scholarly journals Computationally reconstructing cotranscriptional RNA folding from experimental data reveals rearrangement of non-native folding intermediates

2021 ◽  
Vol 81 (4) ◽  
pp. 870-883.e10
Author(s):  
Angela M Yu ◽  
Paul M. Gasper ◽  
Luyi Cheng ◽  
Lien B. Lai ◽  
Simi Kaur ◽  
...  
Keyword(s):  
Experimental Data ◽  
Rna Folding ◽  
Folding Intermediates

scholarly journals Extended Structures in RNA Folding Intermediates Are Due to Nonnative Interactions Rather than Electrostatic Repulsion

2010 ◽  
Vol 397 (5) ◽  
pp. 1298-1306 ◽  
Author(s):  
Nathan J. Baird ◽  
Haipeng Gong ◽  
Syed S. Zaheer ◽  
Karl F. Freed ◽  
Tao Pan ◽  
...  
Keyword(s):  
Rna Folding ◽  
Electrostatic Repulsion ◽  
Folding Intermediates

Finding Attractors on a Folding Energy Landscape

2011 ◽  
pp. 572-582
Author(s):  
Wilfred Ndifon ◽  
Jonathan Dushoff
Keyword(s):  
Experimental Data ◽  
Rna Folding ◽  
Energy Landscape ◽  
Theoretical Models ◽  
Folding Energy ◽  
Energy Landscapes ◽  
Folding Kinetics ◽  
Rna Sequences ◽  
Rna Sequence ◽  
Kinetics Of

RNA sequences fold into their native conformations by means of an adaptive search of their folding energy landscapes. The energy landscape may contain one or more suboptimal attractor conformations, making it possible for an RNA sequence to become trapped in a suboptimal attractor during the folding process. How the probability that an RNA sequence will find a given attractor before it finds another one depends on the relative positions of those attractors on the energy landscape is not well understood. Similarly, there is an inadequate understanding of the mechanisms that underlie differences in the amount of time an RNA sequence spends in a particular state. Elucidation of those mechanisms would contribute to the understanding of constraints operating on RNA folding. This chapter explores the kinetics of RNA folding using theoretical models and experimental data. Discrepancies between experimental predictions and expectations based on prevailing assumptions about the determinants of RNA folding kinetics are highlighted. An analogy between kinetic accessibility and evolutionary accessibility is also discussed.

scholarly journals Computationally Reconstructing Cotranscriptional RNA Folding Pathways from Experimental Data Reveals Rearrangement of Non-Native Folding Intermediates

2018 ◽  
Author(s):  
Angela M Yu ◽  
Paul M. Gasper ◽  
Eric J. Strobel ◽  
Kyle E. Watters ◽  
Alan A. Chen ◽  
...  
Keyword(s):  
Rna Folding ◽  
Signal Recognition Particle ◽  
Point Mutations ◽  
Structural Rearrangement ◽  
Folding Pathway ◽  
List Type ◽  
Folding Intermediates ◽  
Folding Pathways ◽  
Dynamics Simulations ◽  
Srp Rna

SummaryThe series of RNA folding events that occur during transcription, or a cotranscriptional folding pathway, can critically influence the functional roles of RNA in the cell. Here we present a method, Reconstructing RNA Dynamics from Data (R2D2), to uncover details of cotranscriptional folding pathways by predicting RNA secondary and tertiary structures from cotranscriptional SHAPE-Seq data. We applied R2D2 to the folding of the Escherichia coli Signal Recognition Particle (SRP) RNA sequence and show that this sequence undergoes folding through non-native intermediate structures that require significant structural rearrangement before reaching the functional native structure. Secondary structure folding pathway predictions and all-atom molecular dynamics simulations of folding intermediates suggest that this rearrangement can proceed through a toehold mediated strand displacement mechanism, which can be disrupted and rescued with point mutations. These results demonstrate that even RNAs with simple functional folds can undergo complex folding processes during synthesis, and that small variations in their sequence can drastically affect their cotranscriptional folding pathways.Highlights- Computational methods predict RNA structures from cotranscriptional SHAPE-Seq data- The E. coli SRP RNA folds into non-native structural intermediates cotranscriptionally- These structures rearrange dynamically to form an extended functional fold- Point mutations can disrupt and rescue cotranscriptional RNA folding pathways

scholarly journals Native Architecture Encodes Cooperativity and Specificity in RNA Folding Intermediates

2012 ◽  
Vol 102 (3) ◽  
pp. 645a-646a
Author(s):  
Reza Behrouzi ◽  
Sarah A. Woodson
Keyword(s):  
Rna Folding ◽  
Folding Intermediates

Microdiffraction Patterns of Small Metallic Particles II; Theoretical Analysis

1982 ◽  
Vol 40 ◽  
pp. 668-669
Author(s):  
A. Gómez ◽  
P. Schabes-Retchkiman ◽  
M. José-Yacamán ◽  
T. Ocaña
Keyword(s):  
Experimental Data ◽  
Electron Diffraction ◽  
Theoretical Analysis ◽  
Size Range ◽  
Dynamical Theory ◽  
Metallic Particles ◽  
Splitting Effect

The splitting effect that is observed in microdiffraction pat-terns of small metallic particles in the size range 50-500 Å can be understood using the dynamical theory of electron diffraction for the case of a crystal containing a finite wedge. For the experimental data we refer to part I of this work in these proceedings.

