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Protein interface predictor

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https://www.readbyqxmd.com/read/29127686/the-challenge-of-modeling-protein-assemblies-the-casp12-capri-experiment
#1
Marc F Lensink, Sameer Velankar, Minkyung Baek, Lim Heo, Chaok Seok, Shoshana J Wodak
We present the quality assessment of 5613 models submitted by predictor groups from both CAPRI and CASP for the total of 15 most tractable targets from the second joint CASP-CAPRI protein assembly prediction experiment. These targets comprised 12 homo-oligomers and 3 hetero-complexes. The bulk of the analysis focuses on 10 targets (of CAPRI Round 37), which included all 3 hetero-complexes, and whose protein chains or the full assembly could be readily modeled from structural templates in the PDB. On average, 28 CAPRI groups and 10 CASP groups (including automatic servers), submitted models for each of these 10 targets...
November 10, 2017: Proteins
https://www.readbyqxmd.com/read/29071742/assessment-of-protein-assembly-prediction-in-casp12-casp12-assembly
#2
Aleix Lafita, Spencer Bliven, Andriy Kryshtafovych, Martino Bertoni, Bohdan Monastyrskyy, Jose M Duarte, Torsten Schwede, Guido Capitani
We present the results of the first independent assessment of protein assemblies in CASP. A total of 1,624 oligomeric models were submitted by 108 predictor groups for the 30 oligomeric targets in the CASP12 edition. The target assemblies were of diverse topology, composition and prediction difficulty, including eight heteromeric complexes, five viral fibre heads, four dihedral homomers and two membrane dimers. We evaluated the accuracy of oligomeric predictions by comparison to their experimentally determined reference structures at the interface patch and residue contact levels...
October 26, 2017: Proteins
https://www.readbyqxmd.com/read/28990628/computational-identification-of-protein-s-sulfenylation-sites-by-incorporating-the-multiple-sequence-features-information
#3
Md Mehedi Hasan, Dianjing Guo, Hiroyuki Kurata
Cysteine S-sulfenylation is a major type of posttranslational modification that contributes to protein structure and function regulation in many cellular processes. Experimental identification of S-sulfenylation sites is challenging, due to the low abundance of proteins and the inefficient experimental methods. Computational identification of S-sulfenylation sites is an alternative strategy to annotate the S-sulfenylated proteome. In this study, a novel computational predictor SulCysSite was developed for accurate prediction of S-sulfenylation sites based on multiple sequence features, including amino acid index properties, binary amino acid codes, position specific scoring matrix, and compositions of profile-based amino acids...
October 9, 2017: Molecular BioSystems
https://www.readbyqxmd.com/read/28968673/intpred-a-structure-based-predictor-of-protein-protein-interaction-sites
#4
Tom Northey, Anja Barešic, Andrew C R Martin
Motivation: Protein-protein interactions are vital for protein function with the average protein having between three and ten interacting partners. Knowledge of precise protein-protein interfaces comes from crystal structures deposited in the Protein Data Bank (PDB), but only 50% of structures in the PDB are complexes. There is therefore a need to predict protein-protein interfaces in silico and various methods for this purpose. Here we explore the use of a predictor based on structural features and which exploits random forest machine learning, comparing its performance with a number of popular established methods...
September 18, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28901589/the-subcons-web-server-a-user-friendly-web-interface-for-state-of-the-art-subcellular-localization-prediction
#5
M Salvatore, N Shu, A Elofsson
SubCons is a recently developed method that predicts the subcellular localisation of a protein. It combines predictions from four predictors using a Random Forest classifier. Here, we present the user-friendly web-interface implementation of SubCons. Starting from a protein sequence, the server rapidly predicts the subcellular localisations of an individual protein. Additionally, the server accepts the submission of sets of proteins either by uploading the files or programmatically by using command line WSDL API scripts...
