scholarly journals Systematized Analysis of Secondary Structure Dependence of Key Structural Features of Residues in Soluble and Membrane-Bound Proteins

2021 ◽  
pp. 100055
Author(s):  
Mohammed H. A.L. Mughram ◽  
Noah B. Herrington ◽  
Claudio Catalano ◽  
Glen E. Kellogg
Keyword(s):  
Secondary Structure ◽  
Structural Features ◽  
Structure Dependence ◽  
Membrane Bound

A Systematic Review on Popularity, Application and Characteristics of Protein Secondary Structure Prediction Tools

2019 ◽  
Vol 16 (2) ◽  
pp. 159-172 ◽  
Author(s):  
Elaheh Kashani-Amin ◽  
Ozra Tabatabaei-Malazy ◽  
Amirhossein Sakhteman ◽  
Bagher Larijani ◽  
Azadeh Ebrahim-Habibi
Keyword(s):  
Systematic Review ◽  
Secondary Structure ◽  
Structure Prediction ◽  
Web Of Science ◽  
Secondary Structure Prediction ◽  
Structural Information ◽  
Protein Secondary Structure ◽  
Structural Features ◽  
Prediction Tools ◽  
Insight Into

Background: Prediction of proteins’ secondary structure is one of the major steps in the generation of homology models. These models provide structural information which is used to design suitable ligands for potential medicinal targets. However, selecting a proper tool between multiple Secondary Structure Prediction (SSP) options is challenging. The current study is an insight into currently favored methods and tools, within various contexts. Objective: A systematic review was performed for a comprehensive access to recent (2013-2016) studies which used or recommended protein SSP tools. Methods: Three databases, Web of Science, PubMed and Scopus were systematically searched and 99 out of the 209 studies were finally found eligible to extract data. Results: Four categories of applications for 59 retrieved SSP tools were: (I) prediction of structural features of a given sequence, (II) evaluation of a method, (III) providing input for a new SSP method and (IV) integrating an SSP tool as a component for a program. PSIPRED was found to be the most popular tool in all four categories. JPred and tools utilizing PHD (Profile network from HeiDelberg) method occupied second and third places of popularity in categories I and II. JPred was only found in the two first categories, while PHD was present in three fields. Conclusion: This study provides a comprehensive insight into the recent usage of SSP tools which could be helpful for selecting a proper tool.

RNA secondary structure dependence in METTL3–METTL14 mRNA methylation is modulated by the N-terminal domain of METTL3

2020 ◽  
Vol 402 (1) ◽  
pp. 89-98
Author(s):  
Nathalie Meiser ◽  
Nicole Mench ◽  
Martin Hengesbach
Keyword(s):  
Secondary Structure ◽  
Rna Binding ◽  
Specific Protein ◽  
Structure Dependence ◽  
Terminal Domain ◽  
Methylation Assay ◽  
A Site ◽  
Methylation Activity

AbstractN6-methyladenosine (m6A) is the most abundant modification in mRNA. The core of the human N6-methyltransferase complex (MTC) is formed by a heterodimer consisting of METTL3 and METTL14, which specifically catalyzes m6A formation within an RRACH sequence context. Using recombinant proteins in a site-specific methylation assay that allows determination of quantitative methylation yields, our results show that this complex methylates its target RNAs not only sequence but also secondary structure dependent. Furthermore, we demonstrate the role of specific protein domains on both RNA binding and substrate turnover, focusing on postulated RNA binding elements. Our results show that one zinc finger motif within the complex is sufficient to bind RNA, however, both zinc fingers are required for methylation activity. We show that the N-terminal domain of METTL3 alters the secondary structure dependence of methylation yields. Our results demonstrate that a cooperative effect of all RNA-binding elements in the METTL3–METTL14 complex is required for efficient catalysis, and that binding of further proteins affecting the NTD of METTL3 may regulate substrate specificity.

