training and 113 patients for testing) and evaluated the mean absolute difference in all DVHs for the clinical and predicted dose distribution. The results on average are favorable in comparison to our previous approach (1.91 versus 2.57). Comparing our method with and without atlas-selection further validates that atlas-selection improved dose prediction on average in whole breast (0.64 versus 1.59), prostate (2.13 versus 4.07), and rectum (1.46 versus 3.29) while it is less important in breast cavity (0.79 versus 0.92) and lung (1.33 versus 1.27) for which there is high conformity and minimal dose shaping. In CNS brain, atlas-selection has the potential to be impactful (3.65 versus 5.09), but selecting the ideal atlas is the most challenging.

Rotation curve for the Milky Way galaxy in conformal gravity

NASA Astrophysics Data System (ADS)

O'Brien, James G.; Moss, Robert J.

2015-05-01

Galactic rotation curves have proven to be the testing ground for dark matter bounds in galaxies, and our own Milky Way is one of many large spiral galaxies that must follow the same models. Over the last decade, the rotation of the Milky Way galaxy has been studied and extended by many authors. Since the work of conformal gravity has now successfully fit the rotation curves of almost 140 galaxies, we present here the fit to our own Milky Way. However, the Milky Way is not just an ordinary galaxy to append to our list, but instead provides a robust test of a fundamental difference of conformal gravity rotation curves versus standard cold dark matter models. It was shown by Mannheim and O'Brien that in conformal gravity, the presence of a quadratic potential causes the rotation curve to eventually fall off after its flat portion. This effect can currently be seen in only a select few galaxies whose rotation curve is studied well beyond a few multiples of the optical galactic scale length. Due to the recent work of Sofue et al and Kundu et al, the rotation curve of the Milky Way has now been studied to a degree where we can test the predicted fall off in the conformal gravity rotation curve. We find that - like the other galaxies already studied in conformal gravity - we obtain amazing agreement with rotational data and the prediction includes the eventual fall off at large distances from the galactic center.

Machine learning in updating predictive models of planning and scheduling transportation projects

DOT National Transportation Integrated Search

1997-01-01

A method combining machine learning and regression analysis to automatically and intelligently update predictive models used in the Kansas Department of Transportations (KDOTs) internal management system is presented. The predictive models used...

Coupling Protein Side-Chain and Backbone Flexibility Improves the Re-design of Protein-Ligand Specificity.

PubMed

Ollikainen, Noah; de Jong, René M; Kortemme, Tanja

2015-01-01

Interactions between small molecules and proteins play critical roles in regulating and facilitating diverse biological functions, yet our ability to accurately re-engineer the specificity of these interactions using computational approaches has been limited. One main difficulty, in addition to inaccuracies in energy functions, is the exquisite sensitivity of protein-ligand interactions to subtle conformational changes, coupled with the computational problem of sampling the large conformational search space of degrees of freedom of ligands, amino acid side chains, and the protein backbone. Here, we describe two benchmarks for evaluating the accuracy of computational approaches for re-engineering protein-ligand interactions: (i) prediction of enzyme specificity altering mutations and (ii) prediction of sequence tolerance in ligand binding sites. After finding that current state-of-the-art "fixed backbone" design methods perform poorly on these tests, we develop a new "coupled moves" design method in the program Rosetta that couples changes to protein sequence with alterations in both protein side-chain and protein backbone conformations, and allows for changes in ligand rigid-body and torsion degrees of freedom. We show significantly increased accuracy in both predicting ligand specificity altering mutations and binding site sequences. These methodological improvements should be useful for many applications of protein-ligand design. The approach also provides insights into the role of subtle conformational adjustments that enable functional changes not only in engineering applications but also in natural protein evolution.

Distinguishing the affective and cognitive bases of implicit attitudes to improve prediction of food choices.

PubMed

Trendel, Olivier; Werle, Carolina O C

2016-09-01

Eating behaviors largely result from automatic processes. Yet, in existing research, automatic or implicit attitudes toward food often fail to predict eating behaviors. Applying findings in cognitive neuroscience research, we propose and find that a central reason why implicit attitudes toward food are not good predictors of eating behaviors is that implicit attitudes are driven by two distinct constructs that often have diverging evaluative consequences: the automatic affective reactions to food (e.g., tastiness; the affective basis of implicit attitudes) and the automatic cognitive reactions to food (e.g., healthiness; the cognitive basis of implicit attitudes). More importantly, we find that the affective and cognitive bases of implicit attitudes directly and uniquely influence actual food choices under different conditions. While the affective basis of implicit attitude is the main driver of food choices, it is the only driver when cognitive resources during choice are limited. The cognitive basis of implicit attitudes uniquely influences food choices when cognitive resources during choice are plentiful but only for participants low in impulsivity. Researchers interested in automatic processes in eating behaviors could thus benefit by distinguishing between the affective and cognitive bases of implicit attitudes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Self-objectification, feminist activism and conformity to feminine norms among female vegetarians, semi-vegetarians, and non-vegetarians.

PubMed

Brinkman, Britney G; Khan, Aliya; Edner, Benjamin; Rosén, Lee A

2014-01-01

Recent research has suggested that vegetarians may be at an increased risk for developing disordered eating or body image issues when compared to non-vegetarians. However, the results of such studies are mixed, and no research has explored potential connections between vegetarianism and self-objectification. In the current study, the authors examine factors that predicted body surveillance, body shame, and appearance control beliefs; three aspects of self-objectification. Surveys were completed by 386 women from the United States who were categorized as vegetarian, semi-vegetarian, or non-vegetarian. The three groups differed regarding dietary motivations, levels of feminist activism, and body shame, but did not differ on their conformity to feminine norms. While conformity to feminine norms predicted body surveillance and body shame levels among all three groups of women, feminist activism predicted appearance control beliefs among non-vegetarians only. These findings suggest that it is important for researchers and clinicians to distinguish among these three groups when examining the relationship between vegetarianism and self-objectification. Copyright © 2013 Elsevier Ltd. All rights reserved.

Conformational properties of chiral tobacco alkaloids by DFT calculations and vibrational circular dichroism: (-)-S-anabasine.

PubMed

Rodríguez Ortega, P G; Montejo, M; Márquez, F; López González, J J

2015-07-01

A thorough DFT and MM study of the conformational landscape, molecular and electronic structures of (-)-S-anabasine is reported aimed to reveal the mechanism controlling its conformational preference. Although the conformational flexibility and diversity of this system is quite extensive, only two structures are populated both in gas-phase and solution (CCl4 and DMSO). NBO-aided electronic structure analyses performed for the eight conformers representing minima in the potential energy surface of (-)-S-anabasine indicate that both steric and electrostatic factors are determinant in the conformational distribution of the sample in gas phase. Nonetheless, hyperconjugative effects are the key force tipping the balance in the conformational equilibrium between the two main rotamers. Increasing the polarity of the medium (using the IEF-PCM formalism) barely affect the conformational energy profile, although a slight increase in the theoretical population of those structures more affected by electrostatic interactions is predicted. The validity of the theoretical models and calculated conformers populations are endorsed by the accurate reproduction of the IR and VCD spectra (recorded in pure liquid and in CCl4 solution) of the sample (that have been firstly recorded and assigned in the present work) which are consistent with the occurrence of a 2:1 conformational ratio. Copyright © 2015 Elsevier Inc. All rights reserved.

Predicting loop–helix tertiary structural contacts in RNA pseudoknots

PubMed Central

Cao, Song; Giedroc, David P.; Chen, Shi-Jie

2010-01-01

Tertiary interactions between loops and helical stems play critical roles in the biological function of many RNA pseudoknots. However, quantitative predictions for RNA tertiary interactions remain elusive. Here we report a statistical mechanical model for the prediction of noncanonical loop–stem base-pairing interactions in RNA pseudoknots. Central to the model is the evaluation of the conformational entropy for the pseudoknotted folds with defined loop–stem tertiary structural contacts. We develop an RNA virtual bond-based conformational model (Vfold model), which permits a rigorous computation of the conformational entropy for a given fold that contains loop–stem tertiary contacts. With the entropy parameters predicted from the Vfold model and the energy parameters for the tertiary contacts as inserted parameters, we can then predict the RNA folding thermodynamics, from which we can extract the tertiary contact thermodynamic parameters from theory–experimental comparisons. These comparisons reveal a contact enthalpy (ΔH) of −14 kcal/mol and a contact entropy (ΔS) of −38 cal/mol/K for a protonated C+•(G–C) base triple at pH 7.0, and (ΔH = −7 kcal/mol, ΔS = −19 cal/mol/K) for an unprotonated base triple. Tests of the model for a series of pseudoknots show good theory–experiment agreement. Based on the extracted energy parameters for the tertiary structural contacts, the model enables predictions for the structure, stability, and folding pathways for RNA pseudoknots with known or postulated loop–stem tertiary contacts from the nucleotide sequence alone. PMID:20100813

3D flexible alignment using 2D maximum common substructure: dependence of prediction accuracy on target-reference chemical similarity.

PubMed

Kawabata, Takeshi; Nakamura, Haruki

2014-07-28

A protein-bound conformation of a target molecule can be predicted by aligning the target molecule on the reference molecule obtained from the 3D structure of the compound-protein complex. This strategy is called "similarity-based docking". For this purpose, we develop the flexible alignment program fkcombu, which aligns the target molecule based on atomic correspondences with the reference molecule. The correspondences are obtained by the maximum common substructure (MCS) of 2D chemical structures, using our program kcombu. The prediction performance was evaluated using many target-reference pairs of superimposed ligand 3D structures on the same protein in the PDB, with different ranges of chemical similarity. The details of atomic correspondence largely affected the prediction success. We found that topologically constrained disconnected MCS (TD-MCS) with the simple element-based atomic classification provides the best prediction. The crashing potential energy with the receptor protein improved the performance. We also found that the RMSD between the predicted and correct target conformations significantly correlates with the chemical similarities between target-reference molecules. Generally speaking, if the reference and target compounds have more than 70% chemical similarity, then the average RMSD of 3D conformations is <2.0 Å. We compared the performance with a rigid-body molecular alignment program based on volume-overlap scores (ShaEP). Our MCS-based flexible alignment program performed better than the rigid-body alignment program, especially when the target and reference molecules were sufficiently similar.

"Ask Ernö": a self-learning tool for assignment and prediction of nuclear magnetic resonance spectra.

PubMed

Castillo, Andrés M; Bernal, Andrés; Dieden, Reiner; Patiny, Luc; Wist, Julien

2016-01-01

We present "Ask Ernö", a self-learning system for the automatic analysis of NMR spectra, consisting of integrated chemical shift assignment and prediction tools. The output of the automatic assignment component initializes and improves a database of assigned protons that is used by the chemical shift predictor. In turn, the predictions provided by the latter facilitate improvement of the assignment process. Iteration on these steps allows Ask Ernö to improve its ability to assign and predict spectra without any prior knowledge or assistance from human experts. This concept was tested by training such a system with a dataset of 2341 molecules and their (1)H-NMR spectra, and evaluating the accuracy of chemical shift predictions on a test set of 298 partially assigned molecules (2007 assigned protons). After 10 iterations, Ask Ernö was able to decrease its prediction error by 17 %, reaching an average error of 0.265 ppm. Over 60 % of the test chemical shifts were predicted within 0.2 ppm, while only 5 % still presented a prediction error of more than 1 ppm. Ask Ernö introduces an innovative approach to automatic NMR analysis that constantly learns and improves when provided with new data. Furthermore, it completely avoids the need for manually assigned spectra. This system has the potential to be turned into a fully autonomous tool able to compete with the best alternatives currently available.Graphical abstractSelf-learning loop. Any progress in the prediction (forward problem) will improve the assignment ability (reverse problem) and vice versa.

Automatic stereotyping against people with schizophrenia, schizoaffective and affective disorders

PubMed Central

Rüsch, Nicolas; Corrigan, Patrick W.; Todd, Andrew R.; Bodenhausen, Galen V.

2010-01-01

Similar to members of the public, people with mental illness may exhibit general negative automatic prejudice against their own group. However, it is unclear whether more specific negative stereotypes are automatically activated among diagnosed individuals and how such automatic stereotyping may be related to self-reported attitudes and emotional reactions. We therefore studied automatically activated reactions toward mental illness among 85 people with schizophrenia, schizoaffective or affective disorders as well as among 50 members of the general public, using a Lexical Decision Task to measure automatic stereotyping. Deliberately endorsed attitudes and emotional reactions were assessed by self-report. Independent of diagnosis, people with mental illness showed less negative automatic stereotyping than did members of the public. Among members of the public, stronger automatic stereotyping was associated with more self-reported shame about a potential mental illness and more anger toward stigmatized individuals. Reduced automatic stereotyping in the diagnosed group suggests that people with mental illness might not entirely internalize societal stigma. Among members of the public, automatic stereotyping predicted negative emotional reactions to people with mental illness. Initiatives to reduce the impact of public stigma and internalized stigma should take automatic stereotyping and related emotional aspects of stigma into account. PMID:20843560

Brief Report: Attentional Cueing to Images of Social Interactions is Automatic for Neurotypical Individuals But Not Those with ASC.

PubMed

Morrisey, Marcus Neil; Reed, Catherine L; McIntosh, Daniel N; Rutherford, M D

2018-04-25

Human actions induce attentional orienting toward the target of the action. We examined the influence of action cueing in social (man throwing toward a human) and non-social (man throwing toward a tree) contexts in observers with and without autism spectrum condition (ASC). Results suggested that a social interaction enhanced the cueing effect for neurotypical participants. Participants with ASC did not benefit from non-predictive cues and were slower in social contexts, although they benefitted from reliably predictive cues. Social orienting appears to be automatic in the context of an implied social interaction for neurotypical observers, but not those with ASC. Neurotypical participants' behavior may be driven by automatic processing, while participants with ASC use an alternative, effortful strategy.

Cognitive-Affective Dimensions of Female Orgasm: The Role of Automatic Thoughts and Affect During Sexual Activity.

PubMed

Tavares, Inês M; Laan, Ellen T M; Nobre, Pedro J

2017-06-01

Cognitive-affective factors contribute to female sexual dysfunctions, defined as clinically significant difficulties in the ability to respond sexually or to experience sexual pleasure. Automatic thoughts and affect presented during sexual activity are acknowledged as maintenance factors for these difficulties. However, there is a lack of studies on the influence of these cognitive-affective dimensions regarding female orgasm. To assess the role of automatic thoughts and affect during sexual activity in predicting female orgasm occurrence and to investigate the mediator role of these variables in the relation between sexual activity and orgasm occurrence. Nine hundred twenty-six sexually active heterosexual premenopausal women reported on frequency of sexual activities and frequency of orgasm occurrence, cognitive factors, and social desirability. Participants completed the Sexual Modes Questionnaire-Automatic Thoughts Subscale, the Positive and Negative Affect Schedule, and the Socially Desirable Response Set. Multiple linear regressions and mediation analyses were performed, controlling for the effect of covariates such as social desirability, sociodemographic and medical characteristics, and relationship factors. The main outcome measurement was orgasm frequency as predicted and mediated by automatic thoughts and affect experienced during sexual activities. The presence of failure thoughts and lack of erotic thoughts during sexual activity significantly and negatively predicted female orgasm, whereas positive affect experienced during sexual activity significantly and positively predicted female orgasm. Moreover, negative automatic thoughts and positive affect during sexual activity were found to mediate the relation between sexual activity and female orgasm occurrence. These data suggest that the cognitive aspects of sexual involvement are critical to enhancing female orgasm experience and can aid the development of strategies that contemplate the central role of automatic thoughts and of positive emotions experienced during sexual activity. Data were not collected face to face, which constitutes a strength of this study, because it is known that social desirability is lower in self-administered online questionnaires compared with traditional paper-and-pencil questionnaires, particularly for more sensitive sexual issues. The fact that the sample was composed of heterosexual, premenopausal, and relatively young women demands some caution regarding generalization of the present results. The findings support the contribution of cognitive and affective factors to female orgasmic functioning. It is recommended that future research confirm these findings with other samples, particularly clinical samples of women with orgasmic difficulties. Tavares IM, Laan ETM, Nobre PJ. Cognitive-Affective Dimensions of Female Orgasm: The Role of Automatic Thoughts and Affect During Sexual Activity. J Sex Med 2017;14:818-828. Copyright © 2017 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

Dissociable changes in functional network topology underlie early category learning and development of automaticity

PubMed Central

Soto, Fabian A.; Bassett, Danielle S.; Ashby, F. Gregory

2016-01-01

Recent work has shown that multimodal association areas–including frontal, temporal and parietal cortex–are focal points of functional network reconfiguration during human learning and performance of cognitive tasks. On the other hand, neurocomputational theories of category learning suggest that the basal ganglia and related subcortical structures are focal points of functional network reconfiguration during early learning of some categorization tasks, but become less so with the development of automatic categorization performance. Using a combination of network science and multilevel regression, we explore how changes in the connectivity of small brain regions can predict behavioral changes during training in a visual categorization task. We find that initial category learning, as indexed by changes in accuracy, is predicted by increasingly efficient integrative processing in subcortical areas, with higher functional specialization, more efficient integration across modules, but a lower cost in terms of redundancy of information processing. The development of automaticity, as indexed by changes in the speed of correct responses, was predicted by lower clustering (particularly in subcortical areas), higher strength (highest in cortical areas) and higher betweenness centrality. By combining neurocomputational theories and network scientific methods, these results synthesize the dissociative roles of multimodal association areas and subcortical structures in the development of automaticity during category learning. PMID:27453156

A Review on Automatic Mammographic Density and Parenchymal Segmentation

PubMed Central

He, Wenda; Juette, Arne; Denton, Erika R. E.; Oliver, Arnau

2015-01-01

Breast cancer is the most frequently diagnosed cancer in women. However, the exact cause(s) of breast cancer still remains unknown. Early detection, precise identification of women at risk, and application of appropriate disease prevention measures are by far the most effective way to tackle breast cancer. There are more than 70 common genetic susceptibility factors included in the current non-image-based risk prediction models (e.g., the Gail and the Tyrer-Cuzick models). Image-based risk factors, such as mammographic densities and parenchymal patterns, have been established as biomarkers but have not been fully incorporated in the risk prediction models used for risk stratification in screening and/or measuring responsiveness to preventive approaches. Within computer aided mammography, automatic mammographic tissue segmentation methods have been developed for estimation of breast tissue composition to facilitate mammographic risk assessment. This paper presents a comprehensive review of automatic mammographic tissue segmentation methodologies developed over the past two decades and the evidence for risk assessment/density classification using segmentation. The aim of this review is to analyse how engineering advances have progressed and the impact automatic mammographic tissue segmentation has in a clinical environment, as well as to understand the current research gaps with respect to the incorporation of image-based risk factors in non-image-based risk prediction models. PMID:26171249

Human Factors and Safety Evaluation of the Automatic Test and Repair System (AN/MSM-105(V)1)

DTIC Science & Technology

1984-07-01

box and the main breaker box In both the ETF and ERF did not conform to military standards In that they consisted of black letters on a gold ...transportable test and repair system for electronic equipment that consists of an electronic test facility ( ETF ) and an electronic repair facility (ERF...personal gear in both the ETF and the ERF, and in the ETF there was not nearly enough room for the storage of the interconnect devices, tapes and manuals

The role of molecular structure of sugar-phosphate backbone and nucleic acid bases in the formation of single-stranded and double-stranded DNA structures.

PubMed

Poltev, Valeri; Anisimov, Victor M; Danilov, Victor I; Garcia, Dolores; Sanchez, Carolina; Deriabina, Alexandra; Gonzalez, Eduardo; Rivas, Francisco; Polteva, Nina

2014-06-01

Our previous DFT computations of deoxydinucleoside monophosphate complexes with Na(+)-ions (dDMPs) have demonstrated that the main characteristics of Watson-Crick (WC) right-handed duplex families are predefined in the local energy minima of dDMPs. In this work, we study the mechanisms of contribution of chemically monotonous sugar-phosphate backbone and the bases into the double helix irregularity. Geometry optimization of sugar-phosphate backbone produces energy minima matching the WC DNA conformations. Studying the conformational variability of dDMPs in response to sequence permutation, we found that simple replacement of bases in the previously fully optimized dDMPs, e.g. by constructing Pyr-Pur from Pur-Pyr, and Pur-Pyr from Pyr-Pur sequences, while retaining the backbone geometry, automatically produces the mutual base position characteristic of the target sequence. Based on that, we infer that the directionality and the preferable regions of the sugar-phosphate torsions, combined with the difference of purines from pyrimidines in ring shape, determines the sequence dependence of the structure of WC DNA. No such sequence dependence exists in dDMPs corresponding to other DNA conformations (e.g., Z-family and Hoogsteen duplexes). Unlike other duplexes, WC helix is unique by its ability to match the local energy minima of the free single strand to the preferable conformations of the duplex. Copyright © 2013 Wiley Periodicals, Inc.

Modeling the solid-liquid phase transition in saturated triglycerides

NASA Astrophysics Data System (ADS)

Pink, David A.; Hanna, Charles B.; Sandt, Christophe; MacDonald, Adam J.; MacEachern, Ronald; Corkery, Robert; Rousseau, Dérick

2010-02-01

We investigated theoretically two competing published scenarios for the melting transition of the triglyceride trilaurin (TL): those of (1) Corkery et al. [Langmuir 23, 7241 (2007)], in which the average state of each TL molecule in the liquid phase is a discotic "Y" conformer whose three chains are dynamically twisted, with an average angle of ˜120° between them, and those of (2) Cebula et al. [J. Am. Oil Chem. Soc. 69, 130 (1992)], in which the liquid-state conformation of the TL molecule in the liquid phase is a nematic h∗-conformer whose three chains are in a modified "chair" conformation. We developed two competing models for the two scenarios, in which TL molecules are in a nematic compact-chair (or "h") conformation, with extended, possibly all-trans, chains at low-temperatures, and in either a Y conformation or an h∗ conformation in the liquid state at temperatures higher than the phase-transition temperature, T∗=319 K. We defined an h-Y model as a realization of the proposal of Corkery et al. [Langmuir 23, 7241 (2007)], and explored its predictions by mapping it onto an Ising model in a temperature-dependent field, performing a mean-field approximation, and calculating the transition enthalpy ΔH. We found that the most plausible realization of the h-Y model, as applied to the solid-liquid phase transition in TL, and likely to all saturated triglycerides, gave a value of ΔH in reasonable agreement with the experiment. We then defined an alternative h-h∗ model as a realization of the proposal of Cebula et al. [J. Am. Oil Chem. Soc. 69, 130 (1992)], in which the liquid phase exhibits an average symmetry breaking similar to an h conformation, but with twisted chains, to see whether it could describe the TL phase transition. The h-h∗ model gave a value of ΔH that was too small by a factor of ˜3-4. We also predicted the temperature dependence of the 1132 cm-1 Raman band for both models, and performed measurements of the ratios of three TL Raman bands in the temperature range of -20 °C≤T ≤90 °C. The experimental results were in accord with the predictions of the h-Y model and support the proposal of Corkery et al. [Langmuir 23, 7241 (2007)] that the liquid state is made up of molecules that are each, on average, in a Y conformation. Finally, we carried out computer simulations of minimal-model TLs in the liquid phase, and concluded that although the individual TL molecules are, on average, Y conformers, long-range discotic order is unlikely to exist.

Using automated texture features to determine the probability for masking of a tumor on mammography, but not ultrasound.

PubMed

Häberle, Lothar; Hack, Carolin C; Heusinger, Katharina; Wagner, Florian; Jud, Sebastian M; Uder, Michael; Beckmann, Matthias W; Schulz-Wendtland, Rüdiger; Wittenberg, Thomas; Fasching, Peter A

2017-08-30

Tumors in radiologically dense breast were overlooked on mammograms more often than tumors in low-density breasts. A fast reproducible and automated method of assessing percentage mammographic density (PMD) would be desirable to support decisions whether ultrasonography should be provided for women in addition to mammography in diagnostic mammography units. PMD assessment has still not been included in clinical routine work, as there are issues of interobserver variability and the procedure is quite time consuming. This study investigated whether fully automatically generated texture features of mammograms can replace time-consuming semi-automatic PMD assessment to predict a patient's risk of having an invasive breast tumor that is visible on ultrasound but masked on mammography (mammography failure). This observational study included 1334 women with invasive breast cancer treated at a hospital-based diagnostic mammography unit. Ultrasound was available for the entire cohort as part of routine diagnosis. Computer-based threshold PMD assessments ("observed PMD") were carried out and 363 texture features were obtained from each mammogram. Several variable selection and regression techniques (univariate selection, lasso, boosting, random forest) were applied to predict PMD from the texture features. The predicted PMD values were each used as new predictor for masking in logistic regression models together with clinical predictors. These four logistic regression models with predicted PMD were compared among themselves and with a logistic regression model with observed PMD. The most accurate masking prediction was determined by cross-validation. About 120 of the 363 texture features were selected for predicting PMD. Density predictions with boosting were the best substitute for observed PMD to predict masking. Overall, the corresponding logistic regression model performed better (cross-validated AUC, 0.747) than one without mammographic density (0.734), but less well than the one with the observed PMD (0.753). However, in patients with an assigned mammography failure risk >10%, covering about half of all masked tumors, the boosting-based model performed at least as accurately as the original PMD model. Automatically generated texture features can replace semi-automatically determined PMD in a prediction model for mammography failure, such that more than 50% of masked tumors could be discovered.

Cyclo-biphenalenyl Biradicaloid Molecular Materials: Conformation, Tautomerization, Magnetism, and Thermochromism

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Jingsong; Meunier, Vincent; Tian, Yong-Hui

2010-01-01

Phenalenyl and its derivatives have recently attracted a great deal of interest as a result of a two-electron multicenter (2e/mc) - bonding between two -stacked phenalenyl units. The 2e/mc bonded -dimers are close in energy to the -dimers of phenalenyl and therefore fickle properties may emerge from bond fluctuation, yielding smart -functional materials. Here, we examine the valence tautomerization of two cyclo-biphenalenyl biradicaloid molecular materials with chair and boat conformations by spin-restricted (R) and unrestricted (U) DFT using the M06 and B3LYP functionals. We found that the chair conformation involves a 2e/4c - bonded structure, whereas the boat conformation involvesmore » a 2e/12c - bonded structure on their potential energy surfaces. The global minimum for the chair conformation is the -bonded structure, whereas it is the - bonded structure for the boat conformation. The chair conformation exhibits a stepwise [3,3]-sigmatropic rearrangement, and calculations predict a negligible paramagnetic susceptibility near room temperature. In comparison, the paramagnetism of the boat conformation should be observable by SQUID and ESR. According to the energy differences of the respective - and -dimers of the two conformations and the UV-vis calculations, the color of the chair conformation is expected to become darker, whereas that of the boat conformation should become lighter with increasing temperature.« less

Prediction of protein secondary structure content for the twilight zone sequences.

PubMed

Homaeian, Leila; Kurgan, Lukasz A; Ruan, Jishou; Cios, Krzysztof J; Chen, Ke

2007-11-15

Secondary protein structure carries information about local structural arrangements, which include three major conformations: alpha-helices, beta-strands, and coils. Significant majority of successful methods for prediction of the secondary structure is based on multiple sequence alignment. However, multiple alignment fails to provide accurate results when a sequence comes from the twilight zone, that is, it is characterized by low (<30%) homology. To this end, we propose a novel method for prediction of secondary structure content through comprehensive sequence representation, called PSSC-core. The method uses a multiple linear regression model and introduces a comprehensive feature-based sequence representation to predict amount of helices and strands for sequences from the twilight zone. The PSSC-core method was tested and compared with two other state-of-the-art prediction methods on a set of 2187 twilight zone sequences. The results indicate that our method provides better predictions for both helix and strand content. The PSSC-core is shown to provide statistically significantly better results when compared with the competing methods, reducing the prediction error by 5-7% for helix and 7-9% for strand content predictions. The proposed feature-based sequence representation uses a comprehensive set of physicochemical properties that are custom-designed for each of the helix and strand content predictions. It includes composition and composition moment vectors, frequency of tetra-peptides associated with helical and strand conformations, various property-based groups like exchange groups, chemical groups of the side chains and hydrophobic group, auto-correlations based on hydrophobicity, side-chain masses, hydropathy, and conformational patterns for beta-sheets. The PSSC-core method provides an alternative for predicting the secondary structure content that can be used to validate and constrain results of other structure prediction methods. At the same time, it also provides useful insight into design of successful protein sequence representations that can be used in developing new methods related to prediction of different aspects of the secondary protein structure. (c) 2007 Wiley-Liss, Inc.

Predicting the conformations of peptides and proteins in early evolution. A review article submitted to Biology Direct

PubMed Central

Milner-White, E James; Russell, Michael J

2008-01-01

Considering that short, mainly heterochiral, polypeptides with a high glycine content are expected to have played a prominent role in evolution at the earliest stage of life before nucleic acids were available, we review recent knowledge about polypeptide three-dimensional structure to predict the types of conformations they would have adopted. The possible existence of such structures at this time leads to a consideration of their functional significance, and the consequences for the course of evolution. This article was reviewed by Bill Martin, Eugene Koonin and Nick Grishin. PMID:18226248

Comparison of stochastic optimization methods for all-atom folding of the Trp-Cage protein.

PubMed

Schug, Alexander; Herges, Thomas; Verma, Abhinav; Lee, Kyu Hwan; Wenzel, Wolfgang

2005-12-09

The performances of three different stochastic optimization methods for all-atom protein structure prediction are investigated and compared. We use the recently developed all-atom free-energy force field (PFF01), which was demonstrated to correctly predict the native conformation of several proteins as the global optimum of the free energy surface. The trp-cage protein (PDB-code 1L2Y) is folded with the stochastic tunneling method, a modified parallel tempering method, and the basin-hopping technique. All the methods correctly identify the native conformation, and their relative efficiency is discussed.

Automatically-computed prehospital severity scores are equivalent to scores based on medic documentation.

PubMed

Reisner, Andrew T; Chen, Liangyou; McKenna, Thomas M; Reifman, Jaques

2008-10-01

Prehospital severity scores can be used in routine prehospital care, mass casualty care, and military triage. If computers could reliably calculate clinical scores, new clinical and research methodologies would be possible. One obstacle is that vital signs measured automatically can be unreliable. We hypothesized that Signal Quality Indices (SQI's), computer algorithms that differentiate between reliable and unreliable monitored physiologic data, could improve the predictive power of computer-calculated scores. In a retrospective analysis of trauma casualties transported by air ambulance, we computed the Triage Revised Trauma Score (RTS) from archived travel monitor data. We compared the areas-under-the-curve (AUC's) of receiver operating characteristic curves for prediction of mortality and red blood cell transfusion for 187 subjects with comparable quantities of good-quality and poor-quality data. Vital signs deemed reliable by SQI's led to significantly more discriminatory severity scores than vital signs deemed unreliable. We also compared automatically-computed RTS (using the SQI's) versus RTS computed from vital signs documented by medics. For the subjects in whom the SQI algorithms identified 15 consecutive seconds of reliable vital signs data (n = 350), the automatically-computed scores' AUC's were the same as the medic-based scores' AUC's. Using the Prehospital Index in place of RTS led to very similar results, corroborating our findings. SQI algorithms improve automatically-computed severity scores, and automatically-computed scores using SQI's are equivalent to medic-based scores.

Engineering the entropy-driven free-energy landscape of a dynamic nanoporous protein assembly.

PubMed

Alberstein, Robert; Suzuki, Yuta; Paesani, Francesco; Tezcan, F Akif

2018-04-30

De novo design and construction of stimuli-responsive protein assemblies that predictably switch between discrete conformational states remains an essential but highly challenging goal in biomolecular design. We previously reported synthetic, two-dimensional protein lattices self-assembled via disulfide bonding interactions, which endows them with a unique capacity to undergo coherent conformational changes without losing crystalline order. Here, we carried out all-atom molecular dynamics simulations to map the free-energy landscape of these lattices, validated this landscape through extensive structural characterization by electron microscopy and established that it is predominantly governed by solvent reorganization entropy. Subsequent redesign of the protein surface with conditionally repulsive electrostatic interactions enabled us to predictably perturb the free-energy landscape and obtain a new protein lattice whose conformational dynamics can be chemically and mechanically toggled between three different states with varying porosities and molecular densities.

Conformational Asymmetry and Quasicrystal Approximants in Linear Diblock Copolymers

NASA Astrophysics Data System (ADS)

Schulze, Morgan W.; Lewis, Ronald M.; Lettow, James H.; Hickey, Robert J.; Gillard, Timothy M.; Hillmyer, Marc A.; Bates, Frank S.

2017-05-01

Small angle x-ray scattering experiments on three model low molar mass diblock copolymer systems containing minority polylactide and majority hydrocarbon blocks demonstrate that conformational asymmetry stabilizes the Frank-Kasper σ phase. Differences in block flexibility compete with space filling at constant density inducing the formation of polyhedral shaped particles that assemble into this low symmetry ordered state with local tetrahedral coordination. These results confirm predictions from self-consistent field theory that establish the origins of symmetry breaking in the ordering of block polymer melts subjected to compositional and conformational asymmetry.

Leap-dynamics: efficient sampling of conformational space of proteins and peptides in solution.

PubMed

Kleinjung, J; Bayley, P; Fraternali, F

2000-03-31

A molecular simulation scheme, called Leap-dynamics, that provides efficient sampling of protein conformational space in solution is presented. The scheme is a combined approach using a fast sampling method, imposing conformational 'leaps' to force the system over energy barriers, and molecular dynamics (MD) for refinement. The presence of solvent is approximated by a potential of mean force depending on the solvent accessible surface area. The method has been successfully applied to N-acetyl-L-alanine-N-methylamide (alanine dipeptide), sampling experimentally observed conformations inaccessible to MD alone under the chosen conditions. The method predicts correctly the increased partial flexibility of the mutant Y35G compared to native bovine pancreatic trypsin inhibitor. In particular, the improvement over MD consists of the detection of conformational flexibility that corresponds closely to slow motions identified by nuclear magnetic resonance techniques.

Free-energy landscape of the villin headpiece in an all-atom force field.

PubMed

Herges, Thomas; Wenzel, Wolfgang

2005-04-01

We investigate the landscape of the internal free-energy of the 36 amino acid villin headpiece with a modified basin hopping method in the all-atom force field PFF01, which was previously used to predictively fold several helical proteins with atomic resolution. We identify near native conformations of the protein as the global optimum of the force field. More than half of the twenty best simulations started from random initial conditions converge to the folding funnel of the native conformation, but several competing low-energy metastable conformations were observed. From 76,000 independently generated conformations we derived a decoy tree which illustrates the topological structure of the entire low-energy part of the free-energy landscape and characterizes the ensemble of metastable conformations. These emerge as similar in secondary content, but differ in tertiary arrangement.

Doing Gender for Different Reasons: Why Gender Conformity Positively and Negatively Predicts Self-Esteem

ERIC Educational Resources Information Center

Good, Jessica J.; Sanchez, Diana T.

2010-01-01

Past research has shown that valuing gender conformity is associated with both positive and negative consequences for self-esteem and positive affect. The current research (women, n= 226; men, n= 175) explored these conflicting findings by separating out investing in societal gender ideals from personally valuing one's gender identity ("private…

Iterative dataset optimization in automated planning: Implementation for breast and rectal cancer radiotherapy.

PubMed

Fan, Jiawei; Wang, Jiazhou; Zhang, Zhen; Hu, Weigang

2017-06-01

To develop a new automated treatment planning solution for breast and rectal cancer radiotherapy. The automated treatment planning solution developed in this study includes selection of the iterative optimized training dataset, dose volume histogram (DVH) prediction for the organs at risk (OARs), and automatic generation of clinically acceptable treatment plans. The iterative optimized training dataset is selected by an iterative optimization from 40 treatment plans for left-breast and rectal cancer patients who received radiation therapy. A two-dimensional kernel density estimation algorithm (noted as two parameters KDE) which incorporated two predictive features was implemented to produce the predicted DVHs. Finally, 10 additional new left-breast treatment plans are re-planned using the Pinnacle 3 Auto-Planning (AP) module (version 9.10, Philips Medical Systems) with the objective functions derived from the predicted DVH curves. Automatically generated re-optimized treatment plans are compared with the original manually optimized plans. By combining the iterative optimized training dataset methodology and two parameters KDE prediction algorithm, our proposed automated planning strategy improves the accuracy of the DVH prediction. The automatically generated treatment plans using the dose derived from the predicted DVHs can achieve better dose sparing for some OARs without compromising other metrics of plan quality. The proposed new automated treatment planning solution can be used to efficiently evaluate and improve the quality and consistency of the treatment plans for intensity-modulated breast and rectal cancer radiation therapy. © 2017 American Association of Physicists in Medicine.

GalaxyGPCRloop: Template-Based and Ab Initio Structure Sampling of the Extracellular Loops of G-Protein-Coupled Receptors.

PubMed

Won, Jonghun; Lee, Gyu Rie; Park, Hahnbeom; Seok, Chaok

2018-06-07

The second extracellular loops (ECL2s) of G-protein-coupled receptors (GPCRs) are often involved in GPCR functions, and their structures have important implications in drug discovery. However, structure prediction of ECL2 is difficult because of its long length and the structural diversity among different GPCRs. In this study, a new ECL2 conformational sampling method involving both template-based and ab initio sampling was developed. Inspired by the observation of similar ECL2 structures of closely related GPCRs, a template-based sampling method employing loop structure templates selected from the structure database was developed. A new metric for evaluating similarity of the target loop to templates was introduced for template selection. An ab initio loop sampling method was also developed to treat cases without highly similar templates. The ab initio method is based on the previously developed fragment assembly and loop closure method. A new sampling component that takes advantage of secondary structure prediction was added. In addition, a conserved disulfide bridge restraining ECL2 conformation was predicted and analytically incorporated into sampling, reducing the effective dimension of the conformational search space. The sampling method was combined with an existing energy function for comparison with previously reported loop structure prediction methods, and the benchmark test demonstrated outstanding performance.

ClusPro: an automated docking and discrimination method for the prediction of protein complexes.

PubMed

Comeau, Stephen R; Gatchell, David W; Vajda, Sandor; Camacho, Carlos J

2004-01-01

Predicting protein interactions is one of the most challenging problems in functional genomics. Given two proteins known to interact, current docking methods evaluate billions of docked conformations by simple scoring functions, and in addition to near-native structures yield many false positives, i.e. structures with good surface complementarity but far from the native. We have developed a fast algorithm for filtering docked conformations with good surface complementarity, and ranking them based on their clustering properties. The free energy filters select complexes with lowest desolvation and electrostatic energies. Clustering is then used to smooth the local minima and to select the ones with the broadest energy wells-a property associated with the free energy at the binding site. The robustness of the method was tested on sets of 2000 docked conformations generated for 48 pairs of interacting proteins. In 31 of these cases, the top 10 predictions include at least one near-native complex, with an average RMSD of 5 A from the native structure. The docking and discrimination method also provides good results for a number of complexes that were used as targets in the Critical Assessment of PRedictions of Interactions experiment. The fully automated docking and discrimination server ClusPro can be found at http://structure.bu.edu

Global brain dynamics during social exclusion predict subsequent behavioral conformity

PubMed Central

Wasylyshyn, Nick; Hemenway Falk, Brett; Garcia, Javier O; Cascio, Christopher N; O’Donnell, Matthew Brook; Bingham, C Raymond; Simons-Morton, Bruce; Vettel, Jean M; Falk, Emily B

2018-01-01

Abstract Individuals react differently to social experiences; for example, people who are more sensitive to negative social experiences, such as being excluded, may be more likely to adapt their behavior to fit in with others. We examined whether functional brain connectivity during social exclusion in the fMRI scanner can be used to predict subsequent conformity to peer norms. Adolescent males (n = 57) completed a two-part study on teen driving risk: a social exclusion task (Cyberball) during an fMRI session and a subsequent driving simulator session in which they drove alone and in the presence of a peer who expressed risk-averse or risk-accepting driving norms. We computed the difference in functional connectivity between social exclusion and social inclusion from each node in the brain to nodes in two brain networks, one previously associated with mentalizing (medial prefrontal cortex, temporoparietal junction, precuneus, temporal poles) and another with social pain (dorsal anterior cingulate cortex, anterior insula). Using predictive modeling, this measure of global connectivity during exclusion predicted the extent of conformity to peer pressure during driving in the subsequent experimental session. These findings extend our understanding of how global neural dynamics guide social behavior, revealing functional network activity that captures individual differences. PMID:29529310

3dRPC: a web server for 3D RNA-protein structure prediction.

PubMed

Huang, Yangyu; Li, Haotian; Xiao, Yi

2018-04-01

RNA-protein interactions occur in many biological processes. To understand the mechanism of these interactions one needs to know three-dimensional (3D) structures of RNA-protein complexes. 3dRPC is an algorithm for prediction of 3D RNA-protein complex structures and consists of a docking algorithm RPDOCK and a scoring function 3dRPC-Score. RPDOCK is used to sample possible complex conformations of an RNA and a protein by calculating the geometric and electrostatic complementarities and stacking interactions at the RNA-protein interface according to the features of atom packing of the interface. 3dRPC-Score is a knowledge-based potential that uses the conformations of nucleotide-amino-acid pairs as statistical variables and that is used to choose the near-native complex-conformations obtained from the docking method above. Recently, we built a web server for 3dRPC. The users can easily use 3dRPC without installing it locally. RNA and protein structures in PDB (Protein Data Bank) format are the only needed input files. It can also incorporate the information of interface residues or residue-pairs obtained from experiments or theoretical predictions to improve the prediction. The address of 3dRPC web server is http://biophy.hust.edu.cn/3dRPC. yxiao@hust.edu.cn.

A fragment-based approach to the SAMPL3 Challenge

NASA Astrophysics Data System (ADS)

Kulp, John L.; Blumenthal, Seth N.; Wang, Qiang; Bryan, Richard L.; Guarnieri, Frank

2012-05-01

The success of molecular fragment-based design depends critically on the ability to make predictions of binding poses and of affinity ranking for compounds assembled by linking fragments. The SAMPL3 Challenge provides a unique opportunity to evaluate the performance of a state-of-the-art fragment-based design methodology with respect to these requirements. In this article, we present results derived from linking fragments to predict affinity and pose in the SAMPL3 Challenge. The goal is to demonstrate how incorporating different aspects of modeling protein-ligand interactions impact the accuracy of the predictions, including protein dielectric models, charged versus neutral ligands, ΔΔGs solvation energies, and induced conformational stress. The core method is based on annealing of chemical potential in a Grand Canonical Monte Carlo (GC/MC) simulation. By imposing an initially very high chemical potential and then automatically running a sequence of simulations at successively decreasing chemical potentials, the GC/MC simulation efficiently discovers statistical distributions of bound fragment locations and orientations not found reliably without the annealing. This method accounts for configurational entropy, the role of bound water molecules, and results in a prediction of all the locations on the protein that have any affinity for the fragment. Disregarding any of these factors in affinity-rank prediction leads to significantly worse correlation with experimentally-determined free energies of binding. We relate three important conclusions from this challenge as applied to GC/MC: (1) modeling neutral ligands—regardless of the charged state in the active site—produced better affinity ranking than using charged ligands, although, in both cases, the poses were almost exactly overlaid; (2) simulating explicit water molecules in the GC/MC gave better affinity and pose predictions; and (3) applying a ΔΔGs solvation correction further improved the ranking of the neutral ligands. Using the GC/MC method under a variety of parameters in the blinded SAMPL3 Challenge provided important insights to the relevant parameters and boundaries in predicting binding affinities using simulated annealing of chemical potential calculations.