September 13, 2017: Protein Science: a Publication of the Protein Society
https://www.readbyqxmd.com/read/28867223/protein-protein-interaction-site-predictions-with-minimum-covariance-determinant-and-mahalanobis-distance
#6
Zhijun Qiu, Bo Zhou, Jiangfeng Yuan
Protein-protein interaction site (PPIS) prediction must deal with the diversity of interaction sites that limits their prediction accuracy. Use of proteins with unknown or unidentified interactions can also lead to missing interfaces. Such data errors are often brought into the training dataset. In response to these two problems, we used the minimum covariance determinant (MCD) method to refine the training data to build a predictor with better performance, utilizing its ability of removing outliers. In order to predict test data in practice, a method based on Mahalanobis distance was devised to select proper test data as input for the predictor...
September 1, 2017: Journal of Theoretical Biology
https://www.readbyqxmd.com/read/28808256/spoton-high-accuracy-identification-of-protein-protein-interface-hot-spots
#7
Irina S Moreira, Panagiotis I Koukos, Rita Melo, Jose G Almeida, Antonio J Preto, Joerg Schaarschmidt, Mikael Trellet, Zeynep H Gümüş, Joaquim Costa, Alexandre M J J Bonvin
We present SpotOn, a web server to identify and classify interfacial residues as Hot-Spots (HS) and Null-Spots (NS). SpotON implements a robust algorithm with a demonstrated accuracy of 0.95 and sensitivity of 0.98 on an independent test set. The predictor was developed using an ensemble machine learning approach with up-sampling of the minor class. It was trained on 53 complexes using various features, based on both protein 3D structure and sequence. The SpotOn web interface is freely available at: http://milou...
August 14, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28718782/prediction-of-protein-hotspots-from-whole-protein-sequences-by-a-random-projection-ensemble-system
#8
Jinjian Jiang, Nian Wang, Peng Chen, Chunhou Zheng, Bing Wang
Hotspot residues are important in the determination of protein-protein interactions, and they always perform specific functions in biological processes. The determination of hotspot residues is by the commonly-used method of alanine scanning mutagenesis experiments, which is always costly and time consuming. To address this issue, computational methods have been developed. Most of them are structure based, i.e., using the information of solved protein structures. However, the number of solved protein structures is extremely less than that of sequences...
July 18, 2017: International Journal of Molecular Sciences
https://www.readbyqxmd.com/read/28575181/deepsite-protein-binding-site-predictor-using-3d-convolutional-neural-networks
#9
J Jiménez, S Doerr, G Martínez-Rosell, A S Rose, G De Fabritiis
Motivation: An important step in structure-based drug design consists in the prediction of druggable binding sites. Several algorithms for detecting binding cavities, those likely to bind to a small drug compound, have been developed over the years by clever exploitation of geometric, chemical and evolutionary features of the protein. Results: Here we present a novel knowledge-based approach that uses state-of-the-art convolutional neural networks, where the algorithm is learned by examples...
October 1, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28393267/charting-the-perfect-storm-emerging-biological-interfaces-between-stress-and-stroke
#10
REVIEW
G Kronenberg, J Schöner, C Nolte, A Heinz, M Endres, Karen Gertz
A growing body of evidence demonstrates that psychosocial stress is an important and often underestimated risk factor for cardiovascular disease such as myocardial infarction and stroke. In this article, we map out major biological interfaces between stress, stress-related psychiatric disorders, and stroke, placing special emphasis on the fact that stress and psychiatric disorders may be both cause and consequence of cardiovascular disease. Apart from high-risk lifestyle habits such as smoking and lack of exercise, neuroendocrine dysregulation, alterations of the hemostatic system, increased oxidative stress, and inflammatory changes have been implicated in stress-related endothelial dysfunction...
