Computational Screening and Selection of Cyclic Peptide Hairpin Mimetics by Molecular Simulation and Kinetic Network Models

2014 ◽  
Vol 54 (5) ◽  
pp. 1425-1432 ◽  
Author(s):  
Asghar M. Razavi ◽  
William M. Wuest ◽  
Vincent A. Voelz
Keyword(s):  
Molecular Simulation ◽  
Cyclic Peptide ◽  
Network Models ◽  
Computational Screening ◽  
Selection Of

Comparison of Molecular Simulation and Pseudo-Rigid-Body Model Predictions for a Carbon Nanotube–Based Compliant Parallel-Guiding Mechanism

2008 ◽  
Vol 130 (4) ◽  
Author(s):  
Christopher M. DiBiasio ◽  
Martin L. Culpepper ◽  
Robert Panas ◽  
Larry L. Howell ◽  
Spencer P. Magleby
Keyword(s):  
Rigid Body ◽  
Molecular Simulation ◽  
Moment Of Inertia ◽  
Bulk Deformation ◽  
Body Model ◽  
Kinematic Behavior ◽  
Model Predictions ◽  
Rigid Body Model ◽  
Simulation Results ◽  
Selection Of

We report on the accuracy of the pseudo-rigid-body model (PRBM) in predicting the behavior of a nanoscale parallel-guiding mechanism (nPGM) that uses two single-walled (5,5) carbon nanotubes (CNTs) as the flexural guiding elements. The nPGM has two regions of behavior: region 1 is governed by the bulk deformation of the nanotubes, and region 2 is characterized by hingelike flexing of four “kinks” that occur due to buckling of the nanotube walls. PRBM parameters for (5,5) CNTs are proposed. Molecular simulation results of region 1 behavior match PRBM predictions of (1) kinematic behavior with less than 7.3% error and (2) elastomechanic behavior with less than 5.7% error. Although region 1 is of more interest because of its well-defined and stable nature, region 2 motion is also investigated. We show that the PRBM parameters are dependent on the selection of the effective tube thickness and moment of inertia, the lesson being that designers must take care to consider the thickness and moment of inertia values when deriving PRBM constants.

scholarly journals Assessment of van der Waals inclusive density functional theory methods for layered electroactive materials

2017 ◽  
Vol 19 (15) ◽  
pp. 10133-10139 ◽  
Author(s):  
Ariel Lozano ◽  
Bruno Escribano ◽  
Elena Akhmatskaya ◽  
Javier Carrasco
Keyword(s):  
Density Functional Theory ◽  
High Throughput ◽  
Density Functional ◽  
Van Der Waals ◽  
Functional Theory ◽  
Electroactive Materials ◽  
Computational Screening ◽  
Inclusive Density ◽  
Selection Of

This work provides solid guidance for the selection of accurate and robust vdW-inclusive methods for high-throughput computational screening of layered electroactive materials.

scholarly journals Management performance mapping and the value of information for regional prioritization of management interventions

2018 ◽  
Author(s):  
C. E. Buddenhagen ◽  
J. Andrade Piedra ◽  
G. A. Forbes ◽  
P. Kromann ◽  
I. Navarrete ◽  
...  
Keyword(s):  
Decision Making ◽  
Value Of Information ◽  
High Performance ◽  
Agricultural Development ◽  
Network Models ◽  
Potato Seed ◽  
Seed Systems ◽  
Management Performance ◽  
Management Interventions ◽  
Selection Of

ABSTRACTPolicymakers and donors often need to identify the locations and settings where technologies are most likely to have important effects, to increase the benefits from agricultural development or extension efforts. Higher quality information may help to target the high-payoff locations. The value of information (VOI) in this context is formalized by evaluating the results of decision making guided by a set of information compared to the results of acting without taking the information into account. We present a framework for management performance mapping that includes evaluating the VOI for decision making about geographic priorities in regional intervention strategies, in case studies of Andean and Kenyan potato seed systems. We illustrate use of Bayesian network models and recursive partitioning to characterize the relationship between seed health and yield responses and environmental and management predictors used in studies of seed degeneration. These analyses address the expected performance of an intervention based on geographic predictor variables. In the Andean example, positive selection of seed from asymptomatic plants was more effective at high altitudes in Ecuador. In the Kenyan example, there was the potential to target locations with higher technology adoption rates and with higher potato cropland connectivity, i.e., a likely more important role in regional epidemics. Targeting training to high performance areas would often provide more benefits than would random selection of target areas. We illustrate how assessing the VOI can help inform targeted development programs and support a culture of continuous improvement for interventions.

scholarly journals Quantification and selection of ictogenic zones in epilepsy surgery

2019 ◽  
Author(s):  
Petroula Laiou ◽  
Eleftherios Avramidis ◽  
Marinho A. Lopes ◽  
Eugenio Abela ◽  
Michael Müller ◽  
...  
Keyword(s):  
Computational Models ◽  
Brain Networks ◽  
Network Models ◽  
Combinatorial Problem ◽  
Valuable Insight ◽  
Potential Applicability ◽  
Healthy Functioning ◽  
The Brain ◽  
Insight Into ◽  
Selection Of

AbstractNetwork models of brain dynamics provide valuable insight into the healthy functioning of the brain and how this breaks down in disease. A pertinent example is the use of network models to understand seizure generation (ictogenesis) in epilepsy. Recently, computational models have emerged to aid our understanding of seizures and to predict the outcome of surgical perturbations to brain networks. Such approaches provide the opportunity to quantify the effect of removing regions of tissue from brain networks and thereby search for the optimal resection strategy.Here, we use computational models to elucidate how sets of nodes contribute to the ictogenicity of networks. In small networks we fully elucidate the ictogenicity of all possible sets of nodes and demonstrate that the distribution of ictogenicity across sets depends on network topology. However, the full elucidation is a combinatorial problem that becomes intractable for large networks. Therefore, we develop a global optimisation approach to search for minimal sets of nodes that contribute significantly to ictogenesis. We demonstrate the potential applicability of these methods in practice by identifying optimal sets of nodes to resect in networks derived from 20 individuals who underwent resective surgery for epilepsy.

Input Selection of Wavelet-Coupled Neural Network Models for Rainfall-Runoff Modelling

2018 ◽  
Vol 33 (3) ◽  
pp. 955-973 ◽  
Author(s):  
Muhammad Shoaib ◽  
Asaad Y. Shamseldin ◽  
Sher Khan ◽  
Muhammad Sultan ◽  
Fiaz Ahmad ◽  
...  
Keyword(s):  
Neural Network ◽  
Network Models ◽  
Rainfall Runoff ◽  
Neural Network Models ◽  
Input Selection ◽  
Selection Of

Computational screening of branched cyclic peptide motifs as potential enzyme mimetics

2003 ◽  
Vol 9 (3) ◽  
pp. 145-155 ◽  
Author(s):  
Athanassios Stavrakoudis ◽  
Sevasti Makropoulou ◽  
Vassilios Tsikaris ◽  
Maria Sakarellos-Daitsiotis ◽  
Constantinos Sakarellos ◽  
...  
Keyword(s):  
Cyclic Peptide ◽  
Peptide Motifs ◽  
Computational Screening ◽  
Enzyme Mimetics
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