Automatic CT simulation optimization for radiation therapy: A general strategy.

PubMed

Li, Hua; Yu, Lifeng; Anastasio, Mark A; Chen, Hsin-Chen; Tan, Jun; Gay, Hiram; Michalski, Jeff M; Low, Daniel A; Mutic, Sasa

2014-03-01

In radiation therapy, x-ray computed tomography (CT) simulation protocol specifications should be driven by the treatment planning requirements in lieu of duplicating diagnostic CT screening protocols. The purpose of this study was to develop a general strategy that allows for automatically, prospectively, and objectively determining the optimal patient-specific CT simulation protocols based on radiation-therapy goals, namely, maintenance of contouring quality and integrity while minimizing patient CT simulation dose. The authors proposed a general prediction strategy that provides automatic optimal CT simulation protocol selection as a function of patient size and treatment planning task. The optimal protocol is the one that delivers the minimum dose required to provide a CT simulation scan that yields accurate contours. Accurate treatment plans depend on accurate contours in order to conform the dose to actual tumor and normal organ positions. An image quality index, defined to characterize how simulation scan quality affects contour delineation, was developed and used to benchmark the contouring accuracy and treatment plan quality within the predication strategy. A clinical workflow was developed to select the optimal CT simulation protocols incorporating patient size, target delineation, and radiation dose efficiency. An experimental study using an anthropomorphic pelvis phantom with added-bolus layers was used to demonstrate how the proposed prediction strategy could be implemented and how the optimal CT simulation protocols could be selected for prostate cancer patients based on patient size and treatment planning task. Clinical IMRT prostate treatment plans for seven CT scans with varied image quality indices were separately optimized and compared to verify the trace of target and organ dosimetry coverage. Based on the phantom study, the optimal image quality index for accurate manual prostate contouring was 4.4. The optimal tube potentials for patient sizes of 38, 43, 48, 53, and 58 cm were 120, 140, 140, 140, and 140 kVp, respectively, and the corresponding minimum CTDIvol for achieving the optimal image quality index 4.4 were 9.8, 32.2, 100.9, 241.4, and 274.1 mGy, respectively. For patients with lateral sizes of 43-58 cm, 120-kVp scan protocols yielded up to 165% greater radiation dose relative to 140-kVp protocols, and 140-kVp protocols always yielded a greater image quality index compared to the same dose-level 120-kVp protocols. The trace of target and organ dosimetry coverage and the γ passing rates of seven IMRT dose distribution pairs indicated the feasibility of the proposed image quality index for the predication strategy. A general strategy to predict the optimal CT simulation protocols in a flexible and quantitative way was developed that takes into account patient size, treatment planning task, and radiation dose. The experimental study indicated that the optimal CT simulation protocol and the corresponding radiation dose varied significantly for different patient sizes, contouring accuracy, and radiation treatment planning tasks.

Historical maintenance relevant information road-map for a self-learning maintenance prediction procedural approach

NASA Astrophysics Data System (ADS)

Morales, Francisco J.; Reyes, Antonio; Cáceres, Noelia; Romero, Luis M.; Benitez, Francisco G.; Morgado, Joao; Duarte, Emanuel; Martins, Teresa

2017-09-01

A large percentage of transport infrastructures are composed of linear assets, such as roads and rail tracks. The large social and economic relevance of these constructions force the stakeholders to ensure a prolonged health/durability. Even though, inevitable malfunctioning, breaking down, and out-of-service periods arise randomly during the life cycle of the infrastructure. Predictive maintenance techniques tend to diminish the appearance of unpredicted failures and the execution of needed corrective interventions, envisaging the adequate interventions to be conducted before failures show up. This communication presents: i) A procedural approach, to be conducted, in order to collect the relevant information regarding the evolving state condition of the assets involved in all maintenance interventions; this reported and stored information constitutes a rich historical data base to train Machine Learning algorithms in order to generate reliable predictions of the interventions to be carried out in further time scenarios. ii) A schematic flow chart of the automatic learning procedure. iii) Self-learning rules from automatic learning from false positive/negatives. The description, testing, automatic learning approach and the outcomes of a pilot case are presented; finally some conclusions are outlined regarding the methodology proposed for improving the self-learning predictive capability.

SU-F-T-342: Dosimetric Constraint Prediction Guided Automatic Mulit-Objective Optimization for Intensity Modulated Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song, T; Zhou, L; Li, Y

Purpose: For intensity modulated radiotherapy, the plan optimization is time consuming with difficulties of selecting objectives and constraints, and their relative weights. A fast and automatic multi-objective optimization algorithm with abilities to predict optimal constraints and manager their trade-offs can help to solve this problem. Our purpose is to develop such a framework and algorithm for a general inverse planning. Methods: There are three main components contained in this proposed multi-objective optimization framework: prediction of initial dosimetric constraints, further adjustment of constraints and plan optimization. We firstly use our previously developed in-house geometry-dosimetry correlation model to predict the optimal patient-specificmore » dosimetric endpoints, and treat them as initial dosimetric constraints. Secondly, we build an endpoint(organ) priority list and a constraint adjustment rule to repeatedly tune these constraints from their initial values, until every single endpoint has no room for further improvement. Lastly, we implement a voxel-independent based FMO algorithm for optimization. During the optimization, a model for tuning these voxel weighting factors respecting to constraints is created. For framework and algorithm evaluation, we randomly selected 20 IMRT prostate cases from the clinic and compared them with our automatic generated plans, in both the efficiency and plan quality. Results: For each evaluated plan, the proposed multi-objective framework could run fluently and automatically. The voxel weighting factor iteration time varied from 10 to 30 under an updated constraint, and the constraint tuning time varied from 20 to 30 for every case until no more stricter constraint is allowed. The average total costing time for the whole optimization procedure is ∼30mins. By comparing the DVHs, better OAR dose sparing could be observed in automatic generated plan, for 13 out of the 20 cases, while others are with competitive results. Conclusion: We have successfully developed a fast and automatic multi-objective optimization for intensity modulated radiotherapy. This work is supported by the National Natural Science Foundation of China (No: 81571771)« less

Sequence charge decoration dictates coil-globule transition in intrinsically disordered proteins.

PubMed

Firman, Taylor; Ghosh, Kingshuk

2018-03-28

We present an analytical theory to compute conformations of heteropolymers-applicable to describe disordered proteins-as a function of temperature and charge sequence. The theory describes coil-globule transition for a given protein sequence when temperature is varied and has been benchmarked against the all-atom Monte Carlo simulation (using CAMPARI) of intrinsically disordered proteins (IDPs). In addition, the model quantitatively shows how subtle alterations of charge placement in the primary sequence-while maintaining the same charge composition-can lead to significant changes in conformation, even as drastic as a coil (swelled above a purely random coil) to globule (collapsed below a random coil) and vice versa. The theory provides insights on how to control (enhance or suppress) these changes by tuning the temperature (or solution condition) and charge decoration. As an application, we predict the distribution of conformations (at room temperature) of all naturally occurring IDPs in the DisProt database and notice significant size variation even among IDPs with a similar composition of positive and negative charges. Based on this, we provide a new diagram-of-states delineating the sequence-conformation relation for proteins in the DisProt database. Next, we study the effect of post-translational modification, e.g., phosphorylation, on IDP conformations. Modifications as little as two-site phosphorylation can significantly alter the size of an IDP with everything else being constant (temperature, salt concentration, etc.). However, not all possible modification sites have the same effect on protein conformations; there are certain "hot spots" that can cause maximal change in conformation. The location of these "hot spots" in the parent sequence can readily be identified by using a sequence charge decoration metric originally introduced by Sawle and Ghosh. The ability of our model to predict conformations (both expanded and collapsed states) of IDPs at a high-throughput level can provide valuable insights into the different mechanisms by which phosphorylation/charge mutation controls IDP function.

Conformational and spectroscopic study of xanthogen ethyl formates, ROC(S)SC(O)OCH2CH3. Isolation of CH3CH2OC(O)SH

NASA Astrophysics Data System (ADS)

Juncal, Luciana C.; Cozzarín, Melina V.; Romano, Rosana M.

2015-03-01

ROC(S)SC(O)OCH2CH3, with R = CH3sbnd , (CH3)2CHsbnd and CH3(CH2)2sbnd , were obtained through the reaction between potassium xanthate salts, ROC(S)SK, and ethyl chloroformate, ClC(O)OCH2CH3. The liquid compounds were identified and characterized by 1H and 13C NMR and mass spectrometry. The conformations adopted by the molecules were studied by DFT methods. 6 conformers were theoretically predicted for R = CH3sbnd and (CH3)2CHsbnd , while the conformational flexibility of the n-propyl substituent increases the total number of feasible rotamers to 21. For the three molecules, the conformers can be associated in 3 groups, being the most stable the AS forms - the Cdbnd S double bond anti (A) with respect to the Csbnd S single bond and the Ssbnd C single bond syn (S) with respect to the Cdbnd O double bond - followed by AA and SS conformers. The vibrational spectra were interpreted in terms of the predicted conformational equilibrium, presenting the ν(Cdbnd O) spectral region signals corresponding to the three groups of conformers. A moderated pre-resonance Raman enhancement of the ν(Cdbnd S) vibrational mode of CH3(CH2)2OC(S)SC(O)OCH2CH3 was detected, when the excitation radiation approaches the energy of a n → π∗ electronic transition associated with the Cdbnd S chromophore. UV-visible spectra in different solvents were measured and interpreted in terms of TD-DFT calculations. The unknown molecule CH3CH2OC(O)SH was isolated by the UV-visible photolysis of CH3OC(S)SC(O)OCH2CH3 isolated in Ar matrix, and also obtained as a side-product of the reaction between potassium xanthate salts, ROC(S)SK, and ethyl chloroformate, ClC(O)OCH2CH3.

Conformational and spectroscopic study of xanthogen ethyl formates, ROC(S)SC(O)OCH₂CH₃. Isolation of CH₃CH₂OC(O)SH.

PubMed

Juncal, Luciana C; Cozzarín, Melina V; Romano, Rosana M

2015-03-15

ROC(S)SC(O)OCH2CH3, with R=CH3-, (CH3)2CH- and CH3(CH2)2-, were obtained through the reaction between potassium xanthate salts, ROC(S)SK, and ethyl chloroformate, ClC(O)OCH2CH3. The liquid compounds were identified and characterized by (1)H and (13)C NMR and mass spectrometry. The conformations adopted by the molecules were studied by DFT methods. 6 conformers were theoretically predicted for R=CH3- and (CH3)2CH-, while the conformational flexibility of the n-propyl substituent increases the total number of feasible rotamers to 21. For the three molecules, the conformers can be associated in 3 groups, being the most stable the AS forms - the C=S double bond anti (A) with respect to the C-S single bond and the S-C single bond syn (S) with respect to the C=O double bond - followed by AA and SS conformers. The vibrational spectra were interpreted in terms of the predicted conformational equilibrium, presenting the ν(C=O) spectral region signals corresponding to the three groups of conformers. A moderated pre-resonance Raman enhancement of the ν(C=S) vibrational mode of CH3(CH2)2OC(S)SC(O)OCH2CH3 was detected, when the excitation radiation approaches the energy of a n→π∗ electronic transition associated with the C=S chromophore. UV-visible spectra in different solvents were measured and interpreted in terms of TD-DFT calculations. The unknown molecule CH3CH2OC(O)SH was isolated by the UV-visible photolysis of CH3OC(S)SC(O)OCH2CH3 isolated in Ar matrix, and also obtained as a side-product of the reaction between potassium xanthate salts, ROC(S)SK, and ethyl chloroformate, ClC(O)OCH2CH3. Copyright © 2014 Elsevier B.V. All rights reserved.

Sequence charge decoration dictates coil-globule transition in intrinsically disordered proteins

NASA Astrophysics Data System (ADS)

Firman, Taylor; Ghosh, Kingshuk

2018-03-01

We present an analytical theory to compute conformations of heteropolymers—applicable to describe disordered proteins—as a function of temperature and charge sequence. The theory describes coil-globule transition for a given protein sequence when temperature is varied and has been benchmarked against the all-atom Monte Carlo simulation (using CAMPARI) of intrinsically disordered proteins (IDPs). In addition, the model quantitatively shows how subtle alterations of charge placement in the primary sequence—while maintaining the same charge composition—can lead to significant changes in conformation, even as drastic as a coil (swelled above a purely random coil) to globule (collapsed below a random coil) and vice versa. The theory provides insights on how to control (enhance or suppress) these changes by tuning the temperature (or solution condition) and charge decoration. As an application, we predict the distribution of conformations (at room temperature) of all naturally occurring IDPs in the DisProt database and notice significant size variation even among IDPs with a similar composition of positive and negative charges. Based on this, we provide a new diagram-of-states delineating the sequence-conformation relation for proteins in the DisProt database. Next, we study the effect of post-translational modification, e.g., phosphorylation, on IDP conformations. Modifications as little as two-site phosphorylation can significantly alter the size of an IDP with everything else being constant (temperature, salt concentration, etc.). However, not all possible modification sites have the same effect on protein conformations; there are certain "hot spots" that can cause maximal change in conformation. The location of these "hot spots" in the parent sequence can readily be identified by using a sequence charge decoration metric originally introduced by Sawle and Ghosh. The ability of our model to predict conformations (both expanded and collapsed states) of IDPs at a high-throughput level can provide valuable insights into the different mechanisms by which phosphorylation/charge mutation controls IDP function.

Residues with similar hexagon neighborhoods share similar side-chain conformations.

PubMed

Li, Shuai Cheng; Bu, Dongbo; Li, Ming

2012-01-01

We present in this study a new approach to code protein side-chain conformations into hexagon substructures. Classical side-chain packing methods consist of two steps: first, side-chain conformations, known as rotamers, are extracted from known protein structures as candidates for each residue; second, a searching method along with an energy function is used to resolve conflicts among residues and to optimize the combinations of side chain conformations for all residues. These methods benefit from the fact that the number of possible side-chain conformations is limited, and the rotamer candidates are readily extracted; however, these methods also suffer from the inaccuracy of energy functions. Inspired by threading and Ab Initio approaches to protein structure prediction, we propose to use hexagon substructures to implicitly capture subtle issues of energy functions. Our initial results indicate that even without guidance from an energy function, hexagon structures alone can capture side-chain conformations at an accuracy of 83.8 percent, higher than 82.6 percent by the state-of-art side-chain packing methods.

Relation Between Hertz Stress-Life Exponent, Ball-Race Conformity, and Ball Bearing Life

NASA Technical Reports Server (NTRS)

Zaretsky, Erwin V.; Poplawski, Joseph V.; Root, Lawrence E.

2008-01-01

ANSI/ABMA and ISO standards based on Lundberg-Palmgren bearing life theory are normalized for ball bearings having inner- and outerrace conformities of 52 percent (0.52) and made from pre-1940 bearing steel. The Lundberg-Palmgren theory incorporates an inverse 9th power relation between Hertz stress and fatigue life for ball bearings. The effect of race conformity on ball set life independent of race life is not incorporated into the Lundberg-Palmgren theory. In addition, post-1960 vacuum-processed bearing steel exhibits a 12th power relation between Hertz stress and life. The work reported extends the previous work of Zaretsky, Poplawski, and Root to calculate changes in bearing life--that includes the life of the ball set--caused by race conformity, Hertz stress-life exponent, ball bearing type and bearing series. The bearing fatigue life in actual application will usually be equal to or greater than that calculated using the ANSI/ABMA and ISO standards that incorporate the Lundberg-Palmgren theory. The relative fatigue life of an individual race is more sensitive to changes in race conformity for Hertz stress-life exponent n of 12 than where n = 9. However, when the effects are combined to predict actual bearing life for a specified set of conditions and bearing geometry, the predicted life of the bearing will be greater for a value of n = 12 than n = 9.

Relation between Hertz Stress-Life Exponent, Ball-Race Conformity, and Ball Bearing Life

NASA Technical Reports Server (NTRS)

Zaretsky, Erwin V.; Poplawski, Joseph V.; Root, Lawrence E.

2006-01-01

ANSI/ABMA and ISO standards based on Lundberg-Palmgren bearing life theory are normalized for ball bearings having inner- and outer-race conformities of 52 percent (0.52) and made from pre-1940 bearing steel. The Lundberg-Palmgren theory incorporates an inverse 9th power relation between Hertz stress and fatigue life for ball bearings. The effect of race conformity on ball set life independent of race life is not incorporated into the Lundberg-Palmgren theory. In addition, post-1960 vacuum-processed bearing steel exhibits a 12th power relation between Hertz stress and life. The work reported extends the previous work of Zaretsky, Poplawski, and Root to calculate changes in bearing life, that includes the life of the ball set, caused by race conformity, Hertz stress-life exponent, ball bearing type and bearing series. The bearing fatigue life in actual application will usually be equal to or greater than that calculated using the ANSI/ABMA and ISO standards that incorporate the Lundberg-Palmgren theory. The relative fatigue life of an individual race is more sensitive to changes in race conformity for Hertz stress-life exponent n of 12 than where n = 9. However, when the effects are combined to predict actual bearing life for a specified set of conditions and bearing geometry, the predicted life of the bearing will be greater for a value of n = 12 than n = 9.

Molecular determinants of cadherin ideal bond formation: Conformation-dependent unbinding on a multidimensional landscape

PubMed Central

Manibog, Kristine; Sankar, Kannan; Kim, Sun-Ae; Zhang, Yunxiang; Jernigan, Robert L.; Sivasankar, Sanjeevi

2016-01-01

Classical cadherin cell–cell adhesion proteins are essential for the formation and maintenance of tissue structures; their primary function is to physically couple neighboring cells and withstand mechanical force. Cadherins from opposing cells bind in two distinct trans conformations: strand-swap dimers and X-dimers. As cadherins convert between these conformations, they form ideal bonds (i.e., adhesive interactions that are insensitive to force). However, the biophysical mechanism for ideal bond formation is unknown. Here, we integrate single-molecule force measurements with coarse-grained and atomistic simulations to resolve the mechanistic basis for cadherin ideal bond formation. Using simulations, we predict the energy landscape for cadherin adhesion, the transition pathways for interconversion between X-dimers and strand-swap dimers, and the cadherin structures that form ideal bonds. Based on these predictions, we engineer cadherin mutants that promote or inhibit ideal bond formation and measure their force-dependent kinetics using single-molecule force-clamp measurements with an atomic force microscope. Our data establish that cadherins adopt an intermediate conformation as they shuttle between X-dimers and strand-swap dimers; pulling on this conformation induces a torsional motion perpendicular to the pulling direction that unbinds the proteins and forms force-independent ideal bonds. Torsional motion is blocked when cadherins associate laterally in a cis orientation, suggesting that ideal bonds may play a role in mechanically regulating cadherin clustering on cell surfaces. PMID:27621473

Generating Impact Maps from Automatically Detected Bomb Craters in Aerial Wartime Images Using Marked Point Processes

NASA Astrophysics Data System (ADS)

Kruse, Christian; Rottensteiner, Franz; Hoberg, Thorsten; Ziems, Marcel; Rebke, Julia; Heipke, Christian

2018-04-01

The aftermath of wartime attacks is often felt long after the war ended, as numerous unexploded bombs may still exist in the ground. Typically, such areas are documented in so-called impact maps which are based on the detection of bomb craters. This paper proposes a method for the automatic detection of bomb craters in aerial wartime images that were taken during the Second World War. The object model for the bomb craters is represented by ellipses. A probabilistic approach based on marked point processes determines the most likely configuration of objects within the scene. Adding and removing new objects to and from the current configuration, respectively, changing their positions and modifying the ellipse parameters randomly creates new object configurations. Each configuration is evaluated using an energy function. High gradient magnitudes along the border of the ellipse are favored and overlapping ellipses are penalized. Reversible Jump Markov Chain Monte Carlo sampling in combination with simulated annealing provides the global energy optimum, which describes the conformance with a predefined model. For generating the impact map a probability map is defined which is created from the automatic detections via kernel density estimation. By setting a threshold, areas around the detections are classified as contaminated or uncontaminated sites, respectively. Our results show the general potential of the method for the automatic detection of bomb craters and its automated generation of an impact map in a heterogeneous image stock.

Multiple receptor conformation docking and dock pose clustering as tool for CoMFA and CoMSIA analysis - a case study on HIV-1 protease inhibitors.

PubMed

Sivan, Sree Kanth; Manga, Vijjulatha

2012-02-01

Multiple receptors conformation docking (MRCD) and clustering of dock poses allows seamless incorporation of receptor binding conformation of the molecules on wide range of ligands with varied structural scaffold. The accuracy of the approach was tested on a set of 120 cyclic urea molecules having HIV-1 protease inhibitory activity using 12 high resolution X-ray crystal structures and one NMR resolved conformation of HIV-1 protease extracted from protein data bank. A cross validation was performed on 25 non-cyclic urea HIV-1 protease inhibitor having varied structures. The comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models were generated using 60 molecules in the training set by applying leave one out cross validation method, r (loo) (2) values of 0.598 and 0.674 for CoMFA and CoMSIA respectively and non-cross validated regression coefficient r(2) values of 0.983 and 0.985 were obtained for CoMFA and CoMSIA respectively. The predictive ability of these models was determined using a test set of 60 cyclic urea molecules that gave predictive correlation (r (pred) (2) ) of 0.684 and 0.64 respectively for CoMFA and CoMSIA indicating good internal predictive ability. Based on this information 25 non-cyclic urea molecules were taken as a test set to check the external predictive ability of these models. This gave remarkable out come with r (pred) (2) of 0.61 and 0.53 for CoMFA and CoMSIA respectively. The results invariably show that this method is useful for performing 3D QSAR analysis on molecules having different structural motifs.

Newly Enacted Intent Changes to ADS-B MASPS: Emphasis on Operations, Compatibility, and Integrity

NASA Technical Reports Server (NTRS)

Barhydt, Richard; Warren, Anthony W.

2002-01-01

Significant changes to the intent reporting structure in the Minimum Aviation System Performance Standards (MASPS) for Automatic Dependent Surveillance Broadcast (ADS-B) have recently been approved by RTCA Special Committee 186. The re-structured intent formats incorporate two major changes to the current MASPS (DO-242): addition of a Target State (TS) report that provides information on the horizontal and vertical targets for the current flight segment and replacement of the current Trajectory Change Point (TCP) and TCP+1 reports with Trajectory Change (TC) reports. TC reports include expanded information about TCPs and their connecting flight segments, in addition to making provisions for trajectory conformance elements. New intent elements are designed to accommodate a greater range of intent information, better reflect operational use and capabilities of existing and future aircraft avionics, and aid trajectory synthesis and conformance monitoring systems. These elements are expected to benefit near-term and future Air Traffic Management (ATM) applications, including separation assurance, local traffic flow management, and conformance monitoring. The current MASPS revision (DO-242A) implements those intent elements that are supported by current avionics standards and data buses. Additional elements are provisioned for inclusion in future MASPS revisions (beyond DO-242A) as avionics systems are evolved.

Informational and Normative Influences in Conformity from a Neurocomputational Perspective.

PubMed

Toelch, Ulf; Dolan, Raymond J

2015-10-01

We consider two distinct influences that drive conformity behaviour. Whereas informational influences facilitate adaptive and accurate responses, normative influences bias decisions to enhance social acceptance. We explore these influences from a perspective of perceptual and value-based decision-making models and apply these models to classical works on conformity. We argue that an informational account predicts a surprising tendency to conform. Moreover, we detail how normative influences fit into this framework and interact with social influences. Finally, we explore potential neuronal substrates for informational and normative influences based on a consideration of the neurobiological literature, highlighting conceptual shortcomings particularly with regard to a failure to segregate informational and normative influences. Copyright © 2015 Elsevier Ltd. All rights reserved.

A new clustering of antibody CDR loop conformations

PubMed Central

North, Benjamin; Lehmann, Andreas; Dunbrack, Roland L.

2010-01-01

Previous analyses of the complementarity determining regions (CDRs) of antibodies have focused on a small number of “canonical” conformations for each loop. This is primarily the result of the work of Chothia and colleagues, most recently in 1997. Because of the widespread utility of antibodies, we have revisited the clustering of conformations of the six CDR loops with the much larger amount of structural information currently available. In this work, we were careful to use a high-quality data set by eliminating low-resolution structures and CDRs with high B-factors or high conformational energies. We used a distance function based on directional statistics and an effective clustering algorithm using affinity propagation. With this data set of over 300 non-redundant antibody structures, we were able to cover 28 CDR-length combinations (e.g., L1 length 11, or “L1-11” in our nomenclature) for L1, L2, L3, H1 and H2. The Chothia analysis covered only 20 CDR-lengths. Only four of these had more than one conformational cluster, of which two could easily be distinguished by gene source (mouse/human; κ/λ) and one purely by the presence and positions of Pro residues (L3-9). Thus using the Chothia analysis does not require the complicated set of “structure-determining residues” that is often assumed. Of our 28 CDR-lengths, 15 of them have multiple conformational clusters including ten for which Chothia had only one canonical class. We have a total of 72 clusters for the non-H3 CDRs; approximately 85% of the non-H3 sequences can be assigned to a conformational cluster based on gene source and/or sequence. We found that earlier predictions of “bulged” vs. “non-bulged” conformations based on the presence or absence of anchor residues Arg/Lys94 and Asp101 of H3 have not held up, since all four combinations lead to a majority of conformations that are bulged. Thus the earlier analyses have been significantly enhanced by the increased data. We believe the new classification will lead to improved methods for antibody structure prediction and design. PMID:21035459

Crystal Structure, Conformational Analysis, and Charge Density Distribution for Eng-Epifisetinidol: An Explanation for Regiospecific Aromatic Substitution of 5-Deoxyflavan

Treesearch

Fred L. Tobiason; Frank R. Fronczek; Jan P. Steynberg; Elizabeth C. Steynberg; Richard W. Hemingway; Wayne L. Mattice

1993-01-01

Molecular modeling and molecular orbital analyses of ent-epifisetinidol gave &ood predictions of the approximate "reverse half-chair" conformation found for the crystal structure. MNDO and AM1 analyses of HOMO electron densities provided an explanation for the stereospecific electrophilic aromatic substitution at C(6) in 5-deoxy-flavans...

Multivariate Analysis of Conformational Changes Induced by Macromolecular Interactions

NASA Astrophysics Data System (ADS)

Mitra, Indranil; Alexov, Emil

2009-11-01

Understanding protein-protein binding and associated conformational changes is critical for both understanding thermodynamics of protein interactions and successful drug discovery. Our study focuses on computational analysis of plausible correlations between induced conformational changes and set of biophysical characteristics of interacting monomers. It was done by comparing 3D structures of unbound and bound monomers to calculate the RMSD which is used as measure of the structural changed induced by the binding. We correlate RMSD with volumetric and interfacial charge of the monomers, the amino acid composition, the energy of binding, and type of amino acids at the interface. as predictors. The data set was analyzed with SVM in R & SPSS which is trained on a combination of a new robust evolutionary conservation signal with the monomeric properties to predict the induced RMSD. The goal of this study is to undergo parametric tests and heirchiacal cluster and discriminant multivariate analysis to find key predictors which will be used to develop algorithm to predict the magnitude of conformational changes provided by the structure of interacting monomers. Results indicate that the most promising predictor is the net charge of the monomers, however, other parameters as the type of amino acids at the interface have significant contribution as well.

Facet-selective nucleation and conformal epitaxy of Ge shells on Si nanowires

DOE PAGES

Nguyen, Binh -Minh; Swartzentruber, Brian; Ro, Yun Goo; ...

2015-10-08

Knowledge of nanoscale heteroepitaxy is continually evolving as advances in material synthesis reveal new mechanisms that have not been theoretically predicted and are different than what is known about planar structures. In addition to a wide range of potential applications, core/shell nanowire structures offer a useful template to investigate heteroepitaxy at the atomistic scale. We show that the growth of a Ge shell on a Si core can be tuned from the theoretically predicted island growth mode to a conformal, crystalline, and smooth shell by careful adjustment of growth parameters in a narrow growth window that has not been exploredmore » before. In the latter growth mode, Ge adatoms preferentially nucleate islands on the {113} facets of the Si core, which outgrow over the {220} facets. Islands on the low-energy {111} facets appear to have a nucleation delay compared to the {113} islands; however, they eventually coalesce to form a crystalline conformal shell. As a result, synthesis of epitaxial and conformal Si/Ge/Si core/multishell structures enables us to fabricate unique cylindrical ring nanowire field-effect transistors, which we demonstrate to have steeper on/off characteristics than conventional core/shell nanowire transistors.« less

Analysis of rotary balance data for the F-15 airplane including the effect of conformal fuel tanks

NASA Technical Reports Server (NTRS)

Barnhart, B.

1982-01-01

F-15 rotary balance data was analyzed, and the influence of control deflections, Reynolds number and airplane components, i.e., body, wing, horizontal and vertical tails, as well as conformal tanks, on the aerodynamics up to 90 degrees angle of attack are discussed. Steady state spin mode predictions using these data are presented, which show excellent correlation with spin tunnel and flight test results. Generally, the data shows damped yawing moment slopes with rotation at all angles of attack, and good control effectiveness. Differences in the rotary aerodynamics due to the addition of conformal tanks are minimal. The small differences in the region of the flat spin do, however, indicate that the resulting spin mode would be slightly flatter and faster for a conformal tank equipped airplane. The addition of conformal tanks make the airplane more departure susceptible.

Experimentally observed conformation-dependent geometry and hidden strain in proteins.

PubMed Central

Karplus, P. A.

1996-01-01

A database has been compiled documenting the peptide conformations and geometries from 70 diverse proteins refined at 1.75 A or better. Analysis of the well-ordered residues within the database shows phi, psi-distributions that have more fine structure than is generally observed. Also, clear evidence is presented that the peptide covalent geometry depends on conformation, with the interpeptide N-C alpha-C bond angle varying by nearly +/-5 degrees from its standard value. The observed deviations from standard peptide geometry are greatest near the edges of well-populated regions, consistent with strain occurring in these conformations. Minimization of such hidden strain could be an important factor in thermostability of proteins. These empirical data describing how equilibrium peptide geometry varies as a function of conformation confirm and extend quantum mechanics calculations, and have predictive value that will aid both theoretical and experimental analyses of protein structure. PMID:8819173

Conformational plasticity of the Ebola virus matrix protein.

PubMed

Radzimanowski, Jens; Effantin, Gregory; Weissenhorn, Winfried

2014-11-01

Filoviruses are the causative agents of a severe and often fatal hemorrhagic fever with repeated outbreaks in Africa. They are negative sense single stranded enveloped viruses that can cross species barriers from its natural host bats to primates including humans. The small size of the genome poses limits to viral adaption, which may be partially overcome by conformational plasticity. Here we review the different conformational states of the Ebola virus (EBOV) matrix protein VP40 that range from monomers, to dimers, hexamers, and RNA-bound octamers. This conformational plasticity that is required for the viral life cycle poses a unique opportunity for development of VP40 specific drugs. Furthermore, we compare the structure to homologous matrix protein structures from Paramyxoviruses and Bornaviruses and we predict that they do not only share the fold but also the conformational flexibility of EBOV VP40. © 2014 The Protein Society.

Cyclo-biphenalenyl biradicaloid molecular materials: conformation, tautomerization, magnetism, and thermochromism

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Jingsong; Sumpter, Bobby G; Meunier, Vincent

2011-01-01

Phenalenyl and its derivatives have recently attracted a great deal of interest as a result of a 2-electron multicenter (2e/mc) covalent pi-pi bonding between two pi-stacked phenalenyl units. The 2e/mc bonded pi-dimers are close in energy to the sigma-dimers of phenalenyl and therefore fickle properties may emerge from bond fluctuation, yielding smart pi-functional materials. Here we examine the valence tautomerization of two cyclo-biphenalenyl biradicaloid molecular materials with chair- and boat-conformations by spin-restricted (R) and unrestricted (U) DFT using the M06 and B3LYP functionals. We found that the chair-conformation involves a 2e/4c pi-pi bonded structure while the boat-conformation involves a 2e/12cmore » pi-pi bonded structure on their potential energy surfaces. The global minimum for the chair-conformation is the sigma-bonded structure while it is the pi-pi bonded structure for the boat-conformation. The chair-conformation exhibits a stepwise [3,3]-sigmatropic rearrangement, and calculations predict a negligible paramagnetic susceptibility near room temperature. In comparison, the paramagnetism of the boat-conformation should be observable by SQUID and/or ESR. According to the difference of the global minima of the two conformations and the parameterized UV-Vis calculations, the color of the chair-conformation is expected to become darker while that of the boat-conformation become lighter with increasing temperature.« less

On the Relationship Between Automatic Attitudes and Self-Reported Sexual Assault in Men

PubMed Central

Widman, Laura; Olson, Michael

2013-01-01

Research and theory suggest rape supportive attitudes are important predictors of sexual assault; yet, to date, rape supportive attitudes have been assessed exclusively through self-report measures that are methodologically and theoretically limited. To address these limitations, the objectives of the current project were to: (1) develop a novel implicit rape attitude assessment that captures automatic attitudes about rape and does not rely on self-reports, and (2) examine the association between automatic rape attitudes and sexual assault perpetration. We predicted that automatic rape attitudes would be a significant unique predictor of sexual assault even when self-reported rape attitudes (i.e., rape myth acceptance and hostility toward women) were controlled. We tested the generalizability of this prediction in two independent samples: a sample of undergraduate college men (n = 75, M age = 19.3 years) and a sample of men from the community (n = 50, M age = 35.9 years). We found the novel implicit rape attitude assessment was significantly associated with the frequency of sexual assault perpetration in both samples and contributed unique variance in explaining sexual assault beyond rape myth acceptance and hostility toward women. We discuss the ways in which future research on automatic rape attitudes may significantly advance measurement and theory aimed at understanding and preventing sexual assault. PMID:22618119

Analyzing and Detecting Problems in Systems of Systems

NASA Technical Reports Server (NTRS)

Lindvall, Mikael; Ackermann, Christopher; Stratton, William C.; Sibol, Deane E.; Godfrey, Sally

2008-01-01

Many software systems are evolving complex system of systems (SoS) for which inter-system communication is mission-critical. Evidence indicates that transmission failures and performance issues are not uncommon occurrences. In a NASA-supported Software Assurance Research Program (SARP) project, we are researching a new approach addressing such problems. In this paper, we are presenting an approach for analyzing inter-system communications with the goal to uncover both transmission errors and performance problems. Our approach consists of a visualization and an evaluation component. While the visualization of the observed communication aims to facilitate understanding, the evaluation component automatically checks the conformance of an observed communication (actual) to a desired one (planned). The actual and the planned are represented as sequence diagrams. The evaluation algorithm checks the conformance of the actual to the planned diagram. We have applied our approach to the communication of aerospace systems and were successful in detecting and resolving even subtle and long existing transmission problems.

Component Processes Subserving Rapid Automatized Naming in Dyslexic and Non-Dyslexic Readers

ERIC Educational Resources Information Center

Araujo, Susana; Inacio, Filomena; Francisco, Ana; Faisca, Luis; Petersson, Karl Magnus; Reis, Alexandra

2011-01-01

The current study investigated which time components of rapid automatized naming (RAN) predict group differences between dyslexic and non-dyslexic readers (matched for age and reading level), and how these components relate to different reading measures. Subjects performed two RAN tasks (letters and objects), and data were analyzed through a…

The Masculinity of Money: Automatic Stereotypes Predict Gender Differences in Estimated Salaries

ERIC Educational Resources Information Center

Williams, Melissa J.; Paluck, Elizabeth Levy; Spencer-Rodgers, Julie

2010-01-01

We present the first empirical investigation of why men are assumed to earn higher salaries than women (the "salary estimation effect"). Although this phenomenon is typically attributed to conscious consideration of the national wage gap (i.e., real inequities in salary), we hypothesize instead that it reflects differential, automatic economic…

Beyond Prediction: First Steps toward Automatic Intervention in MOOC Student Stopout

ERIC Educational Resources Information Center

Whitehill, Jacob; Williams, Joseph; Lopez, Glenn; Coleman, Cody; Reich, Justin

2015-01-01

High attrition rates in massive open online courses (MOOCs) have motivated growing interest in the automatic detection of student "stopout". Stopout classifiers can be used to orchestrate an intervention before students quit, and to survey students dynamically about why they ceased participation. In this paper we expand on existing…

The Influence of Inattention on Rapid Automatized Naming and Reading Skills

ERIC Educational Resources Information Center

Pham, Andy V.

2010-01-01

The purpose of this study is to determine how behavioral symptoms of inattention predict rapid automatized naming (RAN) performance and reading skills in typically developing children. Participants included 104 third- and fourth-grade children from different elementary schools in mid-Michigan. RAN performance was assessed using the four Rapid…

a Sensor Based Automatic Ovulation Prediction System for Dairy Cows

NASA Astrophysics Data System (ADS)

Mottram, Toby; Hart, John; Pemberton, Roy

2000-12-01

Sensor scientists have been successful in developing detectors for tiny concentrations of rare compounds, but the work is rarely applied in practice. Any but the most trivial application of sensors requires a specification that should include a sampling system, a sensor, a calibration system and a model of how the information is to be used to control the process of interest. The specification of the sensor system should ask the following questions. How will the material to be analysed be sampled? What decision can be made with the information available from a proposed sensor? This project provides a model of a systems approach to the implementation of automatic ovulation prediction in dairy cows. A healthy well managed dairy cow should calve every year to make the best use of forage. As most cows are inseminated artificially it is of vital importance mat cows are regularly monitored for signs of oestrus. The pressure on dairymen to manage more cows often leads to less time being available for observation of cows to detect oestrus. This, together with breeding and feeding for increased yields, has led to a reduction in reproductive performance. In the UK the typical dairy farmer could save € 12800 per year if ovulation could be predicted accurately. Research over a number of years has shown that regular analysis of milk samples with tests based on enzyme linked immunoassay (ELISA) can map the ovulation cycle. However, these tests require the farmer to implement a manually operated sampling and analysis procedure and the technique has not been widely taken up. The best potential method of achieving 98% specificity of prediction of ovulation is to adapt biosensor techniques to emulate the ELISA tests automatically in the milking system. An automated ovulation prediction system for dairy cows is specified. The system integrates a biosensor with automatic milk sampling and a herd management database. The biosensor is a screen printed carbon electrode system capable of measuring concentrations of progesterone in milk in the range 0.3-25 ng/ml. The system is operational in the laboratory is described here and will be working on a test farm in the near future to automatically predict the ovulation of dairy cows routinely.

Automatic Prediction of Conversion from Mild Cognitive Impairment to Probable Alzheimer’s Disease using Structural Magnetic Resonance Imaging

PubMed Central

Nho, Kwangsik; Shen, Li; Kim, Sungeun; Risacher, Shannon L.; West, John D.; Foroud, Tatiana; Jack, Clifford R.; Weiner, Michael W.; Saykin, Andrew J.

2010-01-01

Mild Cognitive Impairment (MCI) is thought to be a precursor to the development of early Alzheimer’s disease (AD). For early diagnosis of AD, the development of a model that is able to predict the conversion of amnestic MCI to AD is challenging. Using automatic whole-brain MRI analysis techniques and pattern classification methods, we developed a model to differentiate AD from healthy controls (HC), and then applied it to the prediction of MCI conversion to AD. Classification was performed using support vector machines (SVMs) together with a SVM-based feature selection method, which selected a set of most discriminating predictors for optimizing prediction accuracy. We obtained 90.5% cross-validation accuracy for classifying AD and HC, and 72.3% accuracy for predicting MCI conversion to AD. These analyses suggest that a classifier trained to separate HC vs. AD has substantial potential for predicting MCI conversion to AD. PMID:21347037

Novel demonstration of the renormalization group invariance of the fixed-order predictions using the principle of maximum conformality and the C -scheme coupling

NASA Astrophysics Data System (ADS)

Wu, Xing-Gang; Shen, Jian-Ming; Du, Bo-Lun; Brodsky, Stanley J.

2018-05-01

As a basic requirement of the renormalization group invariance, any physical observable must be independent of the choice of both the renormalization scheme and the initial renormalization scale. In this paper, we show that by using the newly suggested C -scheme coupling, one can obtain a demonstration that the principle of maximum conformality prediction is scheme-independent to all-orders for any renormalization schemes, thus satisfying all of the conditions of the renormalization group invariance. We illustrate these features for the nonsinglet Adler function and for τ decay to ν + hadrons at the four-loop level.

SimRNA: a coarse-grained method for RNA folding simulations and 3D structure prediction.

PubMed

Boniecki, Michal J; Lach, Grzegorz; Dawson, Wayne K; Tomala, Konrad; Lukasz, Pawel; Soltysinski, Tomasz; Rother, Kristian M; Bujnicki, Janusz M

2016-04-20

RNA molecules play fundamental roles in cellular processes. Their function and interactions with other biomolecules are dependent on the ability to form complex three-dimensional (3D) structures. However, experimental determination of RNA 3D structures is laborious and challenging, and therefore, the majority of known RNAs remain structurally uncharacterized. Here, we present SimRNA: a new method for computational RNA 3D structure prediction, which uses a coarse-grained representation, relies on the Monte Carlo method for sampling the conformational space, and employs a statistical potential to approximate the energy and identify conformations that correspond to biologically relevant structures. SimRNA can fold RNA molecules using only sequence information, and, on established test sequences, it recapitulates secondary structure with high accuracy, including correct prediction of pseudoknots. For modeling of complex 3D structures, it can use additional restraints, derived from experimental or computational analyses, including information about secondary structure and/or long-range contacts. SimRNA also can be used to analyze conformational landscapes and identify potential alternative structures. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

[Prediction and evolution of B cell epitopes of hemagglutinin in human-infecting H6N1 avian influenza virus].

