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Protein contact prediction

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https://www.readbyqxmd.com/read/28932769/microrna-expression-in-a-phosphaturic-mesenchymal-tumour
#1
Darrell Green, Irina Mohorianu, Isabelle Piec, Jeremy Turner, Clare Beadsmoore, Andoni Toms, Richard Ball, John Nolan, Iain McNamara, Tamas Dalmay, William D Fraser
Phosphaturic mesenchymal tumours are a heterogeneous set of bone and soft tissue neoplasms that can cause a number of paraneoplastic syndromes such as tumour induced osteomalacia. The term phosphaturic comes from the common finding that these tumours secrete high levels of fibroblast growth factor 23 which causes renal phosphate wasting leading to hypophosphatemia. Phosphaturic mesenchymal tumours are rare and diagnosis is difficult. A very active 68 year old male presented with bone pain and muscle weakness...
December 2017: Bone Reports
https://www.readbyqxmd.com/read/28923002/deep-learning-methods-for-protein-torsion-angle-prediction
#2
Haiou Li, Jie Hou, Badri Adhikari, Qiang Lyu, Jianlin Cheng
BACKGROUND: Deep learning is one of the most powerful machine learning methods that has achieved the state-of-the-art performance in many domains. Since deep learning was introduced to the field of bioinformatics in 2012, it has achieved success in a number of areas such as protein residue-residue contact prediction, secondary structure prediction, and fold recognition. In this work, we developed deep learning methods to improve the prediction of torsion (dihedral) angles of proteins...
September 18, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28915745/non-local-effects-of-point-mutations-on-the-stability-of-a-protein-module
#3
Mateusz Chwastyk, Andrés M Vera, Albert Galera-Prat, Melissabye Gunnoo, Damien Thompson, Mariano Carrión-Vázquez, Marek Cieplak
We combine experimental and theoretical methods to assess the effect of a set of point mutations on c7A, a highly mechanostable type I cohesin module from scaffoldin CipA from Clostridium thermocellum. We propose a novel robust and computationally expedient theoretical method to determine the effects of point mutations on protein structure and stability. We use all-atom simulations to predict structural shifts with respect to the native protein and then analyze the mutants using a coarse-grained model. We examine transitions in contacts between residues and find that changes in the contact map usually involve a non-local component that can extend up to 50 Å...
September 14, 2017: Journal of Chemical Physics
https://www.readbyqxmd.com/read/28901583/improved-protein-contact-predictions-with-the-metapsicov2-server-in-casp12
#4
Daniel W A Buchan, David T Jones
In this paper we present the results for the MetaPSICOV2 contact prediction server in the CASP12 community experiment (http://predictioncenter.org). Over the 35 assessed Free Modelling target domains the MetaPSICOV2 server achieved a mean precision of 43.27%, a substantial increase relative to the server's performance in the CASP11 experiment (Kinch, Li et al. 2016). In the following paper, we discuss improvements to the MetaPSICOV2 server, covering both changes to the neural network and attempts to integrate contact predictions on a domain basis into the prediction pipeline...
September 13, 2017: Proteins
https://www.readbyqxmd.com/read/28886645/a-multi-state-coarse-grained-modeling-approach-for-an-intrinsically-disordered-peptide
#5
Farhad Ramezanghorbani, Cahit Dalgicdir, Mehmet Sayar
Many proteins display a marginally stable tertiary structure, which can be altered via external stimuli. Since a majority of coarse grained (CG) models are aimed at structure prediction, their success for an intrinsically disordered peptide's conformational space with marginal stability and sensitivity to external stimuli cannot be taken for granted. In this study, by using the LKα14 peptide as a test system, we demonstrate a bottom-up approach for constructing a multi-state CG model, which can capture the conformational behavior of this peptide in three distinct environments with a unique set of interaction parameters...
