Literature DB >> 26414949

In silico approaches for the identification of virulence candidates amongst hypothetical proteins of Mycoplasma pneumoniae 309.

Mohd Shahbaaz1, Krishna Bisetty1, Faizan Ahmad2, Md Imtaiyaz Hassan3.   

Abstract

Mycoplasma 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, cardiac diseases 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.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Function predictions; Hypothetical proteins; Molecular dynamics Simulations; Mycoplasma pneumoniae; Sequence analyses; Virulence factors

Mesh:

Substances:

Year:  2015        PMID: 26414949     DOI: 10.1016/j.compbiolchem.2015.09.007

Source DB:  PubMed          Journal:  Comput Biol Chem        ISSN: 1476-9271            Impact factor:   2.877


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