PubMed

Yang, Jianke; Yuan, Jian; Gao, Jiguang; Zhu, Xiaolei; Lin, Aiqin

2015-01-01

To predict B cell epitopes of hemagglutinin (HA) of human-infecting H6N1 avian influenza virus and analyze their evolutionary characteristics. The dataset was downloaded from GISAID and GenBank databases. And the linear and conformational B cell epitopes of HA were predicted separately by various bioinformatic software. Furthermore, the conservation, adaptation and other evolutionary characteristics were also analyzed by some bioinformatic means. Four linear epitopes (A, B, C and D) and two conformational epitopes (E and F) were obtained after consideration of multiple factors. And the C epitope and sites ( 41, 157, 186, 187) mutated easily, but the other epitopes were very conservative and the D epitope was the most conservative. Interestingly, the site 157 was identified under positive selection, suggesting that it may be a particularly important site to make the virus evade the attack from the host immune system. The HA of human-infecting H6N1 avian influenza virus has five conservative B cell epitopes (three linear and two conformational) and one site under positive selection. The findings would facilitate the vaccine development, virus control and pathogenesis understanding.

Role of conformational sampling in computing mutation-induced changes in protein structure and stability.

PubMed

Kellogg, Elizabeth H; Leaver-Fay, Andrew; Baker, David

2011-03-01

The prediction of changes in protein stability and structure resulting from single amino acid substitutions is both a fundamental test of macromolecular modeling methodology and an important current problem as high throughput sequencing reveals sequence polymorphisms at an increasing rate. In principle, given the structure of a wild-type protein and a point mutation whose effects are to be predicted, an accurate method should recapitulate both the structural changes and the change in the folding-free energy. Here, we explore the performance of protocols which sample an increasing diversity of conformations. We find that surprisingly similar performances in predicting changes in stability are achieved using protocols that involve very different amounts of conformational sampling, provided that the resolution of the force field is matched to the resolution of the sampling method. Methods involving backbone sampling can in some cases closely recapitulate the structural changes accompanying mutations but not surprisingly tend to do more harm than good in cases where structural changes are negligible. Analysis of the outliers in the stability change calculations suggests areas needing particular improvement; these include the balance between desolvation and the formation of favorable buried polar interactions, and unfolded state modeling. Copyright © 2010 Wiley-Liss, Inc.

Trp zipper folding kinetics by molecular dynamics and temperature-jump spectroscopy

PubMed Central

Snow, Christopher D.; Qiu, Linlin; Du, Deguo; Gai, Feng; Hagen, Stephen J.; Pande, Vijay S.

2004-01-01

We studied the microsecond folding dynamics of three β hairpins (Trp zippers 1–3, TZ1–TZ3) by using temperature-jump fluorescence and atomistic molecular dynamics in implicit solvent. In addition, we studied TZ2 by using time-resolved IR spectroscopy. By using distributed computing, we obtained an aggregate simulation time of 22 ms. The simulations included 150, 212, and 48 folding events at room temperature for TZ1, TZ2, and TZ3, respectively. The all-atom optimized potentials for liquid simulations (OPLSaa) potential set predicted TZ1 and TZ2 properties well; the estimated folding rates agreed with the experimentally determined folding rates and native conformations were the global potential-energy minimum. The simulations also predicted reasonable unfolding activation enthalpies. This work, directly comparing large simulated folding ensembles with multiple spectroscopic probes, revealed both the surprising predictive ability of current models as well as their shortcomings. Specifically, for TZ1–TZ3, OPLS for united atom models had a nonnative free-energy minimum, and the folding rate for OPLSaa TZ3 was sensitive to the initial conformation. Finally, we characterized the transition state; all TZs fold by means of similar, native-like transition-state conformations. PMID:15020773

Trp zipper folding kinetics by molecular dynamics and temperature-jump spectroscopy

NASA Astrophysics Data System (ADS)

Snow, Christopher D.; Qiu, Linlin; Du, Deguo; Gai, Feng; Hagen, Stephen J.; Pande, Vijay S.

2004-03-01

We studied the microsecond folding dynamics of three hairpins (Trp zippers 1-3, TZ1-TZ3) by using temperature-jump fluorescence and atomistic molecular dynamics in implicit solvent. In addition, we studied TZ2 by using time-resolved IR spectroscopy. By using distributed computing, we obtained an aggregate simulation time of 22 ms. The simulations included 150, 212, and 48 folding events at room temperature for TZ1, TZ2, and TZ3, respectively. The all-atom optimized potentials for liquid simulations (OPLSaa) potential set predicted TZ1 and TZ2 properties well; the estimated folding rates agreed with the experimentally determined folding rates and native conformations were the global potential-energy minimum. The simulations also predicted reasonable unfolding activation enthalpies. This work, directly comparing large simulated folding ensembles with multiple spectroscopic probes, revealed both the surprising predictive ability of current models as well as their shortcomings. Specifically, for TZ1-TZ3, OPLS for united atom models had a nonnative free-energy minimum, and the folding rate for OPLSaa TZ3 was sensitive to the initial conformation. Finally, we characterized the transition state; all TZs fold by means of similar, native-like transition-state conformations.

Machine learning classification with confidence: application of transductive conformal predictors to MRI-based diagnostic and prognostic markers in depression.

PubMed

Nouretdinov, Ilia; Costafreda, Sergi G; Gammerman, Alexander; Chervonenkis, Alexey; Vovk, Vladimir; Vapnik, Vladimir; Fu, Cynthia H Y

2011-05-15

There is rapidly accumulating evidence that the application of machine learning classification to neuroimaging measurements may be valuable for the development of diagnostic and prognostic prediction tools in psychiatry. However, current methods do not produce a measure of the reliability of the predictions. Knowing the risk of the error associated with a given prediction is essential for the development of neuroimaging-based clinical tools. We propose a general probabilistic classification method to produce measures of confidence for magnetic resonance imaging (MRI) data. We describe the application of transductive conformal predictor (TCP) to MRI images. TCP generates the most likely prediction and a valid measure of confidence, as well as the set of all possible predictions for a given confidence level. We present the theoretical motivation for TCP, and we have applied TCP to structural and functional MRI data in patients and healthy controls to investigate diagnostic and prognostic prediction in depression. We verify that TCP predictions are as accurate as those obtained with more standard machine learning methods, such as support vector machine, while providing the additional benefit of a valid measure of confidence for each prediction. Copyright © 2010 Elsevier Inc. All rights reserved.

The automatic component of habit in health behavior: habit as cue-contingent automaticity.

PubMed

Orbell, Sheina; Verplanken, Bas

2010-07-01

Habit might be usefully characterized as a form of automaticity that involves the association of a cue and a response. Three studies examined habitual automaticity in regard to different aspects of the cue-response relationship characteristic of unhealthy and healthy habits. In each study, habitual automaticity was assessed by the Self-Report Habit Index (SRHI). In Study 1 SRHI scores correlated with attentional bias to smoking cues in a Stroop task. Study 2 examined the ability of a habit cue to elicit an unwanted habit response. In a prospective field study, habitual automaticity in relation to smoking when drinking alcohol in a licensed public house (pub) predicted the likelihood of cigarette-related action slips 2 months later after smoking in pubs had become illegal. In Study 3 experimental group participants formed an implementation intention to floss in response to a specified situational cue. Habitual automaticity of dental flossing was rapidly enhanced compared to controls. The studies provided three different demonstrations of the importance of cues in the automatic operation of habits. Habitual automaticity assessed by the SRHI captured aspects of a habit that go beyond mere frequency or consistency of the behavior. PsycINFO Database Record (c) 2010 APA, all rights reserved.

Blind test of physics-based prediction of protein structures.

PubMed

Shell, M Scott; Ozkan, S Banu; Voelz, Vincent; Wu, Guohong Albert; Dill, Ken A

2009-02-01

We report here a multiprotein blind test of a computer method to predict native protein structures based solely on an all-atom physics-based force field. We use the AMBER 96 potential function with an implicit (GB/SA) model of solvation, combined with replica-exchange molecular-dynamics simulations. Coarse conformational sampling is performed using the zipping and assembly method (ZAM), an approach that is designed to mimic the putative physical routes of protein folding. ZAM was applied to the folding of six proteins, from 76 to 112 monomers in length, in CASP7, a community-wide blind test of protein structure prediction. Because these predictions have about the same level of accuracy as typical bioinformatics methods, and do not utilize information from databases of known native structures, this work opens up the possibility of predicting the structures of membrane proteins, synthetic peptides, or other foldable polymers, for which there is little prior knowledge of native structures. This approach may also be useful for predicting physical protein folding routes, non-native conformations, and other physical properties from amino acid sequences.

Blind Test of Physics-Based Prediction of Protein Structures

PubMed Central

Shell, M. Scott; Ozkan, S. Banu; Voelz, Vincent; Wu, Guohong Albert; Dill, Ken A.

2009-01-01

We report here a multiprotein blind test of a computer method to predict native protein structures based solely on an all-atom physics-based force field. We use the AMBER 96 potential function with an implicit (GB/SA) model of solvation, combined with replica-exchange molecular-dynamics simulations. Coarse conformational sampling is performed using the zipping and assembly method (ZAM), an approach that is designed to mimic the putative physical routes of protein folding. ZAM was applied to the folding of six proteins, from 76 to 112 monomers in length, in CASP7, a community-wide blind test of protein structure prediction. Because these predictions have about the same level of accuracy as typical bioinformatics methods, and do not utilize information from databases of known native structures, this work opens up the possibility of predicting the structures of membrane proteins, synthetic peptides, or other foldable polymers, for which there is little prior knowledge of native structures. This approach may also be useful for predicting physical protein folding routes, non-native conformations, and other physical properties from amino acid sequences. PMID:19186130

A combined deep-learning and deformable-model approach to fully automatic segmentation of the left ventricle in cardiac MRI.

PubMed

Avendi, M R; Kheradvar, Arash; Jafarkhani, Hamid

2016-05-01

Segmentation of the left ventricle (LV) from cardiac magnetic resonance imaging (MRI) datasets is an essential step for calculation of clinical indices such as ventricular volume and ejection fraction. In this work, we employ deep learning algorithms combined with deformable models to develop and evaluate a fully automatic LV segmentation tool from short-axis cardiac MRI datasets. The method employs deep learning algorithms to learn the segmentation task from the ground true data. Convolutional networks are employed to automatically detect the LV chamber in MRI dataset. Stacked autoencoders are used to infer the LV shape. The inferred shape is incorporated into deformable models to improve the accuracy and robustness of the segmentation. We validated our method using 45 cardiac MR datasets from the MICCAI 2009 LV segmentation challenge and showed that it outperforms the state-of-the art methods. Excellent agreement with the ground truth was achieved. Validation metrics, percentage of good contours, Dice metric, average perpendicular distance and conformity, were computed as 96.69%, 0.94, 1.81 mm and 0.86, versus those of 79.2-95.62%, 0.87-0.9, 1.76-2.97 mm and 0.67-0.78, obtained by other methods, respectively. Copyright © 2016 Elsevier B.V. All rights reserved.

A Pressure Plate-Based Method for the Automatic Assessment of Foot Strike Patterns During Running.

PubMed

Santuz, Alessandro; Ekizos, Antonis; Arampatzis, Adamantios

2016-05-01

The foot strike pattern (FSP, description of how the foot touches the ground at impact) is recognized to be a predictor of both performance and injury risk. The objective of the current investigation was to validate an original foot strike pattern assessment technique based on the numerical analysis of foot pressure distribution. We analyzed the strike patterns during running of 145 healthy men and women (85 male, 60 female). The participants ran on a treadmill with integrated pressure plate at three different speeds: preferred (shod and barefoot 2.8 ± 0.4 m/s), faster (shod 3.5 ± 0.6 m/s) and slower (shod 2.3 ± 0.3 m/s). A custom-designed algorithm allowed the automatic footprint recognition and FSP evaluation. Incomplete footprints were simultaneously identified and corrected from the software itself. The widely used technique of analyzing high-speed video recordings was checked for its reliability and has been used to validate the numerical technique. The automatic numerical approach showed a good conformity with the reference video-based technique (ICC = 0.93, p < 0.01). The great improvement in data throughput and the increased completeness of results allow the use of this software as a powerful feedback tool in a simple experimental setup.

Renormalization group invariance and optimal QCD renormalization scale-setting: a key issues review.

PubMed

Wu, Xing-Gang; Ma, Yang; Wang, Sheng-Quan; Fu, Hai-Bing; Ma, Hong-Hao; Brodsky, Stanley J; Mojaza, Matin

2015-12-01

A valid prediction for a physical observable from quantum field theory should be independent of the choice of renormalization scheme--this is the primary requirement of renormalization group invariance (RGI). Satisfying scheme invariance is a challenging problem for perturbative QCD (pQCD), since a truncated perturbation series does not automatically satisfy the requirements of the renormalization group. In a previous review, we provided a general introduction to the various scale setting approaches suggested in the literature. As a step forward, in the present review, we present a discussion in depth of two well-established scale-setting methods based on RGI. One is the 'principle of maximum conformality' (PMC) in which the terms associated with the β-function are absorbed into the scale of the running coupling at each perturbative order; its predictions are scheme and scale independent at every finite order. The other approach is the 'principle of minimum sensitivity' (PMS), which is based on local RGI; the PMS approach determines the optimal renormalization scale by requiring the slope of the approximant of an observable to vanish. In this paper, we present a detailed comparison of the PMC and PMS procedures by analyzing two physical observables R(e+e-) and [Formula: see text] up to four-loop order in pQCD. At the four-loop level, the PMC and PMS predictions for both observables agree within small errors with those of conventional scale setting assuming a physically-motivated scale, and each prediction shows small scale dependences. However, the convergence of the pQCD series at high orders, behaves quite differently: the PMC displays the best pQCD convergence since it eliminates divergent renormalon terms; in contrast, the convergence of the PMS prediction is questionable, often even worse than the conventional prediction based on an arbitrary guess for the renormalization scale. PMC predictions also have the property that any residual dependence on the choice of initial scale is highly suppressed even for low-order predictions. Thus the PMC, based on the standard RGI, has a rigorous foundation; it eliminates an unnecessary systematic error for high precision pQCD predictions and can be widely applied to virtually all high-energy hadronic processes, including multi-scale problems.

Automated use of mutagenesis data in structure prediction.

PubMed

Nanda, Vikas; DeGrado, William F

2005-05-15

In the absence of experimental structural determination, numerous methods are available to indirectly predict or probe the structure of a target molecule. Genetic modification of a protein sequence is a powerful tool for identifying key residues involved in binding reactions or protein stability. Mutagenesis data is usually incorporated into the modeling process either through manual inspection of model compatibility with empirical data, or through the generation of geometric constraints linking sensitive residues to a binding interface. We present an approach derived from statistical studies of lattice models for introducing mutation information directly into the fitness score. The approach takes into account the phenotype of mutation (neutral or disruptive) and calculates the energy for a given structure over an ensemble of sequences. The structure prediction procedure searches for the optimal conformation where neutral sequences either have no impact or improve stability and disruptive sequences reduce stability relative to wild type. We examine three types of sequence ensembles: information from saturation mutagenesis, scanning mutagenesis, and homologous proteins. Incorporating multiple sequences into a statistical ensemble serves to energetically separate the native state and misfolded structures. As a result, the prediction of structure with a poor force field is sufficiently enhanced by mutational information to improve accuracy. Furthermore, by separating misfolded conformations from the target score, the ensemble energy serves to speed up conformational search algorithms such as Monte Carlo-based methods. Copyright 2005 Wiley-Liss, Inc.

Changes in automatic threat processing precede and predict clinical changes with exposure-based cognitive-behavior therapy for panic disorder.

PubMed

Reinecke, Andrea; Waldenmaier, Lara; Cooper, Myra J; Harmer, Catherine J

2013-06-01

Cognitive behavioral therapy (CBT) is an effective treatment for emotional disorders such as anxiety or depression, but the mechanisms underlying successful intervention are far from understood. Although it has been a long-held view that psychopharmacological approaches work by directly targeting automatic emotional information processing in the brain, it is usually postulated that psychological treatments affect these processes only over time, through changes in more conscious thought cycles. This study explored the role of early changes in emotional information processing in CBT action. Twenty-eight untreated patients with panic disorder were randomized to a single session of exposure-based CBT or waiting group. Emotional information processing was measured on the day after intervention with an attentional visual probe task, and clinical symptoms were assessed on the day after intervention and at 4-week follow-up. Vigilance for threat information was decreased in the treated group, compared with the waiting group, the day after intervention, before reductions in clinical symptoms. The magnitude of this early effect on threat vigilance predicted therapeutic response after 4 weeks. Cognitive behavioral therapy rapidly affects automatic processing, and these early effects are predictive of later therapeutic change. Such results suggest very fast action on automatic processes mediating threat sensitivity, and they provide an early marker of treatment response. Furthermore, these findings challenge the notion that psychological treatments work directly on conscious thought processes before automatic information processing and imply a greater similarity between early effects of pharmacological and psychological treatments for anxiety than previously thought. Copyright © 2013 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Want, need and habit as drivers of smoking behaviour: A preliminary analysis.

PubMed

Wehbe, Luis; Ubhi, Harveen Kaur; West, Robert

2018-01-01

Models of tobacco smoking behaviour propose that anticipated pleasure or satisfaction, the need to alleviate a nicotine-induced drive state and a stimulus-driven impulse potentially play an important role. This study aimed to provide a preliminary assessment of how far urges to smoke are reported by smokers and whether the strength of such urges prior to a quit attempt predicts short-term success at quitting. In a prospective study, 566 smokers attending a treatment programme to help smokers quit completed a written questionnaire covering frequency of different types of urge to smoke (automatic impulse - 'automatic urges', anticipated pleasure - 'pleasure urges', and fulfilling a need - 'need urges'). They were asked to rate this for whichever of these urges was dominant for them. The questionnaire also assessed daily cigarette consumption, time to first cigarette of the day, age and gender. Carbon monoxide verified smoking status was recorded at 1 and 4weeks after the target quit date. A total of 47.9% (271) of smokers reported that automatic urges were dominant, 21.7% (123) reported pleasure urges to be dominant, and 30.4% (172) reported need urges to be dominant. The strength of automatic urges predicted abstinence at both 1week (OR=0.74, p=0.005, 95%CI=0.60-0.92) and 4weeks (OR=0.73, p=0.008, 95%CI=0.59-0.92). Associations between other urge types and abstinence were not statistically significant. A substantial proportion of smokers attending a clinic for help with quitting report that their dominant urges to smoke occur without any anticipation of pleasure or relief and the strength of the automatic urges predicts failure to sustain abstinence following a quit attempt. Copyright © 2017. Published by Elsevier Ltd.

Dissociation of recombinant prion autocatalysis from infectivity.

PubMed

Noble, Geoffrey P; Supattapone, Surachai

2015-01-01

Within the mammalian prion field, the existence of recombinant prion protein (PrP) conformers with self-replicating (ie. autocatalytic) activity in vitro but little to no infectious activity in vivo challenges a key prediction of the protein-only hypothesis of prion replication--that autocatalytic PrP conformers should be infectious. To understand this dissociation of autocatalysis from infectivity, we recently performed a structural and functional comparison between a highly infectious and non-infectious pair of autocatalytic recombinant PrP conformers derived from the same initial prion strain. (1) We identified restricted, C-terminal structural differences between these 2 conformers and provided evidence that these relatively subtle differences prevent the non-infectious conformer from templating the conversion of native PrP(C) substrates containing a glycosylphosphatidylinositol (GPI) anchor. (1) In this article we discuss a model, consistent with these findings, in which recombinant PrP, lacking post-translational modifications and associated folding constraints, is capable of adopting a wide variety of autocatalytic conformations. Only a subset of these recombinant conformers can be adopted by post-translationally modified native PrP(C), and this subset represents the recombinant conformers with high specific infectivity. We examine this model's implications for the generation of highly infectious recombinant prions and the protein-only hypothesis of prion replication.

How Diverse are the Protein-Bound Conformations of Small-Molecule Drugs and Cofactors?

NASA Astrophysics Data System (ADS)

Friedrich, Nils-Ole; Simsir, Méliné; Kirchmair, Johannes

2018-03-01

Knowledge of the bioactive conformations of small molecules or the ability to predict them with theoretical methods is of key importance to the design of bioactive compounds such as drugs, agrochemicals and cosmetics. Using an elaborate cheminformatics pipeline, which also evaluates the support of individual atom coordinates by the measured electron density, we compiled a complete set (“Sperrylite Dataset”) of high-quality structures of protein-bound ligand conformations from the PDB. The Sperrylite Dataset consists of a total of 10,936 high-quality structures of 4548 unique ligands. Based on this dataset, we assessed the variability of the bioactive conformations of 91 small molecules—each represented by a minimum of ten structures—and found it to be largely independent of the number of rotatable bonds. Sixty-nine molecules had at least two distinct conformations (defined by an RMSD greater than 1 Å). For a representative subset of 17 approved drugs and cofactors we observed a clear trend for the formation of few clusters of highly similar conformers. Even for proteins that share a very low sequence identity, ligands were regularly found to adopt similar conformations. For cofactors, a clear trend for extended conformations was measured, although in few cases also coiled conformers were observed. The Sperrylite Dataset is available for download from http://www.zbh.uni-hamburg.de/sperrylite_dataset.

Language proficiency and metacognition as predictors of spontaneous rehearsal in children.

PubMed

Bebko, James M; McMorris, Carly A; Metcalfe, Alisa; Ricciuti, Christina; Goldstein, Gayle

2014-03-01

Despite decades of research on fundamental memory strategies such as verbal rehearsal, the potential underlying skills associated with the emergence of rehearsal are still not fully understood. Two studies examined the relative roles of language proficiency and metamemory in predicting rehearsal use, as well as the prediction of metamemory performance by language proficiency. In Study 1, 59 children, 5 to 8 years old, were administered a serial recall task, 2 language measures, a nonverbal cognitive measure, and a rapid automatized naming (RAN) task. Language proficiency, RAN, and age were significant individual predictors of rehearsal use. In hierarchical regression analyses, language proficiency mediated almost completely the age → rehearsal use relation. In addition, automatized naming was a strong but partial mediator of the contribution of language proficiency to rehearsal use. In Study 2, 54 children were administered a metamemory test, a language measure, and a serial recall task. Metamemory skills and, again, language proficiency significantly predicted rehearsal use in the task. The predictive strength of metamemory skills was mediated by the children's language proficiency. The mutually supportive roles of automatized naming, language, and metamemory in the emergence of spontaneous cumulative verbal rehearsal are discussed in the context of the resulting model, along with the minimal roles of age and aspects of intelligence.

Pse-Analysis: a python package for DNA/RNA and protein/ peptide sequence analysis based on pseudo components and kernel methods.

PubMed

Liu, Bin; Wu, Hao; Zhang, Deyuan; Wang, Xiaolong; Chou, Kuo-Chen

2017-02-21

To expedite the pace in conducting genome/proteome analysis, we have developed a Python package called Pse-Analysis. The powerful package can automatically complete the following five procedures: (1) sample feature extraction, (2) optimal parameter selection, (3) model training, (4) cross validation, and (5) evaluating prediction quality. All the work a user needs to do is to input a benchmark dataset along with the query biological sequences concerned. Based on the benchmark dataset, Pse-Analysis will automatically construct an ideal predictor, followed by yielding the predicted results for the submitted query samples. All the aforementioned tedious jobs can be automatically done by the computer. Moreover, the multiprocessing technique was adopted to enhance computational speed by about 6 folds. The Pse-Analysis Python package is freely accessible to the public at http://bioinformatics.hitsz.edu.cn/Pse-Analysis/, and can be directly run on Windows, Linux, and Unix.

Automatically detect and track infrared small targets with kernel Fukunaga-Koontz transform and Kalman prediction.

PubMed

Liu, Ruiming; Liu, Erqi; Yang, Jie; Zeng, Yong; Wang, Fanglin; Cao, Yuan

2007-11-01

Fukunaga-Koontz transform (FKT), stemming from principal component analysis (PCA), is used in many pattern recognition and image-processing fields. It cannot capture the higher-order statistical property of natural images, so its detection performance is not satisfying. PCA has been extended into kernel PCA in order to capture the higher-order statistics. However, thus far there have been no researchers who have definitely proposed kernel FKT (KFKT) and researched its detection performance. For accurately detecting potential small targets from infrared images, we first extend FKT into KFKT to capture the higher-order statistical properties of images. Then a framework based on Kalman prediction and KFKT, which can automatically detect and track small targets, is developed. Results of experiments show that KFKT outperforms FKT and the proposed framework is competent to automatically detect and track infrared point targets.

Automatically detect and track infrared small targets with kernel Fukunaga-Koontz transform and Kalman prediction

NASA Astrophysics Data System (ADS)

Liu, Ruiming; Liu, Erqi; Yang, Jie; Zeng, Yong; Wang, Fanglin; Cao, Yuan

2007-11-01

Fukunaga-Koontz transform (FKT), stemming from principal component analysis (PCA), is used in many pattern recognition and image-processing fields. It cannot capture the higher-order statistical property of natural images, so its detection performance is not satisfying. PCA has been extended into kernel PCA in order to capture the higher-order statistics. However, thus far there have been no researchers who have definitely proposed kernel FKT (KFKT) and researched its detection performance. For accurately detecting potential small targets from infrared images, we first extend FKT into KFKT to capture the higher-order statistical properties of images. Then a framework based on Kalman prediction and KFKT, which can automatically detect and track small targets, is developed. Results of experiments show that KFKT outperforms FKT and the proposed framework is competent to automatically detect and track infrared point targets.

A theoretical and matrix-isolation FT-IR investigation of the conformational landscape of N-acetylcysteine

NASA Astrophysics Data System (ADS)

Boeckx, Bram; Ramaekers, Riet; Maes, Guido

2010-06-01

The conformational landscape of N-acetylcysteine (NAC) has been investigated by a combined experimental matrix-isolation FT-IR and theoretical methodology. This combination is a powerful tool to study the conformational behavior of relatively small molecules. Geometry optimizations at the HF/3-21 level resulted in 438 different geometries with an energy difference smaller than 22 kJ mol -1. Among these, six conformations were detected with a relative energy difference smaller than 10 kJ mol -1 at the DFT(B3LYP)/6-31++G∗∗ level of theory. These were finally subjected to MP2/6-31++G∗∗ optimizations which resulted in five minima. The vibrational and thermodynamical properties of these conformations were calculated at both the DFT and MP2 methodologies. Experimentally NAC was isolated in an argon matrix at 16 K after being sublimated at 323 K. The most stable MP2 form appeared to be dominant in the experimental spectra but the presence of three other conformations with Δ EMP2 < 10 kJ mol -1 was also demonstrated. The experimentally observed abundance of the H-bond containing conformations appeared to be in good accordance with the predicted MP2 value.

Solvent-induced conformational flexibility of a bicyclic proline analogue: Octahydroindole-2-carboxylic acid.

PubMed

Torras, Juan; Warren, Javier G; Revilla-López, Guillem; Jiménez, Ana I; Cativiela, Carlos; Alemán, Carlos

2014-03-01

The conformational preferences of the N-acetyl-N'-methylamide derivatives of the four octahydroindole-2-carboxylic acid (Oic) stereoisomers have been investigated in the gas-phase and in aqueous solution using quantum mechanical calculations. In addition to the conformational effects provoked by the stereochemical diversity of Oic, which presents three chiral centers, results provide evidence of interesting and rather unusual features. The conformational preferences of the Oic stereoisomers in solution are only well described by applying a complete and systematic search process, results achieved by simple re-optimization of the gas-phase minima being very imprecise. This is because the conformational rigidity detected in the gas-phase, which is imposed by the chemical restrictions of the fused bicyclic skeleton, disappears in aqueous solution, the four stereoisomers behaving as flexible molecules in this environment. Thus, in general, the γ-turn is the only minimum energy conformation in the gas-phase while in aqueous solution the helical, polyproline-II and γ-turn motifs are energetically favored. Molecular dynamics simulations indicate that the conformational flexibility predicted by quantum mechanical calculations for the four Oic stereoisomers in solution is satisfactorily reproduced by classical force-fields. Copyright © 2014 Wiley Periodicals, Inc.

Hydration and conformational equilibria of simple hydrophobic and amphiphilic solutes.

PubMed Central

Ashbaugh, H S; Kaler, E W; Paulaitis, M E

1998-01-01

We consider whether the continuum model of hydration optimized to reproduce vacuum-to-water transfer free energies simultaneously describes the hydration free energy contributions to conformational equilibria of the same solutes in water. To this end, transfer and conformational free energies of idealized hydrophobic and amphiphilic solutes in water are calculated from explicit water simulations and compared to continuum model predictions. As benchmark hydrophobic solutes, we examine the hydration of linear alkanes from methane through hexane. Amphiphilic solutes were created by adding a charge of +/-1e to a terminal methyl group of butane. We find that phenomenological continuum parameters fit to transfer free energies are significantly different from those fit to conformational free energies of our model solutes. This difference is attributed to continuum model parameters that depend on solute conformation in water, and leads to effective values for the free energy/surface area coefficient and Born radii that best describe conformational equilibrium. In light of these results, we believe that continuum models of hydration optimized to fit transfer free energies do not accurately capture the balance between hydrophobic and electrostatic contributions that determines the solute conformational state in aqueous solution. PMID:9675177

Updating fire safety standards. Final rule; affirmation.

PubMed

2011-11-16

This document affirms as final, without changes, a provision included in a final rule with request for comments that amended the Department of Veterans Affairs (VA) regulations concerning community residential care facilities, contract facilities for certain outpatient and residential services, and State home facilities. That provision established a five-year period within which all covered buildings with nursing home facilities existing as of June 25, 2001, must conform to the automatic sprinkler requirement of the 2009 edition of the National Fire Protection Association (NFPA) 101. This rule helps ensure the safety of veterans in the affected facilities.

A Not-So-Fundamental Limitation on Studying Complex Systems with Statistics: Comment on Rabin (2011)

NASA Astrophysics Data System (ADS)

Thomas, Drew M.

2012-12-01

Although living organisms are affected by many interrelated and unidentified variables, this complexity does not automatically impose a fundamental limitation on statistical inference. Nor need one invoke such complexity as an explanation of the "Truth Wears Off" or "decline" effect; similar "decline" effects occur with far simpler systems studied in physics. Selective reporting and publication bias, and scientists' biases in favor of reporting eye-catching results (in general) or conforming to others' results (in physics) better explain this feature of the "Truth Wears Off" effect than Rabin's suggested limitation on statistical inference.

Conformational Dynamics of Mechanically Compliant DNA Nanostructures from Coarse-Grained Molecular Dynamics Simulations.

PubMed

Shi, Ze; Castro, Carlos E; Arya, Gaurav

2017-05-23

Structural DNA nanotechnology, the assembly of rigid 3D structures of complex yet precise geometries, has recently been used to design dynamic, mechanically compliant nanostructures with tunable equilibrium conformations and conformational distributions. Here we use coarse-grained molecular dynamics simulations to provide insights into the conformational dynamics of a set of mechanically compliant DNA nanostructures-DNA hinges that use single-stranded DNA "springs" to tune the equilibrium conformation of a layered double-stranded DNA "joint" connecting two stiff "arms" constructed from DNA helix bundles. The simulations reproduce the experimentally measured equilibrium angles between hinge arms for a range of hinge designs. The hinges are found to be structurally stable, except for some fraying of the open ends of the DNA helices comprising the hinge arms and some loss of base-pairing interactions in the joint regions coinciding with the crossover junctions, especially in hinges designed to exhibit a small bending angle that exhibit large local stresses resulting in strong kinks in their joints. Principal component analysis reveals that while the hinge dynamics are dominated by bending motion, some twisting and sliding of hinge arms relative to each other also exists. Forced deformation of the hinges reveals distinct bending mechanisms for hinges with short, inextensible springs versus those with longer, more extensible springs. Lastly, we introduce an approach for rapidly predicting equilibrium hinge angles from individual force-deformation behaviors of its single- and double-stranded DNA components. Taken together, these results demonstrate that coarse-grained modeling is a promising approach for designing, predicting, and studying the dynamics of compliant DNA nanostructures, where conformational fluctuations become important, multiple deformation mechanisms exist, and continuum approaches may not yield accurate properties.

BWM*: A Novel, Provable, Ensemble-based Dynamic Programming Algorithm for Sparse Approximations of Computational Protein Design.

PubMed

Jou, Jonathan D; Jain, Swati; Georgiev, Ivelin S; Donald, Bruce R

2016-06-01

Sparse energy functions that ignore long range interactions between residue pairs are frequently used by protein design algorithms to reduce computational cost. Current dynamic programming algorithms that fully exploit the optimal substructure produced by these energy functions only compute the GMEC. This disproportionately favors the sequence of a single, static conformation and overlooks better binding sequences with multiple low-energy conformations. Provable, ensemble-based algorithms such as A* avoid this problem, but A* cannot guarantee better performance than exhaustive enumeration. We propose a novel, provable, dynamic programming algorithm called Branch-Width Minimization* (BWM*) to enumerate a gap-free ensemble of conformations in order of increasing energy. Given a branch-decomposition of branch-width w for an n-residue protein design with at most q discrete side-chain conformations per residue, BWM* returns the sparse GMEC in O([Formula: see text]) time and enumerates each additional conformation in merely O([Formula: see text]) time. We define a new measure, Total Effective Search Space (TESS), which can be computed efficiently a priori before BWM* or A* is run. We ran BWM* on 67 protein design problems and found that TESS discriminated between BWM*-efficient and A*-efficient cases with 100% accuracy. As predicted by TESS and validated experimentally, BWM* outperforms A* in 73% of the cases and computes the full ensemble or a close approximation faster than A*, enumerating each additional conformation in milliseconds. Unlike A*, the performance of BWM* can be predicted in polynomial time before running the algorithm, which gives protein designers the power to choose the most efficient algorithm for their particular design problem.

A Unified Conformational Selection and Induced Fit Approach to Protein-Peptide Docking

PubMed Central

Trellet, Mikael; Melquiond, Adrien S. J.; Bonvin, Alexandre M. J. J.

2013-01-01

Protein-peptide interactions are vital for the cell. They mediate, inhibit or serve as structural components in nearly 40% of all macromolecular interactions, and are often associated with diseases, making them interesting leads for protein drug design. In recent years, large-scale technologies have enabled exhaustive studies on the peptide recognition preferences for a number of peptide-binding domain families. Yet, the paucity of data regarding their molecular binding mechanisms together with their inherent flexibility makes the structural prediction of protein-peptide interactions very challenging. This leaves flexible docking as one of the few amenable computational techniques to model these complexes. We present here an ensemble, flexible protein-peptide docking protocol that combines conformational selection and induced fit mechanisms. Starting from an ensemble of three peptide conformations (extended, a-helix, polyproline-II), flexible docking with HADDOCK generates 79.4% of high quality models for bound/unbound and 69.4% for unbound/unbound docking when tested against the largest protein-peptide complexes benchmark dataset available to date. Conformational selection at the rigid-body docking stage successfully recovers the most relevant conformation for a given protein-peptide complex and the subsequent flexible refinement further improves the interface by up to 4.5 Å interface RMSD. Cluster-based scoring of the models results in a selection of near-native solutions in the top three for ∼75% of the successfully predicted cases. This unified conformational selection and induced fit approach to protein-peptide docking should open the route to the modeling of challenging systems such as disorder-order transitions taking place upon binding, significantly expanding the applicability limit of biomolecular interaction modeling by docking. PMID:23516555

A unified conformational selection and induced fit approach to protein-peptide docking.

PubMed

Trellet, Mikael; Melquiond, Adrien S J; Bonvin, Alexandre M J J

2013-01-01

Protein-peptide interactions are vital for the cell. They mediate, inhibit or serve as structural components in nearly 40% of all macromolecular interactions, and are often associated with diseases, making them interesting leads for protein drug design. In recent years, large-scale technologies have enabled exhaustive studies on the peptide recognition preferences for a number of peptide-binding domain families. Yet, the paucity of data regarding their molecular binding mechanisms together with their inherent flexibility makes the structural prediction of protein-peptide interactions very challenging. This leaves flexible docking as one of the few amenable computational techniques to model these complexes. We present here an ensemble, flexible protein-peptide docking protocol that combines conformational selection and induced fit mechanisms. Starting from an ensemble of three peptide conformations (extended, a-helix, polyproline-II), flexible docking with HADDOCK generates 79.4% of high quality models for bound/unbound and 69.4% for unbound/unbound docking when tested against the largest protein-peptide complexes benchmark dataset available to date. Conformational selection at the rigid-body docking stage successfully recovers the most relevant conformation for a given protein-peptide complex and the subsequent flexible refinement further improves the interface by up to 4.5 Å interface RMSD. Cluster-based scoring of the models results in a selection of near-native solutions in the top three for ∼75% of the successfully predicted cases. This unified conformational selection and induced fit approach to protein-peptide docking should open the route to the modeling of challenging systems such as disorder-order transitions taking place upon binding, significantly expanding the applicability limit of biomolecular interaction modeling by docking.

Analysis of vibrational spectra of 3-halo-1-propanols CH(2)XCH(2)CH(2)OH (X is Cl and Br).

PubMed

Badawi, Hassan M; Förner, Wolfgang

2008-12-01

The conformational stability and the three rotor internal rotations in 3-chloro- and 3-bromo-1-propanols were investigated by DFT-B3LYP/6-311+G and ab initio MP2/6-311+G, MP3/6-311+G and MP4(SDTQ)//MP3/6-311+G levels of theory. On the calculated potential energy surface twelve distinct minima were located all of which were not predicted to have imaginary frequencies at the B3LYP level of theory. The calculated lowest energy minimum in the potential curves of both molecules was predicted to correspond to the Gauche-gauche-trans (Ggt) conformer in excellent agreement with earlier microwave and electron diffraction results. The equilibrium constants for the conformational interconversion of the two 3-halo-1-propanols were calculated at the B3LYP/6-311+G level of calculation and found to correspond to an equilibrium mixture of about 32% Ggt, 18% Ggg1, 13% Tgt, 8% Tgg and 8% Gtt conformations for 3-chloro-1-propanol and 34% Ggt, 15% Tgt, 13% Ggg1, 9% Tgg and 7% Gtt conformations for 3-bromo-1-propanol at 298.15K. The nature of the high energy conformations was verified by carrying out solvent experiments using formamide ( epsilon=109.5) and MP3 and MP4//MP3 calculations. The vibrational frequencies of each molecule in its three most stable forms were computed at the B3LYP level and complete vibrational assignments were made based on normal coordinate calculations and comparison with experimental data of the molecules.

SU-F-T-450: The Investigation of Radiotherapy Quality Assurance and Automatic Treatment Planning Based On the Kernel Density Estimation Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fan, J; Fan, J; Hu, W

Purpose: To develop a fast automatic algorithm based on the two dimensional kernel density estimation (2D KDE) to predict the dose-volume histogram (DVH) which can be employed for the investigation of radiotherapy quality assurance and automatic treatment planning. Methods: We propose a machine learning method that uses previous treatment plans to predict the DVH. The key to the approach is the framing of DVH in a probabilistic setting. The training consists of estimating, from the patients in the training set, the joint probability distribution of the dose and the predictive features. The joint distribution provides an estimation of the conditionalmore » probability of the dose given the values of the predictive features. For the new patient, the prediction consists of estimating the distribution of the predictive features and marginalizing the conditional probability from the training over this. Integrating the resulting probability distribution for the dose yields an estimation of the DVH. The 2D KDE is implemented to predict the joint probability distribution of the training set and the distribution of the predictive features for the new patient. Two variables, including the signed minimal distance from each OAR (organs at risk) voxel to the target boundary and its opening angle with respect to the origin of voxel coordinate, are considered as the predictive features to represent the OAR-target spatial relationship. The feasibility of our method has been demonstrated with the rectum, breast and head-and-neck cancer cases by comparing the predicted DVHs with the planned ones. Results: The consistent result has been found between these two DVHs for each cancer and the average of relative point-wise differences is about 5% within the clinical acceptable extent. Conclusion: According to the result of this study, our method can be used to predict the clinical acceptable DVH and has ability to evaluate the quality and consistency of the treatment planning.« less

From Ramachandran Maps to Tertiary Structures of Proteins.

PubMed

DasGupta, Debarati; Kaushik, Rahul; Jayaram, B

2015-08-27

Sequence to structure of proteins is an unsolved problem. A possible coarse grained resolution to this entails specification of all the torsional (Φ, Ψ) angles along the backbone of the polypeptide chain. The Ramachandran map quite elegantly depicts the allowed conformational (Φ, Ψ) space of proteins which is still very large for the purposes of accurate structure generation. We have divided the allowed (Φ, Ψ) space in Ramachandran maps into 27 distinct conformations sufficient to regenerate a structure to within 5 Å from the native, at least for small proteins, thus reducing the structure prediction problem to a specification of an alphanumeric string, i.e., the amino acid sequence together with one of the 27 conformations preferred by each amino acid residue. This still theoretically results in 27(n) conformations for a protein comprising "n" amino acids. We then investigated the spatial correlations at the two-residue (dipeptide) and three-residue (tripeptide) levels in what may be described as higher order Ramachandran maps, with the premise that the allowed conformational space starts to shrink as we introduce neighborhood effects. We found, for instance, for a tripeptide which potentially can exist in any of the 27(3) "allowed" conformations, three-fourths of these conformations are redundant to the 95% confidence level, suggesting sequence context dependent preferred conformations. We then created a look-up table of preferred conformations at the tripeptide level and correlated them with energetically favorable conformations. We found in particular that Boltzmann probabilities calculated from van der Waals energies for each conformation of tripeptides correlate well with the observed populations in the structural database (the average correlation coefficient is ∼0.8). An alpha-numeric string and hence the tertiary structure can be generated for any sequence from the look-up table within minutes on a single processor and to a higher level of accuracy if secondary structure can be specified. We tested the methodology on 100 small proteins, and in 90% of the cases, a structure within 5 Å is recovered. We thus believe that the method presented here provides the missing link between Ramachandran maps and tertiary structures of proteins. A Web server to convert a tertiary structure to an alphanumeric string and to predict the tertiary structure from the sequence of a protein using the above methodology is created and made freely accessible at http://www.scfbio-iitd.res.in/software/proteomics/rm2ts.jsp.

Modeling and docking antibody structures with Rosetta

PubMed Central

Weitzner, Brian D.; Jeliazkov, Jeliazko R.; Lyskov, Sergey; Marze, Nicholas; Kuroda, Daisuke; Frick, Rahel; Adolf-Bryfogle, Jared; Biswas, Naireeta; Dunbrack, Roland L.; Gray, Jeffrey J.