Retinol dehydrogenases: Membrane-bound enzymes for the visual function

2014 ◽  
Vol 92 (6) ◽  
pp. 510-523 ◽  
Author(s):  
Mustapha Lhor ◽  
Christian Salesse
Keyword(s):  
Pigment Epithelium ◽  
Retinal Pigment ◽  
Membrane Binding ◽  
Large Family ◽  
Structural Features ◽  
Visual Cycle ◽  
Retinoid Metabolism ◽  
Current State ◽  
Membrane Bound ◽  
Membrane Bound Enzymes

Retinoid metabolism is important for many physiological functions, such as differenciation, growth, and vision. In the visual context, after the absorption of light in rod photoreceptors by the visual pigment rhodopsin, 11-cis retinal is isomerized to all-trans retinal. This retinoid subsequently undergoes a series of modifications during the visual cycle through a cascade of reactions occurring in photoreceptors and in the retinal pigment epithelium. Retinol dehydrogenases (RDHs) are enzymes responsible for crucial steps of this visual cycle. They belong to a large family of proteins designated as short-chain dehydrogenases/reductases. The structure of these RDHs has been predicted using modern bioinformatics tools, which allowed to propose models with similar structures including a common Rossman fold. These enzymes undergo oxidoreduction reactions, whose direction is dictated by the preference and concentration of their individual cofactor (NAD(H)/NADP(H)). This review presents the current state of knowledge on functional and structural features of RDHs involved in the visual cycle as well as knockout models. RDHs are described as integral or peripheral enzymes. A topology model of the membrane binding of these RDHs via their N- and (or) C-terminal domain has been proposed on the basis of their individual properties. Membrane binding is a crucial issue for these enzymes because of the high hydrophobicity of their retinoid substrates.

scholarly journals Mapping the glycosyltransferase fold landscape using interpretable deep learning

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Rahil Taujale ◽  
Zhongliang Zhou ◽  
Wayland Yeung ◽  
Kelley W. Moremen ◽  
Sheng Li ◽  
...  
Keyword(s):  
Deep Learning ◽  
Secondary Structure ◽  
Structural Features ◽  
Functional Diversification ◽  
Sequence Structure ◽  
Cellular Processes ◽  
And Function ◽  
Deep Learning Model ◽  
Fold Prediction ◽  
Primary Sequence Alignment

AbstractGlycosyltransferases (GTs) play fundamental roles in nearly all cellular processes through the biosynthesis of complex carbohydrates and glycosylation of diverse protein and small molecule substrates. The extensive structural and functional diversification of GTs presents a major challenge in mapping the relationships connecting sequence, structure, fold and function using traditional bioinformatics approaches. Here, we present a convolutional neural network with attention (CNN-attention) based deep learning model that leverages simple secondary structure representations generated from primary sequences to provide GT fold prediction with high accuracy. The model learns distinguishing secondary structure features free of primary sequence alignment constraints and is highly interpretable. It delineates sequence and structural features characteristic of individual fold types, while classifying them into distinct clusters that group evolutionarily divergent families based on shared secondary structural features. We further extend our model to classify GT families of unknown folds and variants of known folds. By identifying families that are likely to adopt novel folds such as GT91, GT96 and GT97, our studies expand the GT fold landscape and prioritize targets for future structural studies.

The alternative oxidases: simple oxidoreductase proteins with complex functions

2013 ◽  
Vol 41 (5) ◽  
pp. 1305-1311 ◽  
Author(s):  
Luke Young ◽  
Tomoo Shiba ◽  
Shigeharu Harada ◽  
Kiyoshi Kita ◽  
Mary S. Albury ◽  
...  
Keyword(s):  
Crystal Structure ◽  
Electron Transport ◽  
Alternative Oxidase ◽  
Structural Features ◽  
Transport Proteins ◽  
Integral Membrane Proteins ◽  
Complex Functions ◽  
Membrane Bound ◽  
Iron Carboxylate ◽  
Electron Transport Proteins

The alternative oxidases are membrane-bound monotopic terminal electron transport proteins found in all plants and in some agrochemically important fungi and parasites including Trypansoma brucei, which is the causative agent of trypanosomiasis. They are integral membrane proteins and reduce oxygen to water in a four electron process. The recent elucidation of the crystal structure of the trypanosomal alternative oxidase at 2.85 Å (1 Å=0.1 nm) has revealed salient structural features necessary for its function. In the present review we compare the primary and secondary ligation spheres of the alternative oxidases with other di-iron carboxylate proteins and propose a mechanism for the reduction of oxygen to water.