April 9, 2017: European Archives of Psychiatry and Clinical Neuroscience
https://www.readbyqxmd.com/read/28345534/electron-transfer-processes-occurring-on-platinum-neural-stimulating-electrodes-calculated-charge-storage-capacities-are-inaccessible-during-applied-stimulation
#11
Eric M Hudak, Doe W Kumsa, Heidi B Martin, J Thomas Mortimer
OBJECTIVE: Neural prostheses employing platinum electrodes are often constrained by a charge/charge-density parameter known as the Shannon limit. In examining the relationship between charge injection and observed tissue damage, the electrochemistry at the electrode-tissue interface should be considered. The charge-storage capacity (CSC) is often used as a predictor of how much charge an electrode can inject during stimulation, but calculating charge from a steady-state i-E curve (cyclic voltammogram) over the water window misrepresents how electrodes operate during stimulation...
August 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28073761/seeing-the-trees-through-the-forest-sequence-based-homo-and-heteromeric-protein-protein-interaction-sites-prediction-using-random-forest
#12
Qingzhen Hou, Paul F G De Geest, Wim F Vranken, Jaap Heringa, K Anton Feenstra
Motivation: Genome sequencing is producing an ever-increasing amount of associated protein sequences. Few of these sequences have experimentally validated annotations, however, and computational predictions are becoming increasingly successful in producing such annotations. One key challenge remains the prediction of the amino acids in a given protein sequence that are involved in protein-protein interactions. Such predictions are typically based on machine learning methods that take advantage of the properties and sequence positions of amino acids that are known to be involved in interaction...
May 15, 2017: Bioinformatics
https://www.readbyqxmd.com/read/27792167/predicting-protein-protein-interaction-sites-using-sequence-descriptors-and-site-propensity-of-neighboring-amino-acids
#13
Tzu-Hao Kuo, Kuo-Bin Li
Information about the interface sites of Protein-Protein Interactions (PPIs) is useful for many biological research works. However, despite the advancement of experimental techniques, the identification of PPI sites still remains as a challenging task. Using a statistical learning technique, we proposed a computational tool for predicting PPI interaction sites. As an alternative to similar approaches requiring structural information, the proposed method takes all of the input from protein sequences. In addition to typical sequence features, our method takes into consideration that interaction sites are not randomly distributed over the protein sequence...
October 26, 2016: International Journal of Molecular Sciences
https://www.readbyqxmd.com/read/27667482/modeling-oblong-proteins-and-water-mediated-interfaces-with-rosettadock-in-capri-rounds-28-35
#14
Nicholas A Marze, Jeliazko R Jeliazkov, Shourya S Roy Burman, Scott E Boyken, Frank DiMaio, Jeffrey J Gray
The 28th-35th rounds of the Critical Assessment of PRotein Interactions (CAPRI) served as a practical benchmark for our RosettaDock protein-protein docking protocols, highlighting strengths and weaknesses of the approach. We achieved acceptable or better quality models in three out of 11 targets. For the two α-repeat protein-green fluorescent protein (αrep-GFP) complexes, we used a novel ellipsoidal partial-global docking method (Ellipsoidal Dock) to generate models with 2.2 Å/1.5 Å interface RMSD, capturing 49%/42% of the native contacts, for the 7-/5-repeat αrep complexes...
March 2017: Proteins
https://www.readbyqxmd.com/read/27383535/fastrnabindr-fast-and-accurate-prediction-of-protein-rna-interface-residues
#15
Yasser El-Manzalawy, Mostafa Abbas, Qutaibah Malluhi, Vasant Honavar
A wide range of biological processes, including regulation of gene expression, protein synthesis, and replication and assembly of many viruses are mediated by RNA-protein interactions. However, experimental determination of the structures of protein-RNA complexes is expensive and technically challenging. Hence, a number of computational tools have been developed for predicting protein-RNA interfaces. Some of the state-of-the-art protein-RNA interface predictors rely on position-specific scoring matrix (PSSM)-based encoding of the protein sequences...