2017-01-01

We describe Rosetta-based computational protocols for predicting the three-dimensional structure of an antibody from sequence (RosettaAntibody) and then docking the antibody to protein antigens (SnugDock). Antibody modeling leverages canonical loop conformations to graft large segments from experimentally-determined structures as well as (1) energetic calculations to minimize loops, (2) docking methodology to refine the VL–VH relative orientation, and (3) de novo prediction of the elusive complementarity determining region (CDR) H3 loop. To alleviate model uncertainty, antibody–antigen docking resamples CDR loop conformations and can use multiple models to represent an ensemble of conformations for the antibody, the antigen or both. These protocols can be run fully-automated via the ROSIE web server (http://rosie.rosettacommons.org/) or manually on a computer with user control of individual steps. For best results, the protocol requires roughly 1,000 CPU-hours for antibody modeling and 250 CPU-hours for antibody–antigen docking. Tasks can be completed in under a day by using public supercomputers. PMID:28125104

Chain conformations and phase behavior of conjugated polymers.

PubMed

Kuei, Brooke; Gomez, Enrique D

2016-12-21

Conjugated polymers may play an important role in various emerging optoelectronic applications because they combine the chemical versatility of organic molecules and the flexibility, stretchability and toughness of polymers with semiconducting properties. Nevertheless, in order to achieve the full potential of conjugated polymers, a clear description of how their structure, morphology, and macroscopic properties are interrelated is needed. We propose that the starting point for understanding conjugated polymers includes understanding chain conformations and phase behavior. Efforts to predict and measure the persistence length have significantly refined our intuition of the chain stiffness, and have led to predictions of nematic-to-isotropic transitions. Exploring mixing between conjugated polymers and small molecules or other polymers has demonstrated tremendous advancements in attaining the needed properties for various optoelectronic devices. Current efforts continue to refine our knowledge of chain conformations and phase behavior and the factors that influence these properties, thereby providing opportunities for the development of novel optoelectronic materials based on conjugated polymers.

On vibrational circular dichroism chirality transfer in electron donor-acceptor complexes: a prediction for the quinine···BF3 system.

PubMed

Rode, Joanna E; Jamróz, Michał H; Dobrowolski, Jan Cz; Sadlej, Joanna

2012-08-02

Vibrational circular dichroism (VCD) chirality transfer occurs when an achiral molecule interacts with a chiral one and becomes VCD-active. Unlike for H-bonds, for organic electron donor-acceptor (EDA) complexes this phenomenon remains almost unknown. Here, the VCD chirality transfer from chiral quinine to achiral BF3 is studied at the B3LYP/aug-cc-pVDZ level. Accessibility of four quinine electron donor sites changes with conformation. Therefore, the quinine conformational landscape was explored and a considerable agreement between X-ray and the most stable conformer geometries was achieved. The BF3 complex through the aliphatic quinuclidine N atom is definitely dominating and is predicted to be easily recognizable in the VCD spectrum. Out of several VCD chirality transfer modes, the ν(s)(BF3) mode, the most intense in the entire VCD spectrum, satisfies the VCD mode robustness criterion and can be used for monitoring the chirality transfer phenomenon in quinine···BF3 system.

Docking and scoring with ICM: the benchmarking results and strategies for improvement

PubMed Central

Neves, Marco A. C.; Totrov, Maxim; Abagyan, Ruben

2012-01-01

Flexible docking and scoring using the Internal Coordinate Mechanics software (ICM) was benchmarked for ligand binding mode prediction against the 85 co-crystal structures in the modified Astex data set. The ICM virtual ligand screening was tested against the 40 DUD target benchmarks and 11-target WOMBAT sets. The self-docking accuracy was evaluated for the top 1 and top 3 scoring poses at each ligand binding site with near native conformations below 2 Å RMSD found in 91% and 95% of the predictions, respectively. The virtual ligand screening using single rigid pocket conformations provided the median area under the ROC curves equal to 69.4 with 22.0% true positives recovered at 2% false positive rate. Significant improvements up to ROC AUC= 82.2 and ROC(2%)= 45.2 were achieved following our best practices for flexible pocket refinement and out-of-pocket binding rescore. The virtual screening can be further improved by considering multiple conformations of the target. PMID:22569591

Generative Topographic Mapping of Conformational Space.

PubMed

Horvath, Dragos; Baskin, Igor; Marcou, Gilles; Varnek, Alexandre

2017-10-01

Herein, Generative Topographic Mapping (GTM) was challenged to produce planar projections of the high-dimensional conformational space of complex molecules (the 1LE1 peptide). GTM is a probability-based mapping strategy, and its capacity to support property prediction models serves to objectively assess map quality (in terms of regression statistics). The properties to predict were total, non-bonded and contact energies, surface area and fingerprint darkness. Map building and selection was controlled by a previously introduced evolutionary strategy allowed to choose the best-suited conformational descriptors, options including classical terms and novel atom-centric autocorrellograms. The latter condensate interatomic distance patterns into descriptors of rather low dimensionality, yet precise enough to differentiate between close favorable contacts and atom clashes. A subset of 20 K conformers of the 1LE1 peptide, randomly selected from a pool of 2 M geometries (generated by the S4MPLE tool) was employed for map building and cross-validation of property regression models. The GTM build-up challenge reached robust three-fold cross-validated determination coefficients of Q 2 =0.7…0.8, for all modeled properties. Mapping of the full 2 M conformer set produced intuitive and information-rich property landscapes. Functional and folding subspaces appear as well-separated zones, even though RMSD with respect to the PDB structure was never used as a selection criterion of the maps. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Predictors of Individual Tumor Local Control After Stereotactic Radiosurgery for Non-Small Cell Lung Cancer Brain Metastases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garsa, Adam A.; Badiyan, Shahed N.; DeWees, Todd

2014-10-01

Purpose: To evaluate local control rates and predictors of individual tumor local control for brain metastases from non-small cell lung cancer (NSCLC) treated with stereotactic radiosurgery (SRS). Methods and Materials: Between June 1998 and May 2011, 401 brain metastases in 228 patients were treated with Gamma Knife single-fraction SRS. Local failure was defined as an increase in lesion size after SRS. Local control was estimated using the Kaplan-Meier method. The Cox proportional hazards model was used for univariate and multivariate analysis. Receiver operating characteristic analysis was used to identify an optimal cutpoint for conformality index relative to local control. Amore » P value <.05 was considered statistically significant. Results: Median age was 60 years (range, 27-84 years). There were 66 cerebellar metastases (16%) and 335 supratentorial metastases (84%). The median prescription dose was 20 Gy (range, 14-24 Gy). Median overall survival from time of SRS was 12.1 months. The estimated local control at 12 months was 74%. On multivariate analysis, cerebellar location (hazard ratio [HR] 1.94, P=.009), larger tumor volume (HR 1.09, P<.001), and lower conformality (HR 0.700, P=.044) were significant independent predictors of local failure. Conformality index cutpoints of 1.4-1.9 were predictive of local control, whereas a cutpoint of 1.75 was the most predictive (P=.001). The adjusted Kaplan-Meier 1-year local control for conformality index ≥1.75 was 84% versus 69% for conformality index <1.75, controlling for tumor volume and location. The 1-year adjusted local control for cerebellar lesions was 60%, compared with 77% for supratentorial lesions, controlling for tumor volume and conformality index. Conclusions: Cerebellar tumor location, lower conformality index, and larger tumor volume were significant independent predictors of local failure after SRS for brain metastases from NSCLC. These results warrant further investigation in a prospective setting.« less

Nucleotide-induced conformational dynamics in ABC transporters from structure-based coarse grained modelling.

NASA Astrophysics Data System (ADS)

Flechsig, Holger

2016-02-01

ATP-binding cassette (ABC) transporters are integral membrane proteins which mediate the exchange of diverse substrates across membranes powered by ATP molecules. Our understanding of their activity is still hampered since the conformational dynamics underlying the operation of such proteins cannot yet be resolved in detailed molecular dynamics studies. Here a coarse grained model which allows to mimic binding of nucleotides and follow subsequent conformational motions of full-length transporter structures in computer simulations is proposed and implemented. To justify its explanatory quality, the model is first applied to the maltose transporter system for which multiple conformations are known and we find that the model predictions agree remarkably well with the experimental data. For the MalK subunit the switching from open to the closed dimer configuration upon ATP binding is reproduced and, moreover, for the full-length maltose transporter, progression from inward-facing to the outward-facing state is correctly obtained. For the heme transporter HmuUV, for which only the free structure could yet be determined, the model was then applied to predict nucleotide-induced conformational motions. Upon binding of ATP-mimicking ligands the structure changed from a conformation in which the nucleotide-binding domains formed an open shape, to a conformation in which they were found in tight contact, while, at the same time, a pronounced rotation of the transmembrane domains was observed. This finding is supported by normal mode analysis, and, comparison with structural data of the homologous vitamin B12 transporter BtuCD suggests that the observed rotation mechanism may contribute a common functional aspect for this class of ABC transporters. Although in HmuuV noticeable rearrangement of essential transmembrane helices was detected, there are no indications from our simulations that ATP binding alone may facilitate propagation of substrate molecules in this transporter. Possible explanations are discussed in the light of currently debated transport scenarios of ABC transporters.

The Role of Flexibility and Conformational Selection in the Binding Promiscuity of PDZ Domains

PubMed Central

Münz, Márton; Hein, Jotun; Biggin, Philip C.

2012-01-01

In molecular recognition, it is often the case that ligand binding is coupled to conformational change in one or both of the binding partners. Two hypotheses describe the limiting cases involved; the first is the induced fit and the second is the conformational selection model. The conformational selection model requires that the protein adopts conformations that are similar to the ligand-bound conformation in the absence of ligand, whilst the induced-fit model predicts that the ligand-bound conformation of the protein is only accessible when the ligand is actually bound. The flexibility of the apo protein clearly plays a major role in these interpretations. For many proteins involved in signaling pathways there is the added complication that they are often promiscuous in that they are capable of binding to different ligand partners. The relationship between protein flexibility and promiscuity is an area of active research and is perhaps best exemplified by the PDZ domain family of proteins. In this study we use molecular dynamics simulations to examine the relationship between flexibility and promiscuity in five PDZ domains: the human Dvl2 (Dishevelled-2) PDZ domain, the human Erbin PDZ domain, the PDZ1 domain of InaD (inactivation no after-potential D protein) from fruit fly, the PDZ7 domain of GRIP1 (glutamate receptor interacting protein 1) from rat and the PDZ2 domain of PTP-BL (protein tyrosine phosphatase) from mouse. We show that despite their high structural similarity, the PDZ binding sites have significantly different dynamics. Importantly, the degree of binding pocket flexibility was found to be closely related to the various characteristics of peptide binding specificity and promiscuity of the five PDZ domains. Our findings suggest that the intrinsic motions of the apo structures play a key role in distinguishing functional properties of different PDZ domains and allow us to make predictions that can be experimentally tested. PMID:23133356

Equilibrium and Dynamics Properties of Poly(oxyethylene) Melts and Related Poly(alkylethers) from Simulations and Ab Initio Calculations

NASA Technical Reports Server (NTRS)

Smith, Grant D.; Jaffe, R. L.; Yoon, D. Y.; Arnold, James O. (Technical Monitor)

1994-01-01

Molecular dynamics simulations of POE melts have been performed utilizing a potential force field parameterized to reproduce conformer energies and rotational energy barriers in dimethoxyethane as determined from ab initio electronic structure calculations. Chain conformations and dimensions of POE from the simulations were found to be in good agreement with predictions of a rotational isomeric state (RIS) model based upon the ab initio conformational. energies. The melt chains were found to be somewhat extended relative to chains at theta conditions. This effect will be discussed in light of neutron scattering experiments which indicate that POE chains are extended in the melt relative to theta solutions. The conformational characteristics of POE chains will also be compared with those of other poly (alkylethers), namely poly(oxymethylene), poly(oxytrimethylene) and poly(oxytetramethylene). Local conformational dynamics were found to be more rapid than in polymethylene. Calculated C-H vector correlation times were found to be in reasonable agreement with experimental values from C-13 NMR spin-lattice relaxation times. The influence of ionic salts on local conformations and dynamics will also be discussed.

Relative electronic and free energies of octane's unique conformations

NASA Astrophysics Data System (ADS)

Kirschner, Karl N.; Heiden, Wolfgang; Reith, Dirk

2017-06-01

This study reports the geometries and electronic energies of n-octane's unique conformations using perturbation methods that best mimic CCSD(T) results. In total, the fully optimised minima of n-butane (2 conformations), n-pentane (4 conformations), n-hexane (12 conformations) and n-octane (96 conformations) were investigated at several different theory levels and basis sets. We find that DF-MP2.5/aug-cc-pVTZ is in very good agreement with the more expensive CCSD(T) results. At this level, we can clearly confirm the 96 stable minima which were previously found using a reparameterised density functional theory (DFT). Excellent agreement was found between their DFT results and our DF-MP2.5 perturbation results. Subsequent Gibbs free energy calculations, using scaled MP2/aug-cc-pVTZ zero-point vibrational energy and frequencies, indicate a significant temperature dependency of the relative energies, with a change in the predicted global minimum. The results of this work will be important for future computational investigations of fuel-related octane reactions and for optimisation of molecular force fields (e.g. lipids).

Spectra and structure of silicon containing compounds. XXXII. Raman and infrared spectra, conformational stability, vibrational assignment and ab initio calculations of n-propylsilane-d0 and Si-d3.

PubMed

Durig, James R; Pan, Chunhua; Guirgis, Gamil A

2003-03-15

The infrared (3100-40 cm(-1)) and Raman (3100-20 cm(-1)) spectra of gaseous and solid n-propylsilane, CH(3)CH(2)CH(2)SiH(3) and the Si-d(3) isotopomer, CH(3)CH(2)CH(2)SiD(3), have been recorded. Additionally, the Raman spectra of the liquids have been recorded and qualitative depolarization values obtained. Both the anti and gauche conformers have been identified in the fluid phases but only the anti conformer remains in the solid. Variable temperature (-105 to -150 degrees C) studies of the infrared spectra of n-propylsilane dissolved in liquid krypton have been recorded and the enthalpy difference has been determined to be 220+/-22 cm(-1) (2.63+/-0.26 kJ mol(-1)) with the anti conformer the more stable form. A similar value of 234+/-23 cm(-1) (2.80+/-0.28 kJ mol(-1)) was obtained for deltaH for the Si-d(3) isotopomer. At ambient temperature it is estimated that there is 30+/-2% of the gauche conformer present. The potential function governing the conformation interchange has been estimated from the far infrared spectral data, the enthalpy difference, and the dihedral angle of the gauche conformer, which is compared to the one predicted from ab initio MP2/6-31G(d) calculations. The barriers to conformational interchange are: 942, 970 and 716 cm(-1) for the anti to gauche, gauche to gauche, and gauche to anti conformers, respectively. Relatively complete vibrational assignments are proposed for both the n-propylsilane-d(0) and Si-d(3) molecules based on the relative infrared and Raman spectral intensities, infrared band contours, depolarization ratios, and normal coordinate calculations. The geometrical parameters, harmonic force constants, vibrational frequencies, infrared intensities, Raman activities and depolarization ratios, and energy differences have been obtained for the anti and gauche conformers from ab initio MP2/6-31G(d) calculations. Structural parameters and energy differences have also been obtained utilizing the larger 6-311 + G(d,p) and 6-311 + G(2d,2p) basis sets. From the isolated Si-H stretching frequency from the Si-d(2) isotopomer the r(0) distances of 1.484 and 1.485 A have been determined for the SiH(s) and SiH(a) bonds, respectively, for the anti conformer, and 1.486 A for the SiH bond for the gauche conformer. Utilizing previously reported microwave rotational constants for the anti conformer and the determined SiH distances along with ab initio predicted parameters 'adjusted r(0)' parameters have been obtained for the anti conformer. The results are discussed and compared to those obtained for some similar molecules. Copyright 2002 Elsevier Science B.V.

Spectra and structure of silicon containing compounds. XXXII. Raman and infrared spectra, conformational stability, vibrational assignment and ab initio calculations of n-propylsilane-d 0 and Si-d 3

NASA Astrophysics Data System (ADS)

Durig, James R.; Pan, Chunhua; Guirgis, Gamil A.

2003-03-01

The infrared (3100-40 cm -1) and Raman (3100-20 cm -1) spectra of gaseous and solid n-propylsilane, CH 3CH 2CH 2SiH 3 and the Si-d 3 isotopomer, CH 3CH 2CH 2SiD 3, have been recorded. Additionally, the Raman spectra of the liquids have been recorded and qualitative depolarization values obtained. Both the anti and gauche conformers have been identified in the fluid phases but only the anti conformer remains in the solid. Variable temperature (-105 to -150 °C) studies of the infrared spectra of n-propylsilane dissolved in liquid krypton have been recorded and the enthalpy difference has been determined to be 220±22 cm -1 (2.63±0.26 kJ mol -1) with the anti conformer the more stable form. A similar value of 234±23 cm -1 (2.80±0.28 kJ mol -1) was obtained for Δ H for the Si-d 3 isotopomer. At ambient temperature it is estimated that there is 30±2% of the gauche conformer present. The potential function governing the conformation interchange has been estimated from the far infrared spectral data, the enthalpy difference, and the dihedral angle of the gauche conformer, which is compared to the one predicted from ab initio MP2/6-31G(d) calculations. The barriers to conformational interchange are: 942, 970 and 716 cm -1 for the anti to gauche, gauche to gauche, and gauche to anti conformers, respectively. Relatively complete vibrational assignments are proposed for both the n-propylsilane-d 0 and Si-d 3 molecules based on the relative infrared and Raman spectral intensities, infrared band contours, depolarization ratios, and normal coordinate calculations. The geometrical parameters, harmonic force constants, vibrational frequencies, infrared intensities, Raman activities and depolarization ratios, and energy differences have been obtained for the anti and gauche conformers from ab initio MP2/6-31G(d) calculations. Structural parameters and energy differences have also been obtained utilizing the larger 6-311+G(d,p) and 6-311+G(2d,2p) basis sets. From the isolated SiH stretching frequency from the Si-d 2 isotopomer the r0 distances of 1.484 and 1.485 Å have been determined for the SiH s and SiH a bonds, respectively, for the anti conformer, and 1.486 Å for the SiH bond for the gauche conformer. Utilizing previously reported microwave rotational constants for the anti conformer and the determined SiH distances along with ab initio predicted parameters 'adjusted r0' parameters have been obtained for the anti conformer. The results are discussed and compared to those obtained for some similar molecules.

The effect of word prediction settings (frequency of use) on text input speed in persons with cervical spinal cord injury: a prospective study.

PubMed

Pouplin, Samuel; Roche, Nicolas; Antoine, Jean-Yves; Vaugier, Isabelle; Pottier, Sandra; Figere, Marjorie; Bensmail, Djamel

2017-06-01

To determine whether activation of the frequency of use and automatic learning parameters of word prediction software has an impact on text input speed. Forty-five participants with cervical spinal cord injury between C4 and C8 Asia A or B accepted to participate to this study. Participants were separated in two groups: a high lesion group for participants with lesion level is at or above C5 Asia AIS A or B and a low lesion group for participants with lesion is between C6 and C8 Asia AIS A or B. A single evaluation session was carried out for each participant. Text input speed was evaluated during three copying tasks: • without word prediction software (WITHOUT condition) • with automatic learning of words and frequency of use deactivated (NOT_ACTIV condition) • with automatic learning of words and frequency of use activated (ACTIV condition) Results: Text input speed was significantly higher in the WITHOUT than the NOT_ACTIV (p< 0.001) or ACTIV conditions (p = 0.02) for participants with low lesions. Text input speed was significantly higher in the ACTIV than in the NOT_ACTIV (p = 0.002) or WITHOUT (p < 0.001) conditions for participants with high lesions. Use of word prediction software with the activation of frequency of use and automatic learning increased text input speed in participants with high-level tetraplegia. For participants with low-level tetraplegia, the use of word prediction software with frequency of use and automatic learning activated only decreased the number of errors. Implications in rehabilitation   Access to technology can be difficult for persons with disabilities such as cervical spinal cord injury (SCI). Several methods have been developed to increase text input speed such as word prediction software.This study show that parameter of word prediction software (frequency of use) affected text input speed in persons with cervical SCI and differed according to the level of the lesion. • For persons with high-level lesion, our results suggest that this parameter must be activated so that text input speed is increased. • For persons with low lesion group, this parameter must be activated so that the numbers of errors are decreased. • In all cases, the activation of the parameter of frequency of use is essential in order to improve the efficiency of the word prediction software. • Health-related professionals should use these results in their clinical practice for better results and therefore better patients 'satisfaction.

A method for probing the mutational landscape of amyloid structure.

PubMed

O'Donnell, Charles W; Waldispühl, Jérôme; Lis, Mieszko; Halfmann, Randal; Devadas, Srinivas; Lindquist, Susan; Berger, Bonnie

2011-07-01

Proteins of all kinds can self-assemble into highly ordered β-sheet aggregates known as amyloid fibrils, important both biologically and clinically. However, the specific molecular structure of a fibril can vary dramatically depending on sequence and environmental conditions, and mutations can drastically alter amyloid function and pathogenicity. Experimental structure determination has proven extremely difficult with only a handful of NMR-based models proposed, suggesting a need for computational methods. We present AmyloidMutants, a statistical mechanics approach for de novo prediction and analysis of wild-type and mutant amyloid structures. Based on the premise of protein mutational landscapes, AmyloidMutants energetically quantifies the effects of sequence mutation on fibril conformation and stability. Tested on non-mutant, full-length amyloid structures with known chemical shift data, AmyloidMutants offers roughly 2-fold improvement in prediction accuracy over existing tools. Moreover, AmyloidMutants is the only method to predict complete super-secondary structures, enabling accurate discrimination of topologically dissimilar amyloid conformations that correspond to the same sequence locations. Applied to mutant prediction, AmyloidMutants identifies a global conformational switch between Aβ and its highly-toxic 'Iowa' mutant in agreement with a recent experimental model based on partial chemical shift data. Predictions on mutant, yeast-toxic strains of HET-s suggest similar alternate folds. When applied to HET-s and a HET-s mutant with core asparagines replaced by glutamines (both highly amyloidogenic chemically similar residues abundant in many amyloids), AmyloidMutants surprisingly predicts a greatly reduced capacity of the glutamine mutant to form amyloid. We confirm this finding by conducting mutagenesis experiments. Our tool is publically available on the web at http://amyloid.csail.mit.edu/. lindquist_admin@wi.mit.edu; bab@csail.mit.edu.

Protein secondary structure and stability determined by combining exoproteolysis and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.

PubMed

Villanueva, Josep; Villegas, Virtudes; Querol, Enrique; Avilés, Francesc X; Serrano, Luis

2002-09-01

In the post-genomic era, several projects focused on the massive experimental resolution of the three-dimensional structures of all the proteins of different organisms have been initiated. Simultaneously, significant progress has been made in the ab initio prediction of protein three-dimensional structure. One of the keys to the success of such a prediction is the use of local information (i.e. secondary structure). Here we describe a new limited proteolysis methodology, based on the use of unspecific exoproteases coupled with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), to map quickly secondary structure elements of a protein from both ends, the N- and C-termini. We show that the proteolytic patterns (mass spectra series) obtained can be interpreted in the light of the conformation and local stability of the analyzed proteins, a direct correlation being observed between the predicted and the experimentally derived protein secondary structure. Further, this methodology can be easily applied to check rapidly the folding state of a protein and characterize mutational effects on protein conformation and stability. Moreover, given global stability information, this methodology allows one to locate the protein regions of increased or decreased conformational stability. All of this can be done with a small fraction of the amount of protein required by most of the other methods for conformational analysis. Thus limited exoproteolysis, together with MALDI-TOF MS, can be a useful tool to achieve quickly the elucidation of protein structure and stability. Copyright 2002 John Wiley & Sons, Ltd.

An Injury Severity-, Time Sensitivity-, and Predictability-Based Advanced Automatic Crash Notification Algorithm Improves Motor Vehicle Crash Occupant Triage.

PubMed

Stitzel, Joel D; Weaver, Ashley A; Talton, Jennifer W; Barnard, Ryan T; Schoell, Samantha L; Doud, Andrea N; Martin, R Shayn; Meredith, J Wayne

2016-06-01

Advanced Automatic Crash Notification algorithms use vehicle telemetry measurements to predict risk of serious motor vehicle crash injury. The objective of the study was to develop an Advanced Automatic Crash Notification algorithm to reduce response time, increase triage efficiency, and improve patient outcomes by minimizing undertriage (<5%) and overtriage (<50%), as recommended by the American College of Surgeons. A list of injuries associated with a patient's need for Level I/II trauma center treatment known as the Target Injury List was determined using an approach based on 3 facets of injury: severity, time sensitivity, and predictability. Multivariable logistic regression was used to predict an occupant's risk of sustaining an injury on the Target Injury List based on crash severity and restraint factors for occupants in the National Automotive Sampling System - Crashworthiness Data System 2000-2011. The Advanced Automatic Crash Notification algorithm was optimized and evaluated to minimize triage rates, per American College of Surgeons recommendations. The following rates were achieved: <50% overtriage and <5% undertriage in side impacts and 6% to 16% undertriage in other crash modes. Nationwide implementation of our algorithm is estimated to improve triage decisions for 44% of undertriaged and 38% of overtriaged occupants. Annually, this translates to more appropriate care for >2,700 seriously injured occupants and reduces unnecessary use of trauma center resources for >162,000 minimally injured occupants. The algorithm could be incorporated into vehicles to inform emergency personnel of recommended motor vehicle crash triage decisions. Lower under- and overtriage was achieved, and nationwide implementation of the algorithm would yield improved triage decision making for an estimated 165,000 occupants annually. Copyright © 2016. Published by Elsevier Inc.

Single-Point Mutation with a Rotamer Library Toolkit: Toward Protein Engineering.

PubMed

Pottel, Joshua; Moitessier, Nicolas

2015-12-28

Protein engineers have long been hard at work to harness biocatalysts as a natural source of regio-, stereo-, and chemoselectivity in order to carry out chemistry (reactions and/or substrates) not previously achieved with these enzymes. The extreme labor demands and exponential number of mutation combinations have induced computational advances in this domain. The first step in our virtual approach is to predict the correct conformations upon mutation of residues (i.e., rebuilding side chains). For this purpose, we opted for a combination of molecular mechanics and statistical data. In this work, we have developed automated computational tools to extract protein structural information and created conformational libraries for each amino acid dependent on a variable number of parameters (e.g., resolution, flexibility, secondary structure). We have also developed the necessary tool to apply the mutation and optimize the conformation accordingly. For side-chain conformation prediction, we obtained overall average root-mean-square deviations (RMSDs) of 0.91 and 1.01 Å for the 18 flexible natural amino acids within two distinct sets of over 3000 and 1500 side-chain residues, respectively. The commonly used dihedral angle differences were also evaluated and performed worse than the state of the art. These two metrics are also compared. Furthermore, we generated a family-specific library for kinases that produced an average 2% lower RMSD upon side-chain reconstruction and a residue-specific library that yielded a 17% improvement. Ultimately, since our protein engineering outlook involves using our docking software, Fitted/Impacts, we applied our mutation protocol to a benchmarked data set for self- and cross-docking. Our side-chain reconstruction does not hinder our docking software, demonstrating differences in pose prediction accuracy of approximately 2% (RMSD cutoff metric) for a set of over 200 protein/ligand structures. Similarly, when docking to a set of over 100 kinases, side-chain reconstruction (using both general and biased conformation libraries) had minimal detriment to the docking accuracy.

Rotational Spectrum, Conformational Composition, and Quantum Chemical Calculations of Cyanomethyl Formate (HC(O)OCH2C≡N), a Compound of Potential Astrochemical Interest.

PubMed

Samdal, Svein; Møllendal, Harald; Carles, Sophie

2015-08-27

The rotational spectrum of cyanomethyl formate (HC(O)OCH2C≡N) has been recorded in the 12–123 GHz spectral range. The spectra of two conformers were assigned. The rotamer denoted I has a symmetry plane and two out-of plane hydrogen atoms belonging to the cyanomethyl (CH2CN) moiety. In the conformer called II, the cyanomethyl group is rotated 80.3° out of this plane. Conformer I has an energy that is 1.4(6) kJ/mol lower than the energy of II according to relative intensity measurements. A large number of rotational transitions have been assigned for the ground and vibrationally excited states of the two conformers and accurate spectroscopic constants have been obtained. These constants should predict frequencies of transitions outside the investigated spectral range with a very high degree of precision. It is suggested that cyanomethyl formate is a potential interstellar compound. This suggestion is based on the fact that its congener methyl formate (HC(O)OCH3) exists across a large variety of interstellar environments and the fact that cyanides are very prevalent in the Universe. The experimental work has been augmented by high-level quantum chemical calculations. The CCSD/cc-pVQZ calculations are found to predict structures of the two forms that are very close to the Born–Oppenheimer equilibrium structures. MP2/cc-pVTZ predictions of several vibration–rotation interaction constants were generally found to be rather inaccurate. A gas-phase reaction between methyl formate and the cyanomethyl radical CH2CN to produce a hydrogen atom and cyanomethyl formate was mimicked using MP2/cc-pVTZ calculations. It was found that this reaction is not favored thermodynamically. It is also conjectured that the possible formation of cyanomethyl formate might be catalyzed and take place on interstellar particles.

Validating a Coarse-Grained Potential Energy Function through Protein Loop Modelling

PubMed Central

MacDonald, James T.; Kelley, Lawrence A.; Freemont, Paul S.

2013-01-01

Coarse-grained (CG) methods for sampling protein conformational space have the potential to increase computational efficiency by reducing the degrees of freedom. The gain in computational efficiency of CG methods often comes at the expense of non-protein like local conformational features. This could cause problems when transitioning to full atom models in a hierarchical framework. Here, a CG potential energy function was validated by applying it to the problem of loop prediction. A novel method to sample the conformational space of backbone atoms was benchmarked using a standard test set consisting of 351 distinct loops. This method used a sequence-independent CG potential energy function representing the protein using -carbon positions only and sampling conformations with a Monte Carlo simulated annealing based protocol. Backbone atoms were added using a method previously described and then gradient minimised in the Rosetta force field. Despite the CG potential energy function being sequence-independent, the method performed similarly to methods that explicitly use either fragments of known protein backbones with similar sequences or residue-specific /-maps to restrict the search space. The method was also able to predict with sub-Angstrom accuracy two out of seven loops from recently solved crystal structures of proteins with low sequence and structure similarity to previously deposited structures in the PDB. The ability to sample realistic loop conformations directly from a potential energy function enables the incorporation of additional geometric restraints and the use of more advanced sampling methods in a way that is not possible to do easily with fragment replacement methods and also enable multi-scale simulations for protein design and protein structure prediction. These restraints could be derived from experimental data or could be design restraints in the case of computational protein design. C++ source code is available for download from http://www.sbg.bio.ic.ac.uk/phyre2/PD2/. PMID:23824634

Knowing what to expect, forecasting monthly emergency department visits: A time-series analysis.

PubMed

Bergs, Jochen; Heerinckx, Philipe; Verelst, Sandra

2014-04-01

To evaluate an automatic forecasting algorithm in order to predict the number of monthly emergency department (ED) visits one year ahead. We collected retrospective data of the number of monthly visiting patients for a 6-year period (2005-2011) from 4 Belgian Hospitals. We used an automated exponential smoothing approach to predict monthly visits during the year 2011 based on the first 5 years of the dataset. Several in- and post-sample forecasting accuracy measures were calculated. The automatic forecasting algorithm was able to predict monthly visits with a mean absolute percentage error ranging from 2.64% to 4.8%, indicating an accurate prediction. The mean absolute scaled error ranged from 0.53 to 0.68 indicating that, on average, the forecast was better compared with in-sample one-step forecast from the naïve method. The applied automated exponential smoothing approach provided useful predictions of the number of monthly visits a year in advance. Copyright © 2013 Elsevier Ltd. All rights reserved.

Test of a potential link between analytic and nonanalytic category learning and automatic, effortful processing.

PubMed

Tracy, J I; Pinsk, M; Helverson, J; Urban, G; Dietz, T; Smith, D J

2001-08-01

The link between automatic and effortful processing and nonanalytic and analytic category learning was evaluated in a sample of 29 college undergraduates using declarative memory, semantic category search, and pseudoword categorization tasks. Automatic and effortful processing measures were hypothesized to be associated with nonanalytic and analytic categorization, respectively. Results suggested that contrary to prediction strong criterion-attribute (analytic) responding on the pseudoword categorization task was associated with strong automatic, implicit memory encoding of frequency-of-occurrence information. Data are discussed in terms of the possibility that criterion-attribute category knowledge, once established, may be expressed with few attentional resources. The data indicate that attention resource requirements, even for the same stimuli and task, vary depending on the category rule system utilized. Also, the automaticity emerging from familiarity with analytic category exemplars is very different from the automaticity arising from extensive practice on a semantic category search task. The data do not support any simple mapping of analytic and nonanalytic forms of category learning onto the automatic and effortful processing dichotomy and challenge simple models of brain asymmetries for such procedures. Copyright 2001 Academic Press.

Automatically identifying health outcome information in MEDLINE records.

PubMed

Demner-Fushman, Dina; Few, Barbara; Hauser, Susan E; Thoma, George

2006-01-01

Understanding the effect of a given intervention on the patient's health outcome is one of the key elements in providing optimal patient care. This study presents a methodology for automatic identification of outcomes-related information in medical text and evaluates its potential in satisfying clinical information needs related to health care outcomes. An annotation scheme based on an evidence-based medicine model for critical appraisal of evidence was developed and used to annotate 633 MEDLINE citations. Textual, structural, and meta-information features essential to outcome identification were learned from the created collection and used to develop an automatic system. Accuracy of automatic outcome identification was assessed in an intrinsic evaluation and in an extrinsic evaluation, in which ranking of MEDLINE search results obtained using PubMed Clinical Queries relied on identified outcome statements. The accuracy and positive predictive value of outcome identification were calculated. Effectiveness of the outcome-based ranking was measured using mean average precision and precision at rank 10. Automatic outcome identification achieved 88% to 93% accuracy. The positive predictive value of individual sentences identified as outcomes ranged from 30% to 37%. Outcome-based ranking improved retrieval accuracy, tripling mean average precision and achieving 389% improvement in precision at rank 10. Preliminary results in outcome-based document ranking show potential validity of the evidence-based medicine-model approach in timely delivery of information critical to clinical decision support at the point of service.

Structure and conformational dynamics of scaffolded DNA origami nanoparticles

DTIC Science & Technology

2017-05-08

all-atom molecular dynamics and coarse-grained finite element modeling to DX-based nanoparticles to elucidate their fine-scale and global conforma... finite element (FE) modeling approach CanDo is also routinely used to predict the 3D equilibrium conformation of programmed DNA assemblies based on a...model with both experimental cryo-electron microscopy (cryo-EM) data and all-atom modeling. MATERIALS AND METHODS Lattice-free finite element model

Viscous plasma evolution from gravity using anti-de sitter/conformal-field-theory correspondence.

PubMed

Janik, Romuald A

2007-01-12

We analyze the anti-de Sitter/conformal-field-theory dual geometry of an expanding boost-invariant plasma. We show that the requirement of nonsingularity of the dual geometry for leading and subasymptotic times predicts, without any further assumptions about gauge theory dynamics, hydrodynamic expansion of the plasma with viscosity coefficient exactly matching the one obtained earlier in the static case by Policastro, Son, and Starinets.

An Experimental and Computational Study of the Gas-Phase Acidities of the Common Amino Acid Amides.

PubMed

Plummer, Chelsea E; Stover, Michele L; Bokatzian, Samantha S; Davis, John T M; Dixon, David A; Cassady, Carolyn J

2015-07-30

Using proton-transfer reactions in a Fourier transform ion cyclotron resonance mass spectrometer and correlated molecular orbital theory at the G3(MP2) level, gas-phase acidities (GAs) and the associated structures for amides corresponding to the common amino acids have been determined for the first time. These values are important because amino acid amides are models for residues in peptides and proteins. For compounds whose most acidic site is the C-terminal amide nitrogen, two ions populations were observed experimentally with GAs that differ by 4-7 kcal/mol. The lower energy, more acidic structure accounts for the majority of the ions formed by electrospray ionization. G3(MP2) calculations predict that the lowest energy anionic conformer has a cis-like orientation of the [-C(═O)NH](-) group whereas the higher energy, less acidic conformer has a trans-like orientation of this group. These two distinct conformers were predicted for compounds with aliphatic, amide, basic, hydroxyl, and thioether side chains. For the most acidic amino acid amides (tyrosine, cysteine, tryptophan, histidine, aspartic acid, and glutamic acid amides) only one conformer was observed experimentally, and its experimental GA correlates with the theoretical GA related to side chain deprotonation.

Metamorphic Proteins: Emergence of Dual Protein Folds from One Primary Sequence.

PubMed

Lella, Muralikrishna; Mahalakshmi, Radhakrishnan

2017-06-20

Every amino acid exhibits a different propensity for distinct structural conformations. Hence, decoding how the primary amino acid sequence undergoes the transition to a defined secondary structure and its final three-dimensional fold is presently considered predictable with reasonable certainty. However, protein sequences that defy the first principles of secondary structure prediction (they attain two different folds) have recently been discovered. Such proteins, aptly named metamorphic proteins, decrease the conformational constraint by increasing flexibility in the secondary structure and thereby result in efficient functionality. In this review, we discuss the major factors driving the conformational switch related both to protein sequence and to structure using illustrative examples. We discuss the concept of an evolutionary transition in sequence and structure, the functional impact of the tertiary fold, and the pressure of intrinsic and external factors that give rise to metamorphic proteins. We mainly focus on the major components of protein architecture, namely, the α-helix and β-sheet segments, which are involved in conformational switching within the same or highly similar sequences. These chameleonic sequences are widespread in both cytosolic and membrane proteins, and these folds are equally important for protein structure and function. We discuss the implications of metamorphic proteins and chameleonic peptide sequences in de novo peptide design.

First Principles Predictions of the Structure and Function of G-Protein-Coupled Receptors: Validation for Bovine Rhodopsin

PubMed Central

Trabanino, Rene J.; Hall, Spencer E.; Vaidehi, Nagarajan; Floriano, Wely B.; Kam, Victor W. T.; Goddard, William A.

2004-01-01

G-protein-coupled receptors (GPCRs) are involved in cell communication processes and with mediating such senses as vision, smell, taste, and pain. They constitute a prominent superfamily of drug targets, but an atomic-level structure is available for only one GPCR, bovine rhodopsin, making it difficult to use structure-based methods to design receptor-specific drugs. We have developed the MembStruk first principles computational method for predicting the three-dimensional structure of GPCRs. In this article we validate the MembStruk procedure by comparing its predictions with the high-resolution crystal structure of bovine rhodopsin. The crystal structure of bovine rhodopsin has the second extracellular (EC-II) loop closed over the transmembrane regions by making a disulfide linkage between Cys-110 and Cys-187, but we speculate that opening this loop may play a role in the activation process of the receptor through the cysteine linkage with helix 3. Consequently we predicted two structures for bovine rhodopsin from the primary sequence (with no input from the crystal structure)—one with the EC-II loop closed as in the crystal structure, and the other with the EC-II loop open. The MembStruk-predicted structure of bovine rhodopsin with the closed EC-II loop deviates from the crystal by 2.84 Å coordinate root mean-square (CRMS) in the transmembrane region main-chain atoms. The predicted three-dimensional structures for other GPCRs can be validated only by predicting binding sites and energies for various ligands. For such predictions we developed the HierDock first principles computational method. We validate HierDock by predicting the binding site of 11-cis-retinal in the crystal structure of bovine rhodopsin. Scanning the whole protein without using any prior knowledge of the binding site, we find that the best scoring conformation in rhodopsin is 1.1 Å CRMS from the crystal structure for the ligand atoms. This predicted conformation has the carbonyl O only 2.82 Å from the N of Lys-296. Making this Schiff base bond and minimizing leads to a final conformation only 0.62 Å CRMS from the crystal structure. We also used HierDock to predict the binding site of 11-cis-retinal in the MembStruk-predicted structure of bovine rhodopsin (closed loop). Scanning the whole protein structure leads to a structure in which the carbonyl O is only 2.85 Å from the N of Lys-296. Making this Schiff base bond and minimizing leads to a final conformation only 2.92 Å CRMS from the crystal structure. The good agreement of the ab initio-predicted protein structures and ligand binding site with experiment validates the use of the MembStruk and HierDock first principles' methods. Since these methods are generic and applicable to any GPCR, they should be useful in predicting the structures of other GPCRs and the binding site of ligands to these proteins. PMID:15041637

Amide I vibrational circular dichroism of dipeptide: Conformation dependence and fragment analysis

NASA Astrophysics Data System (ADS)

Choi, Jun-Ho; Cho, Minhaeng

2004-03-01

The amide I vibrational circular dichroic response of alanine dipeptide analog (ADA) was theoretically investigated and the density functional theory calculation and fragment analysis results are presented. A variety of vibrational spectroscopic properties, local and normal mode frequencies, coupling constant, dipole, and rotational strengths, are calculated by varying two dihedral angles determining the three-dimensional ADA conformation. Considering two monopeptide fragments separately, we show that the amide I vibrational circular dichroism of the ADA can be quantitatively predicted. For several representative conformations of the model ADA, vibrational circular dichroism spectra are calculated by using both the density functional theory calculation and fragment analysis methods.

Choosing the appropriate forecasting model for predictive parameter control.

PubMed

Aleti, Aldeida; Moser, Irene; Meedeniya, Indika; Grunske, Lars

2014-01-01

All commonly used stochastic optimisation algorithms have to be parameterised to perform effectively. Adaptive parameter control (APC) is an effective method used for this purpose. APC repeatedly adjusts parameter values during the optimisation process for optimal algorithm performance. The assignment of parameter values for a given iteration is based on previously measured performance. In recent research, time series prediction has been proposed as a method of projecting the probabilities to use for parameter value selection. In this work, we examine the suitability of a variety of prediction methods for the projection of future parameter performance based on previous data. All considered prediction methods have assumptions the time series data has to conform to for the prediction method to provide accurate projections. Looking specifically at parameters of evolutionary algorithms (EAs), we find that all standard EA parameters with the exception of population size conform largely to the assumptions made by the considered prediction methods. Evaluating the performance of these prediction methods, we find that linear regression provides the best results by a very small and statistically insignificant margin. Regardless of the prediction method, predictive parameter control outperforms state of the art parameter control methods when the performance data adheres to the assumptions made by the prediction method. When a parameter's performance data does not adhere to the assumptions made by the forecasting method, the use of prediction does not have a notable adverse impact on the algorithm's performance.

Automatic Speech Recognition Predicts Speech Intelligibility and Comprehension for Listeners with Simulated Age-Related Hearing Loss

ERIC Educational Resources Information Center

Fontan, Lionel; Ferrané, Isabelle; Farinas, Jérôme; Pinquier, Julien; Tardieu, Julien; Magnen, Cynthia; Gaillard, Pascal; Aumont, Xavier; Füllgrabe, Christian

2017-01-01

Purpose: The purpose of this article is to assess speech processing for listeners with simulated age-related hearing loss (ARHL) and to investigate whether the observed performance can be replicated using an automatic speech recognition (ASR) system. The long-term goal of this research is to develop a system that will assist…

Automatic and controlled attentional orienting in the elderly: A dual-process view of the positivity effect.