September 7, 2017: Journal of Chemical Physics
https://www.readbyqxmd.com/read/28881974/large-scale-structure-prediction-by-improved-contact-predictions-and-model-quality-assessment
#6
Mirco Michel, David Menéndez Hurtado, Karolis Uziela, Arne Elofsson
Motivation: Accurate contact predictions can be used for predicting the structure of proteins. Until recently these methods were limited to very big protein families, decreasing their utility. However, recent progress by combining direct coupling analysis with machine learning methods has made it possible to predict accurate contact maps for smaller families. To what extent these predictions can be used to produce accurate models of the families is not known. Results: We present the PconsFold2 pipeline that uses contact predictions from PconsC3, the CONFOLD folding algorithm and model quality estimations to predict the structure of a protein...
July 15, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28881217/protein-%C3%AE-sheet-prediction-using-an-efficient-dynamic-programming-algorithm
#7
Mostafa Sabzekar, Mahmoud Naghibzadeh, Mahdie Eghdami, Zafer Aydin
Predicting the β-sheet structure of a protein is one of the most important intermediate steps towards the identification of its tertiary structure. However, it is regarded as the primary bottleneck due to the presence of non-local interactions between several discontinuous regions in β-sheets. To achieve reliable long-range interactions, a promising approach is to enumerate and rank all β-sheet conformations for a given protein and find the one with the highest score. The problem with this solution is that the search space of the problem grows exponentially with respect to the number of β-strands...
August 24, 2017: Computational Biology and Chemistry
https://www.readbyqxmd.com/read/28880549/binding-and-release-between-polymeric-carrier-and-protein-drug-ph-mediated-interplay-of-coulomb-forces-hydrogen-bonding-van-der-waals-interactions-and-entropy
#8
Sergio De Luca, Fan Chen, Prasenjit Seal, Martina H Stenzel, Sean C Smith
The accelerating search for new types of drugs and delivery strategies poses the challenge to understand the mechanism of delivery. To this end, a detailed atomistic picture of binding between the drug and the carrier is quintessential. While many studies focus on the electrostatics of drug-vector interactions, it has also been pointed out that entropic factors relating to water and counter ions can play an important role. By carrying out extensive molecular dynamics simulations and subsequently validating with experiment, we shed light herein on the binding in aqueous solution between a protein drug and a polymeric carrier...
September 7, 2017: Biomacromolecules
https://www.readbyqxmd.com/read/28874505/molecular-recognition-of-pre-trna-by-arabidopsis-protein-only-ribonuclease-p
#9
Bradley P Klemm, Agnes Karasik, Kipchumba J Kaitany, Aranganathan Shanmuganathan, Matthew J Henley, Adam Z Thelen, Allison Jl Dewar, Nathaniel D Jackson, Markos Koutmos, Carol A Fierke
Protein-only ribonuclease P (PRORP) is an enzyme responsible for catalyzing the 5' end maturation of precursor transfer ribonucleic acids (pre-tRNAs) encoded by various cellular compartments in many eukaryotes. PRORPs from plants act as single-subunit enzymes and have been used as a model system for analyzing the function of the metazoan PRORP nuclease subunit, which requires two additional proteins for efficient catalysis. There are currently few molecular details known about the PRORP-pre-tRNA complex. Here, we characterize the determinants of substrate recognition by the single subunit Arabidopsis thaliana PRORP1 and PRORP2 using kinetic and thermodynamic experiments...
September 5, 2017: RNA
https://www.readbyqxmd.com/read/28872899/two-novel-variants-affecting-cdkl5-transcript-associated-with-epileptic-encephalopathy
#10
Jana Neupauerová, Katalin Štěrbová, Markéta Vlčková, Věra Sebroňová, Tat'ána Maříková, Marcela Krůtová, David Staněk, Pavel Kršek, Markéta Žaliová, Pavel Seeman, Petra Laššuthová
BACKGROUND: Variants in the human X-linked cyclin-dependent kinase-like 5 (CDKL5) gene have been reported as being etiologically associated with early infantile epileptic encephalopathy type 2 (EIEE2). We report on two patients, a boy and a girl, with EIEE2 that present with early onset epilepsy, hypotonia, severe intellectual disability, and poor eye contact. METHODS: Massively parallel sequencing (MPS) of a custom-designed gene panel for epilepsy and epileptic encephalopathy containing 112 epilepsy-related genes was performed...