Characterization of cytosolic female rat liver receptors of the lactogenic type

1990 ◽  
Vol 123 (2) ◽  
pp. 231-237
Author(s):  
M. Emtner ◽  
P. Roos
Keyword(s):  
Molecular Weight ◽  
Growth Hormone ◽  
Rat Liver ◽  
Microsomal Fraction ◽  
Sodium Dodecyl ◽  
Human Growth ◽  
Structural Features ◽  
Female Rat ◽  
Membrane Bound

Abstract. Some properties of cytosolic receptors of the lactogenic type from female rat liver were studied and compared with those of membrane-bound (microsomal) receptors. The association constant between the cytosolic receptors and human growth hormone was 2.2 l/nmol, which was not significantly different from the value obtained for the microsomal receptors (3.6 l/nmol). Since unlabelled hGH and human prolactin, but not bovine growth hormone, displaced [125I]hGH bound to receptors from both sources, the cytosolic receptors, like the microsomal receptors, must be lactogenic. Furthermore, the cytosolic receptors were recognized by a monoclonal antibody raised against microsomal receptors from female rat liver. However, covalent cross-linking of cytosolic receptors to [125I]hGH and subsequent sodium dodecyl sulphate electrophoresis gave a single band corresponding to a molecular weight of 42 200 (after subtraction of the molecular weight of hGH), which differs significantly (p<0.01) from the values determined for the two distinct bands given by the microsomal fraction. Moreover, upon molecular sieve chromatography the receptor activity in the two fractions appeared at significantly (p<0.05) different elution volumes. These results show that the cytosolic and microsomal receptors have some structural features in common but are definitely not identical.

scholarly journals Structural and Functional Analysis of the RNA Transport Element, a Member of an Extensive Family Present in the Mouse Genome

2005 ◽  
Vol 79 (4) ◽  
pp. 2356-2365 ◽  
Author(s):  
Sergey Smulevitch ◽  
Daniel Michalowski ◽  
Andrei S. Zolotukhin ◽  
Ralf Schneider ◽  
Jenifer Bear ◽  
...  
Keyword(s):  
Secondary Structure ◽  
Nuclear Export ◽  
Mammalian Cells ◽  
Minimal Element ◽  
Structural Features ◽  
Rna Transport ◽  
Immunodeficiency Virus ◽  
Responsive Element ◽  
Nuclear Export Receptor ◽  
Intracisternal A Particle

ABSTRACT We previously identified an RNA transport element (RTE), present in a subclass of rodent intracisternal A particle retroelements (F. Nappi, R. Schneider, A. Zolotukhin, S. Smulevitch, D. Michalowski, J. Bear, B. Felber, and G. Pavlakis, J. Virol. 75:4558-4569, 2001), that is able to replace Rev-responsive element regulation in human immunodeficiency virus type 1. RTE-directed mRNA export is mediated by a still-unknown cellular factor(s), is independent of the CRM1 nuclear export receptor, and is conserved among vertebrates. Here we show that this RTE folds into an extended RNA secondary structure and thus does not resemble any known RTEs. Computer searches revealed the presence of 105 identical elements and more than 3,000 related elements which share at least 70% sequence identity with the RTE and which are found on all mouse chromosomes. These related elements are predicted to fold into RTE-like structures. Comparison of the sequences and structures revealed that the RTE and related elements can be divided into four groups. Mutagenesis of the RTE revealed that the minimal element contains four internal stem-loops, which are indispensable for function in mammalian cells. In contrast, only part of the element is essential to mediate RNA transport in microinjected Xenopus laevis oocyte nuclei. Importantly, the minimal RTE able to promote RNA transport has key structural features which are preserved in all the RTE-related elements, further supporting their functional importance. Therefore, RTE function depends on a complex secondary structure that is important for the interaction with the cellular export factor(s).

