scholarly journals Van Dooren's Index Sum Theorem and Rational Matrices with Prescribed Structural Data

2019 ◽  
Vol 40 (2) ◽  
pp. 720-738
Author(s):  
Luis M. Anguas ◽  
Froilán M. Dopico ◽  
Richard Hollister ◽  
D. Steven Mackey
Keyword(s):  
Structural Data ◽  
Sum Theorem

Tubulin structure at intermediate resolution

1995 ◽  
Vol 53 ◽  
pp. 852-853
Author(s):  
K. H. Downing ◽  
S. G. Wolf ◽  
E. Nogales
Keyword(s):  
High Resolution ◽  
Structural Data ◽  
Therapeutic Drug ◽  
Zinc Ions ◽  
Two Dimensional ◽  
X Ray Diffraction ◽  
X Ray ◽  
Negative Stain ◽  
Functional Mechanisms ◽  
Tubulin Structure

Microtubules are involved in a host of critical cell activities, many of which involve transport of organelles through the cell. Different sets of microtubules appear to form during the cell cycle for different functions. Knowledge of the structure of tubulin will be necessary in order to understand the various functional mechanisms of microtubule assemble, disassembly, and interaction with other molecules, but tubulin has so far resisted crystallization for x-ray diffraction studies. Fortuitously, in the presence of zinc ions, tubulin also forms two-dimensional, crystalline sheets that are ideally suited for study by electron microscopy. We have refined procedures for forming the sheets and preparing them for EM, and have been able to obtain high-resolution structural data that sheds light on the formation and stabilization of microtubules, and even the interaction with a therapeutic drug.Tubulin sheets had been extensively studied in negative stain, demonstrating that the same protofilament structure was formed in the sheets and microtubules. For high resolution studies, we have found that the sheets embedded in either glucose or tannin diffract to around 3 Å.

HRTEM study of valleriite, a hydroxide-bearing copper sulfide

1990 ◽  
Vol 48 (4) ◽  
pp. 462-463
Author(s):  
S. Wang ◽  
P. R. Buseck
Keyword(s):  
Electron Microscope ◽  
High Resolution ◽  
Copper Sulfide ◽  
Carbonaceous Chondrite ◽  
Structural Data ◽  
Basic Structure ◽  
Long Period ◽  
Selected Area Electron Diffraction ◽  
Transmission Electron ◽  
Wavy Structure

Valleriite is an unusual mineral, consisting of intergrowths of sulfide layers (corresponding in structure to the mineral smythite - Fe9S11) and hydroxide layers (corresponding to brucite - Mg(OH2)). It has a composition of approximately 1.526[Mg.68Al.32(OH)2].[Fe1.07Cu.93S2] and consists of two interpenetrating lattices, each of which retains its individual structural and diffraction characteristics parallel to the layering. The valleriite structure is related to that of tochilinite, an unusual iron-rich mineral that is of considerable interest for the origin of certain carbonaceous chondrite meteorites and to those of franckeite and cylindrite, two minerals that are of interest because of their unique morphological and crystallographic properties, e.g., the distinctive curved form of cylindrite and the perfect mica-like cleavage with unusual striations and the long-period wavy structure of franckeite.Our selected-area electron diffraction (SAED) patterns and high-resolution transmission electron microscope (HRTEM) images of valleriite provide new structural data. A basic structure and a new superstructure have been observed.

The glycomes of Caenorhabditis elegans and other model organisms

2002 ◽  
Vol 69 ◽  
pp. 117-134 ◽  
Author(s):  
Stuart M. Haslam ◽  
David Gems ◽  
Howard R. Morris ◽  
Anne Dell
Keyword(s):  
Caenorhabditis Elegans ◽  
Current Knowledge ◽  
Structural Data ◽  
Model Organisms ◽  
Entire Genome ◽  
C Elegans ◽  
The Face ◽  
Area Of Concern ◽  
Nematode Worm

There is no doubt that the immense amount of information that is being generated by the initial sequencing and secondary interrogation of various genomes will change the face of glycobiological research. However, a major area of concern is that detailed structural knowledge of the ultimate products of genes that are identified as being involved in glycoconjugate biosynthesis is still limited. This is illustrated clearly by the nematode worm Caenorhabditis elegans, which was the first multicellular organism to have its entire genome sequenced. To date, only limited structural data on the glycosylated molecules of this organism have been reported. Our laboratory is addressing this problem by performing detailed MS structural characterization of the N-linked glycans of C. elegans; high-mannose structures dominate, with only minor amounts of complex-type structures. Novel, highly fucosylated truncated structures are also present which are difucosylated on the proximal N-acetylglucosamine of the chitobiose core as well as containing unusual Fucα1–2Gal1–2Man as peripheral structures. The implications of these results in terms of the identification of ligands for genomically predicted lectins and potential glycosyltransferases are discussed in this chapter. Current knowledge on the glycomes of other model organisms such as Dictyostelium discoideum, Saccharomyces cerevisiae and Drosophila melanogaster is also discussed briefly.