PubMed

Gronchi, G; Righi, S; Pierguidi, L; Giovannelli, F; Murasecco, I; Viggiano, M P

2018-04-01

The positivity effect in the elderly consists of an attentional preference for positive information as well as avoidance of negative information. Extant theories predict either that the positivity effect depends on controlled attentional processes (socio-emotional selectivity theory), or on an automatic gating selection mechanism (dynamic integration theory). This study examined the role of automatic and controlled attention in the positivity effect. Two dot-probe tasks (with the duration of the stimuli lasting 100 ms and 500 ms, respectively) were employed to compare the attentional bias of 35 elderly people to that of 35 young adults. The stimuli used were expressive faces displaying neutral, disgusted, fearful, and happy expressions. In comparison to young people, the elderly allocated more attention to happy faces at 100 ms and they tended to avoid fearful faces at 500 ms. The findings are not predicted by either theory taken alone, but support the hypothesis that the positivity effect in the elderly is driven by two different processes: an automatic attention bias toward positive stimuli, and a controlled mechanism that diverts attention away from negative stimuli. Copyright © 2018 Elsevier B.V. All rights reserved.

An image-based approach for automatic detecting five true-leaves stage of cotton

NASA Astrophysics Data System (ADS)

Li, Yanan; Cao, Zhiguo; Wu, Xi; Yu, Zhenghong; Wang, Yu; Bai, Xiaodong

2013-10-01

Cotton, as one of the four major economic crops, is of great significance to the development of the national economy. Monitoring cotton growth status by automatic image-based detection makes sense due to its low-cost, low-labor and the capability of continuous observations. However, little research has been done to improve close observation of different growth stages of field crops using digital cameras. Therefore, algorithms proposed by us were developed to detect the growth information and predict the starting date of cotton automatically. In this paper, we introduce an approach for automatic detecting five true-leaves stage, which is a critical growth stage of cotton. On account of the drawbacks caused by illumination and the complex background, we cannot use the global coverage as the unique standard of judgment. Consequently, we propose a new method to determine the five true-leaves stage through detecting the node number between the main stem and the side stems, based on the agricultural meteorological observation specification. The error of the results between the predicted starting date with the proposed algorithm and artificial observations is restricted to no more than one day.

Conformer lifetimes of ethyl cyanoformate from exchange-averaged rotational spectra.

PubMed

True, Nancy S

2009-06-25

Ethyl cyanoformate exists as a mixture of two conformers but displays three R-branch a-type band series in its rotational spectrum. Simulations with population fractions 0.37 at 210 K and 0.70 at 297 K undergoing conformer exchange with average conformer lifetimes, , shorter than approximately 40 ps at approximately 210 K and shorter than approximately 37 ps at 297 K reproduce the experimental spectra between 26.5 and 38 GHz, the exchanging species accounting for the third set of bands. The upper-limit 's are 1 order of magnitude longer than RRKM theory predictions and the population fractions are consistent with the total population with energy above 700 cm(-1), approximately twice the conformer interconversion barrier height. Model calculations indicate that extensive K-sublevel mixing in individual molecular eigenstates can produce the large population and the narrow distribution of the rotational-constant sum, B + C, consistent with the observed exchange-averaged band series.

Relative Packing Groups in Template-Based Structure Prediction: Cooperative Effects of True Positive Constraints

PubMed Central

Day, Ryan; Qu, Xiaotao; Swanson, Rosemarie; Bohannan, Zach; Bliss, Robert

2011-01-01

Abstract Most current template-based structure prediction methods concentrate on finding the correct backbone conformation and then packing sidechains within that backbone. Our packing-based method derives distance constraints from conserved relative packing groups (RPGs). In our refinement approach, the RPGs provide a level of resolution that restrains global topology while allowing conformational sampling. In this study, we test our template-based structure prediction method using 51 prediction units from CASP7 experiments. RPG-based constraints are able to substantially improve approximately two-thirds of starting templates. Upon deeper investigation, we find that true positive spatial constraints, especially those non-local in sequence, derived from the RPGs were important to building nearer native models. Surprisingly, the fraction of incorrect or false positive constraints does not strongly influence the quality of the final candidate. This result indicates that our RPG-based true positive constraints sample the self-consistent, cooperative interactions of the native structure. The lack of such reinforcing cooperativity explains the weaker effect of false positive constraints. Generally, these findings are encouraging indications that RPGs will improve template-based structure prediction. PMID:21210729

Ab initio RNA folding by discrete molecular dynamics: From structure prediction to folding mechanisms

PubMed Central

Ding, Feng; Sharma, Shantanu; Chalasani, Poornima; Demidov, Vadim V.; Broude, Natalia E.; Dokholyan, Nikolay V.

2008-01-01

RNA molecules with novel functions have revived interest in the accurate prediction of RNA three-dimensional (3D) structure and folding dynamics. However, existing methods are inefficient in automated 3D structure prediction. Here, we report a robust computational approach for rapid folding of RNA molecules. We develop a simplified RNA model for discrete molecular dynamics (DMD) simulations, incorporating base-pairing and base-stacking interactions. We demonstrate correct folding of 150 structurally diverse RNA sequences. The majority of DMD-predicted 3D structures have <4 Å deviations from experimental structures. The secondary structures corresponding to the predicted 3D structures consist of 94% native base-pair interactions. Folding thermodynamics and kinetics of tRNAPhe, pseudoknots, and mRNA fragments in DMD simulations are in agreement with previous experimental findings. Folding of RNA molecules features transient, non-native conformations, suggesting non-hierarchical RNA folding. Our method allows rapid conformational sampling of RNA folding, with computational time increasing linearly with RNA length. We envision this approach as a promising tool for RNA structural and functional analyses. PMID:18456842

Automatic Adaptation to Fast Input Changes in a Time-Invariant Neural Circuit

PubMed Central

Bharioke, Arjun; Chklovskii, Dmitri B.

2015-01-01

Neurons must faithfully encode signals that can vary over many orders of magnitude despite having only limited dynamic ranges. For a correlated signal, this dynamic range constraint can be relieved by subtracting away components of the signal that can be predicted from the past, a strategy known as predictive coding, that relies on learning the input statistics. However, the statistics of input natural signals can also vary over very short time scales e.g., following saccades across a visual scene. To maintain a reduced transmission cost to signals with rapidly varying statistics, neuronal circuits implementing predictive coding must also rapidly adapt their properties. Experimentally, in different sensory modalities, sensory neurons have shown such adaptations within 100 ms of an input change. Here, we show first that linear neurons connected in a feedback inhibitory circuit can implement predictive coding. We then show that adding a rectification nonlinearity to such a feedback inhibitory circuit allows it to automatically adapt and approximate the performance of an optimal linear predictive coding network, over a wide range of inputs, while keeping its underlying temporal and synaptic properties unchanged. We demonstrate that the resulting changes to the linearized temporal filters of this nonlinear network match the fast adaptations observed experimentally in different sensory modalities, in different vertebrate species. Therefore, the nonlinear feedback inhibitory network can provide automatic adaptation to fast varying signals, maintaining the dynamic range necessary for accurate neuronal transmission of natural inputs. PMID:26247884

Perturbational formulation of principal component analysis in molecular dynamics simulation.

PubMed

Koyama, Yohei M; Kobayashi, Tetsuya J; Tomoda, Shuji; Ueda, Hiroki R

2008-10-01

Conformational fluctuations of a molecule are important to its function since such intrinsic fluctuations enable the molecule to respond to the external environmental perturbations. For extracting large conformational fluctuations, which predict the primary conformational change by the perturbation, principal component analysis (PCA) has been used in molecular dynamics simulations. However, several versions of PCA, such as Cartesian coordinate PCA and dihedral angle PCA (dPCA), are limited to use with molecules with a single dominant state or proteins where the dihedral angle represents an important internal coordinate. Other PCAs with general applicability, such as the PCA using pairwise atomic distances, do not represent the physical meaning clearly. Therefore, a formulation that provides general applicability and clearly represents the physical meaning is yet to be developed. For developing such a formulation, we consider the conformational distribution change by the perturbation with arbitrary linearly independent perturbation functions. Within the second order approximation of the Kullback-Leibler divergence by the perturbation, the PCA can be naturally interpreted as a method for (1) decomposing a given perturbation into perturbations that independently contribute to the conformational distribution change or (2) successively finding the perturbation that induces the largest conformational distribution change. In this perturbational formulation of PCA, (i) the eigenvalue measures the Kullback-Leibler divergence from the unperturbed to perturbed distributions, (ii) the eigenvector identifies the combination of the perturbation functions, and (iii) the principal component determines the probability change induced by the perturbation. Based on this formulation, we propose a PCA using potential energy terms, and we designate it as potential energy PCA (PEPCA). The PEPCA provides both general applicability and clear physical meaning. For demonstrating its power, we apply the PEPCA to an alanine dipeptide molecule in vacuum as a minimal model of a nonsingle dominant conformational biomolecule. The first and second principal components clearly characterize two stable states and the transition state between them. Positive and negative components with larger absolute values of the first and second eigenvectors identify the electrostatic interactions, which stabilize or destabilize each stable state and the transition state. Our result therefore indicates that PCA can be applied, by carefully selecting the perturbation functions, not only to identify the molecular conformational fluctuation but also to predict the conformational distribution change by the perturbation beyond the limitation of the previous methods.

Perturbational formulation of principal component analysis in molecular dynamics simulation

NASA Astrophysics Data System (ADS)

Koyama, Yohei M.; Kobayashi, Tetsuya J.; Tomoda, Shuji; Ueda, Hiroki R.

2008-10-01

Conformational fluctuations of a molecule are important to its function since such intrinsic fluctuations enable the molecule to respond to the external environmental perturbations. For extracting large conformational fluctuations, which predict the primary conformational change by the perturbation, principal component analysis (PCA) has been used in molecular dynamics simulations. However, several versions of PCA, such as Cartesian coordinate PCA and dihedral angle PCA (dPCA), are limited to use with molecules with a single dominant state or proteins where the dihedral angle represents an important internal coordinate. Other PCAs with general applicability, such as the PCA using pairwise atomic distances, do not represent the physical meaning clearly. Therefore, a formulation that provides general applicability and clearly represents the physical meaning is yet to be developed. For developing such a formulation, we consider the conformational distribution change by the perturbation with arbitrary linearly independent perturbation functions. Within the second order approximation of the Kullback-Leibler divergence by the perturbation, the PCA can be naturally interpreted as a method for (1) decomposing a given perturbation into perturbations that independently contribute to the conformational distribution change or (2) successively finding the perturbation that induces the largest conformational distribution change. In this perturbational formulation of PCA, (i) the eigenvalue measures the Kullback-Leibler divergence from the unperturbed to perturbed distributions, (ii) the eigenvector identifies the combination of the perturbation functions, and (iii) the principal component determines the probability change induced by the perturbation. Based on this formulation, we propose a PCA using potential energy terms, and we designate it as potential energy PCA (PEPCA). The PEPCA provides both general applicability and clear physical meaning. For demonstrating its power, we apply the PEPCA to an alanine dipeptide molecule in vacuum as a minimal model of a nonsingle dominant conformational biomolecule. The first and second principal components clearly characterize two stable states and the transition state between them. Positive and negative components with larger absolute values of the first and second eigenvectors identify the electrostatic interactions, which stabilize or destabilize each stable state and the transition state. Our result therefore indicates that PCA can be applied, by carefully selecting the perturbation functions, not only to identify the molecular conformational fluctuation but also to predict the conformational distribution change by the perturbation beyond the limitation of the previous methods.

A Twist on Facial Selectivity of Hydride Reductions of Cyclic Ketones: Twist-Boat Conformers in Cyclohexanone, Piperidone, and Tropinone Reactions

PubMed Central

2015-01-01

The role of twist-boat conformers of cyclohexanones in hydride reductions was explored. The hydride reductions of a cis-2,6-disubstituted N-acylpiperidone, an N-acyltropinone, and tert-butylcyclohexanone by lithium aluminum hydride and by a bulky borohydride reagent were investigated computationally and compared to experiment. Our results indicate that in certain cases, factors such as substrate conformation, nucleophile bulkiness, and remote steric features can affect stereoselectivity in ways that are difficult to predict by the general Felkin–Anh model. In particular, we have calculated that a twist-boat conformation is relevant to the reactivity and facial selectivity of hydride reduction of cis-2,6-disubstituted N-acylpiperidones with a small hydride reagent (LiAlH4) but not with a bulky hydride (lithium triisopropylborohydride). PMID:25372509

Conformational interpretation of vescalagin and castalagin physicochemical properties.

PubMed

Vivas, Nicolas; Laguerre, Michel; Pianet de Boissel, Isabelle; Vivas de Gaulejac, Nathalie; Nonier, Marie-Françoise

2004-04-07

Vescalagin and castalagin are two diastereoisomers. The variability of their principal physicochemical properties, compared with their small structural differences, suggests important conformational variations. This study shows, experimentally, that vescalagin has a greater effect on polarity, oxidizability in solution, and thermodegradability than castalagin. Conformational analysis by molecular mechanics demonstrated that vescalagin was more hydrophilic and was more reactive to electrophilic reagents than castalagin. Experimental results were thus explained and demonstrated the distinct behaviors of vescalagin and castalagin. These results were attributed to the C1 position of the two compounds because vescalin and castalin have comparable characteristics. Experimental data were confirmed and interpreted by molecular mechanics. This work represents one of the first attempts to correlate conformation and the properties of phenolic compounds. This step constitutes a predictive method for the pharmacology or chemistry of new compounds.

Conformational flexibility and packing plausibility of repaglinide polymorphs

NASA Astrophysics Data System (ADS)

Rani, Dimpy; Goyal, Parnika; Chadha, Renu

2018-04-01

The present manuscript highlights the structural insight into the repaglinide polymorphs. The experimental screening for the possible crystal forms were carried out using various solvents, which generated three forms. The crystal structure of Form II and III was determined using PXRD pattern whereas structural analysis of Form I has already been reported. Form I, II and II was found to exist in P212121, PNA21 and P21/c space groups respectively. Conformational analysis was performed to account the conformational flexibility of RPG. The obtained conformers were further utilized to obtain the information about the crystal packing pattern of RPG polymorphs by polymorph prediction module. The lattice energy landscape, depicting the relationship between lattice energy and density of the polymorphs has been obtained for various possible polymorphs. The experimentally isolated polymorphs were successfully fitted into lattice energy landscape.

Me, us, or them: who is more conformist? Perception of conformity and political orientation.

PubMed

Cavazza, Nicoletta; Mucchi-Faina, Angelica

2008-06-01

Research has shown that people perceive others as more vulnerable than themselves to media communication, and their political out-group as more vulnerable than their political in-group. In the present study, the authors predicted that the same two biases would appear with respect to another kind of influence--conformity--but that participants' judgments would display a different pattern according to their political orientations. Right-wing and left-wing university students were asked to evaluate conformity and to estimate how conformist they, their political in-group, their political out-group, and other groups are. As hypothesized, right-wingers expressed more ambivalence toward conformity and viewed it less negatively than did left-wingers. Political orientation had no impact on the discrepancy between self and others, but it did moderate the in-group-out-group discrepancy.

DICOM router: an open source toolbox for communication and correction of DICOM objects.

PubMed

Hackländer, Thomas; Kleber, Klaus; Martin, Jens; Mertens, Heinrich

2005-03-01

Today, the exchange of medical images and clinical information is well defined by the digital imaging and communications in medicine (DICOM) and Health Level Seven (ie, HL7) standards. The interoperability among information systems is specified by the integration profiles of IHE (Integrating the Healthcare Enterprise). However, older imaging modalities frequently do not correctly support these interfaces and integration profiles, and some use cases are not yet specified by IHE. Therefore, corrections of DICOM objects are necessary to establish conformity. The aim of this project was to develop a toolbox that can automatically perform these recurrent corrections of the DICOM objects. The toolbox is composed of three main components: 1) a receiver to receive DICOM objects, 2) a processing pipeline to correct each object, and 3) one or more senders to forward each corrected object to predefined addressees. The toolbox is implemented under Java as an open source project. The processing pipeline is realized by means of plug ins. One of the plug ins can be programmed by the user via an external eXtensible Stylesheet Language (ie, XSL) file. Using this plug in, DICOM objects can also be converted into eXtensible Markup Language (ie, XML) documents or other data formats. DICOM storage services, DICOM CD-ROMs, and the local file system are defined as input and output channel. The toolbox is used clinically for different application areas. These are the automatic correction of DICOM objects from non-IHE-conforming modalities, the import of DICOM CD-ROMs into the picture archiving and communication system and the pseudo naming of DICOM images. The toolbox has been accepted by users in a clinical setting. Because of the open programming interfaces, the functionality can easily be adapted to future applications.

Finite element fatigue analysis of rectangular clutch spring of automatic slack adjuster

NASA Astrophysics Data System (ADS)

Xu, Chen-jie; Luo, Zai; Hu, Xiao-feng; Jiang, Wen-song

2015-02-01

The failure of rectangular clutch spring of automatic slack adjuster directly affects the work of automatic slack adjuster. We establish the structural mechanics model of automatic slack adjuster rectangular clutch spring based on its working principle and mechanical structure. In addition, we upload such structural mechanics model to ANSYS Workbench FEA system to predict the fatigue life of rectangular clutch spring. FEA results show that the fatigue life of rectangular clutch spring is 2.0403×105 cycle under the effect of braking loads. In the meantime, fatigue tests of 20 automatic slack adjusters are carried out on the fatigue test bench to verify the conclusion of the structural mechanics model. The experimental results show that the mean fatigue life of rectangular clutch spring is 1.9101×105, which meets the results based on the finite element analysis using ANSYS Workbench FEA system.

Protein Structure Prediction Using Gas Phase Molecular Dynamics Simulation: EOTAXIN-3 Cytokine as a Case Study

NASA Astrophysics Data System (ADS)

Khairudin, Nurul Bahiyah Ahmad; Wahab, Habibah A.

In the current work, the structure of the enzyme CC chemokine eotaxin-3 (1G2S) was chosen as a case study to investigate the effects of gas phase on the predicted protein conformation using molecular dynamics simulation. Generally, simulating proteins in the gas phase tend to suffer from various drawbacks, among which excessive numbers of protein-protein hydrogen bonds. However, current results showed that the effects of gas phase simulation on 1G2S did not amplify the protein-protein hydrogen bonds. It was also found that some of the hydrogen bonds which were crucial in maintaining the secondary structural elements were disrupted. The predicted models showed high values of RMSD, 11.5 Å and 13.5 Å for both vacuum and explicit solvent simulations, respectively, indicating that the conformers were very much different from the native conformation. Even though the RMSD value for the in vacuo model was slightly lower, it somehow suffered from lower fraction of native contacts, poor hydrogen bonding networks and fewer occurrences of secondary structural elements compared to the solvated model. This finding supports the notion that water plays a dominant role in guiding the protein to fold along the correct path.

Development of a prototype automatic controller for liquid cooling garment inlet temperature

NASA Technical Reports Server (NTRS)

Weaver, C. S.; Webbon, B. W.; Montgomery, L. D.

1982-01-01

The development of a computer control of a liquid cooled garment (LCG) inlet temperature is descirbed. An adaptive model of the LCG is used to predict the heat-removal rates for various inlet temperatures. An experimental system that contains a microcomputer was constructed. The LCG inlet and outlet temperatures and the heat exchanger outlet temperature form the inputs to the computer. The adaptive model prediction method of control is successful during tests where the inlet temperature is automatically chosen by the computer. It is concluded that the program can be implemented in a microprocessor of a size that is practical for a life support back-pack.

An Automatic Prediction of Epileptic Seizures Using Cloud Computing and Wireless Sensor Networks.

PubMed

Sareen, Sanjay; Sood, Sandeep K; Gupta, Sunil Kumar

2016-11-01

Epilepsy is one of the most common neurological disorders which is characterized by the spontaneous and unforeseeable occurrence of seizures. An automatic prediction of seizure can protect the patients from accidents and save their life. In this article, we proposed a mobile-based framework that automatically predict seizures using the information contained in electroencephalography (EEG) signals. The wireless sensor technology is used to capture the EEG signals of patients. The cloud-based services are used to collect and analyze the EEG data from the patient's mobile phone. The features from the EEG signal are extracted using the fast Walsh-Hadamard transform (FWHT). The Higher Order Spectral Analysis (HOSA) is applied to FWHT coefficients in order to select the features set relevant to normal, preictal and ictal states of seizure. We subsequently exploit the selected features as input to a k-means classifier to detect epileptic seizure states in a reasonable time. The performance of the proposed model is tested on Amazon EC2 cloud and compared in terms of execution time and accuracy. The findings show that with selected HOS based features, we were able to achieve a classification accuracy of 94.6 %.

RNA2D3D: a program for generating, viewing, and comparing 3-dimensional models of RNA.

PubMed

Martinez, Hugo M; Maizel, Jacob V; Shapiro, Bruce A

2008-06-01

Using primary and secondary structure information of an RNA molecule, the program RNA2D3D automatically and rapidly produces a first-order approximation of a 3-dimensional conformation consistent with this information. Applicable to structures of arbitrary branching complexity and pseudoknot content, it features efficient interactive graphical editing for the removal of any overlaps introduced by the initial generating procedure and for making conformational changes favorable to targeted features and subsequent refinement. With emphasis on fast exploration of alternative 3D conformations, one may interactively add or delete base-pairs, adjacent stems can be coaxially stacked or unstacked, single strands can be shaped to accommodate special constraints, and arbitrary subsets can be defined and manipulated as rigid bodies. Compaction, whereby base stacking within stems is optimally extended into connecting single strands, is also available as a means of strategically making the structures more compact and revealing folding motifs. Subsequent refinement of the first-order approximation, of modifications, and for the imposing of tertiary constraints is assisted with standard energy refinement techniques. Previously determined coordinates for any part of the molecule are readily incorporated, and any part of the modeled structure can be output as a PDB or XYZ file. Illustrative applications in the areas of ribozymes, viral kissing loops, viral internal ribosome entry sites, and nanobiology are presented.

The conformational free-energy landscape of β-D-mannopyranose: evidence for a (1)S(5) → B(2,5) → (O)S(2) catalytic itinerary in β-mannosidases.

PubMed

Ardèvol, Albert; Biarnés, Xevi; Planas, Antoni; Rovira, Carme

2010-11-17

The mechanism of glycosidic bond cleavage by glycosidases involves substrate ring distortions in the Michaelis complex that favor catalysis. Retaining β-mannosidases bind the substrate in a (1)S(5) conformation, and recent experiments have proposed an unusual substrate conformational pathway ((1)S(5) → B(2,5) → (O)S(2)) for the hydrolysis reaction. By means of Car-Parrinello metadynamics simulations, we have obtained the conformational free-energy surface (FES) of a β-d-mannopyranose molecule associated with the ideal Stoddart conformational diagram. We have found that (1)S(5) is among the most stable conformers and simultaneously is the most preactivated conformation in terms of elongation/shortening of the C1-O1/C1-O5 bonds, C1-O1 orientation, and charge development at the anomeric carbon. Analysis of the computed FES gives support to the proposed (1)S(5) → B(2,5) → (O)S(2) catalytic itinerary, showing that the degree of preactivation of the substrate in glycoside hydrolases (GHs) is related to the properties of an isolated sugar ring. We introduce a simple preactivation index integrating several structural, electronic, and energetic properties that can be used to predict the conformation of the substrate in the Michaelis complex of any GH.

NMR investigation and theoretical calculations of the solvent effect on the conformation of valsartan

NASA Astrophysics Data System (ADS)

Chashmniam, Saeed; Tafazzoli, Mohsen

2017-11-01

Structure and conformational properties of valsartan were studied by advanced NMR techniques and quantum calculation methods. Potential energy scanning using B3LYP/6-311++g** and B3LYP-D3/6-311++g** methods were performed and four conformers (V1-V4) at minimum points of PES diagram were observed. According to the NMR spectra in acetone-d6, there are two conformers (M and m) with m/M = 0.52 ratio simultaneously and energy barriers of the two conformers were predicted from chemical shifts and multiplicities. While, intramolecular hydrogen bond at tetrazole ring and carboxylic groups prevent the free rotation on N6sbnd C11 bond in M-conformer, this bond rotates freely in m-conformer. On the other hand, intramolecular hydrogen bond at carbonyl and carboxylic acid can be observed at m-conformer. So, different intramolecular hydrogen bond is the reason for the stability of both M and m structures. Quite interestingly, 1H NMR spectra in CDCl3 show two distinct conformers (N and n) with unequal ratio which are differ from M-m conformers. Also, intramolecular hydrogen bond seven-member ring involving five-membered tetrazole ring and carboxylic acid group observed in both N and n-conformers Solvent effect, by using a set of polar and non-polar solvents including DMSO-d6, methanol-d4, benzene-d6, THF-d8, nitromethane-d3, methylene chloride-d2 and acetonitrile-d3 were investigated. NMR parameters include chemical shifts and spin-spin coupling constants were obtained from a set of 2D NMR spectra (H-H COSY, HMQC and HMBC). For this purpose, several DFT functionals from LDA, GGA and hybrid categories were used which the hybrid method showed better agreement with experiment values.

On the Use of Enveloping Distribution Sampling (EDS) to Compute Free Enthalpy Differences between Different Conformational States of Molecules: Application to 310-, α-, and π-Helices.

PubMed

Lin, Zhixiong; Liu, Haiyan; Riniker, Sereina; van Gunsteren, Wilfred F

2011-12-13

Enveloping distribution sampling (EDS) is a powerful method to compute relative free energies from simulation. So far, the EDS method has only been applied to alchemical free energy differences, i.e., between different Hamiltonians defining different systems, and not yet to obtain free energy differences between different conformations or conformational states of a system. In this article, we extend the EDS formalism such that it can be applied to compute free energy differences of different conformations and apply it to compute the relative free enthalpy ΔG of 310-, α-, and π-helices of an alanine deca-peptide in explicit water solvent. The resulting ΔG values are compared to those obtained by standard thermodynamic integration (TI) and from so-called end-state simulations. A TI simulation requires the definition of a λ-dependent pathway which in the present case is based on hydrogen bonds of the different helical conformations. The values of ⟨(∂VTI)/(∂λ)⟩λ show a sharp change for a particular range of λ values, which is indicative of an energy barrier along the pathway, which lowers the accuracy of the resulting ΔG value. In contrast, in a two-state EDS simulation, an unphysical reference-state Hamiltonian which connects the parts of conformational space that are relevant to the different end states is constructed automatically; that is, no pathway needs to be defined. In the simulation using this reference state, both helices were sampled, and many transitions between them occurred, thus ensuring the accuracy of the resulting free enthalpy difference. According to the EDS simulations, the free enthalpy differences of the π-helix and the 310-helix versus the α-helix are 5 kJ mol(-1) and 47 kJ mol(-1), respectively, for an alanine deca-peptide in explicit SPC water solvent using the GROMOS 53A6 force field. The EDS method, which is a particular form of umbrella sampling, is thus applicable to compute free energy differences between conformational states as well as between systems and has definite advantages over the traditional TI and umbrella sampling methods to compute relative free energies.

Predicting protein interactions by Brownian dynamics simulations.

PubMed

Meng, Xuan-Yu; Xu, Yu; Zhang, Hong-Xing; Mezei, Mihaly; Cui, Meng

2012-01-01

We present a newly adapted Brownian-Dynamics (BD)-based protein docking method for predicting native protein complexes. The approach includes global BD conformational sampling, compact complex selection, and local energy minimization. In order to reduce the computational costs for energy evaluations, a shell-based grid force field was developed to represent the receptor protein and solvation effects. The performance of this BD protein docking approach has been evaluated on a test set of 24 crystal protein complexes. Reproduction of experimental structures in the test set indicates the adequate conformational sampling and accurate scoring of this BD protein docking approach. Furthermore, we have developed an approach to account for the flexibility of proteins, which has been successfully applied to reproduce the experimental complex structure from the structure of two unbounded proteins. These results indicate that this adapted BD protein docking approach can be useful for the prediction of protein-protein interactions.

Mismatch repair factor MSH2-MSH3 binds and alters the conformation of branched DNA structures predicted to form during genetic recombination.

PubMed

Surtees, Jennifer A; Alani, Eric

2006-07-14

Genetic studies in Saccharomyces cerevisiae predict that the mismatch repair (MMR) factor MSH2-MSH3 binds and stabilizes branched recombination intermediates that form during single strand annealing and gene conversion. To test this model, we constructed a series of DNA substrates that are predicted to form during these recombination events. We show in an electrophoretic mobility shift assay that S. cerevisiae MSH2-MSH3 specifically binds branched DNA substrates containing 3' single-stranded DNA and that ATP stimulates its release from these substrates. Chemical footprinting analyses indicate that MSH2-MSH3 specifically binds at the double-strand/single-strand junction of branched substrates, alters its conformation and opens up the junction. Therefore, MSH2-MSH3 binding to its substrates creates a unique nucleoprotein structure that may signal downstream steps in repair that include interactions with MMR and nucleotide excision repair factors.

Drug search for leishmaniasis: a virtual screening approach by grid computing

NASA Astrophysics Data System (ADS)

Ochoa, Rodrigo; Watowich, Stanley J.; Flórez, Andrés; Mesa, Carol V.; Robledo, Sara M.; Muskus, Carlos

2016-07-01

The trypanosomatid protozoa Leishmania is endemic in 100 countries, with infections causing 2 million new cases of leishmaniasis annually. Disease symptoms can include severe skin and mucosal ulcers, fever, anemia, splenomegaly, and death. Unfortunately, therapeutics approved to treat leishmaniasis are associated with potentially severe side effects, including death. Furthermore, drug-resistant Leishmania parasites have developed in most endemic countries. To address an urgent need for new, safe and inexpensive anti-leishmanial drugs, we utilized the IBM World Community Grid to complete computer-based drug discovery screens (Drug Search for Leishmaniasis) using unique leishmanial proteins and a database of 600,000 drug-like small molecules. Protein structures from different Leishmania species were selected for molecular dynamics (MD) simulations, and a series of conformational "snapshots" were chosen from each MD trajectory to simulate the protein's flexibility. A Relaxed Complex Scheme methodology was used to screen 2000 MD conformations against the small molecule database, producing >1 billion protein-ligand structures. For each protein target, a binding spectrum was calculated to identify compounds predicted to bind with highest average affinity to all protein conformations. Significantly, four different Leishmania protein targets were predicted to strongly bind small molecules, with the strongest binding interactions predicted to occur for dihydroorotate dehydrogenase (LmDHODH; PDB:3MJY). A number of predicted tight-binding LmDHODH inhibitors were tested in vitro and potent selective inhibitors of Leishmania panamensis were identified. These promising small molecules are suitable for further development using iterative structure-based optimization and in vitro/in vivo validation assays.

Computational prediction of hinge axes in proteins

PubMed Central

2014-01-01

Background A protein's function is determined by the wide range of motions exhibited by its 3D structure. However, current experimental techniques are not able to reliably provide the level of detail required for elucidating the exact mechanisms of protein motion essential for effective drug screening and design. Computational tools are instrumental in the study of the underlying structure-function relationship. We focus on a special type of proteins called "hinge proteins" which exhibit a motion that can be interpreted as a rotation of one domain relative to another. Results This work proposes a computational approach that uses the geometric structure of a single conformation to predict the feasible motions of the protein and is founded in recent work from rigidity theory, an area of mathematics that studies flexibility properties of general structures. Given a single conformational state, our analysis predicts a relative axis of motion between two specified domains. We analyze a dataset of 19 structures known to exhibit this hinge-like behavior. For 15, the predicted axis is consistent with a motion to a second, known conformation. We present a detailed case study for three proteins whose dynamics have been well-studied in the literature: calmodulin, the LAO binding protein and the Bence-Jones protein. Conclusions Our results show that incorporating rigidity-theoretic analyses can lead to effective computational methods for understanding hinge motions in macromolecules. This initial investigation is the first step towards a new tool for probing the structure-dynamics relationship in proteins. PMID:25080829

Drug search for leishmaniasis: a virtual screening approach by grid computing.

PubMed

Ochoa, Rodrigo; Watowich, Stanley J; Flórez, Andrés; Mesa, Carol V; Robledo, Sara M; Muskus, Carlos

2016-07-01

The trypanosomatid protozoa Leishmania is endemic in ~100 countries, with infections causing ~2 million new cases of leishmaniasis annually. Disease symptoms can include severe skin and mucosal ulcers, fever, anemia, splenomegaly, and death. Unfortunately, therapeutics approved to treat leishmaniasis are associated with potentially severe side effects, including death. Furthermore, drug-resistant Leishmania parasites have developed in most endemic countries. To address an urgent need for new, safe and inexpensive anti-leishmanial drugs, we utilized the IBM World Community Grid to complete computer-based drug discovery screens (Drug Search for Leishmaniasis) using unique leishmanial proteins and a database of 600,000 drug-like small molecules. Protein structures from different Leishmania species were selected for molecular dynamics (MD) simulations, and a series of conformational "snapshots" were chosen from each MD trajectory to simulate the protein's flexibility. A Relaxed Complex Scheme methodology was used to screen ~2000 MD conformations against the small molecule database, producing >1 billion protein-ligand structures. For each protein target, a binding spectrum was calculated to identify compounds predicted to bind with highest average affinity to all protein conformations. Significantly, four different Leishmania protein targets were predicted to strongly bind small molecules, with the strongest binding interactions predicted to occur for dihydroorotate dehydrogenase (LmDHODH; PDB:3MJY). A number of predicted tight-binding LmDHODH inhibitors were tested in vitro and potent selective inhibitors of Leishmania panamensis were identified. These promising small molecules are suitable for further development using iterative structure-based optimization and in vitro/in vivo validation assays.

Automatic construction of a recurrent neural network based classifier for vehicle passage detection

NASA Astrophysics Data System (ADS)

Burnaev, Evgeny; Koptelov, Ivan; Novikov, German; Khanipov, Timur

2017-03-01

Recurrent Neural Networks (RNNs) are extensively used for time-series modeling and prediction. We propose an approach for automatic construction of a binary classifier based on Long Short-Term Memory RNNs (LSTM-RNNs) for detection of a vehicle passage through a checkpoint. As an input to the classifier we use multidimensional signals of various sensors that are installed on the checkpoint. Obtained results demonstrate that the previous approach to handcrafting a classifier, consisting of a set of deterministic rules, can be successfully replaced by an automatic RNN training on an appropriately labelled data.

Identification of key residues for protein conformational transition using elastic network model.

PubMed

Su, Ji Guo; Xu, Xian Jin; Li, Chun Hua; Chen, Wei Zu; Wang, Cun Xin

2011-11-07

Proteins usually undergo conformational transitions between structurally disparate states to fulfill their functions. The large-scale allosteric conformational transitions are believed to involve some key residues that mediate the conformational movements between different regions of the protein. In the present work, a thermodynamic method based on the elastic network model is proposed to predict the key residues involved in protein conformational transitions. In our method, the key functional sites are identified as the residues whose perturbations largely influence the free energy difference between the protein states before and after transition. Two proteins, nucleotide binding domain of the heat shock protein 70 and human/rat DNA polymerase β, are used as case studies to identify the critical residues responsible for their open-closed conformational transitions. The results show that the functionally important residues mainly locate at the following regions for these two proteins: (1) the bridging point at the interface between the subdomains that control the opening and closure of the binding cleft; (2) the hinge region between different subdomains, which mediates the cooperative motions between the corresponding subdomains; and (3) the substrate binding sites. The similarity in the positions of the key residues for these two proteins may indicate a common mechanism in their conformational transitions.

Classification of auxin plant hormones by interaction property similarity indices

NASA Astrophysics Data System (ADS)

Tomić, Sanja; Gabdoulline, Razif R.; Kojić-Prodić, Biserka; Wade, Rebecca C.

1998-01-01

Although auxins were the first type of plant hormone to be identified, little is known about the molecular mechanism of this important class of plant hormones. We present a classification of a set of about 50 compounds with measured auxin activities, according to their interaction properties. Four classes of compounds were defined: strongly active, weakly active with weak antiauxin behaviour, inactive and inhibitory. All compounds were modeled in two low-energy conformations, `P' and `T', so as to obtain the best match to the `planar' and `tilted' conformations, respectively, of indole 3-acetic acid. Each set of conformers was superimposed separately using several different alignment schemes. Molecular interaction energy fields were computed for each molecule with five different chemical probes and then compared by computing similarity indices. Similarity analysis showed that the classes are on average distinguishable, with better differentiation achieved for the T conformers than the P conformers. This indicates that the T conformation might be the active one. Further, a screening was developed which could distinguish compounds with auxin activity from inactive compounds and most antiauxins using the T conformers. The classifications rationalize ambiguities in activity data found in the literature and should be of value in predicting the activities of new plant growth substances and herbicides.

Distributions of experimental protein structures on coarse-grained free energy landscapes

PubMed Central

Liu, Jie; Jernigan, Robert L.

2015-01-01

Predicting conformational changes of proteins is needed in order to fully comprehend functional mechanisms. With the large number of available structures in sets of related proteins, it is now possible to directly visualize the clusters of conformations and their conformational transitions through the use of principal component analysis. The most striking observation about the distributions of the structures along the principal components is their highly non-uniform distributions. In this work, we use principal component analysis of experimental structures of 50 diverse proteins to extract the most important directions of their motions, sample structures along these directions, and estimate their free energy landscapes by combining knowledge-based potentials and entropy computed from elastic network models. When these resulting motions are visualized upon their coarse-grained free energy landscapes, the basis for conformational pathways becomes readily apparent. Using three well-studied proteins, T4 lysozyme, serum albumin, and sarco-endoplasmic reticular Ca2+ adenosine triphosphatase (SERCA), as examples, we show that such free energy landscapes of conformational changes provide meaningful insights into the functional dynamics and suggest transition pathways between different conformational states. As a further example, we also show that Monte Carlo simulations on the coarse-grained landscape of HIV-1 protease can directly yield pathways for force-driven conformational changes. PMID:26723638

Automatic assessment of average diaphragm motion trajectory from 4DCT images through machine learning.

PubMed

Li, Guang; Wei, Jie; Huang, Hailiang; Gaebler, Carl Philipp; Yuan, Amy; Deasy, Joseph O

2015-12-01

To automatically estimate average diaphragm motion trajectory (ADMT) based on four-dimensional computed tomography (4DCT), facilitating clinical assessment of respiratory motion and motion variation and retrospective motion study. We have developed an effective motion extraction approach and a machine-learning-based algorithm to estimate the ADMT. Eleven patients with 22 sets of 4DCT images (4DCT1 at simulation and 4DCT2 at treatment) were studied. After automatically segmenting the lungs, the differential volume-per-slice (dVPS) curves of the left and right lungs were calculated as a function of slice number for each phase with respective to the full-exhalation. After 5-slice moving average was performed, the discrete cosine transform (DCT) was applied to analyze the dVPS curves in frequency domain. The dimensionality of the spectrum data was reduced by using several lowest frequency coefficients ( f v ) to account for most of the spectrum energy (Σ f v 2 ). Multiple linear regression (MLR) method was then applied to determine the weights of these frequencies by fitting the ground truth-the measured ADMT, which are represented by three pivot points of the diaphragm on each side. The 'leave-one-out' cross validation method was employed to analyze the statistical performance of the prediction results in three image sets: 4DCT1, 4DCT2, and 4DCT1 + 4DCT2. Seven lowest frequencies in DCT domain were found to be sufficient to approximate the patient dVPS curves ( R = 91%-96% in MLR fitting). The mean error in the predicted ADMT using leave-one-out method was 0.3 ± 1.9 mm for the left-side diaphragm and 0.0 ± 1.4 mm for the right-side diaphragm. The prediction error is lower in 4DCT2 than 4DCT1, and is the lowest in 4DCT1 and 4DCT2 combined. This frequency-analysis-based machine learning technique was employed to predict the ADMT automatically with an acceptable error (0.2 ± 1.6 mm). This volumetric approach is not affected by the presence of the lung tumors, providing an automatic robust tool to evaluate diaphragm motion.

Proline cis-trans isomerization in staphylococcal nuclease: multi-substrate free energy perturbation calculations.

PubMed Central

Hodel, A.; Rice, L. M.; Simonson, T.; Fox, R. O.; Brünger, A. T.

1995-01-01

Staphylococcal nuclease A exists in two folded forms that differ in the isomerization state of the Lys 116-Pro 117 peptide bond. The dominant form (90% occupancy) adopts a cis peptide bond, which is observed in the crystal structure. NMR studies show that the relatively small difference in free energy between the cis and trans forms (delta Gcis-->trans approximately 1.2 kcal/mol) results from large and nearly compensating differences in enthalpy and entropy (delta Hcis-->trans approximately delta TScis-->trans approximately 10 kcal/mol). There is evidence from X-ray crystal structures that the structural differences between the cis and the trans forms of nuclease are confined to the conformation of residues 112-117, a solvated protein loop. Here, we obtain a thermodynamic and structural description of the conformational equilibrium of this protein loop through an exhaustive conformational search that identified several substates followed by free energy simulations between the substrates. By partitioning the search into conformational substates, we overcame the multiple minima problem in this particular case and obtained precise and reproducible free energy values. The protein and water environment was implicitly modeled by appropriately chosen nonbonded terms between the explicitly treated loop and the rest of the protein. These simulations correctly predicted a small free energy difference between the cis and trans forms composed of larger, compensating differences in enthalpy and entropy. The structural predictions of these simulations were qualitatively consistent with known X-ray structures of nuclease variants and yield a model of the unknown minor trans conformation. PMID:7613463

Genetic correlations between methane production and fertility, health, and body type traits in Danish Holstein cows.

