In silico  structural and functional prediction of African swine fever virus protein-B263R reveals features of a TATA-binding protein

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Abstract

African swine fever virus (ASFV) is the etiological agent of ASF, a fatal hemorrhagic fever that affects domestic pigs. There is currently no vaccine against ASFV, making it a significant threat to the pork industry. The ASFV genome sequence has been published; however, about half of ASFV open reading frames have not been characterized in terms of their structure and function despite being essential for our understanding of ASFV pathogenicity. The present study reports the three-dimensional structure and function of uncharacterized protein, pB263R ( NP_042780.1), an open reading frame found in all ASFV strains. Sequence-based profiling and hidden Markov model search methods were used to identify remote pB263R homologs. Iterative Threading ASSEmbly Refinement (I-TASSER) was used to model the three-dimensional structure of pB263R. The posterior probability of fold family assignment was calculated using TM-fold, and biological function was assigned using TM-site, RaptorXBinding, Gene Ontology, and TM-align. Our results suggests that pB263R has the features of a TATA-binding protein and is thus likely to be involved in viral gene transcription.

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Structure validation by Calpha geometry: phi,psi and Cbeta deviation.

Simon C. Lovell, Ian W. Davis, W Bryan Arendall … (2003)

Geometrical validation around the Calpha is described, with a new Cbeta measure and updated Ramachandran plot. Deviation of the observed Cbeta atom from ideal position provides a single measure encapsulating the major structure-validation information contained in bond angle distortions. Cbeta deviation is sensitive to incompatibilities between sidechain and backbone caused by misfit conformations or inappropriate refinement restraints. A new phi,psi plot using density-dependent smoothing for 81,234 non-Gly, non-Pro, and non-prePro residues with B < 30 from 500 high-resolution proteins shows sharp boundaries at critical edges and clear delineation between large empty areas and regions that are allowed but disfavored. One such region is the gamma-turn conformation near +75 degrees,-60 degrees, counted as forbidden by common structure-validation programs; however, it occurs in well-ordered parts of good structures, it is overrepresented near functional sites, and strain is partly compensated by the gamma-turn H-bond. Favored and allowed phi,psi regions are also defined for Pro, pre-Pro, and Gly (important because Gly phi,psi angles are more permissive but less accurately determined). Details of these accurate empirical distributions are poorly predicted by previous theoretical calculations, including a region left of alpha-helix, which rates as favorable in energy yet rarely occurs. A proposed factor explaining this discrepancy is that crowding of the two-peptide NHs permits donating only a single H-bond. New calculations by Hu et al. [Proteins 2002 (this issue)] for Ala and Gly dipeptides, using mixed quantum mechanics and molecular mechanics, fit our nonrepetitive data in excellent detail. To run our geometrical evaluations on a user-uploaded file, see MOLPROBITY (http://kinemage.biochem.duke.edu) or RAMPAGE (http://www-cryst.bioc.cam.ac.uk/rampage). Copyright 2003 Wiley-Liss, Inc.

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Protein-ligand binding site recognition using complementary binding-specific substructure comparison and sequence profile alignment.

Jianyi Yang, Ambrish Roy, Yang Zhang (2013)

Identification of protein-ligand binding sites is critical to protein function annotation and drug discovery. However, there is no method that could generate optimal binding site prediction for different protein types. Combination of complementary predictions is probably the most reliable solution to the problem. We develop two new methods, one based on binding-specific substructure comparison (TM-SITE) and another on sequence profile alignment (S-SITE), for complementary binding site predictions. The methods are tested on a set of 500 non-redundant proteins harboring 814 natural, drug-like and metal ion molecules. Starting from low-resolution protein structure predictions, the methods successfully recognize >51% of binding residues with average Matthews correlation coefficient (MCC) significantly higher (with P-value <10(-9) in student t-test) than other state-of-the-art methods, including COFACTOR, FINDSITE and ConCavity. When combining TM-SITE and S-SITE with other structure-based programs, a consensus approach (COACH) can increase MCC by 15% over the best individual predictions. COACH was examined in the recent community-wide COMEO experiment and consistently ranked as the best method in last 22 individual datasets with the Area Under the Curve score 22.5% higher than the second best method. These data demonstrate a new robust approach to protein-ligand binding site recognition, which is ready for genome-wide structure-based function annotations. http://zhanglab.ccmb.med.umich.edu/COACH/

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How significant is a protein structure similarity with TM-score = 0.5?

Jinrui Xu, Yang Zhang (2010)

Protein structure similarity is often measured by root mean squared deviation, global distance test score and template modeling score (TM-score). However, the scores themselves cannot provide information on how significant the structural similarity is. Also, it lacks a quantitative relation between the scores and conventional fold classifications. This article aims to answer two questions: (i) what is the statistical significance of TM-score? (ii) What is the probability of two proteins having the same fold given a specific TM-score? We first made an all-to-all gapless structural match on 6684 non-homologous single-domain proteins in the PDB and found that the TM-scores follow an extreme value distribution. The data allow us to assign each TM-score a P-value that measures the chance of two randomly selected proteins obtaining an equal or higher TM-score. With a TM-score at 0.5, for instance, its P-value is 5.5 x 10(-7), which means we need to consider at least 1.8 million random protein pairs to acquire a TM-score of no less than 0.5. Second, we examine the posterior probability of the same fold proteins from three datasets SCOP, CATH and the consensus of SCOP and CATH. It is found that the posterior probability from different datasets has a similar rapid phase transition around TM-score=0.5. This finding indicates that TM-score can be used as an approximate but quantitative criterion for protein topology classification, i.e. protein pairs with a TM-score >0.5 are mostly in the same fold while those with a TM-score <0.5 are mainly not in the same fold.

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Author and article information

Contributors

Dickson Kinyanyi

Journal

Journal ID (nlm-ta): PeerJ

Journal ID (iso-abbrev): PeerJ

Journal ID (publisher-id): peerj

Journal ID (pmc): peerj

Title: PeerJ

Publisher: PeerJ Inc. (San Francisco, USA )

ISSN (Electronic): 2167-8359

Publication date (Electronic): 22 February 2018

Publication date Collection: 2018

Volume: 6

Electronic Location Identifier: e4396

Affiliations

[1 ]Department of Biochemistry and Biotechnology, Technical University of Kenya , Nairobi, Kenya

[2 ]Center for Biotechnology and Bioinformatics, University Of Nairobi , Nairobi, Kenya

[3 ]Department of Biochemistry and Biotechnology, Kenyatta University , Ruiru, Kenya

Article

Publisher ID: 4396

DOI: 10.7717/peerj.4396

PMC ID: 5825884

PubMed ID: 29492339

SO-VID: 9c6ebee2-3459-41fc-80dd-f3bdf7121585

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This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

History

Date received : 4 October 2017

Date accepted : 30 January 2018

Funding

The authors received no funding for this work.

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In silico structural and functional prediction of African swine fever virus protein-B263R reveals features of a TATA-binding protein

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Abstract

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Most cited references 26

Structure validation by Calpha geometry: phi,psi and Cbeta deviation.

Protein-ligand binding site recognition using complementary binding-specific substructure comparison and sequence profile alignment.

How significant is a protein structure similarity with TM-score = 0.5?

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Cited by 8

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