scholarly journals Data Reduction in the String Space for Efficient kNN Classification Through Space Partitioning

2020 ◽  
Vol 10 (10) ◽  
pp. 3356 ◽  
Author(s):  
Jose J. Valero-Mas ◽  
Francisco J. Castellanos
Keyword(s):  
Data Reduction ◽  
Structural Data ◽  
Data Representation ◽  
Space Partitioning ◽  
Classification Rate ◽  
Symbolic Data ◽  
Knn Classifier ◽  
Initial Dataset ◽  
Low Efficiency ◽  
High Level

Within the Pattern Recognition field, two representations are generally considered for encoding the data: statistical codifications, which describe elements as feature vectors, and structural representations, which encode elements as high-level symbolic data structures such as strings, trees or graphs. While the vast majority of classifiers are capable of addressing statistical spaces, only some particular methods are suitable for structural representations. The kNN classifier constitutes one of the scarce examples of algorithms capable of tackling both statistical and structural spaces. This method is based on the computation of the dissimilarity between all the samples of the set, which is the main reason for its high versatility, but in turn, for its low efficiency as well. Prototype Generation is one of the possibilities for palliating this issue. These mechanisms generate a reduced version of the initial dataset by performing data transformation and aggregation processes on the initial collection. Nevertheless, these generation processes are quite dependent on the data representation considered, being not generally well defined for structural data. In this work we present the adaptation of the generation-based reduction algorithm Reduction through Homogeneous Clusters to the case of string data. This algorithm performs the reduction by partitioning the space into class-homogeneous clusters for then generating a representative prototype as the median value of each group. Thus, the main issue to tackle is the retrieval of the median element of a set of strings. Our comprehensive experimentation comparatively assesses the performance of this algorithm in both the statistical and the string-based spaces. Results prove the relevance of our approach by showing a competitive compromise between classification rate and data reduction.

scholarly journals Diaminoimidazopyrimidines: Access via the Groebke-Blackburn-Bienaymé Reaction and Structural Data Mining

2020 ◽  
Author(s):  
Markella Konstantinidou ◽  
Zlata Boiarska ◽  
Roberto Butera ◽  
Constantinos G. Neochoritis ◽  
Katarzyna Kurpiewska ◽  
...  
Keyword(s):  
Data Mining ◽  
Structural Data

scholarly journals Water and Deuterium Oxide Permeability through Aquaporin 1: MD Predictions and Experimental Verification

2007 ◽  
Vol 130 (1) ◽  
pp. 111-116 ◽  
Author(s):  
Artem B. Mamonov ◽  
Rob D. Coalson ◽  
Mark L. Zeidel ◽  
John C. Mathai
Keyword(s):  
Deuterium Oxide ◽  
Diffusion Constant ◽  
Structural Data ◽  
Md Simulations ◽  
Water Model ◽  
Aquaporin 1 ◽  
Self Diffusion ◽  
Osmotic Permeability ◽  
Protein Channels ◽  
And Diffusion

Determining the mechanisms of flux through protein channels requires a combination of structural data, permeability measurement, and molecular dynamics (MD) simulations. To further clarify the mechanism of flux through aquaporin 1 (AQP1), osmotic pf (cm3/s/pore) and diffusion pd (cm3/s/pore) permeability coefficients per pore of H2O and D2O in AQP1 were calculated using MD simulations. We then compared the simulation results with experimental measurements of the osmotic AQP1 permeabilities of H2O and D2O. In this manner we evaluated the ability of MD simulations to predict actual flux results. For the MD simulations, the force field parameters of the D2O model were reparameterized from the TIP3P water model to reproduce the experimentally observed difference in the bulk self diffusion constants of H2O vs. D2O. Two MD systems (one for each solvent) were constructed, each containing explicit palmitoyl-oleoyl-phosphatidyl-ethanolamine (POPE) phospholipid molecules, solvent, and AQP1. It was found that the calculated value of pf for D2O is ∼15% smaller than for H2O. Bovine AQP1 was reconstituted into palmitoyl-oleoyl-phosphatidylcholine (POPC) liposomes, and it was found that the measured macroscopic osmotic permeability coefficient Pf (cm/s) of D2O is ∼21% lower than for H2O. The combined computational and experimental results suggest that deuterium oxide permeability through AQP1 is similar to that of water. The slightly lower observed osmotic permeability of D2O compared to H2O in AQP1 is most likely due to the lower self diffusion constant of D2O.