PubMed

Zetouni, L; Kargo, M; Norberg, E; Lassen, J

2018-03-01

Our aim was to investigate the genetic correlations between CH 4 production and body conformation, fertility, and health traits in dairy cows. Data were collected from 10 commercial Holstein herds in Denmark, including 5,758 cows with records for body conformation traits, 7,390 for fertility traits, 7,439 for health traits, and 1,397 with individual CH 4 measurements. Methane production was measured during milking in automatic milking systems, using a sniffer approach. Correlations between CH 4 and several different traits were estimated. These traits were interval between calving and first insemination, interval between first and last insemination, number of inseminations, udder diseases, other diseases, height, body depth, chest width, dairy character, top line, and body condition score. Bivariate linear models were used to estimate the genetic parameters within and between CH 4 and the other traits. In general, the genetic correlations between CH 4 and the traits investigated were low. The heritability of CH 4 was 0.25, and ranged from 0.02 to 0.07 for fertility and health traits, and from 0.17 to 0.74 for body conformation traits. Further research with a larger data set should be performed to more accurately establish how CH 4 relates to fertility, health, and body conformation traits in dairy cattle. This will be useful in the design of future breeding goals that consider the production of CH 4 . The Authors. Published by the Federation of Animal Science Societies and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Phonological Awareness and Rapid Automatized Naming Predicting Early Development in Reading and Spelling: Results from a Cross-Linguistic Longitudinal Study

ERIC Educational Resources Information Center

Furnes, Bjarte; Samuelsson, Stefan

2011-01-01

In this study, the relationship between latent constructs of phonological awareness (PA) and rapid automatized naming (RAN) was investigated and related to later measures of reading and spelling in children learning to read in different alphabetic writing systems (i.e., Norwegian/Swedish vs. English). 750 U.S./Australian children and 230…

Validation of Mission Plans Through Simulation

NASA Astrophysics Data System (ADS)

St-Pierre, J.; Melanson, P.; Brunet, C.; Crabtree, D.

2002-01-01

The purpose of a spacecraft mission planning system is to automatically generate safe and optimized mission plans for a single spacecraft, or more functioning in unison. The system verifies user input syntax, conformance to commanding constraints, absence of duty cycle violations, timing conflicts, state conflicts, etc. Present day constraint-based systems with state-based predictive models use verification rules derived from expert knowledge. A familiar solution found in Mission Operations Centers, is to complement the planning system with a high fidelity spacecraft simulator. Often a dedicated workstation, the simulator is frequently used for operator training and procedure validation, and may be interfaced to actual control stations with command and telemetry links. While there are distinct advantages to having a planning system offer realistic operator training using the actual flight control console, physical verification of data transfer across layers and procedure validation, experience has revealed some drawbacks and inefficiencies in ground segment operations: With these considerations, two simulation-based mission plan validation projects are under way at the Canadian Space Agency (CSA): RVMP and ViSION. The tools proposed in these projects will automatically run scenarios and provide execution reports to operations planning personnel, prior to actual command upload. This can provide an important safeguard for system or human errors that can only be detected with high fidelity, interdependent spacecraft models running concurrently. The core element common to these projects is a spacecraft simulator, built with off-the- shelf components such as CAE's Real-Time Object-Based Simulation Environment (ROSE) technology, MathWork's MATLAB/Simulink, and Analytical Graphics' Satellite Tool Kit (STK). To complement these tools, additional components were developed, such as an emulated Spacecraft Test and Operations Language (STOL) interpreter and CCSDS TM/TC encoders and decoders. This paper discusses the use of simulation in the context of space mission planning, describes the projects under way and proposes additional venues of investigation and development.

Protein docking prediction using predicted protein-protein interface.

PubMed

Li, Bin; Kihara, Daisuke

2012-01-10

Many important cellular processes are carried out by protein complexes. To provide physical pictures of interacting proteins, many computational protein-protein prediction methods have been developed in the past. However, it is still difficult to identify the correct docking complex structure within top ranks among alternative conformations. We present a novel protein docking algorithm that utilizes imperfect protein-protein binding interface prediction for guiding protein docking. Since the accuracy of protein binding site prediction varies depending on cases, the challenge is to develop a method which does not deteriorate but improves docking results by using a binding site prediction which may not be 100% accurate. The algorithm, named PI-LZerD (using Predicted Interface with Local 3D Zernike descriptor-based Docking algorithm), is based on a pair wise protein docking prediction algorithm, LZerD, which we have developed earlier. PI-LZerD starts from performing docking prediction using the provided protein-protein binding interface prediction as constraints, which is followed by the second round of docking with updated docking interface information to further improve docking conformation. Benchmark results on bound and unbound cases show that PI-LZerD consistently improves the docking prediction accuracy as compared with docking without using binding site prediction or using the binding site prediction as post-filtering. We have developed PI-LZerD, a pairwise docking algorithm, which uses imperfect protein-protein binding interface prediction to improve docking accuracy. PI-LZerD consistently showed better prediction accuracy over alternative methods in the series of benchmark experiments including docking using actual docking interface site predictions as well as unbound docking cases.

A Value Model for Depressive Symptoms and Hopelessness among University Students in Turkey

ERIC Educational Resources Information Center

Bilican, F. Isil; Yapici, Asim; Kutlu, M. Oguz

2016-01-01

This study aimed to examine which values predicted depressive symptoms and hopelessness in Turkey. While it was hypothesized that values emphasizing universalism, benevolence, conformity, security, tradition, spirituality, self-direction, and achievement would predict lower levels of depressive symptoms and hopelessness, those values emphasizing…

Why significant variables aren't automatically good predictors.

PubMed

Lo, Adeline; Chernoff, Herman; Zheng, Tian; Lo, Shaw-Hwa

2015-11-10

Thus far, genome-wide association studies (GWAS) have been disappointing in the inability of investigators to use the results of identified, statistically significant variants in complex diseases to make predictions useful for personalized medicine. Why are significant variables not leading to good prediction of outcomes? We point out that this problem is prevalent in simple as well as complex data, in the sciences as well as the social sciences. We offer a brief explanation and some statistical insights on why higher significance cannot automatically imply stronger predictivity and illustrate through simulations and a real breast cancer example. We also demonstrate that highly predictive variables do not necessarily appear as highly significant, thus evading the researcher using significance-based methods. We point out that what makes variables good for prediction versus significance depends on different properties of the underlying distributions. If prediction is the goal, we must lay aside significance as the only selection standard. We suggest that progress in prediction requires efforts toward a new research agenda of searching for a novel criterion to retrieve highly predictive variables rather than highly significant variables. We offer an alternative approach that was not designed for significance, the partition retention method, which was very effective predicting on a long-studied breast cancer data set, by reducing the classification error rate from 30% to 8%.

Neural signatures of social conformity: A coordinate-based activation likelihood estimation meta-analysis of functional brain imaging studies.

PubMed

Wu, Haiyan; Luo, Yi; Feng, Chunliang

2016-12-01

People often align their behaviors with group opinions, known as social conformity. Many neuroscience studies have explored the neuropsychological mechanisms underlying social conformity. Here we employed a coordinate-based meta-analysis on neuroimaging studies of social conformity with the purpose to reveal the convergence of the underlying neural architecture. We identified a convergence of reported activation foci in regions associated with normative decision-making, including ventral striatum (VS), dorsal posterior medial frontal cortex (dorsal pMFC), and anterior insula (AI). Specifically, consistent deactivation of VS and activation of dorsal pMFC and AI are identified when people's responses deviate from group opinions. In addition, the deviation-related responses in dorsal pMFC predict people's conforming behavioral adjustments. These are consistent with current models that disagreement with others might evoke "error" signals, cognitive imbalance, and/or aversive feelings, which are plausibly detected in these brain regions as control signals to facilitate subsequent conforming behaviors. Finally, group opinions result in altered neural correlates of valuation, manifested as stronger responses of VS to stimuli endorsed than disliked by others. Copyright © 2016 Elsevier Ltd. All rights reserved.

Characterizing the Conformational Landscape of Flavivirus Fusion Peptides via Simulation and Experiment

PubMed Central

Marzinek, Jan K.; Lakshminarayanan, Rajamani; Goh, Eunice; Huber, Roland G.; Panzade, Sadhana; Verma, Chandra; Bond, Peter J.

2016-01-01

Conformational changes in the envelope proteins of flaviviruses help to expose the highly conserved fusion peptide (FP), a region which is critical to membrane fusion and host cell infection, and which represents a significant target for antiviral drugs and antibodies. In principle, extended timescale atomic-resolution simulations may be used to characterize the dynamics of such peptides. However, the resultant accuracy is critically dependent upon both the underlying force field and sufficient conformational sampling. In the present study, we report a comprehensive comparison of three simulation methods and four force fields comprising a total of more than 40 μs of sampling. Additionally, we describe the conformational landscape of the FP fold across all flavivirus family members. All investigated methods sampled conformations close to available X-ray structures, but exhibited differently populated ensembles. The best force field / sampling combination was sufficiently accurate to predict that the solvated peptide fold is less ordered than in the crystallographic state, which was subsequently confirmed via circular dichroism and spectrofluorometric measurements. Finally, the conformational landscape of a mutant incapable of membrane fusion was significantly shallower than wild-type variants, suggesting that dynamics should be considered when therapeutically targeting FP epitopes. PMID:26785994

Molecular dynamics study of the conformational properties of cyclohexadecane

NASA Astrophysics Data System (ADS)

Zhang, Renshi; Mattice, Wayne L.

1993-06-01

Molecular dynamics has been used for the first time for the study of the conformational properties of cyclohexadecane, c-C16H32. By analyzing a long molecular dynamics trajectory (14.5 ns) at 450 K, equilibrium statistics such as the relative populations of different isomeric conformers and the probability ratios, p(gt)/p(tt), p(gg)/p(tt), and p(gg)/p(gtg), of different conformational segments, have been studied. The dynamic properties including the transition modes of gauche migration and gauche-pair creation, which have been reported before in n-alkanes, and the auto- and cross-correlations of the bond dihedral angles, have also been obtained. It was possible to make direct comparisons on some of the statistics with theory and experiment. Most of the results extracted from the molecular dynamics trajectory lie in between previously reported experimental and theoretical values. Many previously predicted conformers have been confirmed by our simulations. The results of the population probability of the most populated conformer seems to suggest that an earlier discrepancy between the theoretical works and an experimental work originates from insufficient samplings in earlier theoretical works, rather than from their inaccurate force field.

Sixty-five years of the long march in protein secondary structure prediction: the final stretch?

PubMed Central

Yang, Yuedong; Gao, Jianzhao; Wang, Jihua; Heffernan, Rhys; Hanson, Jack; Paliwal, Kuldip; Zhou, Yaoqi

2018-01-01

Abstract Protein secondary structure prediction began in 1951 when Pauling and Corey predicted helical and sheet conformations for protein polypeptide backbone even before the first protein structure was determined. Sixty-five years later, powerful new methods breathe new life into this field. The highest three-state accuracy without relying on structure templates is now at 82–84%, a number unthinkable just a few years ago. These improvements came from increasingly larger databases of protein sequences and structures for training, the use of template secondary structure information and more powerful deep learning techniques. As we are approaching to the theoretical limit of three-state prediction (88–90%), alternative to secondary structure prediction (prediction of backbone torsion angles and Cα-atom-based angles and torsion angles) not only has more room for further improvement but also allows direct prediction of three-dimensional fragment structures with constantly improved accuracy. About 20% of all 40-residue fragments in a database of 1199 non-redundant proteins have <6 Å root-mean-squared distance from the native conformations by SPIDER2. More powerful deep learning methods with improved capability of capturing long-range interactions begin to emerge as the next generation of techniques for secondary structure prediction. The time has come to finish off the final stretch of the long march towards protein secondary structure prediction. PMID:28040746

Progress in protein-protein docking: atomic resolution predictions in the CAPRI experiment using RosettaDock with an improved treatment of side-chain flexibility.

PubMed

Schueler-Furman, Ora; Wang, Chu; Baker, David

2005-08-01

RosettaDock uses real-space Monte Carlo minimization (MCM) on both rigid-body and side-chain degrees of freedom to identify the lowest free energy docked arrangement of 2 protein structures. An improved version of the method that uses gradient-based minimization for off-rotamer side-chain optimization and includes information from unbound structures was used to create predictions for Rounds 4 and 5 of CAPRI. First, large numbers of independent MCM trajectories were carried out and the lowest free energy docked configurations identified. Second, new trajectories were started from these lowest energy structures to thoroughly sample the surrounding conformation space, and the lowest energy configurations were submitted as predictions. For all cases in which there were no significant backbone conformational changes, a small number of very low-energy configurations were identified in the first, global search and subsequently found to be close to the center of the basin of attraction in the free energy landscape in the second, local search. Following the release of the experimental coordinates, it was found that the centers of these free energy minima were remarkably close to the native structures in not only the rigid-body orientation but also the detailed conformations of the side-chains. Out of 8 targets, the lowest energy models had interface root-mean-square deviations (RMSDs) less than 1.1 A from the correct structures for 6 targets, and interface RMSDs less than 0.4 A for 3 targets. The predictions were top submissions to CAPRI for Targets 11, 12, 14, 15, and 19. The close correspondence of the lowest free energy structures found in our searches to the experimental structures suggests that our free energy function is a reasonable representation of the physical chemistry, and that the real space search with full side-chain flexibility to some extent solves the protein-protein docking problem in the absence of significant backbone conformational changes. On the other hand, the approach fails when there are significant backbone conformational changes as the steric complementarity of the 2 proteins cannot be modeled without incorporating backbone flexibility, and this is the major goal of our current work.

Investigating the Effect of Advanced Automatic Transmissions of Fuel Consumption Using Vehicle Testing and Modeling (SAE 2016-01-1142)

EPA Science Inventory

EPA used the validated ALPHA model to predict the effectiveness improvement of real-world transmissions over a baseline four-speed transmission and to predict further improvements possible from future eight-speed transmissions.

Predicting conformational ensembles and genome-wide transcription factor binding sites from DNA sequences.

PubMed

Andrabi, Munazah; Hutchins, Andrew Paul; Miranda-Saavedra, Diego; Kono, Hidetoshi; Nussinov, Ruth; Mizuguchi, Kenji; Ahmad, Shandar

2017-06-22

DNA shape is emerging as an important determinant of transcription factor binding beyond just the DNA sequence. The only tool for large scale DNA shape estimates, DNAshape was derived from Monte-Carlo simulations and predicts four broad and static DNA shape features, Propeller twist, Helical twist, Minor groove width and Roll. The contributions of other shape features e.g. Shift, Slide and Opening cannot be evaluated using DNAshape. Here, we report a novel method DynaSeq, which predicts molecular dynamics-derived ensembles of a more exhaustive set of DNA shape features. We compared the DNAshape and DynaSeq predictions for the common features and applied both to predict the genome-wide binding sites of 1312 TFs available from protein interaction quantification (PIQ) data. The results indicate a good agreement between the two methods for the common shape features and point to advantages in using DynaSeq. Predictive models employing ensembles from individual conformational parameters revealed that base-pair opening - known to be important in strand separation - was the best predictor of transcription factor-binding sites (TFBS) followed by features employed by DNAshape. Of note, TFBS could be predicted not only from the features at the target motif sites, but also from those as far as 200 nucleotides away from the motif.

CisMapper: predicting regulatory interactions from transcription factor ChIP-seq data

PubMed Central

O'Connor, Timothy; Bodén, Mikael

2017-01-01

Abstract Identifying the genomic regions and regulatory factors that control the transcription of genes is an important, unsolved problem. The current method of choice predicts transcription factor (TF) binding sites using chromatin immunoprecipitation followed by sequencing (ChIP-seq), and then links the binding sites to putative target genes solely on the basis of the genomic distance between them. Evidence from chromatin conformation capture experiments shows that this approach is inadequate due to long-distance regulation via chromatin looping. We present CisMapper, which predicts the regulatory targets of a TF using the correlation between a histone mark at the TF's bound sites and the expression of each gene across a panel of tissues. Using both chromatin conformation capture and differential expression data, we show that CisMapper is more accurate at predicting the target genes of a TF than the distance-based approaches currently used, and is particularly advantageous for predicting the long-range regulatory interactions typical of tissue-specific gene expression. CisMapper also predicts which TF binding sites regulate a given gene more accurately than using genomic distance. Unlike distance-based methods, CisMapper can predict which transcription start site of a gene is regulated by a particular binding site of the TF. PMID:28204599

Toward a detailed understanding of search trajectories in fragment assembly approaches to protein structure prediction

PubMed Central

Handl, Julia; Lovell, Simon C.

2016-01-01

ABSTRACT Energy functions, fragment libraries, and search methods constitute three key components of fragment‐assembly methods for protein structure prediction, which are all crucial for their ability to generate high‐accuracy predictions. All of these components are tightly coupled; efficient searching becomes more important as the quality of fragment libraries decreases. Given these relationships, there is currently a poor understanding of the strengths and weaknesses of the sampling approaches currently used in fragment‐assembly techniques. Here, we determine how the performance of search techniques can be assessed in a meaningful manner, given the above problems. We describe a set of techniques that aim to reduce the impact of the energy function, and assess exploration in view of the search space defined by a given fragment library. We illustrate our approach using Rosetta and EdaFold, and show how certain features of these methods encourage or limit conformational exploration. We demonstrate that individual trajectories of Rosetta are susceptible to local minima in the energy landscape, and that this can be linked to non‐uniform sampling across the protein chain. We show that EdaFold's novel approach can help balance broad exploration with locating good low‐energy conformations. This occurs through two mechanisms which cannot be readily differentiated using standard performance measures: exclusion of false minima, followed by an increasingly focused search in low‐energy regions of conformational space. Measures such as ours can be helpful in characterizing new fragment‐based methods in terms of the quality of conformational exploration realized. Proteins 2016; 84:411–426. © 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc. PMID:26799916

Correlation Functions in Two-Dimensional Critical Systems with Conformal Symmetry

NASA Astrophysics Data System (ADS)

Flores, Steven Miguel

This thesis presents a study of certain conformal field theory (CFT) correlation functions that describe physical observables in conform ally invariant two-dimensional critical systems. These are typically continuum limits of critical lattice models in a domain within the complex plane and with a boundary. Certain clusters, called boundary clusters, anchor to the boundary of the domain, and many of their features are governed by a conformally invariant probability measure. For example, percolaion is an example of a critical lattice model, and when it is confined to a domain with a boundary, connected clusters of activated bonds that touch that boundary are the boundary clusters. This thesis is concerned with how the boundary clusters interact with each other according to that measure. One question that it considers are "how likely are these clusters to repel each other or to connect with one another in a certain topological configuration?" Chapter one non-rigorously derives an already well-known elliptic system of differential equations closely tied to this matter by using standard techniques of CFT, chapters two and three rigorously infer certain properties concerning the solution space of this system, and chapter four uses some of those results to predict an answer to this question. This thesis also considers local variations of this question such as "what regions of the domain do the perimeters of the boundary clusters explore," and "how often will several boundary clusters connect at just a single, specified point in the domain?" Chapter five predicts precise answers to these questions. All of these answers are quantitative predictions that we verify via high-precision computer simulation. Chapters four and five also present these simulation results. Further material that supplements chapter one is included in two appendices.

13C ENDOR Spectroscopy of Lipoxygenase-Substrate Complexes Reveals the Structural Basis for C-H Activation by Tunneling.

PubMed

Horitani, Masaki; Offenbacher, Adam R; Carr, Cody A Marcus; Yu, Tao; Hoeke, Veronika; Cutsail, George E; Hammes-Schiffer, Sharon; Klinman, Judith P; Hoffman, Brian M

2017-02-08

In enzymatic C-H activation by hydrogen tunneling, reduced barrier width is important for efficient hydrogen wave function overlap during catalysis. For native enzymes displaying nonadiabatic tunneling, the dominant reactive hydrogen donor-acceptor distance (DAD) is typically ca. 2.7 Å, considerably shorter than normal van der Waals distances. Without a ground state substrate-bound structure for the prototypical nonadiabatic tunneling system, soybean lipoxygenase (SLO), it has remained unclear whether the requisite close tunneling distance occurs through an unusual ground state active site arrangement or by thermally sampling conformational substates. Herein, we introduce Mn 2+ as a spin-probe surrogate for the SLO Fe ion; X-ray diffraction shows Mn-SLO is structurally faithful to the native enzyme. 13 C ENDOR then reveals the locations of 13 C10 and reactive 13 C11 of linoleic acid relative to the metal; 1 H ENDOR and molecular dynamics simulations of the fully solvated SLO model using ENDOR-derived restraints give additional metrical information. The resulting three-dimensional representation of the SLO active site ground state contains a reactive (a) conformer with hydrogen DAD of ∼3.1 Å, approximately van der Waals contact, plus an inactive (b) conformer with even longer DAD, establishing that stochastic conformational sampling is required to achieve reactive tunneling geometries. Tunneling-impaired SLO variants show increased DADs and variations in substrate positioning and rigidity, confirming previous kinetic and theoretical predictions of such behavior. Overall, this investigation highlights the (i) predictive power of nonadiabatic quantum treatments of proton-coupled electron transfer in SLO and (ii) sensitivity of ENDOR probes to test, detect, and corroborate kinetically predicted trends in active site reactivity and to reveal unexpected features of active site architecture.

Conformational properties of a pyridyl-substituted cinnamic acid studied by NMR measurements and computations

NASA Astrophysics Data System (ADS)

Csankó, K.; Forgo, P.; Boros, K.; Hohmann, J.; Sipos, P.; Pálinkó, I.

2013-07-01

Following a preliminary exploration of the conformational space by the PM3 and HF/6-31 G*ab initio methods the conformational characteristics of the scarcely available Z isomer of an α-pyridyl-substituted cinnamic acid dimer [Z-2(3‧-pyridyl)-3-phenylpropanoic acid] was studied by NMR spectroscopy (NOESY measurements) in DMSO(d6), methanol(d4) and chloroform(d1). Calculations predicted that full conjugation was overruled by steric interactions and the rotation of the pyridyl ring was not restricted. NOESY measurements verified indeed that in all three solvents the pyridyl group was virtually freely rotating, while some restriction applied for that of the phenyl group.

Automatic variable selection method and a comparison for quantitative analysis in laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Duan, Fajie; Fu, Xiao; Jiang, Jiajia; Huang, Tingting; Ma, Ling; Zhang, Cong

2018-05-01

In this work, an automatic variable selection method for quantitative analysis of soil samples using laser-induced breakdown spectroscopy (LIBS) is proposed, which is based on full spectrum correction (FSC) and modified iterative predictor weighting-partial least squares (mIPW-PLS). The method features automatic selection without artificial processes. To illustrate the feasibility and effectiveness of the method, a comparison with genetic algorithm (GA) and successive projections algorithm (SPA) for different elements (copper, barium and chromium) detection in soil was implemented. The experimental results showed that all the three methods could accomplish variable selection effectively, among which FSC-mIPW-PLS required significantly shorter computation time (12 s approximately for 40,000 initial variables) than the others. Moreover, improved quantification models were got with variable selection approaches. The root mean square errors of prediction (RMSEP) of models utilizing the new method were 27.47 (copper), 37.15 (barium) and 39.70 (chromium) mg/kg, which showed comparable prediction effect with GA and SPA.

The construction of ``realistic'' four-dimensional strings through orbifolds

NASA Astrophysics Data System (ADS)

Font, A.; Ibáñez, L. E.; Quevedo, F.; Sierra, A.

1990-02-01

We discuss the construction of "realistic" lower rank 4-dimensional strings, through symmetric orbifolds with background fields. We present Z 3 three-generation SU(3) × SU(2) × U(1) models as well as models incorporating a left-right SU(2) L × SU(2) R × U(1) B-L symmetry in which proton stability is automatically guaranteed. Conformal field theory selection rules are used to find the flat directions to all orders which lead to these low-rank models and to study the relevant Yukawa couplings. A hierarchical structure of quark-lepton masses appears naturally in some models. We also present a detailed study of the structure of the Z 3 × Z 3 orbifold including the generalized GSO projection, the effect of discrete torsion and the conformal field theory Yukawa coupling selection rules. All these points are illustrated with a three-generation Z 3 × Z 3 model. We have made an effort to write a self-contained presentation in order to make this material available to non-string experts interested in the phenomenological aspects of this theory.

A python tool for the implementation of domain-specific languages

NASA Astrophysics Data System (ADS)

Dejanović, Igor; Vaderna, Renata; Milosavljević, Gordana; Simić, Miloš; Vuković, Željko

2017-07-01

In this paper we describe textX, a meta-language and a tool for building Domain-Specific Languages. It is implemented in Python using Arpeggio PEG (Parsing Expression Grammar) parser library. From a single language description (grammar) textX will build a parser and a meta-model (a.k.a. abstract syntax) of the language. The parser is used to parse textual representations of models conforming to the meta-model. As a result of parsing, a Python object graph will be automatically created. The structure of the object graph will conform to the meta-model defined by the grammar. This approach frees a developer from the need to manually analyse a parse tree and transform it to other suitable representation. The textX library is independent of any integrated development environment and can be easily integrated in any Python project. The textX tool works as a grammar interpreter. The parser is configured at run-time using the grammar. The textX tool is a free and open-source project available at GitHub.

SuperNatural: a searchable database of available natural compounds

PubMed Central

Dunkel, Mathias; Fullbeck, Melanie; Neumann, Stefanie; Preissner, Robert

2006-01-01

Although tremendous effort has been put into synthetic libraries, most drugs on the market are still natural compounds or derivatives thereof. There are encyclopaedias of natural compounds, but the availability of these compounds is often unclear and catalogues from numerous suppliers have to be checked. To overcome these problems we have compiled a database of ∼50 000 natural compounds from different suppliers. To enable efficient identification of the desired compounds, we have implemented substructure searches with typical templates. Starting points for in silico screenings are about 2500 well-known and classified natural compounds from a compendium that we have added. Possible medical applications can be ascertained via automatic searches for similar drugs in a free conformational drug database containing WHO indications. Furthermore, we have computed about three million conformers, which are deployed to account for the flexibilities of the compounds when the 3D superposition algorithm that we have developed is used. The SuperNatural Database is publicly available at . Viewing requires the free Chime-plugin from MDL (Chime) or Java2 Runtime Environment (MView), which is also necessary for using Marvin application for chemical drawing. PMID:16381957

Near-field testing of the 15-meter hoop-column antenna

NASA Technical Reports Server (NTRS)

Schroeder, Lyle C.; Adams, Richard R.; Bailey, M. C.; Belvin, W. Keith; Butler, David H.; Campbell, Thomas G.

1989-01-01

A 15-m-diameter antenna was tested to verify that dimensional tolerances for acceptable performance could be achieved and to verify structural, electromagnetic, and mechanical performance predictions. This antenna utilized the hoop column structure, a gold plated molybdenum mesh reflector, and 96 control cables to adjust the reflector conformance with a paraboloid. The dimensional conformance of the antenna structure and surface was measured with metric camera and theodolites. Near field pattern data were used to assess the electromagnetic performance at five frequencies from 2.225 to 11.6 GHz. The reflector surface was adjusted to greatly improve electromagnetic performance with a finite element model and the surface measurements. Measurement results show that antenna surface figure and adjustments and electromagnetic patterns agree well with predictions.

Blind Pose Prediction, Scoring, and Affinity Ranking of the CSAR 2014 Dataset.

PubMed

Martiny, Virginie Y; Martz, François; Selwa, Edithe; Iorga, Bogdan I

2016-06-27

The 2014 CSAR Benchmark Exercise was focused on three protein targets: coagulation factor Xa, spleen tyrosine kinase, and bacterial tRNA methyltransferase. Our protocol involved a preliminary analysis of the structural information available in the Protein Data Bank for the protein targets, which allowed the identification of the most appropriate docking software and scoring functions to be used for the rescoring of several docking conformations datasets, as well as for pose prediction and affinity ranking. The two key points of this study were (i) the prior evaluation of molecular modeling tools that are most adapted for each target and (ii) the increased search efficiency during the docking process to better explore the conformational space of big and flexible ligands.

Multiple Simulated Annealing-Molecular Dynamics (MSA-MD) for Conformational Space Search of Peptide and Miniprotein

PubMed Central

Hao, Ge-Fei; Xu, Wei-Fang; Yang, Sheng-Gang; Yang, Guang-Fu

2015-01-01

Protein and peptide structure predictions are of paramount importance for understanding their functions, as well as the interactions with other molecules. However, the use of molecular simulation techniques to directly predict the peptide structure from the primary amino acid sequence is always hindered by the rough topology of the conformational space and the limited simulation time scale. We developed here a new strategy, named Multiple Simulated Annealing-Molecular Dynamics (MSA-MD) to identify the native states of a peptide and miniprotein. A cluster of near native structures could be obtained by using the MSA-MD method, which turned out to be significantly more efficient in reaching the native structure compared to continuous MD and conventional SA-MD simulation. PMID:26492886

[The mediating role of anger in the relationship between automatic thoughts and physical aggression in adolescents].

PubMed

Yavuzer, Yasemin; Karataş, Zeynep

2013-01-01

This study aimed to examine the mediating role of anger in the relationship between automatic thoughts and physical aggression in adolescents. The study included 224 adolescents in the 9th grade of 3 different high schools in central Burdur during the 2011-2012 academic year. Participants completed the Aggression Questionnaire and Automatic Thoughts Scale in their classrooms during counseling sessions. Data were analyzed using simple and multiple linear regression analysis. There were positive correlations between the adolescents' automatic thoughts, and physical aggression, and anger. According to regression analysis, automatic thoughts effectively predicted the level of physical aggression (b= 0.233, P < 0.001)) and anger (b= 0.325, P < 0.001). Analysis of the mediating role of anger showed that anger fully mediated the relationship between automatic thoughts and physical aggression (Sobel z = 5.646, P < 0.001). Anger fully mediated the relationship between automatic thoughts and physical aggression. Providing adolescents with anger management skills training is very important for the prevention of physical aggression. Such training programs should include components related to the development of an awareness of dysfunctional and anger-triggering automatic thoughts, and how to change them. As the study group included adolescents from Burdur, the findings can only be generalized to groups with similar characteristics.

The system neurophysiological basis of non-adaptive cognitive control: Inhibition of implicit learning mediated by right prefrontal regions.

PubMed

Stock, Ann-Kathrin; Steenbergen, Laura; Colzato, Lorenza; Beste, Christian

2016-12-01

Cognitive control is adaptive in the sense that it inhibits automatic processes to optimize goal-directed behavior, but high levels of control may also have detrimental effects in case they suppress beneficial automatisms. Until now, the system neurophysiological mechanisms and functional neuroanatomy underlying these adverse effects of cognitive control have remained elusive. This question was examined by analyzing the automatic exploitation of a beneficial implicit predictive feature under conditions of high versus low cognitive control demands, combining event-related potentials (ERPs) and source localization. It was found that cognitive control prohibits the beneficial automatic exploitation of additional implicit information when task demands are high. Bottom-up perceptual and attentional selection processes (P1 and N1 ERPs) are not modulated by this, but the automatic exploitation of beneficial predictive information in case of low cognitive control demands was associated with larger response-locked P3 amplitudes and stronger activation of the right inferior frontal gyrus (rIFG, BA47). This suggests that the rIFG plays a key role in the detection of relevant task cues, the exploitation of alternative task sets, and the automatic (bottom-up) implementation and reprogramming of action plans. Moreover, N450 amplitudes were larger under high cognitive control demands, which was associated with activity differences in the right medial frontal gyrus (BA9). This most likely reflects a stronger exploitation of explicit task sets which hinders the exploration of the implicit beneficial information in case of high cognitive control demands. Hum Brain Mapp 37:4511-4522, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

SU-F-T-352: Development of a Knowledge Based Automatic Lung IMRT Planning Algorithm with Non-Coplanar Beams

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, W; Wu, Q; Yuan, L

Purpose: To improve the robustness of a knowledge based automatic lung IMRT planning method and to further validate the reliability of this algorithm by utilizing for the planning of clinical cases with non-coplanar beams. Methods: A lung IMRT planning method which automatically determines both plan optimization objectives and beam configurations with non-coplanar beams has been reported previously. A beam efficiency index map is constructed to guide beam angle selection in this algorithm. This index takes into account both the dose contributions from individual beams and the combined effect of multiple beams which is represented by a beam separation score. Wemore » studied the effect of this beam separation score on plan quality and determined the optimal weight for this score.14 clinical plans were re-planned with the knowledge-based algorithm. Significant dosimetric metrics for the PTV and OARs in the automatic plans are compared with those in the clinical plans by the two-sample t-test. In addition, a composite dosimetric quality index was defined to obtain the relationship between the plan quality and the beam separation score. Results: On average, we observed more than 15% reduction on conformity index and homogeneity index for PTV and V{sub 40}, V{sub 60} for heart while an 8% and 3% increase on V{sub 5}, V{sub 20} for lungs, respectively. The variation curve of the composite index as a function of angle spread score shows that 0.6 is the best value for the weight of the beam separation score. Conclusion: Optimal value for beam angle spread score in automatic lung IMRT planning is obtained. With this value, model can result in statistically the “best” achievable plans. This method can potentially improve the quality and planning efficiency for IMRT plans with no-coplanar angles.« less

Controlled versus automatic processes: which is dominant to safety? The moderating effect of inhibitory control.

PubMed

Xu, Yaoshan; Li, Yongjuan; Ding, Weidong; Lu, Fan

2014-01-01

This study explores the precursors of employees' safety behaviors based on a dual-process model, which suggests that human behaviors are determined by both controlled and automatic cognitive processes. Employees' responses to a self-reported survey on safety attitudes capture their controlled cognitive process, while the automatic association concerning safety measured by an Implicit Association Test (IAT) reflects employees' automatic cognitive processes about safety. In addition, this study investigates the moderating effects of inhibition on the relationship between self-reported safety attitude and safety behavior, and that between automatic associations towards safety and safety behavior. The results suggest significant main effects of self-reported safety attitude and automatic association on safety behaviors. Further, the interaction between self-reported safety attitude and inhibition and that between automatic association and inhibition each predict unique variances in safety behavior. Specifically, the safety behaviors of employees with lower level of inhibitory control are influenced more by automatic association, whereas those of employees with higher level of inhibitory control are guided more by self-reported safety attitudes. These results suggest that safety behavior is the joint outcome of both controlled and automatic cognitive processes, and the relative importance of these cognitive processes depends on employees' individual differences in inhibitory control. The implications of these findings for theoretical and practical issues are discussed at the end.

Controlled versus Automatic Processes: Which Is Dominant to Safety? The Moderating Effect of Inhibitory Control

PubMed Central

Xu, Yaoshan; Li, Yongjuan; Ding, Weidong; Lu, Fan

2014-01-01

This study explores the precursors of employees' safety behaviors based on a dual-process model, which suggests that human behaviors are determined by both controlled and automatic cognitive processes. Employees' responses to a self-reported survey on safety attitudes capture their controlled cognitive process, while the automatic association concerning safety measured by an Implicit Association Test (IAT) reflects employees' automatic cognitive processes about safety. In addition, this study investigates the moderating effects of inhibition on the relationship between self-reported safety attitude and safety behavior, and that between automatic associations towards safety and safety behavior. The results suggest significant main effects of self-reported safety attitude and automatic association on safety behaviors. Further, the interaction between self-reported safety attitude and inhibition and that between automatic association and inhibition each predict unique variances in safety behavior. Specifically, the safety behaviors of employees with lower level of inhibitory control are influenced more by automatic association, whereas those of employees with higher level of inhibitory control are guided more by self-reported safety attitudes. These results suggest that safety behavior is the joint outcome of both controlled and automatic cognitive processes, and the relative importance of these cognitive processes depends on employees' individual differences in inhibitory control. The implications of these findings for theoretical and practical issues are discussed at the end. PMID:24520338

The CoFactor database: organic cofactors in enzyme catalysis.

PubMed

Fischer, Julia D; Holliday, Gemma L; Thornton, Janet M

2010-10-01

Organic enzyme cofactors are involved in many enzyme reactions. Therefore, the analysis of cofactors is crucial to gain a better understanding of enzyme catalysis. To aid this, we have created the CoFactor database. CoFactor provides a web interface to access hand-curated data extracted from the literature on organic enzyme cofactors in biocatalysis, as well as automatically collected information. CoFactor includes information on the conformational and solvent accessibility variation of the enzyme-bound cofactors, as well as mechanistic and structural information about the hosting enzymes. The database is publicly available and can be accessed at http://www.ebi.ac.uk/thornton-srv/databases/CoFactor.

An exact operator that knows its location

NASA Astrophysics Data System (ADS)

Anand, N.; Chen, Hongbin; Fitzpatrick, A. Liam; Kaplan, Jared; Li, Daliang

2018-02-01

We use conformal symmetry to define an AdS3 proto-field ϕ as an exact linear combination of Virasoro descendants of a CFT2 primary operator O . We find that both symmetry considerations and a gravitational Wilson line formalism lead to the same results. The operator ϕ has many desirable properties; in particular it has correlators that agree with gravitational perturbation theory when expanded at large c, and that automatically take the correct form in all vacuum AdS3 geometries, including BTZ black hole backgrounds. In the future it should be possible to use ϕ to probe bulk locality and black hole horizons at a non-perturbative level.

Configurations of base-pair complexes in solutions. [nucleotide chemistry

NASA Technical Reports Server (NTRS)

Egan, J. T.; Nir, S.; Rein, R.; Macelroy, R.

1978-01-01

A theoretical search for the most stable conformations (i.e., stacked or hydrogen bonded) of the base pairs A-U and G-C in water, CCl4, and CHCl3 solutions is presented. The calculations of free energies indicate a significant role of the solvent in determining the conformations of the base-pair complexes. The application of the continuum method yields preferred conformations in good agreement with experiment. Results of the calculations with this method emphasize the importance of both the electrostatic interactions between the two bases in a complex, and the dipolar interaction of the complex with the entire medium. In calculations with the solvation shell method, the last term, i.e., dipolar interaction of the complex with the entire medium, was added. With this modification the prediction of the solvation shell model agrees both with the continuum model and with experiment, i.e., in water the stacked conformation of the bases is preferred.

Excited-state dynamics of bis(9-fluorenyl)methane and its derivative 9-(9-ethylfluorenyl)-9'-fluorenylmethane: steric effect on energetics and dynamics of ground- and excited-state conformations.

PubMed

Boo, Bong Hyun; Lee, Minyung; Jeon, Ki-Seok; Kim, Seung-Joon

2014-03-27

Intramolecular excimer formation of bis(9-fluorenyl)methane (BFM) and 9-(9'-ethylfluorenyl)-9-fluorenylmethane (EFFM), in which an ethyl group is substituted to a 9-H atom in BFM, was studied by means of steady-state and time-resolved fluorescence. Ab initio and DFT calculations enabled the prediction of three conformers as stable species of orthogonal, trans-gauche, and gauche-gauche. The theoretical and experimental results reveal that the substitution effect is also found to appreciably influence the energies, spectroscopy, and kinetics associated with the interconversion of various conformers of the diaryl compounds. We have not observed the rising components in the excimer fluorescence decay of BFM and EFFM in PMMA as observed in the liquid solutions probably because of the existence of the sandwich conformer responsible for the excimer fluorescence prior to the laser irradiation.

Conformational change of adenosine deaminase during ligand-exchange in a crystal.

PubMed

Kinoshita, Takayoshi; Tada, Toshiji; Nakanishi, Isao

2008-08-15

Adenosine deaminase (ADA) perpetuates chronic inflammation by degrading extracellular adenosine which is toxic for lymphocytes. ADA has two distinct conformations: open form and closed form. From the crystal structures with various ligands, the non-nucleoside type inhibitors bind to the active site occupying the critical water-binding-position and sustain the open form of apo-ADA. In contrast, substrate mimics do not occupy the critical position, and induce the large conformational change to the closed form. However, it is difficult to predict the binding of (+)-erythro-9-(2-hydroxy-3-nonyl)adenine (EHNA), as it possesses characteristic parts of both the substrate and the non-nucleoside inhibitors. The crystal structure shows that EHNA binds to the open form through a novel recognition of the adenine base accompanying conformational change from the closed form of the PR-ADA complex in crystalline state.

Fitting of Hadron Mass Spectra and Contributions to Perturbation Theory of Conformal Quantum Field Theory

NASA Astrophysics Data System (ADS)

Luna Acosta, German Aurelio

The masses of observed hadrons are fitted according to the kinematic predictions of Conformal Relativity. The hypothesis gives a remarkably good fit. The isospin SU(2) gauge invariant Lagrangian L(,(pi)NN)(x,(lamda)) is used in the calculation of d(sigma)/d(OMEGA) to 2nd-order Feynman graphs for simplified models of (pi)N(--->)(pi)N. The resulting infinite mass sums over the nucleon (Conformal) families are done via the Generalized-Sommerfeld-Watson Transform Theorem. Even though the models are too simple to be realistic, they indicate that if (DELTA)-internal lines were to be included, 2nd-order Feynman graphs may reproduce the experimental data qualitatively. The energy -dependence of the propagator and couplings in Conformal QFT is different from that of ordinary QFT. Suggestions for further work are made in the areas of ultra-violet divergences and OPEC calculations.

Combining theoretical and experimental data to decipher CFTR 3D structures and functions.

PubMed

Hoffmann, Brice; Elbahnsi, Ahmad; Lehn, Pierre; Décout, Jean-Luc; Pietrucci, Fabio; Mornon, Jean-Paul; Callebaut, Isabelle

2018-05-19

Cryo-electron microscopy (cryo-EM) has recently provided invaluable experimental data about the full-length cystic fibrosis transmembrane conductance regulator (CFTR) 3D structure. However, this experimental information deals with inactive states of the channel, either in an apo, quiescent conformation, in which nucleotide-binding domains (NBDs) are widely separated or in an ATP-bound, yet closed conformation. Here, we show that 3D structure models of the open and closed forms of the channel, now further supported by metadynamics simulations and by comparison with the cryo-EM data, could be used to gain some insights into critical features of the conformational transition toward active CFTR forms. These critical elements lie within membrane-spanning domains but also within NBD1 and the N-terminal extension, in which conformational plasticity is predicted to occur to help the interaction with filamin, one of the CFTR cellular partners.

How Conformational Dynamics of DNA Polymerase Select Correct Substrates: Experiments and Simulations

PubMed Central

Kirmizialtin, Serdal; Nguyen, Virginia; Johnson, Kenneth A.; Elber, Ron

2012-01-01

Summary Nearly every enzyme undergoes a significant change in structure after binding it’s substrate. New experimental and theoretical analyses of the role of changes in HIV reverse transcriptase structure in selecting a correct substrate are presented. Atomically detailed simulations using the Milestoning method predict a rate and free energy profile of the conformational change commensurate with experimental data. A large conformational change occurring on a ms timescale locks the correct nucleotide at the active site, but promotes release of a mismatched nucleotide. The positions along the reaction coordinate that decide the yield of the reaction are not determined by the chemical step. Rather, the initial steps of weak substrate binding and protein conformational transition significantly enrich the yield of a reaction with a correct substrate, while the same steps diminish the reaction probability of an incorrect substrate. PMID:22483109

Predicting protein decomposition: the case of aspartic-acid racemization kinetics.