Bioinformatics Analysis and Characteristics of Ser/Thr Protein Kinase Encoded by UL13 Gene of Duck Plague Virus

2011 ◽  
Vol 393-395 ◽  
pp. 617-627
Author(s):  
Xi Xia Hu ◽  
An Chun Cheng ◽  
Ming Shu Wang
Keyword(s):  
Protein Kinase ◽  
Secondary Structure ◽  
Physicochemical Properties ◽  
Evolutionary Relationship ◽  
Alpha Helix ◽  
Structural Features ◽  
Functional Study ◽  
Online Tools ◽  
Multiple Sequences ◽  
Sequences Alignment

This report showed some physicochemical properties and structural features about DPV-UL13 protein predicted by some software and online tools. The online analysis of the physicochemical properties demonstrates that the protein has thirty-four potential phosphorylation sites when the threshold of prediction score is above 0.5 and both the signal peptide and the transmembrance region are not found. In addition, the protein has hydrophilic amine acid districts more than hydrophobic districts and subcellular localization largely locates at mitochondrial with 43.5%. The secondary structure results revealed that random coils dominated among secondary structure elements followed by alpha helix and extended strand. The phylogenetic tree shows that DPV-UL13 protein has close evolutionary relationship with the genus Mardivirus. And the multiple sequences alignment of UL13 protein in 156-436 sequence among DPV, HSV-1 and Mardivirus genus suggests highly conserved characteristic. These analysis surpports the guess that DPV-UL13 product may be a Ser/Thr protein kinase. All the data will be a basis for the further functional study of the DPV-UL13 protein.

scholarly journals Quantitative high-throughput tests of ubiquitous RNA secondary structure prediction algorithms via RNA/protein binding

2019 ◽  
Author(s):  
Winston R. Becker ◽  
Inga Jarmoskaite ◽  
Kalli Kappel ◽  
Pavanapuresan P. Vaidyanathan ◽  
Sarah K. Denny ◽  
...  
Keyword(s):  
Secondary Structure ◽  
Protein Binding ◽  
Rna Structure ◽  
Structure Prediction ◽  
Rna Secondary Structure ◽  
Nearest Neighbor ◽  
Secondary Structure Prediction ◽  
Structural Features ◽  
Vast Number ◽  
Prediction Algorithms

AbstractNearest-neighbor (NN) rules provide a simple and powerful quantitative framework for RNA structure prediction that is strongly supported for canonical Watson-Crick duplexes from a plethora of thermodynamic measurements. Predictions of RNA secondary structure based on nearest-neighbor (NN) rules are routinely used to understand biological function and to engineer and control new functions in biotechnology. However, NN applications to RNA structural features such as internal and terminal loops rely on approximations and assumptions, with sparse experimental coverage of the vast number of possible sequence and structural features. To test to what extent NN rules accurately predict thermodynamic stabilities across RNAs with non-WC features, we tested their predictions using a quantitative high-throughput assay platform, RNA-MaP. Using a thermodynamic assay with coupled protein binding, we carried out equilibrium measurements for over 1000 RNAs with a range of predicted secondary structure stabilities. Our results revealed substantial scatter and systematic deviations between NN predictions and observed stabilities. Solution salt effects and incorrect or omitted loop parameters contribute to these observed deviations. Our results demonstrate the need to independently and quantitatively test NN computational algorithms to identify their capabilities and limitations. RNA-MaP and related approaches can be used to test computational predictions and can be adapted to obtain experimental data to improve RNA secondary structure and other prediction algorithms.Significance statementRNA secondary structure prediction algorithms are routinely used to understand, predict and design functional RNA structures in biology and biotechnology. Given the vast number of RNA sequence and structural features, these predictions rely on a series of approximations, and independent tests are needed to quantitatively evaluate the accuracy of predicted RNA structural stabilities. Here we measure the stabilities of over 1000 RNA constructs by using a coupled protein binding assay. Our results reveal substantial deviations from the RNA stabilities predicted by popular algorithms, and identify factors contributing to the observed deviations. We demonstrate the importance of quantitative, experimental tests of computational RNA structure predictions and present an approach that can be used to routinely test and improve the prediction accuracy.

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