title: In Silico Identification of Potential American Cockroach (Periplaneta americana) Allergens.
abstract: BACKGROUND
  Cockroaches have been recognized as a powerful indoor allergen. Cockroach allergy can be a major factor in serious asthma and nasal allergy. Bioinformatics tools have been developed to identify potential allergens. The present study was conducted to identify potential allergens in Periplaneta americana (Linnaeus).
  
  
  METHODS
  The study focused on the identification of potential allergens among the characterized proteins of P. americana using web-based and publicly available allergen prediction tools that follow the FAO/WHO guidelines for prediction of allergenic proteins. P. americana protein sequences were retrieved from UniProtKB. The sequences obtained were analyzed using AlgPred. The potential allergens obtained were further analyzed by SDAP for confirmation.
  
  
  RESULTS
  Protein sequences (233 cases) of P. americana were obtained from UniProtKB out of which 25 were known allergens. Out of the remaining 208 proteins, 102 potential allergens were predicted by AlgPred. However, only 9 were found to be potential allergens after screening with SDAP. Arginine kinases, RNA polymerase II subunit, parcxpwnx02, peptidylprolyl cis-trans isomerase, hemocyanin subunit type I and type II, homologue of Sarcophaga proteinase and alpha amylase were confirmed to be potential allergens by SDAP.
  
  
  CONCLUSIONS
  We have identified nine potential allergens in P. americana that may be used as preliminary support for further laboratory experiments.
authors.affiliation: Dept. of Biosciences, COMSATS Institute of Information Technology, Chak Shahzad, Park Road, Islamabad 44000, Pakistan.
authors.forename: A
authors.initials: A
authors.lastname: Ahmed
authors.forename: K
authors.initials: K
authors.lastname: Minhas
authors.lastname: Namood-E-Sahar
authors.forename: O
authors.initials: O
authors.lastname: Aftab
authors.forename: F Sher
authors.initials: FS
authors.lastname: Khan
keywords: Allergen; Bioinformatics; Periplaneta americana; Prediction