Please use this identifier to cite or link to this item: https://hdl.handle.net/10321/1588
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dc.contributor.authorShahbaaz, Mohden_US
dc.contributor.authorBisetty, Krishnaen_US
dc.contributor.authorAhmad, Faizanen_US
dc.contributor.authorHassan, Md. Imtaiyazen_US
dc.date.accessioned2016-08-05T05:50:42Z-
dc.date.available2016-08-05T05:50:42Z-
dc.date.issued2015-
dc.identifier.citationShahbaaz, M. et al. 2015. In silico approaches for the identification of virulence candidates amongst hypothetical proteins of Mycoplasma pneumoniae 309. Computational Biology and Chemistry 59 : 67–80en_US
dc.identifier.issn1476-9271-
dc.identifier.urihttp://hdl.handle.net/10321/1588-
dc.description.abstractMycoplasma pneumoniae type 2a strain 309 is a simplest known bacterium and is the primary cause of community acquired pneumonia in the children. It mainly causes severe atypical pneumonia as well as several other non-pulmonary manifestations such as neurological, hepatic, hemolytic anemia, cardiacdiseases and polyarthritis. The size of M. pneumoniae genome (Accession number: NC_016807.1) is relatively smaller as compared to other bacteria and contains 707 functional proteins, in which 204 are classified as hypothetical proteins (HPs) because of the unavailability of experimentally validated functions. The functions of the HPs were predicted by integrating a variety of protein classification systems, motif discovery tools as well as methods that are based on characteristic features obtained from the protein sequence and metabolic pathways. The probable functions of 83HPs were predicted successfully. The accuracy of the diverse tools used in the adopted pipeline was evaluated on the basis of statistical techniques of Receiver Operating Characteristic (ROC), which indicated the reliability of the functional predictions. Furthermore, the virulent HPs present in the set of 83 functionally annotated proteins were predicted by using the Bioinformatics tools and the conformational behaviours of the proteins with highest virulence scores were studied by using the molecular dynamics (MD) simulations. This study will facilitate in the better understanding of various drug resistance and pathogenesis mechanisms present in the M. pneumoniae and can be utilized in designing of better therapeutic agents.en_US
dc.format.extent14 pen_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofComputational biology and chemistry (Print)en_US
dc.subjectHypothetical proteinsen_US
dc.subjectMycoplasma pneumoniaeen_US
dc.subjectFunction predictionsen_US
dc.subjectSequence analysesen_US
dc.subjectVirulence factorsen_US
dc.subjectMolecular dynamics Simulationsen_US
dc.titleIn silico approaches for the identification of virulence candidates amongst hypothetical proteins of Mycoplasma pneumoniae 309en_US
dc.typeArticleen_US
dc.publisher.urihttp://dx.doi.org/10.1016/j.compbiolchem.2015.09.007en_US
dc.dut-rims.pubnumDUT-005106en_US
dc.description.availabilityCopyright: 2015. Elsevier. Due to copyright restrictions, only the abstract is available. For access to the full text item, please consult the publisher's website. The definitive version of the work is published in Computational Biology and Chemistry, September, 2014, Vol. 59, Pages 67-80en_US
dc.identifier.doihttp://dx.doi.org/10.1016/j.compbiolchem.2015.09.007-
local.sdgSDG03-
item.grantfulltextnone-
item.cerifentitytypePublications-
item.fulltextNo Fulltext-
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairetypeArticle-
Appears in Collections:Research Publications (Applied Sciences)
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