Evidence for ordered Fe3Ni

1987 ◽  
Vol 45 ◽  
pp. 216-217
Author(s):  
K.B. Reuter ◽  
D.B. Williams ◽  
J.I. Goldstein
Keyword(s):  
Experimental Data ◽  
Martensitic Transformation ◽  
Electron Diffraction ◽  
Room Temperature ◽  
Direct Evidence ◽  
Transformation Product ◽  
Iron Meteorites ◽  
X Ray ◽  
Ni Content ◽  
Temperature Transformation

In the Fe-Ni system, although ordered FeNi and ordered Ni3Fe are experimentally well established, direct evidence for ordered Fe3Ni is unconvincing. Little experimental data for Fe3Ni exists because diffusion is sluggish at temperatures below 400°C and because alloys containing less than 29 wt% Ni undergo a martensitic transformation at room temperature. Fe-Ni phases in iron meteorites were examined in this study because iron meteorites have cooled at slow rates of about 10°C/106 years, allowing phase transformations below 400°C to occur. One low temperature transformation product, called clear taenite 2 (CT2), was of particular interest because it contains less than 30 wtZ Ni and is not martensitic. Because CT2 is only a few microns in size, the structure and Ni content were determined through electron diffraction and x-ray microanalysis. A Philips EM400T operated at 120 kV, equipped with a Tracor Northern 2000 multichannel analyzer, was used.

EELS white line intensities calculated for the 3d and 4d metals

1989 ◽  
Vol 47 ◽  
pp. 388-389
Author(s):  
C. C. Ahn ◽  
D. H. Pearson ◽  
P. Rez ◽  
B. Fultz
Keyword(s):  
Experimental Data ◽  
Line Intensity ◽  
Transition Probabilities ◽  
Initial Increase ◽  
White Line ◽  
Hartree Fock ◽  
Line Intensities ◽  
Integrated Intensity ◽  
X Ray Absorption ◽  
The Continuum

Previous experimental measurements of the total white line intensities from L2,3 energy loss spectra of 3d transition metals reported a linear dependence of the white line intensity on 3d occupancy. These results are inconsistent, however, with behavior inferred from relativistic one electron Dirac-Fock calculations, which show an initial increase followed by a decrease of total white line intensity across the 3d series. This inconsistency with experimental data is especially puzzling in light of work by Thole, et al., which successfully calculates x-ray absorption spectra of the lanthanide M4,5 white lines by employing a less rigorous Hartree-Fock calculation with relativistic corrections based on the work of Cowan. When restricted to transitions allowed by dipole selection rules, the calculated spectra of the lanthanide M4,5 white lines show a decreasing intensity as a function of Z that was consistent with the available experimental data.Here we report the results of Dirac-Fock calculations of the L2,3 white lines of the 3d and 4d elements, and compare the results to the experimental work of Pearson et al. In a previous study, similar calculations helped to account for the non-statistical behavior of L3/L2 ratios of the 3d metals. We assumed that all metals had a single 4s electron. Because these calculations provide absolute transition probabilities, to compare the calculated white line intensities to the experimental data, we normalized the calculated intensities to the intensity of the continuum above the L3 edges. The continuum intensity was obtained by Hartree-Slater calculations, and the normalization factor for the white line intensities was the integrated intensity in an energy window of fixed width and position above the L3 edge of each element.

A fuzzy neural network approach for modeling the growth kinetics of FeB and Fe2B layers during the boronizing process

2018 ◽  
Vol 106 (6) ◽  
pp. 603 ◽  
Author(s):  
Bendaoud Mebarek ◽  
Mourad Keddam
Keyword(s):  
Neural Network ◽  
Experimental Data ◽  
Fuzzy Neural Network ◽  
Treatment Time ◽  
Calculation Model ◽  
Average Error ◽  
Network Approach ◽  
Neural Network Approach ◽  
Fuzzy Neural ◽  
Kinetics Of

In this paper, we develop a boronizing process simulation model based on fuzzy neural network (FNN) approach for estimating the thickness of the FeB and Fe2B layers. The model represents a synthesis of two artificial intelligence techniques; the fuzzy logic and the neural network. Characteristics of the fuzzy neural network approach for the modelling of boronizing process are presented in this study. In order to validate the results of our calculation model, we have used the learning base of experimental data of the powder-pack boronizing of Fe-15Cr alloy in the temperature range from 800 to 1050 °C and for a treatment time ranging from 0.5 to 12 h. The obtained results show that it is possible to estimate the influence of different process parameters. Comparing the results obtained by the artificial neural network to experimental data, the average error generated from the fuzzy neural network was 3% for the FeB layer and 3.5% for the Fe2B layer. The results obtained from the fuzzy neural network approach are in agreement with the experimental data. Finally, the utilization of fuzzy neural network approach is well adapted for the boronizing kinetics of Fe-15Cr alloy.

Use of Posterior Probabilities to Evaluate Methods of Discriminant Analysis

1981 ◽  
Vol 20 (04) ◽  
pp. 207-212 ◽  
Author(s):  
J. Hermans ◽  
B. van Zomeren ◽  
J. W. Raatgever ◽  
P. J. Sterk ◽  
J. D. F. Habbema
Keyword(s):  
Experimental Data ◽  
Discriminant Analysis ◽  
Posterior Probabilities

By means of a case study the choice between several methods of discriminant analysis is presented. Experimental data of a two-groups problem with one or two variables is analysed. The different methods are compared according to posterior probabilities which can be computed for each subject and which are the basis of discriminant analysis. These posterior probabilities are analysed graphically as well as numerically.

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