2016: PloS One
https://www.readbyqxmd.com/read/27378293/metapred2cs-a-sequence-based-meta-predictor-for-protein-protein-interactions-of-prokaryotic-two-component-system-proteins
#16
Altan Kara, Martin Vickers, Martin Swain, David E Whitworth, Narcis Fernandez-Fuentes
MOTIVATION: Two-component systems (TCS) are the main signalling pathways of prokaryotes, and control a wide range of biological phenomena. Their functioning depends on interactions between TCS proteins, the specificity of which is poorly understood. RESULTS: The MetaPred2CS web-server interfaces a sequence-based meta-predictor specifically designed to predict pairing of the histidine kinase and response-regulator proteins forming TCSs. MetaPred2CS integrates six sequence-based methods using a support vector machine classifier and has been intensively tested under different benchmarking conditions: (i) species specific gene sets; (ii) neighbouring versus orphan pairs; and (iii) k-fold cross validation on experimentally validated datasets...
November 1, 2016: Bioinformatics
https://www.readbyqxmd.com/read/27378157/chronic-impedance-spectroscopy-of-an-endovascular-stent-electrode-array
#17
Nicholas L Opie, Sam E John, Gil S Rind, Stephen M Ronayne, David B Grayden, Anthony N Burkitt, Clive N May, Terence J O'Brien, Thomas J Oxley
OBJECTIVE: Recently, we reported a minimally invasive stent-electrode array capable of recording neural signals from within a blood vessel. We now investigate the use of electrochemical impedance spectroscopy (EIS) measurements to infer changes occurring to the electrode-tissue interface from devices implanted in a cohort of sheep for up to 190 days. APPROACH: In a cohort of 15 sheep, endovascular stent-electrode arrays were implanted in the superior sagittal sinus overlying the motor cortex for up to 190 days...
August 2016: Journal of Neural Engineering
https://www.readbyqxmd.com/read/27303709/sstar-a-stand-alone-easy-to-use-antimicrobial-resistance-gene-predictor
#18
Tom J B de Man, Brandi M Limbago
We present the easy-to-use Sequence Search Tool for Antimicrobial Resistance, SSTAR. It combines a locally executed BLASTN search against a customizable database with an intuitive graphical user interface for identifying antimicrobial resistance (AR) genes from genomic data. Although the database is initially populated from a public repository of acquired resistance determinants (i.e., ARG-ANNOT), it can be customized for particular pathogen groups and resistance mechanisms. For instance, outer membrane porin sequences associated with carbapenem resistance phenotypes can be added, and known intrinsic mechanisms can be included...
January 2016: MSphere
https://www.readbyqxmd.com/read/27284087/exploring-the-interplay-between-experimental-methods-and-the-performance-of-predictors-of-binding-affinity-change-upon-mutations-in-protein-complexes
#19
Cunliang Geng, Anna Vangone, Alexandre M J J Bonvin
Reliable prediction of binding affinity changes (ΔΔG) upon mutations in protein complexes relies not only on the performance of computational methods but also on the availability and quality of experimental data. Binding affinity changes can be measured by various experimental methods with different accuracies and limitations. To understand the impact of these on the prediction of binding affinity change, we present the Database of binding Affinity Change Upon Mutation (DACUM), a database of 1872 binding affinity changes upon single-point mutations, a subset of the SKEMPI database (Moal,I...
August 2016: Protein Engineering, Design & Selection: PEDS
https://www.readbyqxmd.com/read/27224906/predictsnp2-a-unified-platform-for-accurately-evaluating-snp-effects-by-exploiting-the-different-characteristics-of-variants-in-distinct-genomic-regions
#20
Jaroslav Bendl, Miloš Musil, Jan Štourač, Jaroslav Zendulka, Jiří Damborský, Jan Brezovský
An important message taken from human genome sequencing projects is that the human population exhibits approximately 99.9% genetic similarity. Variations in the remaining parts of the genome determine our identity, trace our history and reveal our heritage. The precise delineation of phenotypically causal variants plays a key role in providing accurate personalized diagnosis, prognosis, and treatment of inherited diseases. Several computational methods for achieving such delineation have been reported recently...
May 2016: PLoS Computational Biology
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