September 5, 2017: Genetic Testing and Molecular Biomarkers
https://www.readbyqxmd.com/read/28865433/rrcrank-a-fusion-method-using-rank-strategy-for-residue-residue-contact-prediction
#11
Xiaoyang Jing, Qiwen Dong, Ruqian Lu
BACKGROUND: In structural biology area, protein residue-residue contacts play a crucial role in protein structure prediction. Some researchers have found that the predicted residue-residue contacts could effectively constrain the conformational search space, which is significant for de novo protein structure prediction. In the last few decades, related researchers have developed various methods to predict residue-residue contacts, especially, significant performance has been achieved by using fusion methods in recent years...
September 2, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28863193/a-refined-model-of-claudin-15-tight-junction-paracellular-architecture-by-molecular-dynamics-simulations
#12
Giulio Alberini, Fabio Benfenati, Luca Maragliano
Tight-junctions between epithelial cells of biological barriers are specialized molecular structures that regulate the flux of solutes across the barrier, parallel to cell walls. The tight-junction backbone is made of strands of transmembrane proteins from the claudin family, but the molecular mechanism of its function is still not completely understood. Recently, the crystal structure of a mammalian claudin-15 was reported, displaying for the first time the detailed features of transmembrane and extracellular domains...
2017: PloS One
https://www.readbyqxmd.com/read/28860650/a-membrane-inserted-structural-model-of-the-yeast-mitofusin-fzo1
#13
Dario De Vecchis, Laetitia Cavellini, Marc Baaden, Jérôme Hénin, Mickaël M Cohen, Antoine Taly
Mitofusins are large transmembrane GTPases of the dynamin-related protein family, and are required for the tethering and fusion of mitochondrial outer membranes. Their full-length structures remain unknown, which is a limiting factor in the study of outer membrane fusion. We investigated the structure and dynamics of the yeast mitofusin Fzo1 through a hybrid computational and experimental approach, combining molecular modelling and all-atom molecular dynamics simulations in a lipid bilayer with site-directed mutagenesis and in vivo functional assays...
August 31, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28857774/combined-in-silico-and-in-vitro-approach-predicts-low-wall-shear-stress-regions-in-a-hemofilter-that-correlate-with-thrombus-formation-in-vivo
#14
Amanda K W Buck, Joseph J Groszek, Daniel C Colvin, Sara B Keller, Clark Kensinger, Rachel Forbes, Seth Karp, Phillip Williams, Shuvo Roy, William H Fissell
A major challenge in developing blood-contacting medical devices is mitigating thrombogenicity of an intravascular device. Thrombi may interfere with device function or embolize from the device to occlude distant vascular beds with catastrophic consequences. Chemical interactions between plasma proteins and bioengineered surface occur at the nanometer scale; however, continuum models of blood predict local shear stresses that lead to platelet activation or aggregation and thrombosis. Here, an iterative approach to blood flow path design incorporating in silico, in vitro, and in vivo experiments predicted the occurrence and location of thrombi in an implantable hemofilter...
August 29, 2017: ASAIO Journal: a Peer-reviewed Journal of the American Society for Artificial Internal Organs
https://www.readbyqxmd.com/read/28854238/elastic-network-model-of-learned-maintained-contacts-to-predict-protein-motion
#15
Ines Putz, Oliver Brock
We present a novel elastic network model, lmcENM, to determine protein motion even for localized functional motions that involve substantial changes in the protein's contact topology. Existing elastic network models assume that the contact topology remains unchanged throughout the motion and are thus most appropriate to simulate highly collective function-related movements. lmcENM uses machine learning to differentiate breaking from maintained contacts. We show that lmcENM accurately captures functional transitions unexplained by the classical ENM and three reference ENM variants, while preserving the simplicity of classical ENM...