PubMed Central

Collins, M J; Waite, E R; van Duin, A C

1999-01-01

The increase in proportion of the non-biological (D-) isomer of aspartic acid (Asp) relative to the L-isomer has been widely used in archaeology and geochemistry as a tool for dating. the method has proved controversial, particularly when used for bones. The non-linear kinetics of Asp racemization have prompted a number of suggestions as to the underlying mechanism(s) and have led to the use of mathematical transformations which linearize the increase in D-Asp with respect to time. Using one example, a suggestion that the initial rapid phase of Asp racemization is due to a contribution from asparagine (Asn), we demonstrate how a simple model of the degradation and racemization of Asn can be used to predict the observed kinetics. A more complex model of peptide bound Asx (Asn + Asp) racemization, which occurs via the formation of a cyclic succinimide (Asu), can be used to correctly predict Asx racemization kinetics in proteins at high temperatures (95-140 degrees C). The model fails to predict racemization kinetics in dentine collagen at 37 degrees C. The reason for this is that Asu formation is highly conformation dependent and is predicted to occur extremely slowly in triple helical collagen. As conformation strongly influences the rate of Asu formation and hence Asx racemization, the use of extrapolation from high temperatures to estimate racemization kinetics of Asx in proteins below their denaturation temperature is called into question. In the case of archaeological bone, we argue that the D:L ratio of Asx reflects the proportion of non-helical to helical collagen, overlain by the effects of leaching of more soluble (and conformationally unconstrained) peptides. Thus, racemization kinetics in bone are potentially unpredictable, and the proposed use of Asx racemization to estimate the extent of DNA depurination in archaeological bones is challenged. PMID:10091247

Effects of Catalytic Action and Ligand Binding on Conformational Ensembles of Adenylate Kinase.

PubMed

Onuk, Emre; Badger, John; Wang, Yu Jing; Bardhan, Jaydeep; Chishti, Yasmin; Akcakaya, Murat; Brooks, Dana H; Erdogmus, Deniz; Minh, David D L; Makowski, Lee

2017-08-29

Crystal structures of adenylate kinase (AdK) from Escherichia coli capture two states: an "open" conformation (apo) obtained in the absence of ligands and a "closed" conformation in which ligands are bound. Other AdK crystal structures suggest intermediate conformations that may lie on the transition pathway between these two states. To characterize the transition from open to closed states in solution, X-ray solution scattering data were collected from AdK in the apo form and with progressively increasing concentrations of five different ligands. Scattering data from apo AdK are consistent with scattering predicted from the crystal structure of AdK in the open conformation. In contrast, data from AdK samples saturated with Ap5A do not agree with that calculated from AdK in the closed conformation. Using cluster analysis of available structures, we selected representative structures in five conformational states: open, partially open, intermediate, partially closed, and closed. We used these structures to estimate the relative abundances of these states for each experimental condition. X-ray solution scattering data obtained from AdK with AMP are dominated by scattering from AdK in the open conformation. For AdK in the presence of high concentrations of ATP and ADP, the conformational ensemble shifts to a mixture of partially open and closed states. Even when AdK is saturated with Ap5A, a significant proportion of AdK remains in a partially open conformation. These results are consistent with an induced-fit model in which the transition of AdK from an open state to a closed state is initiated by ATP binding.

Automatic imitation effects are influenced by experience of synchronous action in children.

PubMed

O'Sullivan, Eoin P; Bijvoet-van den Berg, Simone; Caldwell, Christine A

2018-07-01

By their fourth year of life, children are expert imitators, but it is unclear how this ability develops. One approach suggests that certain types of experience might forge associations between the sensory and motor representations of an action that may facilitate imitation at a later time. Sensorimotor experience of this sort may occur when an infant's action is imitated by a caregiver or when socially synchronous action occurs. This learning approach, therefore, predicts that the strength of sensory-motor associations should depend on the frequency and quality of previous experience. Here, we tested this prediction by examining automatic imitation, that is, the tendency of an action stimulus to facilitate the performance of that action and interfere with the performance of an incompatible action. We required children (aged between 3 years 8 months and 7 years 11 months) to respond to actions performed by an experimenter (e.g., two hands clapping) with both compatible actions (i.e., two hands clapping) and incompatible actions (i.e., two hands waving) at different stages in the experimental procedure. As predicted by a learning account, actions thought to be performed in synchrony (i.e., clapping/waving) produced stronger automatic imitation effects when compared with actions where previous sensorimotor experience is likely to be more limited (e.g., pointing/hand closing). Furthermore, these automatic imitation effects were not found to vary with age, with both compatible and incompatible responses quickening with age. These findings suggest a role for sensorimotor experience in the development of imitative ability. Copyright © 2018 Elsevier Inc. All rights reserved.

Conformal completion of the standard model with a fourth generation

NASA Astrophysics Data System (ADS)

Ho, Chiu Man; Hung, Pham Q.; Kephart, Thomas W.

2012-06-01

We study dynamical electroweak symmetry breaking with a fourth generation within the Z n orbifolded AdS 5 ⊗ S 5 framework. A realistic Z 7 example is discussed. The initial theory reduces dynamically, due to the induced condensates, to a four-family trinification near a TeV-scale conformal fixed point where the gauge hierarchy problem does not exist. We predict new gauge bosons and bifundamental fermions and scalars accessible by the LHC.

The geometry of organophosphonates: Fourier-transform microwave spectroscopy and ab initio study of diethyl methylphosphonate, diethyl ethylphosphonate, and diisopropyl methylphosphonate

NASA Astrophysics Data System (ADS)

DaBell, Ryan S.; Suenram, Richard D.; Lavrich, Richard J.; Lochner, J. Michael; Ellzy, Michael W.; Sumpter, Kenneth; Jensen, James O.; Samuels, Alan C.

2004-12-01

The rotational spectra of diethyl methylphosphonate (DEMP), diethyl ethylphosphonate (DEEP), and diisopropyl methylphosphonate (DIMP) in supersonic expansions have been acquired using Fourier-transform microwave spectroscopy. Spectroscopic constants have been determined for five distinct conformers of the three molecules. Experimental data have been compared to ab initio calculations performed for each species. For both DEMP and DEEP, the calculations indicate the presence of several low-energy conformers (i.e., ⩽˜400 cm -1 above the ground state) may be present at room temperature (300 K) for both DEMP and DEEP. When entrained in a supersonic expansion, the rotational temperatures of the samples are much colder (˜2 K); nonetheless, spectra from three conformers of DEEP are still observed experimentally, whereas only one conformer of DEMP is observed. In contrast, only a single low-energy conformer of DIMP is predicted by theory, and is present in the molecular beam. The relative abundance of low-energy conformers of DEMP and DEEP is attributed to the flexibility of the ethoxy groups within each molecule. The presence of multiple DEEP conformers in the supersonic beam indicates a more complex potential energy surface for this molecule that is directly related to conformational shifts of the PCH 2CH 3 group. Conversely, the absence of low-energy conformers of DIMP is attributed to steric hindrance between isopropoxy groups in the molecule. The internal rotation barrier for the PCH 3 group in DEMP and DIMP is compared to that found in DMMP and several phosphonate-based chemical weapon agents.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, Qianlong; Blissard, Gary W.; Liu, Tong-Xian

The Autographa californica multiple nucleopolyhedrovirus GP64 is a class III viral fusion protein. Although the post-fusion structure of GP64 has been solved, its pre-fusion structure and the detailed mechanism of conformational change are unknown. In GP64, domain V is predicted to interact with two domain I segments that flank fusion loop 2. To evaluate the significance of the amino acids involved in these interactions, we examined 24 amino acid positions that represent interacting and conserved residues within domains I and V. In several cases, substitution of a single amino acid involved in a predicted interaction disrupted membrane fusion activity, butmore » no single amino acid pair appears to be absolutely required. We identified 4 critical residues in domain V (G438, W439, T452, and T456) that are important for membrane fusion, and two residues (G438 and W439) that appear to be important for formation or stability of the pre-fusion conformation of GP64. - Highlights: • The baculovirus envelope glycoprotein GP64 is a class III viral fusion protein. • The detailed mechanism of conformational change of GP64 is unknown. • We analyzed 24 positions that might stabilize the post-fusion structure of GP64. • We identified 4 residues in domain V that were critical for membrane fusion. • Two residues are critical for formation of the pre-fusion conformation of GP64.« less

Ab initio investigation of the first hydration shell of protonated glycine

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wei, Zhichao; Chen, Dong, E-mail: dongchen@henu.edu.cn, E-mail: boliu@henu.edu.cn; Zhao, Huiling

2014-02-28

The first hydration shell of the protonated glycine is built up using Monte Carlo multiple minimum conformational search analysis with the MMFFs force field. The potential energy surfaces of the protonated glycine and its hydration complexes with up to eight water molecules have been scanned and the energy-minimized structures are predicted using the ab initio calculations. First, three favorable structures of protonated glycine were determined, and the micro-hydration processes showed that water can significantly stabilize the unstable conformers, and then their first hydration shells were established. Finally, we found that seven water molecules are required to fully hydrate the firstmore » hydration shell for the most stable conformer of protonated glycine. In order to analyse the hydration process, the dominant hydration sites located around the ammonium and carboxyl groups are studied carefully and systemically. The results indicate that, water molecules hydrate the protonated glycine in an alternative dynamic hydration process which is driven by the competition between different hydration sites. The first three water molecules are strongly attached by the ammonium group, while only the fourth water molecule is attached by the carboxyl group in the ultimate first hydration shell of the protonated glycine. In addition, the first hydration shell model has predicted most identical structures and a reasonable accord in hydration energy and vibrational frequencies of the most stable conformer with the conductor-like polarizable continuum model.« less

Multi-rotor internal rotations and conformational equilibria in oxiraneethanol and assignment of its vibrational spectra

NASA Astrophysics Data System (ADS)

Badawi, Hassan M.; Ali, Shaikh A.

2009-09-01

The complex internal rotations and conformational equilibria in oxiraneethanol were investigated at the DFT-B3LYP/6-311G** level of theory. Four minima were predicted in the CCOH potential energy scans of the molecule to have relative energies of about 2 kcal/mol or less and all were calculated to have real frequencies upon full optimization of structural parameters and the calculation of the Gibb's free-energies at the DFT level of calculation. At the DFT-B3LYP, the MP2 and the MP4(SDQ) levels of theory, the G1gg1 conformation, predicted to be the lowest energy conformation for oxiraneethanol, was in excellent agreement with the rotational microwave study. The equilibrium mixture was calculated to be about 47% G1gg1, 32% Cg1g, 15% Gg1t and 6% G1g1g at the B3LYP/6-311G** level of theory at 298.15 K. Solvent study corroborated the presence of the high energy Cg1g form in the liquid phase of oxiraneethanol. The vibrational frequencies of oxiraneethanol in its two stable forms were computed at the B3LYP level and vibrational assignments were made for the two lowest energy G1gg1 and Cg1g forms on the basis of calculated and experimental data of the molecule.

The making of the minibody: an engineered beta-protein for the display of conformationally constrained peptides.

PubMed

Tramontano, A; Bianchi, E; Venturini, S; Martin, F; Pessi, A; Sollazzo, M

1994-03-01

Conformationally constraining selectable peptides onto a suitable scaffold that enables their conformation to be predicted or readily determined by experimental techniques would considerably boost the drug discovery process by reducing the gap between the discovery of a peptide lead and the design of a peptidomimetic with a more desirable pharmacological profile. With this in mind, we designed the minibody, a 61-residue beta-protein aimed at retaining some desirable features of immunoglobulin variable domains, such as tolerance to sequence variability in selected regions of the protein and predictability of the main chain conformation of the same regions, based on the 'canonical structures' model. To test the ability of the minibody scaffold to support functional sites we also designed a metal binding version of the protein by suitably choosing the sequences of its loops. The minibody was produced both by chemical synthesis and expression in E. coli and characterized by size exclusion chromatography, UV CD (circular dichroism) spectroscopy and metal binding activity. All our data supported the model, but a more detailed structural characterization of the molecule was impaired by its low solubility. We were able to overcome this problem both by further mutagenesis of the framework and by addition of a solubilizing motif. The minibody is being used to select constrained human IL-6 peptidic ligands from a library displayed on the surface of the f1 bacteriophage.

An automatically tuning intrusion detection system.

PubMed

Yu, Zhenwei; Tsai, Jeffrey J P; Weigert, Thomas

2007-04-01

An intrusion detection system (IDS) is a security layer used to detect ongoing intrusive activities in information systems. Traditionally, intrusion detection relies on extensive knowledge of security experts, in particular, on their familiarity with the computer system to be protected. To reduce this dependence, various data-mining and machine learning techniques have been deployed for intrusion detection. An IDS is usually working in a dynamically changing environment, which forces continuous tuning of the intrusion detection model, in order to maintain sufficient performance. The manual tuning process required by current systems depends on the system operators in working out the tuning solution and in integrating it into the detection model. In this paper, an automatically tuning IDS (ATIDS) is presented. The proposed system will automatically tune the detection model on-the-fly according to the feedback provided by the system operator when false predictions are encountered. The system is evaluated using the KDDCup'99 intrusion detection dataset. Experimental results show that the system achieves up to 35% improvement in terms of misclassification cost when compared with a system lacking the tuning feature. If only 10% false predictions are used to tune the model, the system still achieves about 30% improvement. Moreover, when tuning is not delayed too long, the system can achieve about 20% improvement, with only 1.3% of the false predictions used to tune the model. The results of the experiments show that a practical system can be built based on ATIDS: system operators can focus on verification of predictions with low confidence, as only those predictions determined to be false will be used to tune the detection model.

Automated assessment of cognitive health using smart home technologies.

PubMed

Dawadi, Prafulla N; Cook, Diane J; Schmitter-Edgecombe, Maureen; Parsey, Carolyn

2013-01-01

The goal of this work is to develop intelligent systems to monitor the wellbeing of individuals in their home environments. This paper introduces a machine learning-based method to automatically predict activity quality in smart homes and automatically assess cognitive health based on activity quality. This paper describes an automated framework to extract set of features from smart home sensors data that reflects the activity performance or ability of an individual to complete an activity which can be input to machine learning algorithms. Output from learning algorithms including principal component analysis, support vector machine, and logistic regression algorithms are used to quantify activity quality for a complex set of smart home activities and predict cognitive health of participants. Smart home activity data was gathered from volunteer participants (n=263) who performed a complex set of activities in our smart home testbed. We compare our automated activity quality prediction and cognitive health prediction with direct observation scores and health assessment obtained from neuropsychologists. With all samples included, we obtained statistically significant correlation (r=0.54) between direct observation scores and predicted activity quality. Similarly, using a support vector machine classifier, we obtained reasonable classification accuracy (area under the ROC curve=0.80, g-mean=0.73) in classifying participants into two different cognitive classes, dementia and cognitive healthy. The results suggest that it is possible to automatically quantify the task quality of smart home activities and perform limited assessment of the cognitive health of individual if smart home activities are properly chosen and learning algorithms are appropriately trained.

Automated Assessment of Cognitive Health Using Smart Home Technologies

PubMed Central

Dawadi, Prafulla N.; Cook, Diane J.; Schmitter-Edgecombe, Maureen; Parsey, Carolyn

2014-01-01

BACKGROUND The goal of this work is to develop intelligent systems to monitor the well being of individuals in their home environments. OBJECTIVE This paper introduces a machine learning-based method to automatically predict activity quality in smart homes and automatically assess cognitive health based on activity quality. METHODS This paper describes an automated framework to extract set of features from smart home sensors data that reflects the activity performance or ability of an individual to complete an activity which can be input to machine learning algorithms. Output from learning algorithms including principal component analysis, support vector machine, and logistic regression algorithms are used to quantify activity quality for a complex set of smart home activities and predict cognitive health of participants. RESULTS Smart home activity data was gathered from volunteer participants (n=263) who performed a complex set of activities in our smart home testbed. We compare our automated activity quality prediction and cognitive health prediction with direct observation scores and health assessment obtained from neuropsychologists. With all samples included, we obtained statistically significant correlation (r=0.54) between direct observation scores and predicted activity quality. Similarly, using a support vector machine classifier, we obtained reasonable classification accuracy (area under the ROC curve = 0.80, g-mean = 0.73) in classifying participants into two different cognitive classes, dementia and cognitive healthy. CONCLUSIONS The results suggest that it is possible to automatically quantify the task quality of smart home activities and perform limited assessment of the cognitive health of individual if smart home activities are properly chosen and learning algorithms are appropriately trained. PMID:23949177

MovieMaker: a web server for rapid rendering of protein motions and interactions

PubMed Central

Maiti, Rajarshi; Van Domselaar, Gary H.; Wishart, David S.

2005-01-01

MovieMaker is a web server that allows short (∼10 s), downloadable movies of protein motions to be generated. It accepts PDB files or PDB accession numbers as input and automatically calculates, renders and merges the necessary image files to create colourful animations covering a wide range of protein motions and other dynamic processes. Users have the option of animating (i) simple rotation, (ii) morphing between two end-state conformers, (iii) short-scale, picosecond vibrations, (iv) ligand docking, (v) protein oligomerization, (vi) mid-scale nanosecond (ensemble) motions and (vii) protein folding/unfolding. MovieMaker does not perform molecular dynamics calculations. Instead it is an animation tool that uses a sophisticated superpositioning algorithm in conjunction with Cartesian coordinate interpolation to rapidly and automatically calculate the intermediate structures needed for many of its animations. Users have extensive control over the rendering style, structure colour, animation quality, background and other image features. MovieMaker is intended to be a general-purpose server that allows both experts and non-experts to easily generate useful, informative protein animations for educational and illustrative purposes. MovieMaker is accessible at . PMID:15980488

Automatic gender detection of dream reports: A promising approach.

PubMed

Wong, Christina; Amini, Reza; De Koninck, Joseph

2016-08-01

A computer program was developed in an attempt to differentiate the dreams of males from females. Hypothesized gender predictors were based on previous literature concerning both dream content and written language features. Dream reports from home-collected dream diaries of 100 male (144 dreams) and 100 female (144 dreams) adolescent Anglophones were matched for equal length. They were first scored with the Hall and Van de Castle (HVDC) scales and quantified using DreamSAT. Two male and two female undergraduate students were asked to read all dreams and predict the dreamer's gender. They averaged a pairwise percent correct gender prediction of 75.8% (κ=0.516), while the Automatic Analysis showed that the computer program's accuracy was 74.5% (κ=0.492), both of which were higher than chance of 50% (κ=0.00). The prediction levels were maintained when dreams containing obvious gender identifiers were eliminated and integration of HVDC scales did not improve prediction. Copyright © 2016 Elsevier Inc. All rights reserved.

Learning diagnostic models using speech and language measures.

PubMed

Peintner, Bart; Jarrold, William; Vergyriy, Dimitra; Richey, Colleen; Tempini, Maria Luisa Gorno; Ogar, Jennifer

2008-01-01

We describe results that show the effectiveness of machine learning in the automatic diagnosis of certain neurodegenerative diseases, several of which alter speech and language production. We analyzed audio from 9 control subjects and 30 patients diagnosed with one of three subtypes of Frontotemporal Lobar Degeneration. From this data, we extracted features of the audio signal and the words the patient used, which were obtained using our automated transcription technologies. We then automatically learned models that predict the diagnosis of the patient using these features. Our results show that learned models over these features predict diagnosis with accuracy significantly better than random. Future studies using higher quality recordings will likely improve these results.

A Structural and Functional Comparison Between Infectious and Non-Infectious Autocatalytic Recombinant PrP Conformers

PubMed Central

Noble, Geoffrey P.; Wang, Daphne W.; Walsh, Daniel J.; Barone, Justin R.; Miller, Michael B.; Nishina, Koren A.; Li, Sheng; Supattapone, Surachai

2015-01-01

Infectious prions contain a self-propagating, misfolded conformer of the prion protein termed PrPSc. A critical prediction of the protein-only hypothesis is that autocatalytic PrPSc molecules should be infectious. However, some autocatalytic recombinant PrPSc molecules have low or undetectable levels of specific infectivity in bioassays, and the essential determinants of recombinant prion infectivity remain obscure. To identify structural and functional features specifically associated with infectivity, we compared the properties of two autocatalytic recombinant PrP conformers derived from the same original template, which differ by >105-fold in specific infectivity for wild-type mice. Structurally, hydrogen/deuterium exchange mass spectrometry (DXMS) studies revealed that solvent accessibility profiles of infectious and non-infectious autocatalytic recombinant PrP conformers are remarkably similar throughout their protease-resistant cores, except for two domains encompassing residues 91-115 and 144-163. Raman spectroscopy and immunoprecipitation studies confirm that these domains adopt distinct conformations within infectious versus non-infectious autocatalytic recombinant PrP conformers. Functionally, in vitro prion propagation experiments show that the non-infectious conformer is unable to seed mouse PrPC substrates containing a glycosylphosphatidylinositol (GPI) anchor, including native PrPC. Taken together, these results indicate that having a conformation that can be specifically adopted by post-translationally modified PrPC molecules is an essential determinant of biological infectivity for recombinant prions, and suggest that this ability is associated with discrete features of PrPSc structure. PMID:26125623

Automated prediction of protein function and detection of functional sites from structure.

PubMed

Pazos, Florencio; Sternberg, Michael J E

2004-10-12

Current structural genomics projects are yielding structures for proteins whose functions are unknown. Accordingly, there is a pressing requirement for computational methods for function prediction. Here we present PHUNCTIONER, an automatic method for structure-based function prediction using automatically extracted functional sites (residues associated to functions). The method relates proteins with the same function through structural alignments and extracts 3D profiles of conserved residues. Functional features to train the method are extracted from the Gene Ontology (GO) database. The method extracts these features from the entire GO hierarchy and hence is applicable across the whole range of function specificity. 3D profiles associated with 121 GO annotations were extracted. We tested the power of the method both for the prediction of function and for the extraction of functional sites. The success of function prediction by our method was compared with the standard homology-based method. In the zone of low sequence similarity (approximately 15%), our method assigns the correct GO annotation in 90% of the protein structures considered, approximately 20% higher than inheritance of function from the closest homologue.

Development of an automatic cow body condition scoring using body shape signature and Fourier descriptors.

PubMed

Bercovich, A; Edan, Y; Alchanatis, V; Moallem, U; Parmet, Y; Honig, H; Maltz, E; Antler, A; Halachmi, I

2013-01-01

Body condition evaluation is a common tool to assess energy reserves of dairy cows and to estimate their fatness or thinness. This study presents a computer-vision tool that automatically estimates cow's body condition score. Top-view images of 151 cows were collected on an Israeli research dairy farm using a digital still camera located at the entrance to the milking parlor. The cow's tailhead area and its contour were segmented and extracted automatically. Two types of features of the tailhead contour were extracted: (1) the angles and distances between 5 anatomical points; and (2) the cow signature, which is a 1-dimensional vector of the Euclidean distances from each point in the normalized tailhead contour to the shape center. Two methods were applied to describe the cow's signature and to reduce its dimension: (1) partial least squares regression, and (2) Fourier descriptors of the cow signature. Three prediction models were compared with manual scores of an expert. Results indicate that (1) it is possible to automatically extract and predict body condition from color images without any manual interference; and (2) Fourier descriptors of the cow's signature result in improved performance (R(2)=0.77). Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Ionic tethering contributes to the conformational stability and function of complement C3b.

PubMed

López-Perrote, Andrés; Harrison, Reed E S; Subías, Marta; Alcorlo, Martín; Rodríguez de Córdoba, Santiago; Morikis, Dimitrios; Llorca, Oscar

2017-05-01

C3b, the central component of the alternative pathway (AP) of the complement system, coexists as a mixture of conformations in solution. These conformational changes can affect interactions with other proteins and complement regulators. Here we combine a computational model for electrostatic interactions within C3b with molecular imaging to study the conformation of C3b. The computational analysis shows that the TED domain in C3b is tethered ionically to the macroglobulin (MG) ring. Monovalent counterion concentration affects the magnitude of electrostatic forces anchoring the TED domain to the rest of the C3b molecule in a thermodynamic model. This is confirmed by observing NaCl concentration dependent conformational changes using single molecule electron microscopy (EM). We show that the displacement of the TED domain is compatible with C3b binding to Factor B (FB), suggesting that the regulation of the C3bBb convertase could be affected by conditions that promote movement in the TED domain. Our molecular model also predicts mutations that could alter the positioning of the TED domain, including the common R102G polymorphism, a risk variant for developing age-related macular degeneration. The common C3b isoform, C3bS, and the risk isoform, C3bF, show distinct energetic barriers to displacement in the TED that are related to a network of electrostatic interactions at the interface of the TED and MG-ring domains of C3b. These computational predictions agree with experimental evidence that shows differences in conformation observed in C3b isoforms purified from homozygous donors. Altogether, we reveal an ionic, reversible attachment of the TED domain to the MG ring that may influence complement regulation in some mutations and polymorphisms of C3b. Copyright © 2016 Elsevier Ltd. All rights reserved.

Structural Fluctuations of the Chromatin Fiber within Topologically Associating Domains.

PubMed

Tiana, Guido; Amitai, Assaf; Pollex, Tim; Piolot, Tristan; Holcman, David; Heard, Edith; Giorgetti, Luca

2016-03-29

Experiments based on chromosome conformation capture have shown that mammalian genomes are partitioned into topologically associating domains (TADs), within which the chromatin fiber preferentially interacts. TADs may provide three-dimensional scaffolds allowing genes to contact their appropriate distal regulatory DNA sequences (e.g., enhancers) and thus to be properly regulated. Understanding the cell-to-cell and temporal variability of the chromatin fiber within TADs, and what determines them, is thus of great importance to better understand transcriptional regulation. We recently described an equilibrium polymer model that can accurately predict cell-to-cell variation of chromosome conformation within single TADs, from chromosome conformation capture-based data. Here we further analyze the conformational and energetic properties of our model. We show that the chromatin fiber within TADs can easily fluctuate between several conformational states, which are hierarchically organized and are not separated by important free energy barriers, and that this is facilitated by the fact that the chromatin fiber within TADs is close to the onset of the coil-globule transition. We further show that in this dynamic state the properties of the chromatin fiber, and its contact probabilities in particular, are determined in a nontrivial manner not only by site-specific interactions between strongly interacting loci along the fiber, but also by nonlocal correlations between pairs of contacts. Finally, we use live-cell experiments to measure the dynamics of the chromatin fiber in mouse embryonic stem cells, in combination with dynamical simulations, and predict that conformational changes within one TAD are likely to occur on timescales that are much shorter than the duration of one cell cycle. This suggests that genes and their regulatory elements may come together and disassociate several times during a cell cycle. These results have important implications for transcriptional regulation as they support the concept of highly dynamic interactions driven by a complex interplay between site-specific interactions and the intrinsic biophysical properties of the chromatin fiber. Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Conformational stability from temperature-dependent fourier transform infrared spectra of noble gas solutions, r0 structural parameters, and barriers to internal rotation for ethylamine.

PubMed

Durig, James R; Zheng, Chao; Gounev, Todor K; Herrebout, Wouter A; van der Veken, Benjamin J

2006-05-04

Variable temperature (-55 to -145 degrees C) studies of the infrared spectra (3500 to 100 cm(-1)) of ethylamine, CH(3)CH(2)NH(2), dissolved in liquid krypton and/or xenon have been recorded. From these data, the enthalpy differences have been determined to be 54 +/- 4 cm(-1) (0.65 +/- 0.05 kJ/mol), with the trans conformer (methyl group relative to the lone pair of electrons on nitrogen) being the more stable form. It is estimated that there is 61 +/- 1% of the doubly degenerate gauche form present at ambient temperature. The conformational energetics have been calculated with the Møller-Plesset perturbation method to the second order (MP2(full)) and the fourth order (MP4(SDTQ)) as well as with density functional theory by the B3LYP method utilizing a variety of basis sets. Basis sets with diffuse functions lead to incorrect prediction of the conformational stability. On the basis of the frequencies of the torsional transitions along with the determined experimental enthalpy difference and gauche dihedral angle, the potential function governing conformational interchange has been obtained, and the determined Fourier cosine coefficients are V(1) = -207 +/- 48, V(2) = 320 +/- 67, V(3) = 1072 +/- 25, V(4) = 55 +/- 11, and V(5) = -96 +/- 28 cm(-1), with a trans-to-gauche barrier of 1286 cm(-1), and a gauche-to-gauche barrier of 715 cm(-1). The 3-fold methyl rotational barriers have been determined to be 1241 +/- 4 and 1281 +/- 10 cm(-1) for the gauche and trans conformers, respectively. By utilizing the previously reported microwave rotational constants combined with the structural parameters predicted at the MP2(full)/6-311+ G(d,p) level, adjusted r(0) structural parameters have been obtained. A complete vibrational assignment is given for the trans conformer, which is supported by normal coordinate calculations utilizing scaled force constants from ab initio B3LYP/6-311++G(3df,3pd) calculations. Proposed assignments are also made for the fundamentals of the gauche conformer. The results of these spectroscopic and theoretical studies are discussed and compared to the corresponding results for similar molecules.

Interaction of formic acid with nitrogen: stabilization of the higher-energy conformer.

PubMed

Marushkevich, Kseniya; Räsänen, Markku; Khriachtchev, Leonid

2010-10-07

Conformational change is an important concept in chemistry and physics. In the present work, we study conformations of formic acid (HCOOH, FA) and report the preparation and identification of the complex of the higher-energy conformer cis-FA with N(2) in an argon matrix. The cis-FA···N(2) complex was synthesized by combining annealing and vibrational excitation of the ground-state trans-FA in a FA/N(2)/Ar matrix. The assignment is based on IR spectroscopic measurements and ab initio calculations. The cis-FA···N(2) complex decay in an argon matrix is much slower compared with the cis-FA monomer. In agreement with the experimental observations, the calculations predict a substantial increase in the stabilization barrier for the cis-FA···N(2) complex compared with the uncomplexed cis-FA monomer. A number of solvation effects in an argon matrix are computationally estimated and discussed. The present results on the cis-FA···N(2) complex show that intermolecular interaction can stabilize intrinsically unstable conformers, as previously found for some other cis-FA complexes.

Nonbonded interactions in membrane active cyclic biopolymers. IV - Cation dependence

NASA Technical Reports Server (NTRS)

Radhakrishnan, R.; Srinivasan, S.; Prasad, C. V.; Brinda, S. R.; Macelroy, R. D.; Sundaram, K.

1980-01-01

Interactions of valinomycin and form of its analogs in several conformations with the central ions Li(+), Na(+), K(+), Rb(+) and Cs(+) are investigated as part of a study of the specific preference of valinomycin for potassium and the mechanisms of carrier-mediated ion transport across membranes. Ion binding energies and conformational potential energies are calculated taking into account polarization energy formulas and repulsive energy between the central ion and the ligand atoms for conformations representing various stages in ion capture and release for each of the two ring chiralities of valinomycin and its analogs. Results allow the prediction of the chirality and conformation most likely to be observed for a given analog, and may be used to synthesize analogs with a desired rigidity or flexibility. The binding energies with the alkali metal cations are found to decrease with increasing ion size, and to be smaller than the corresponding ion hydration energies. It is pointed out that the observed potassium preference may be explainable in terms of differences between binding and hydration energies. Binding energies are also noted to depend on ligand conformation.

Automated large-scale file preparation, docking, and scoring: evaluation of ITScore and STScore using the 2012 Community Structure-Activity Resource benchmark.

PubMed

Grinter, Sam Z; Yan, Chengfei; Huang, Sheng-You; Jiang, Lin; Zou, Xiaoqin

2013-08-26

In this study, we use the recently released 2012 Community Structure-Activity Resource (CSAR) data set to evaluate two knowledge-based scoring functions, ITScore and STScore, and a simple force-field-based potential (VDWScore). The CSAR data set contains 757 compounds, most with known affinities, and 57 crystal structures. With the help of the script files for docking preparation, we use the full CSAR data set to evaluate the performances of the scoring functions on binding affinity prediction and active/inactive compound discrimination. The CSAR subset that includes crystal structures is used as well, to evaluate the performances of the scoring functions on binding mode and affinity predictions. Within this structure subset, we investigate the importance of accurate ligand and protein conformational sampling and find that the binding affinity predictions are less sensitive to non-native ligand and protein conformations than the binding mode predictions. We also find the full CSAR data set to be more challenging in making binding mode predictions than the subset with structures. The script files used for preparing the CSAR data set for docking, including scripts for canonicalization of the ligand atoms, are offered freely to the academic community.

New developments in isotropic turbulent models for FENE-P fluids

NASA Astrophysics Data System (ADS)

Resende, P. R.; Cavadas, A. S.

2018-04-01

The evolution of viscoelastic turbulent models, in the last years, has been significant due to the direct numeric simulation (DNS) advances, which allowed us to capture in detail the evolution of the viscoelastic effects and the development of viscoelastic closures. New viscoelastic closures are proposed for viscoelastic fluids described by the finitely extensible nonlinear elastic-Peterlin constitutive model. One of the viscoelastic closure developed in the context of isotropic turbulent models, consists in a modification of the turbulent viscosity to include an elastic effect, capable of predicting, with good accuracy, the behaviour for different drag reductions. Another viscoelastic closure essential to predict drag reduction relates the viscoelastic term involving velocity and the tensor conformation fluctuations. The DNS data show the high impact of this term to predict correctly the drag reduction, and for this reason is proposed a simpler closure capable of predicting the viscoelastic behaviour with good performance. In addition, a new relation is developed to predict the drag reduction, quantity based on the trace of the tensor conformation at the wall, eliminating the need of the typically parameters of Weissenberg and Reynolds numbers, which depend on the friction velocity. This allows future developments for complex geometries.

Cooperative Allosteric Ligand Binding in Calmodulin

NASA Astrophysics Data System (ADS)

Nandigrami, Prithviraj

Conformational dynamics is often essential for a protein's function. For example, proteins are able to communicate the effect of binding at one site to a distal region of the molecule through changes in its conformational dynamics. This so called allosteric coupling fine tunes the sensitivity of ligand binding to changes in concentration. A conformational change between a "closed" (apo) and an "open" (holo) conformation upon ligation often produces this coupling between binding sites. Enhanced sensitivity between the unbound and bound ensembles leads to a sharper binding curve. There are two basic conceptual frameworks that guide our visualization about ligand binding mechanisms. First, a ligand can stabilize the unstable "open" state from a dynamic ensemble of conformations within the unbound basin. This binding mechanism is called conformational selection. Second, a ligand can weakly bind to the low-affinity "closed" state followed by a conformational transition to the "open" state. In this dissertation, I focus on molecular dynamics simulations to understand microscopic origins of ligand binding cooperativity. A minimal model of allosteric binding transitions must include ligand binding/unbinding events, while capturing the transition mechanism between two distinct meta-stable free energy basins. Due in part to computational timescales limitations, work in this dissertation describes large-scale conformational transitions through a simplified, coarse-grained model based on the energy basins defined by the open and closed conformations of the protein Calmodulin (CaM). CaM is a ubiquitous calcium-binding protein consisting of two structurally similar globular domains connected by a flexible linker. The two domains of CaM, N-terminal domain (nCaM) and C-terminal domain (cCaM) consists of two helix-loop-helix motifs (the EF-hands) connected by a flexible linker. Each domain of CaM consists of two binding loops and binds 2 calcium ions each. The intact domain binds up to 4 calcium ions. The simulations use a coupled molecular dynamics/monte carlo scheme where the protein dynamics is simulated explicitly, while ligand binding/unbinding are treated implicitly. In the model, ligand binding/unbinding events coupled with a conformational change of the protein within the grand canonical ensemble. Here, ligand concentration is controlled through the chemical potential (micro). This allows us to use a simple thermodynamic model to analyze the simulated data and quantify binding cooperativity. Simulated binding titration curves are calculated through equilibrium simulations at different values of micro. First, I study domain opening transitions of isolated nCaM and cCaM in the absence of calcium. This work is motivated by results from a recent analytic variational model that predicts distinct domain opening transition mechanism for the domains of CaM. This is a surprising result because the domains have the same folded state topology. In the simulations, I find the two domains of CaM have distinct transition mechanism over a broad range of temperature, in harmony with the analytic predictions. In particular, the simulated transition mechanism of nCaM follows a two-state behavior, while domain opening in cCaM involves global unfolding and refolding of the tertiary structure. The unfolded intermediate also appears in the landscape of nCaM, but at a higher temperature than it appears in cCaM's energy landscape. This is consistent with nCaM's higher thermal stability. Under approximate physiological conditions, majority of the sampled transitions in cCaM involves unfolding and refolding during conformational change. Kinetically, the transient unfolding and refolding in cCaM significantly slows the domain opening and closing rates in cCaM. Second, I investigate the structural origins of binding affinity and allosteric cooperativity of binding 2 calcium-ions to each domain of CaM. In my work, I predict the order of binding strength of CaM's loops. I analyze simulated binding curves within the framework of the classic Monod-Wyman-Changeux (MWC) model of allostery to extract the binding free energies to the closed and open ensembles. The simulations predict that cCaM binds calcium with higher affinity and greater cooperativity than nCaM. Where it is possible to compare, these predictions are in good agreement with experimental results. The analysis of the simulations offers a rationale for why the two domains differ in cooperativity: the higher cooperativity of cCaM is due to larger difference in affinity of its binding loops. Third, I extend the work to investigate structural origins of binding cooperativity of 4 calcium-ions to intact CaM. I characterize the microscopic cooperativities of each ligation state and provide a kinetic description of the binding mechanism. Due to the heterogeneous nature of CaM's loops, as predicted in our simulations of isolated domains, I focus on investigating the influence of this heterogeneity on the kinetic flux of binding pathways as a function of concentration. The formalism developed for Network Models of protein folding kinetics, is used to evaluate the directed flux of all possible pathways between unligated and fully loaded CaM. (Abstract shortened by ProQuest.).

Prediction of Solution Properties of Flexible-Chain Polymers: A Computer Simulation Undergraduate Experiment

ERIC Educational Resources Information Center

de la Torre, Jose Garcia; Cifre, Jose G. Hernandez; Martinez, M. Carmen Lopez

2008-01-01

This paper describes a computational exercise at undergraduate level that demonstrates the employment of Monte Carlo simulation to study the conformational statistics of flexible polymer chains, and to predict solution properties. Three simple chain models, including excluded volume interactions, have been implemented in a public-domain computer…

Anharmonic Vibrational Analyses of Pentapeptide Conformations Explored with Enhanced Sampling Simulations.

PubMed

Otaki, Hiroki; Yagi, Kiyoshi; Ishiuchi, Shun-Ichi; Fujii, Masaaki; Sugita, Yuji

2016-10-06

An accurate theoretical prediction of the vibrational spectrum of polypeptides remains to be a challenge due to (1) their conformational flexibility and (2) non-negligible anharmonic effects. The former makes the search for conformers that contribute to the spectrum difficult, and the latter requires an expensive, quantum mechanical calculation for both electrons and vibrations. Here, we propose a new theoretical approach, which implements an enhanced conformational sampling by the replica-exchange molecular dynamics method, a structural clustering to identify distinct conformations, and a vibrational structure calculation by the second-order vibrational quasi-degenerate perturbation theory (VQDPT2). A systematic mode-selection scheme is developed to reduce the cost of VQDPT2 and the generation of a potential energy surface by the electronic structure calculation. The proposed method is applied to a pentapeptide, SIVSF-NH 2 , for which the infrared spectrum has recently been measured in the gas phase with high resolution in the OH and NH stretching region. The theoretical spectrum of the lowest energy conformer is obtained with a mean absolute deviation of 11.2 cm -1 from the experimental spectrum. Furthermore, the NH stretching frequencies of the five lowest energy conformers are found to be consistent with the literature values measured for small peptides with a similar secondary structure. Therefore, the proposed method is a promising way to analyze the vibrational spectrum of polypeptides.

Influence of rotational energy barriers to the conformational search of protein loops in molecular dynamics and ranking the conformations.

PubMed

Tappura, K

2001-08-15

An adjustable-barrier dihedral angle potential was added as an extension to a novel, previously presented soft-core potential to study its contribution to the efficacy of the search of the conformational space in molecular dynamics. As opposed to the conventional soft-core potential functions, the leading principle in the design of the new soft-core potential, as well as of its extension, the soft-core and adjustable-barrier dihedral angle (SCADA) potential (referred as the SCADA potential), was to maintain the main equilibrium properties of the original force field. This qualifies the methods for a variety of a priori modeling problems without need for additional restraints typically required with the conventional soft-core potentials. In the present study, the different potential energy functions are applied to the problem of predicting loop conformations in proteins. Comparison of the performance of the soft-core and SCADA potential showed that the main hurdles for the efficient sampling of the conformational space of (loops in) proteins are related to the high-energy barriers caused by the Lennard-Jones and Coulombic energy terms, and not to the rotational barriers, although the conformational search can be further enhanced by lowering the rotational barriers of the dihedral angles. Finally, different evaluation methods were studied and a few promising criteria found to distinguish the near-native loop conformations from the wrong ones.

Encompassing receptor flexibility in virtual screening using ensemble docking-based hybrid QSAR: discovery of novel phytochemicals for BACE1 inhibition.

PubMed

Chakraborty, Sandipan; Ramachandran, Balaji; Basu, Soumalee

2014-10-01

Mimicking receptor flexibility during receptor-ligand binding is a challenging task in computational drug design since it is associated with a large increase in the conformational search space. In the present study, we have devised an in silico design strategy incorporating receptor flexibility in virtual screening to identify potential lead compounds as inhibitors for flexible proteins. We have considered BACE1 (β-secretase), a key target protease from a therapeutic perspective for Alzheimer's disease, as the highly flexible receptor. The protein undergoes significant conformational transitions from open to closed form upon ligand binding, which makes it a difficult target for inhibitor design. We have designed a hybrid structure-activity model containing both ligand based descriptors and energetic descriptors obtained from molecular docking based on a dataset of structurally diverse BACE1 inhibitors. An ensemble of receptor conformations have been used in the docking study, further improving the prediction ability of the model. The designed model that shows significant prediction ability judged by several statistical parameters has been used to screen an in house developed 3-D structural library of 731 phytochemicals. 24 highly potent, novel BACE1 inhibitors with predicted activity (Ki) ≤ 50 nM have been identified. Detailed analysis reveals pharmacophoric features of these novel inhibitors required to inhibit BACE1.

Microvascular fractal dimension predicts prognosis and response to chemotherapy in glioblastoma: an automatic image analysis study.

PubMed

Chen, Cong; He, Zhi-Cheng; Shi, Yu; Zhou, Wenchao; Zhang, Xia; Xiao, Hua-Liang; Wu, Hai-Bo; Yao, Xiao-Hong; Luo, Wan-Chun; Cui, You-Hong; Bao, Shideng; Kung, Hsiang-Fu; Bian, Xiu-Wu; Ping, Yi-Fang

2018-05-15

The microvascular profile has been included in the WHO glioma grading criteria. Nevertheless, microvessels in gliomas of the same WHO grade, e.g., WHO IV glioblastoma (GBM), exhibit heterogeneous and polymorphic morphology, whose possible clinical significance remains to be determined. In this study, we employed a fractal geometry-derived parameter, microvascular fractal dimension (mvFD), to quantify microvessel complexity and developed a home-made macro in Image J software to automatically determine mvFD from the microvessel-stained immunohistochemical images of GBM. We found that mvFD effectively quantified the morphological complexity of GBM microvasculature. Furthermore, high mvFD favored the survival of GBM patients as an independent prognostic indicator and predicted a better response to chemotherapy of GBM patients. When investigating the underlying relations between mvFD and tumor growth by deploying Ki67/mvFD as an index for microvasculature-normalized tumor proliferation, we discovered an inverse correlation between mvFD and Ki67/mvFD. Furthermore, mvFD inversely correlated with the expressions of a glycolytic marker, LDHA, which indicated poor prognosis of GBM patients. Conclusively, we developed an automatic approach for mvFD measurement, and demonstrated that mvFD could predict the prognosis and response to chemotherapy of GBM patients.