scholarly journals Integrating genome sequence and structural data for statistical learning to predict transcription factor binding sites

2020 ◽  
Vol 48 (22) ◽  
pp. 12604-12617
Author(s):  
Pengpeng Long ◽  
Lu Zhang ◽  
Bin Huang ◽  
Quan Chen ◽  
Haiyan Liu
Keyword(s):  
Genome Sequence ◽  
Energy Function ◽  
Structural Information ◽  
Structural Data ◽  
P Values ◽  
A Genome ◽  
Z Scores ◽  
Transcription Regulators ◽  
Dna Specificity ◽  
Tetracycline Repressor

Abstract We report an approach to predict DNA specificity of the tetracycline repressor (TetR) family transcription regulators (TFRs). First, a genome sequence-based method was streamlined with quantitative P-values defined to filter out reliable predictions. Then, a framework was introduced to incorporate structural data and to train a statistical energy function to score the pairing between TFR and TFR binding site (TFBS) based on sequences. The predictions benchmarked against experiments, TFBSs for 29 out of 30 TFRs were correctly predicted by either the genome sequence-based or the statistical energy-based method. Using P-values or Z-scores as indicators, we estimate that 59.6% of TFRs are covered with relatively reliable predictions by at least one of the two methods, while only 28.7% are covered by the genome sequence-based method alone. Our approach predicts a large number of new TFBs which cannot be correctly retrieved from public databases such as FootprintDB. High-throughput experimental assays suggest that the statistical energy can model the TFBSs of a significant number of TFRs reliably. Thus the energy function may be applied to explore for new TFBSs in respective genomes. It is possible to extend our approach to other transcriptional factor families with sufficient structural information.

scholarly journals Analysis of the Structural Mechanism of ATP Inhibition at the AAA1 Subunit of Cytoplasmic Dynein-1 Using a Chemical “Toolkit”

2021 ◽  
Vol 22 (14) ◽  
pp. 7704
Author(s):  
Sayi’Mone Tati ◽  
Laleh Alisaraie
Keyword(s):  
Binding Affinity ◽  
Atp Hydrolysis ◽  
Critical Role ◽  
Motor Protein ◽  
Structural Data ◽  
Retrograde Transport ◽  
Cytoplasmic Dynein ◽  
Motor Domain ◽  
Conformational Search ◽  
Structural Mechanism

Dynein is a ~1.2 MDa cytoskeletal motor protein that carries organelles via retrograde transport in eukaryotic cells. The motor protein belongs to the ATPase family of proteins associated with diverse cellular activities and plays a critical role in transporting cargoes to the minus end of the microtubules. The motor domain of dynein possesses a hexameric head, where ATP hydrolysis occurs. The presented work analyzes the structure–activity relationship (SAR) of dynapyrazole A and B, as well as ciliobrevin A and D, in their various protonated states and their 46 analogues for their binding in the AAA1 subunit, the leading ATP hydrolytic site of the motor domain. This study exploits in silico methods to look at the analogues’ effects on the functionally essential subsites of the motor domain of dynein 1, since no similar experimental structural data are available. Ciliobrevin and its analogues bind to the ATP motifs of the AAA1, namely, the walker-A (W-A) or P-loop, the walker-B (W-B), and the sensor I and II. Ciliobrevin A shows a better binding affinity than its D analogue. Although the double bond in ciliobrevin A and D was expected to decrease the ligand potency, they show a better affinity to the AAA1 binding site than dynapyrazole A and B, lacking the bond. In addition, protonation of the nitrogen atom in ciliobrevin A and D, as well as dynapyrazole A and B, at the N9 site of ciliobrevin and the N7 of the latter increased their binding affinity. Exploring ciliobrevin A geometrical configuration suggests the E isomer has a superior binding profile over the Z due to binding at the critical ATP motifs. Utilizing the refined structure of the motor domain obtained through protein conformational search in this study exhibits that Arg1852 of the yeast cytoplasmic dynein could involve in the “glutamate switch” mechanism in cytoplasmic dynein 1 in lieu of the conserved Asn in AAA+ protein family.

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