2017: PloS One
https://www.readbyqxmd.com/read/28851269/improved-protein-structure-reconstruction-using-secondary-structures-contacts-at-higher-distance-thresholds-and-non-contacts
#16
Badri Adhikari, Jianlin Cheng
BACKGROUND: Residue-residue contacts are key features for accurate de novo protein structure prediction. For the optimal utilization of these predicted contacts in folding proteins accurately, it is important to study the challenges of reconstructing protein structures using true contacts. Because contact-guided protein modeling approach is valuable for predicting the folds of proteins that do not have structural templates, it is necessary for reconstruction studies to focus on hard-to-predict protein structures...
August 29, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28845538/analysis-of-deep-learning-methods-for-blind-protein-contact-prediction-in-casp12
#17
Sheng Wang, Siqi Sun, Jinbo Xu
Here we present the results of protein contact prediction achieved in CASP12 by our RaptorX-Contact server, which is an early implementation of our deep learning method for contact prediction. On a set of 38 free-modeling target domains with a median family size of around 58 effective sequences, our server obtained an average top L/5 long- and medium-range contact accuracy of 47% and 44%, respectively (L = length). A complete implementation has an average accuracy of 59% and 57%, respectively. Our deep learning method formulates contact prediction as a pixel-level image labeling problem and simultaneously predicts all residue pairs of a protein using a combination of two deep residual neural networks, taking as input the residue conservation information, predicted secondary structure and solvent accessibility, contact potential, and coevolution information...
August 28, 2017: Proteins
https://www.readbyqxmd.com/read/28836962/microrna-expression-profiling-of-porcine-mammary-epithelial-cells-after-challenge-with-escherichia-coli-in-vitro
#18
A Jaeger, F Hadlich, N Kemper, A Lübke-Becker, E Muráni, K Wimmers, S Ponsuksili
BACKGROUND: Coliform mastitis is a symptom of postpartum dysgalactia syndrome (PDS), a multifactorial infectious disease of sows. Our previous study showed gene expression profile change after bacterial challenge of porcine mammary epithelial cells (PMECs). These mRNA expression changes may be regulated through microRNAs (miRNAs) which play critical roles in biological processes. Therefore, miRNA expression profile was investigated in PMECs. RESULTS: PMECs were isolated from three lactating sows and challenged with heat-inactivated potential mastitis-causing pathogen Escherichia coli (E...
August 24, 2017: BMC Genomics
https://www.readbyqxmd.com/read/28833538/predicting-the-helix-helix-interactions-from-correlated-residue-mutations
#19
Dapeng Xiong, Wenzhi Mao, Haipeng Gong
Helix-helix interactions are crucial in the structure assembly, stability and function of helix-rich proteins including many membrane proteins. In spite of remarkable progresses over the past decades, the accuracy of predicting protein structures from their amino acid sequences is still far from satisfaction. In this work, we focused on a simpler problem, the prediction of helix-helix interactions, the results of which could facilitate practical protein structure prediction by constraining the sampling space...
August 17, 2017: Proteins
https://www.readbyqxmd.com/read/28831657/performance-of-haddock-and-a-simple-contact-based-protein-ligand-binding-affinity-predictor-in-the-d3r-grand-challenge-2
#20
Zeynep Kurkcuoglu, Panagiotis I Koukos, Nevia Citro, Mikael E Trellet, J P G L M Rodrigues, Irina S Moreira, Jorge Roel-Touris, Adrien S J Melquiond, Cunliang Geng, Jörg Schaarschmidt, Li C Xue, Anna Vangone, A M J J Bonvin
We present the performance of HADDOCK, our information-driven docking software, in the second edition of the D3R Grand Challenge. In this blind experiment, participants were requested to predict the structures and binding affinities of complexes between the Farnesoid X nuclear receptor and 102 different ligands. The models obtained in Stage1 with HADDOCK and ligand-specific protocol show an average ligand RMSD of 5.1 Å from the crystal structure. Only 6/35 targets were within 2.5 Å RMSD from the reference, which prompted us to investigate the limiting factors and revise our protocol for Stage2...
August 22, 2017: Journal of Computer-aided Molecular Design
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