Can tail damage outbreaks in the pig be predicted by behavioural change?

PubMed

Larsen, Mona Lilian Vestbjerg; Andersen, Heidi Mai-Lis; Pedersen, Lene Juul

2016-03-01

Tail biting, resulting in outbreaks of tail damage in pigs, is a multifactorial welfare and economic problem which is usually partly prevented through tail docking. According to European Union legislation, tail docking is not allowed on a routine basis; thus there is a need for alternative preventive methods. One strategy is the surveillance of the pigs' behaviour for known preceding indicators of tail damage, which makes it possible to predict a tail damage outbreak and prevent it in proper time. This review discusses the existing literature on behavioural changes observed prior to a tail damage outbreak. Behaviours found to change prior to an outbreak include increased activity level, increased performance of enrichment object manipulation, and a changed proportion of tail posture with more tails between the legs. Monitoring these types of behaviours is also discussed for the purpose of developing an automatic warning system for tail damage outbreaks, with activity level showing promising results for being monitored automatically. Encouraging results have been found so far for the development of an automatic warning system; however, there is a need for further investigation and development, starting with the description of the temporal development of the predictive behaviour in relation to tail damage outbreaks. Copyright © 2016 Elsevier Ltd. All rights reserved.

Rational Design and Tuning of Functional RNA Switch to Control an Allosteric Intermolecular Interaction.

PubMed

Endoh, Tamaki; Sugimoto, Naoki

2015-08-04

Conformational transitions of biomolecules in response to specific stimuli control many biological processes. In natural functional RNA switches, often called riboswitches, a particular RNA structure that has a suppressive or facilitative effect on gene expression transitions to an alternative structure with the opposite effect upon binding of a specific metabolite to the aptamer region. Stability of RNA secondary structure (-ΔG°) can be predicted based on thermodynamic parameters and is easily tuned by changes in nucleobases. We envisioned that tuning of a functional RNA switch that causes an allosteric interaction between an RNA and a peptide would be possible based on a predicted switching energy (ΔΔG°) that corresponds to the energy difference between the RNA secondary structure before (-ΔG°before) and after (-ΔG°after) the RNA conformational transition. We first selected functional RNA switches responsive to neomycin with predicted ΔΔG° values ranging from 5.6 to 12.2 kcal mol(-1). We then demonstrated a simple strategy to rationally convert the functional RNA switch to switches responsive to natural metabolites thiamine pyrophosphate, S-adenosyl methionine, and adenine based on the predicted ΔΔG° values. The ΔΔG° values of the designed RNA switches proportionally correlated with interaction energy (ΔG°interaction) between the RNA and peptide, and we were able to tune the sensitivity of the RNA switches for the trigger molecule. The strategy demonstrated here will be generally applicable for construction of functional RNA switches and biosensors in which mechanisms are based on conformational transition of nucleic acids.

SwiSpot: modeling riboswitches by spotting out switching sequences.

PubMed

Barsacchi, Marco; Novoa, Eva Maria; Kellis, Manolis; Bechini, Alessio

2016-11-01

Riboswitches are cis-regulatory elements in mRNA, mostly found in Bacteria, which exhibit two main secondary structure conformations. Although one of them prevents the gene from being expressed, the other conformation allows its expression, and this switching process is typically driven by the presence of a specific ligand. Although there are a handful of known riboswitches, our knowledge in this field has been greatly limited due to our inability to identify their alternate structures from their sequences. Indeed, current methods are not able to predict the presence of the two functionally distinct conformations just from the knowledge of the plain RNA nucleotide sequence. Whether this would be possible, for which cases, and what prediction accuracy can be achieved, are currently open questions. Here we show that the two alternate secondary structures of riboswitches can be accurately predicted once the 'switching sequence' of the riboswitch has been properly identified. The proposed SwiSpot approach is capable of identifying the switching sequence inside a putative, complete riboswitch sequence, on the basis of pairing behaviors, which are evaluated on proper sets of configurations. Moreover, it is able to model the switching behavior of riboswitches whose generated ensemble covers both alternate configurations. Beyond structural predictions, the approach can also be paired to homology-based riboswitch searches. SwiSpot software, along with the reference dataset files, is available at: http://www.iet.unipi.it/a.bechini/swispot/Supplementary information: Supplementary data are available at Bioinformatics online. a.bechini@ing.unipi.it. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Prediction of lamb meat eating quality in two divergent breeds using various live animal and carcass measurements.

PubMed

Lambe, N R; Navajas, E A; Fisher, A V; Simm, G; Roehe, R; Bünger, L

2009-11-01

This study investigated how accurately taste panel sensory assessments of meat eating quality (MEQ) could be predicted in two divergent lamb breeds, using predictors measured in live animals (weights, subjective conformation assessments, ultrasound, computed tomography (CT) and video image analysis measurements) and carcasses (weights, MLC fat and conformation classes, pH, temperature, carcass dimensions and cross-sectional tissue dimensions), individually and in optimal combinations. Grilled muscle samples from the pelvic limb (semimembranosus) and loin (Longissimus lumborum) of 120 Texel (TEX) and 112 Scottish Blackface (SBF) lambs were assessed by a trained taste panel for texture, juiciness, flavour, abnormal flavour and overall liking. Residual correlations (adjusted for fixed effects, age and sire) between MEQ and predictor traits were low to moderate in size (<±0.42). MEQ traits predicted best by single measurements were loin flavour and overall liking for TEX (using fat area in a CT scan or subcutaneous fat depth measured post-mortem), and for SBF were leg texture (using carcass weight or temperature) and juiciness (using CT fat area or shoulder conformation score). Combining live animal and carcass measurements increased MEQ prediction accuracies, compared with using either set alone, to explain >40% of residual variation in several MEQ traits, with the highest adjusted R(2) values for leg juiciness in TEX (0.53) and leg texture in SBF (0.59). The most useful predictors of MEQ depended on breed, with measurements of fatness generally more important in the lean breed and carcass size and muscling more important in the fatter breed.

Investigating the Effect of Advanced Automatic Transmissions ...

EPA Pesticide Factsheets

EPA used the validated ALPHA model to predict the effectiveness improvement of real-world transmissions over a baseline four-speed transmission and to predict further improvements possible from future eight-speed transmissions. In preparation for the midterm evaluation (MTE) of the 2017-2025 light-duty GHG emissions rule.

Why Does Rapid Naming Predict Chinese Word Reading?

ERIC Educational Resources Information Center

Shum, Kathy Kar-man; Au, Terry Kit-fong

2017-01-01

Rapid automatized naming (RAN) robustly predicts early reading abilities across languages, but its underlying mechanism remains unclear. This study found that RAN associated significantly with processing speed but not with phonological awareness or orthographic knowledge in 89 Hong Kong Chinese second-graders. RAN overlaps more with processing…

Transitions of tethered chain molecules under tension.

PubMed

Luettmer-Strathmann, Jutta; Binder, Kurt

2014-09-21

An applied tension force changes the equilibrium conformations of a polymer chain tethered to a planar substrate and thus affects the adsorption transition as well as the coil-globule and crystallization transitions. Conversely, solvent quality and surface attraction are reflected in equilibrium force-extension curves that can be measured in experiments. To investigate these effects theoretically, we study tethered chains under tension with Wang-Landau simulations of a bond-fluctuation lattice model. Applying our model to pulling experiments on biological molecules we obtain a good description of experimental data in the intermediate force range, where universal features dominate and finite size effects are small. For tethered chains in poor solvent, we observe the predicted two-phase coexistence at transitions from the globule to stretched conformations and also discover direct transitions from crystalline to stretched conformations. A phase portrait for finite chains constructed by evaluating the density of states for a broad range of solvent conditions and tensions shows how increasing tension leads to a disappearance of the globular phase. For chains in good solvents tethered to hard and attractive surfaces we find the predicted scaling with the chain length in the low-force regime and show that our results are well described by an analytical, independent-bond approximation for the bond-fluctuation model for the highest tensions. Finally, for a hard or slightly attractive surface the stretching of a tethered chain is a conformational change that does not correspond to a phase transition. However, when the surface attraction is sufficient to adsorb a chain it will undergo a desorption transition at a critical value of the applied force. Our results for force-induced desorption show the transition to be discontinuous with partially desorbed conformations in the coexistence region.

Insight into structural rearrangements and interdomain interactions related to electron transfer between flavin mononucleotide and heme in nitric oxide synthase: A molecular dynamics study.

PubMed

Sheng, Yinghong; Zhong, Linghao; Guo, Dahai; Lau, Gavin; Feng, Changjian

2015-12-01

Calmodulin (CaM) binding to nitric oxide synthase (NOS) enables a conformational change, in which the FMN domain shuttles between the FAD and heme domains to deliver electrons to the active site heme center. A clear understanding of this large conformational change is critical, since this step is the rate-limiting in NOS catalysis. Herein molecular dynamics simulations were conducted on a model of an oxygenase/FMN (oxyFMN) construct of human inducible NOS (iNOS). This is to investigate the structural rearrangements and the domain interactions related to the FMN-heme interdomain electron transfer (IET). We carried out simulations on the iNOS oxyFMN·CaM complex models in [Fe(III)][FMNH(-)] and [Fe(II)][FMNH] oxidation states, the pre- and post-IET states. The comparison of the dynamics and conformations of the iNOS construct at the two oxidation states has allowed us to identify key factors related to facilitating the FMN-heme IET process. The computational results demonstrated, for the first time, that the conformational change is redox-dependent. Predictions of the key interacting sites in optimal interdomain FMN/heme docking are well supported by experimental data in the literature. An intra-subunit pivot region is predicted to modulate the FMN domain motion and correlate with existence of a bottleneck in the conformational sampling that leads to the electron transfer-competent state. Interactions of the residues identified in this work are proposed to ensure that the FMN domain moves with appropriate degrees of freedom and docks to proper positions at the heme domain, resulting in efficient IET and nitric oxide production. Copyright © 2015 Elsevier Inc. All rights reserved.

3D-QSAR and docking studies on 4-anilinoquinazoline and 4-anilinoquinoline epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors

NASA Astrophysics Data System (ADS)

Assefa, Haregewein; Kamath, Shantaram; Buolamwini, John K.

2003-08-01

The overexpression and/or mutation of the epidermal growth factor receptor (EGFR) tyrosine kinase has been observed in many human solid tumors, and is under intense investigation as a novel anticancer molecular target. Comparative 3D-QSAR analyses using different alignments were undertaken employing comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) for 122 anilinoquinazoline and 50 anilinoquinoline inhibitors of EGFR kinase. The SYBYL multifit alignment rule was applied to three different conformational templates, two obtained from a MacroModel Monte Carlo conformational search, and one from the bound conformation of erlotinib in complex with EGFR in the X-ray crystal structure. In addition, a flexible ligand docking alignment obtained with the GOLD docking program, and a novel flexible receptor-guided consensus dynamics alignment obtained with the DISCOVER program in the INSIGHTII modeling package were also investigated. 3D-QSAR models with q2 values up to 0.70 and r2 values up to 0.97 were obtained. Among the 4-anilinoquinazoline set, the q2 values were similar, but the ability of the different conformational models to predict the activities of an external test set varied considerably. In this regard, the model derived using the X-ray crystallographically determined bioactive conformation of erlotinib afforded the best predictive model. Electrostatic, hydrophobic and H-bond donor descriptors contributed the most to the QSAR models of the 4-anilinoquinazolines, whereas electrostatic, hydrophobic and H-bond acceptor descriptors contributed the most to the 4-anilinoquinoline QSAR, particularly the H-bond acceptor descriptor. A novel receptor-guided consensus dynamics alignment has also been introduced for 3D-QSAR studies. This new alignment method may incorporate to some extent ligand-receptor induced fit effects into 3D-QSAR models.

DNA Sequence-Dependent Ionic Currents in Ultra-Small Solid-State Nanopores†

PubMed Central

Comer, Jeffrey

2016-01-01

Measurements of ionic currents through nanopores partially blocked by DNA have emerged as a powerful method for characterization of the DNA nucleotide sequence. Although the effect of the nucleotide sequence on the nanopore blockade current has been experimentally demonstrated, prediction and interpretation of such measurements remain a formidable challenge. Using atomic resolution computational approaches, here we show how the sequence, molecular conformation, and pore geometry affect the blockade ionic current in model solid-state nanopores. We demonstrate that the blockade current from a DNA molecule is determined by the chemical identities and conformations of at least three consecutive nucleotides. We find the blockade currents produced by the nucleotide triplets to vary considerably with their nucleotide sequence despite having nearly identical molecular conformations. Encouragingly, we find blockade current differences as large as 25% for single-base substitutions in ultra small (1.6 nm × 1.1 nm cross section; 2 nm length) solid-state nanopores. Despite the complex dependence of the blockade current on the sequence and conformation of the DNA triplets, we find that, under many conditions, the number of thymine bases is positively correlated with the current, whereas the number of purine bases and the presence of both purine and pyrimidines in the triplet are negatively correlated with the current. Based on these observations, we construct a simple theoretical model that relates the ion current to the base content of a solid-state nanopore. Furthermore, we show that compact conformations of DNA in narrow pores provide the greatest signal-to-noise ratio for single base detection, whereas reduction of the nanopore length increases the ionic current noise. Thus, the sequence dependence of nanopore blockade current can be theoretically rationalized, although the predictions will likely need to be customized for each nanopore type. PMID:27103233

Learning representative features for facial images based on a modified principal component analysis

NASA Astrophysics Data System (ADS)

Averkin, Anton; Potapov, Alexey

2013-05-01

The paper is devoted to facial image analysis and particularly deals with the problem of automatic evaluation of the attractiveness of human faces. We propose a new approach for automatic construction of feature space based on a modified principal component analysis. Input data sets for the algorithm are the learning data sets of facial images, which are rated by one person. The proposed approach allows one to extract features of the individual subjective face beauty perception and to predict attractiveness values for new facial images, which were not included into a learning data set. The Pearson correlation coefficient between values predicted by our method for new facial images and personal attractiveness estimation values equals to 0.89. This means that the new approach proposed is promising and can be used for predicting subjective face attractiveness values in real systems of the facial images analysis.

Rule Mining Techniques to Predict Prokaryotic Metabolic Pathways.

PubMed

Saidi, Rabie; Boudellioua, Imane; Martin, Maria J; Solovyev, Victor

2017-01-01

It is becoming more evident that computational methods are needed for the identification and the mapping of pathways in new genomes. We introduce an automatic annotation system (ARBA4Path Association Rule-Based Annotator for Pathways) that utilizes rule mining techniques to predict metabolic pathways across wide range of prokaryotes. It was demonstrated that specific combinations of protein domains (recorded in our rules) strongly determine pathways in which proteins are involved and thus provide information that let us very accurately assign pathway membership (with precision of 0.999 and recall of 0.966) to proteins of a given prokaryotic taxon. Our system can be used to enhance the quality of automatically generated annotations as well as annotating proteins with unknown function. The prediction models are represented in the form of human-readable rules, and they can be used effectively to add absent pathway information to many proteins in UniProtKB/TrEMBL database.

Conformational B-cell epitopes prediction from sequences using cost-sensitive ensemble classifiers and spatial clustering.

PubMed

Zhang, Jian; Zhao, Xiaowei; Sun, Pingping; Gao, Bo; Ma, Zhiqiang

2014-01-01

B-cell epitopes are regions of the antigen surface which can be recognized by certain antibodies and elicit the immune response. Identification of epitopes for a given antigen chain finds vital applications in vaccine and drug research. Experimental prediction of B-cell epitopes is time-consuming and resource intensive, which may benefit from the computational approaches to identify B-cell epitopes. In this paper, a novel cost-sensitive ensemble algorithm is proposed for predicting the antigenic determinant residues and then a spatial clustering algorithm is adopted to identify the potential epitopes. Firstly, we explore various discriminative features from primary sequences. Secondly, cost-sensitive ensemble scheme is introduced to deal with imbalanced learning problem. Thirdly, we adopt spatial algorithm to tell which residues may potentially form the epitopes. Based on the strategies mentioned above, a new predictor, called CBEP (conformational B-cell epitopes prediction), is proposed in this study. CBEP achieves good prediction performance with the mean AUC scores (AUCs) of 0.721 and 0.703 on two benchmark datasets (bound and unbound) using the leave-one-out cross-validation (LOOCV). When compared with previous prediction tools, CBEP produces higher sensitivity and comparable specificity values. A web server named CBEP which implements the proposed method is available for academic use.

"Rate My Therapist": Automated Detection of Empathy in Drug and Alcohol Counseling via Speech and Language Processing.

PubMed

Xiao, Bo; Imel, Zac E; Georgiou, Panayiotis G; Atkins, David C; Narayanan, Shrikanth S

2015-01-01

The technology for evaluating patient-provider interactions in psychotherapy-observational coding-has not changed in 70 years. It is labor-intensive, error prone, and expensive, limiting its use in evaluating psychotherapy in the real world. Engineering solutions from speech and language processing provide new methods for the automatic evaluation of provider ratings from session recordings. The primary data are 200 Motivational Interviewing (MI) sessions from a study on MI training methods with observer ratings of counselor empathy. Automatic Speech Recognition (ASR) was used to transcribe sessions, and the resulting words were used in a text-based predictive model of empathy. Two supporting datasets trained the speech processing tasks including ASR (1200 transcripts from heterogeneous psychotherapy sessions and 153 transcripts and session recordings from 5 MI clinical trials). The accuracy of computationally-derived empathy ratings were evaluated against human ratings for each provider. Computationally-derived empathy scores and classifications (high vs. low) were highly accurate against human-based codes and classifications, with a correlation of 0.65 and F-score (a weighted average of sensitivity and specificity) of 0.86, respectively. Empathy prediction using human transcription as input (as opposed to ASR) resulted in a slight increase in prediction accuracies, suggesting that the fully automatic system with ASR is relatively robust. Using speech and language processing methods, it is possible to generate accurate predictions of provider performance in psychotherapy from audio recordings alone. This technology can support large-scale evaluation of psychotherapy for dissemination and process studies.

Fully automatic assignment of small molecules' NMR spectra without relying on chemical shift predictions.

PubMed

Castillo, Andrés M; Bernal, Andrés; Patiny, Luc; Wist, Julien

2015-08-01

We present a method for the automatic assignment of small molecules' NMR spectra. The method includes an automatic and novel self-consistent peak-picking routine that validates NMR peaks in each spectrum against peaks in the same or other spectra that are due to the same resonances. The auto-assignment routine used is based on branch-and-bound optimization and relies predominantly on integration and correlation data; chemical shift information may be included when available to fasten the search and shorten the list of viable assignments, but in most cases tested, it is not required in order to find the correct assignment. This automatic assignment method is implemented as a web-based tool that runs without any user input other than the acquired spectra. Copyright © 2015 John Wiley & Sons, Ltd.

Do the Contents of Visual Working Memory Automatically Influence Attentional Selection During Visual Search?

PubMed Central

Woodman, Geoffrey F.; Luck, Steven J.

2007-01-01

In many theories of cognition, researchers propose that working memory and perception operate interactively. For example, in previous studies researchers have suggested that sensory inputs matching the contents of working memory will have an automatic advantage in the competition for processing resources. The authors tested this hypothesis by requiring observers to perform a visual search task while concurrently maintaining object representations in visual working memory. The hypothesis that working memory activation produces a simple but uncontrollable bias signal leads to the prediction that items matching the contents of working memory will automatically capture attention. However, no evidence for automatic attentional capture was obtained; instead, the participants avoided attending to these items. Thus, the contents of working memory can be used in a flexible manner for facilitation or inhibition of processing. PMID:17469973

Do the contents of visual working memory automatically influence attentional selection during visual search?

PubMed

Woodman, Geoffrey F; Luck, Steven J

2007-04-01

In many theories of cognition, researchers propose that working memory and perception operate interactively. For example, in previous studies researchers have suggested that sensory inputs matching the contents of working memory will have an automatic advantage in the competition for processing resources. The authors tested this hypothesis by requiring observers to perform a visual search task while concurrently maintaining object representations in visual working memory. The hypothesis that working memory activation produces a simple but uncontrollable bias signal leads to the prediction that items matching the contents of working memory will automatically capture attention. However, no evidence for automatic attentional capture was obtained; instead, the participants avoided attending to these items. Thus, the contents of working memory can be used in a flexible manner for facilitation or inhibition of processing.

Using genetic algorithms to optimize the analogue method for precipitation prediction in the Swiss Alps

NASA Astrophysics Data System (ADS)

Horton, Pascal; Jaboyedoff, Michel; Obled, Charles

2018-01-01

Analogue methods provide a statistical precipitation prediction based on synoptic predictors supplied by general circulation models or numerical weather prediction models. The method samples a selection of days in the archives that are similar to the target day to be predicted, and consider their set of corresponding observed precipitation (the predictand) as the conditional distribution for the target day. The relationship between the predictors and predictands relies on some parameters that characterize how and where the similarity between two atmospheric situations is defined. This relationship is usually established by a semi-automatic sequential procedure that has strong limitations: (i) it cannot automatically choose the pressure levels and temporal windows (hour of the day) for a given meteorological variable, (ii) it cannot handle dependencies between parameters, and (iii) it cannot easily handle new degrees of freedom. In this work, a global optimization approach relying on genetic algorithms could optimize all parameters jointly and automatically. The global optimization was applied to some variants of the analogue method for the Rhône catchment in the Swiss Alps. The performance scores increased compared to reference methods, especially for days with high precipitation totals. The resulting parameters were found to be relevant and coherent between the different subregions of the catchment. Moreover, they were obtained automatically and objectively, which reduces the effort that needs to be invested in exploration attempts when adapting the method to a new region or for a new predictand. For example, it obviates the need to assess a large number of combinations of pressure levels and temporal windows of predictor variables that were manually selected beforehand. The optimization could also take into account parameter inter-dependencies. In addition, the approach allowed for new degrees of freedom, such as a possible weighting between pressure levels, and non-overlapping spatial windows.

Puckering free energy of pyranoses: A NMR and metadynamics-umbrella sampling investigation

NASA Astrophysics Data System (ADS)

Autieri, E.; Sega, M.; Pederiva, F.; Guella, G.

2010-09-01

We present the results of a combined metadynamics-umbrella sampling investigation of the puckered conformers of pyranoses described using the GROMOS 45a4 force field. The free energy landscape of Cremer-Pople puckering coordinates has been calculated for the whole series of α and β aldohexoses, showing that the current force field parameters fail in reproducing proper puckering free energy differences between chair conformers. We suggest a modification to the GROMOS 45a4 parameter set which improves considerably the agreement of simulation results with theoretical and experimental estimates of puckering free energies. We also report on the experimental measurement of altrose conformer populations by means of NMR spectroscopy, which show good agreement with the predictions of current theoretical models.

Computational analysis of the binding ability of heterocyclic and conformationally constrained epibatidine analogs in the neuronal nicotinic acetylcholine receptor.

PubMed

Soriano, Elena; Marco-Contelles, José; Colmena, Inés; Gandía, Luis

2010-05-01

One of the most critical issues on the study of ligand-receptor interactions in drug design is the knowledge of the bioactive conformation of the ligand. In this study, we describe a computational approach aimed at estimating the binding ability of epibatidine analogs to interact with the neuronal nicotinic acetylcholine receptor (nAChR) and get insights into the bioactive conformation. The protocol followed consists of a docking analysis and evaluation of pharmacophore parameters of the docked structures. On the basis of the biological data, the results have revealed that the docking analysis is able to predict active ligands, whereas further efforts are needed to develop a suitable and solid pharmacophore model.

GENIUS In Silico Screening Technology for HCV Drug Discovery.

PubMed

Patil, Vaishali M; Masand, Neeraj; Gupta, Satya P

2016-01-01

The various reported in silico screening protocols such as molecular docking are associated with various drawbacks as well as benefits. In molecular docking, on interaction with ligand, the protein or receptor molecule gets activated by adopting conformational changes. These conformational changes cannot be utilized to predict the 3D structure of a protein-ligand complex from unbound protein conformations rigid docking, which necessitates the demand for understanding protein flexibility. Therefore, efficiency and accuracy of docking should be achieved and various available/developed protocols may be adopted. One such protocol is GENIUS induced-fit docking and it is used effectively for the development of anti-HCV NS3-4A serine protease inhibitors. The present review elaborates the GENIUS docking protocol along with its benefits and drawbacks.

PubChem3D: Conformer generation

PubMed Central

2011-01-01

Background PubChem, an open archive for the biological activities of small molecules, provides search and analysis tools to assist users in locating desired information. Many of these tools focus on the notion of chemical structure similarity at some level. PubChem3D enables similarity of chemical structure 3-D conformers to augment the existing similarity of 2-D chemical structure graphs. It is also desirable to relate theoretical 3-D descriptions of chemical structures to experimental biological activity. As such, it is important to be assured that the theoretical conformer models can reproduce experimentally determined bioactive conformations. In the present study, we investigate the effects of three primary conformer generation parameters (the fragment sampling rate, the energy window size, and force field variant) upon the accuracy of theoretical conformer models, and determined optimal settings for PubChem3D conformer model generation and conformer sampling. Results Using the software package OMEGA from OpenEye Scientific Software, Inc., theoretical 3-D conformer models were generated for 25,972 small-molecule ligands, whose 3-D structures were experimentally determined. Different values for primary conformer generation parameters were systematically tested to find optimal settings. Employing a greater fragment sampling rate than the default did not improve the accuracy of the theoretical conformer model ensembles. An ever increasing energy window did increase the overall average accuracy, with rapid convergence observed at 10 kcal/mol and 15 kcal/mol for model building and torsion search, respectively; however, subsequent study showed that an energy threshold of 25 kcal/mol for torsion search resulted in slightly improved results for larger and more flexible structures. Exclusion of coulomb terms from the 94s variant of the Merck molecular force field (MMFF94s) in the torsion search stage gave more accurate conformer models at lower energy windows. Overall average accuracy of reproduction of bioactive conformations was remarkably linear with respect to both non-hydrogen atom count ("size") and effective rotor count ("flexibility"). Using these as independent variables, a regression equation was developed to predict the RMSD accuracy of a theoretical ensemble to reproduce bioactive conformations. The equation was modified to give a minimum RMSD conformer sampling value to help ensure that 90% of the sampled theoretical models should contain at least one conformer within the RMSD sampling value to a "bioactive" conformation. Conclusion Optimal parameters for conformer generation using OMEGA were explored and determined. An equation was developed that provides an RMSD sampling value to use that is based on the relative accuracy to reproduce bioactive conformations. The optimal conformer generation parameters and RMSD sampling values determined are used by the PubChem3D project to generate theoretical conformer models. PMID:21272340

QSPR models for various physical properties of carbohydrates based on molecular mechanics and quantum chemical calculations.

PubMed

Dyekjaer, Jane Dannow; Jónsdóttir, Svava Osk

2004-01-22

Quantitative Structure-Property Relationships (QSPR) have been developed for a series of monosaccharides, including the physical properties of partial molar heat capacity, heat of solution, melting point, heat of fusion, glass-transition temperature, and solid state density. The models were based on molecular descriptors obtained from molecular mechanics and quantum chemical calculations, combined with other types of descriptors. Saccharides exhibit a large degree of conformational flexibility, therefore a methodology for selecting the energetically most favorable conformers has been developed, and was used for the development of the QSPR models. In most cases good correlations were obtained for monosaccharides. For five of the properties predictions were made for disaccharides, and the predicted values for the partial molar heat capacities were in excellent agreement with experimental values.

NIAS-Server: Neighbors Influence of Amino acids and Secondary Structures in Proteins.

PubMed

Borguesan, Bruno; Inostroza-Ponta, Mario; Dorn, Márcio

2017-03-01

The exponential growth in the number of experimentally determined three-dimensional protein structures provide a new and relevant knowledge about the conformation of amino acids in proteins. Only a few of probability densities of amino acids are publicly available for use in structure validation and prediction methods. NIAS (Neighbors Influence of Amino acids and Secondary structures) is a web-based tool used to extract information about conformational preferences of amino acid residues and secondary structures in experimental-determined protein templates. This information is useful, for example, to characterize folds and local motifs in proteins, molecular folding, and can help the solution of complex problems such as protein structure prediction, protein design, among others. The NIAS-Server and supplementary data are available at http://sbcb.inf.ufrgs.br/nias .

Efficient Semi-Automatic 3D Segmentation for Neuron Tracing in Electron Microscopy Images

PubMed Central

Jones, Cory; Liu, Ting; Cohan, Nathaniel Wood; Ellisman, Mark; Tasdizen, Tolga

2015-01-01

0.1. Background In the area of connectomics, there is a significant gap between the time required for data acquisition and dense reconstruction of the neural processes contained in the same dataset. Automatic methods are able to eliminate this timing gap, but the state-of-the-art accuracy so far is insufficient for use without user corrections. If completed naively, this process of correction can be tedious and time consuming. 0.2. New Method We present a new semi-automatic method that can be used to perform 3D segmentation of neurites in EM image stacks. It utilizes an automatic method that creates a hierarchical structure for recommended merges of superpixels. The user is then guided through each predicted region to quickly identify errors and establish correct links. 0.3. Results We tested our method on three datasets with both novice and expert users. Accuracy and timing were compared with published automatic, semi-automatic, and manual results. 0.4. Comparison with Existing Methods Post-automatic correction methods have also been used in [1] and [2]. These methods do not provide navigation or suggestions in the manner we present. Other semi-automatic methods require user input prior to the automatic segmentation such as [3] and [4] and are inherently different than our method. 0.5. Conclusion Using this method on the three datasets, novice users achieved accuracy exceeding state-of-the-art automatic results, and expert users achieved accuracy on par with full manual labeling but with a 70% time improvement when compared with other examples in publication. PMID:25769273

Analysis of the interface variability in NMR structure ensembles of protein-protein complexes.

PubMed

Calvanese, Luisa; D'Auria, Gabriella; Vangone, Anna; Falcigno, Lucia; Oliva, Romina

2016-06-01

NMR structures consist in ensembles of conformers, all satisfying the experimental restraints, which exhibit a certain degree of structural variability. We analyzed here the interface in NMR ensembles of protein-protein heterodimeric complexes and found it to span a wide range of different conservations. The different exhibited conservations do not simply correlate with the size of the systems/interfaces, and are most probably the result of an interplay between different factors, including the quality of experimental data and the intrinsic complex flexibility. In any case, this information is not to be missed when NMR structures of protein-protein complexes are analyzed; especially considering that, as we also show here, the first NMR conformer is usually not the one which best reflects the overall interface. To quantify the interface conservation and to analyze it, we used an approach originally conceived for the analysis and ranking of ensembles of docking models, which has now been extended to directly deal with NMR ensembles. We propose this approach, based on the conservation of the inter-residue contacts at the interface, both for the analysis of the interface in whole ensembles of NMR complexes and for the possible selection of a single conformer as the best representative of the overall interface. In order to make the analyses automatic and fast, we made the protocol available as a web tool at: https://www.molnac.unisa.it/BioTools/consrank/consrank-nmr.html. Copyright © 2016 Elsevier Inc. All rights reserved.

Dosimetric differences between intraoperative and postoperative plans using Cs-131 in transrectal ultrasound–guided brachytherapy for prostatic carcinoma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jones, Andrew, E-mail: aojones@geisinger.edu; Treas, Jared; Yavoich, Brian

2014-01-01

The aim of the study was to investigate the differences between intraoperative and postoperative dosimetry for transrectal ultrasound–guided transperineal prostate implants using cesium-131 ({sup 131}Cs). Between 2006 and 2010, 166 patients implanted with {sup 131}Cs had both intraoperative and postoperative dosimetry studies. All cases were monotherapy and doses of 115 were prescribed to the prostate. The dosimetric properties (D{sub 90}, V{sub 150}, and V{sub 100} for the prostate) of the studies were compared. Two conformity indices were also calculated and compared. Finally, the prostate was automatically sectioned into 6 sectors (anterior and posterior sectors at the base, midgland, and apex)more » and the intraoperative and postoperative dosimetry was compared in each individual sector. Postoperative dosimetry showed statistically significant changes (p < 0.01) in every dosimetric value except V{sub 150}. In each significant case, the postoperative plans showed lower dose coverage. The conformity indexes also showed a bimodal frequency distribution with the index indicating poorer dose conformity in the postoperative plans. Sector analysis revealed less dose coverage postoperatively in the base and apex sectors with an increase in dose to the posterior midgland sector. Postoperative dosimetry overall and in specific sectors of the prostate differs significantly from intraoperative planning. Care must be taken during the intraoperative planning stage to ensure complete dose coverage of the prostate with the understanding that the final postoperative dosimetry will show less dose coverage.« less

Rapid, Potentially Automatable, Method Extract Biomarkers for HPLC/ESI/MS/MS to Detect and Identify BW Agents

DTIC Science & Technology

1997-11-01

status can sometimes be reflected in the infectious potential or drug resistance of those pathogens. For example, in Mycobacterium tuberculosis ... Mycobacterium tuberculosis , its antibiotic resistance and prediction of pathogenicity amongst Mycobacterium spp. based on signature lipid biomarkers ...TITLE AND SUBTITLE Rapid, Potentially Automatable, Method Extract Biomarkers for HPLC/ESI/MS/MS to Detect and Identify BW Agents 5a. CONTRACT NUMBER 5b

From Extraction of Local Structures of Protein Energy Landscapes to Improved Decoy Selection in Template-Free Protein Structure Prediction.

PubMed

Akhter, Nasrin; Shehu, Amarda

2018-01-19

Due to the essential role that the three-dimensional conformation of a protein plays in regulating interactions with molecular partners, wet and dry laboratories seek biologically-active conformations of a protein to decode its function. Computational approaches are gaining prominence due to the labor and cost demands of wet laboratory investigations. Template-free methods can now compute thousands of conformations known as decoys, but selecting native conformations from the generated decoys remains challenging. Repeatedly, research has shown that the protein energy functions whose minima are sought in the generation of decoys are unreliable indicators of nativeness. The prevalent approach ignores energy altogether and clusters decoys by conformational similarity. Complementary recent efforts design protein-specific scoring functions or train machine learning models on labeled decoys. In this paper, we show that an informative consideration of energy can be carried out under the energy landscape view. Specifically, we leverage local structures known as basins in the energy landscape probed by a template-free method. We propose and compare various strategies of basin-based decoy selection that we demonstrate are superior to clustering-based strategies. The presented results point to further directions of research for improving decoy selection, including the ability to properly consider the multiplicity of native conformations of proteins.

Accelerating the Conformational Sampling of Intrinsically Disordered Proteins.

PubMed

Do, Trang Nhu; Choy, Wing-Yiu; Karttunen, Mikko

2014-11-11

Intrinsically disordered proteins (IDPs) are a class of proteins lacking a well-defined secondary structure. Instead, they are able to attain multiple conformations, bind to multiple targets, and respond to changes in their surroundings. Functionally, IDPs have been associated with molecular recognition, cell regulation, and signal transduction. The dynamic conformational ensemble of IDPs is highly environmental and binding partner dependent, rendering the characterization of IDPs extremely challenging. Here, we compare the sampling efficiencies of conventional molecular dynamics (MD), well-tempered metadynamics (WT-META), and bias-exchange metadynamics (BE-META). The total simulation time was over 10 μs, and a 20-mer peptide derived from the Neh2 domain of the Nuclear factor erythroid 2-related factor 2 (Nrf2) protein was simulated. BE-META, with a neutral replica and seven biased replicas employing a set of seven relevant collective variables (CVs), provided the most reliable and efficient sampling. Finally, we propose a free-energy reconstruction method based on the probability distribution of the secondary structure contents. This postprocessing analysis confirms the presence of not only the β-hairpin conformation of the free Neh2 peptide but also its rare bound-state-like conformation, both of that have been experimentally observed. In addition, our simulations also predict other possible conformations to be verified with future experiments.

Improvements to robotics-inspired conformational sampling in rosetta.

PubMed

Stein, Amelie; Kortemme, Tanja

2013-01-01

To accurately predict protein conformations in atomic detail, a computational method must be capable of sampling models sufficiently close to the native structure. All-atom sampling is difficult because of the vast number of possible conformations and extremely rugged energy landscapes. Here, we test three sampling strategies to address these difficulties: conformational diversification, intensification of torsion and omega-angle sampling and parameter annealing. We evaluate these strategies in the context of the robotics-based kinematic closure (KIC) method for local conformational sampling in Rosetta on an established benchmark set of 45 12-residue protein segments without regular secondary structure. We quantify performance as the fraction of sub-Angstrom models generated. While improvements with individual strategies are only modest, the combination of intensification and annealing strategies into a new "next-generation KIC" method yields a four-fold increase over standard KIC in the median percentage of sub-Angstrom models across the dataset. Such improvements enable progress on more difficult problems, as demonstrated on longer segments, several of which could not be accurately remodeled with previous methods. Given its improved sampling capability, next-generation KIC should allow advances in other applications such as local conformational remodeling of multiple segments simultaneously, flexible backbone sequence design, and development of more accurate energy functions.

Improvements to Robotics-Inspired Conformational Sampling in Rosetta

PubMed Central

Stein, Amelie; Kortemme, Tanja

2013-01-01

To accurately predict protein conformations in atomic detail, a computational method must be capable of sampling models sufficiently close to the native structure. All-atom sampling is difficult because of the vast number of possible conformations and extremely rugged energy landscapes. Here, we test three sampling strategies to address these difficulties: conformational diversification, intensification of torsion and omega-angle sampling and parameter annealing. We evaluate these strategies in the context of the robotics-based kinematic closure (KIC) method for local conformational sampling in Rosetta on an established benchmark set of 45 12-residue protein segments without regular secondary structure. We quantify performance as the fraction of sub-Angstrom models generated. While improvements with individual strategies are only modest, the combination of intensification and annealing strategies into a new “next-generation KIC” method yields a four-fold increase over standard KIC in the median percentage of sub-Angstrom models across the dataset. Such improvements enable progress on more difficult problems, as demonstrated on longer segments, several of which could not be accurately remodeled with previous methods. Given its improved sampling capability, next-generation KIC should allow advances in other applications such as local conformational remodeling of multiple segments simultaneously, flexible backbone sequence design, and development of more accurate energy functions. PMID:23704889

Predicting Third Grade Reading Success from Kindergarten Phonological Awareness

ERIC Educational Resources Information Center

Robinson, Stephanie J.

2013-01-01

Although phonological awareness (PA) is an essential preliteracy skill with well-established predictive validity for elementary school reading success, previous research indicates that PA intervention does not demonstrate long term effects on reading. The theory of automaticity was the underlying foundation used to understand the importance of…

49 CFR Appendix D to Part 222 - Determining Risk Levels

Code of Federal Regulations, 2012 CFR

2012-10-01

... collision probability. There are three formulas, one for each warning device category: 1. automatic gates... risk for all public highway-rail grade crossings that are part of a quiet zone. The Prediction Formulas (a) The Prediction Formulas were developed by DOT as a guide for allocating scarce traffic safety...

49 CFR Appendix D to Part 222 - Determining Risk Levels

Code of Federal Regulations, 2014 CFR

2014-10-01

... collision probability. There are three formulas, one for each warning device category: 1. automatic gates... risk for all public highway-rail grade crossings that are part of a quiet zone. The Prediction Formulas (a) The Prediction Formulas were developed by DOT as a guide for allocating scarce traffic safety...

49 CFR Appendix D to Part 222 - Determining Risk Levels

Code of Federal Regulations, 2013 CFR

2013-10-01

... collision probability. There are three formulas, one for each warning device category: 1. automatic gates... risk for all public highway-rail grade crossings that are part of a quiet zone. The Prediction Formulas (a) The Prediction Formulas were developed by DOT as a guide for allocating scarce traffic safety...

Early prediction of eruption site using lightning location data: An operational real-time system in Iceland

NASA Astrophysics Data System (ADS)

Arason, Þórður; Bjornsson, Halldór; Nína Petersen, Guðrún

2013-04-01

Eruption of subglacial volcanoes may lead to catastrophic floods and thus early determination of the exact eruption site may be critical to civil protection evacuation plans. A system is being developed that automatically monitors and analyses volcanic lightning in Iceland. The system predicts the eruption site location from mean lightning locations, taking into account upper level wind. In estimating mean lightning locations, outliers are automatically omitted. A simple wind correction is performed based on the vector wind at the 500 hPa pressure level in the latest radiosonde from Keflavík airport. The system automatically creates a web page with maps and tables showing individual lightning locations and mean locations with and without wind corrections along with estimates of uncetainty. A dormant automatic monitoring system, waiting for a rare event, potentially for several years, is quite susceptible to degeneration during the waiting period, e.g. due to computer or other IT-system upgrades. However, ordinary weather thunderstorms in Iceland should initiate special monitoring and automatic analysis of this system in the same fashion as during a volcanic eruption. Such ordinary weather thunderstorm events will be used to observe anomalies and malfunctions in the system. The essential elements of this system will be described. An example is presented of how the system would have worked during the first hours of the Grímsvötn 2011 eruption. In that case the exact eruption site, within the Grímsvötn caldera, was first known about 15 hours into the eruption.

De Novo Chromosome Structure Prediction

NASA Astrophysics Data System (ADS)

di Pierro, Michele; Cheng, Ryan R.; Lieberman-Aiden, Erez; Wolynes, Peter G.; Onuchic, Jose'n.

Chromatin consists of DNA and hundreds of proteins that interact with the genetic material. In vivo, chromatin folds into nonrandom structures. The physical mechanism leading to these characteristic conformations, however, remains poorly understood. We recently introduced MiChroM, a model that generates chromosome conformations by using the idea that chromatin can be subdivided into types based on its biochemical interactions. Here we extend and complete our previous finding by showing that structural chromatin types can be inferred from ChIP-Seq data. Chromatin types, which are distinct from DNA sequence, are partially epigenetically controlled and change during cell differentiation, thus constituting a link between epigenetics, chromosomal organization, and cell development. We show that, for GM12878 lymphoblastoid cells we are able to predict accurate chromosome structures with the only input of genomic data. The degree of accuracy achieved by our prediction supports the viability of the proposed physical mechanism of chromatin folding and makes the computational model a powerful tool for future investigations.