Sequence Protein Identification by Randomized Sequence Database and Transcriptome Mass Spectrometry (SPIDER-TMS): From Manual to Automatic Application of a 'de Novo Sequencing' Approach. Issue 4 (August 2016)

• Record Type: Journal Article
• Authors: Pascale, Raffaella; Grossi, Gerarda; Cruciani, Gabriele; Mecca, Giansalvatore; Santoro, Donatello; Calace, Renzo Sarli; Falabella, Patrizia; Bianco, Giuliana
• Is Part Of: European journal of mass spectrometry. Volume 22:Issue 4(2015)
• Page Start: 193
• Page End: 198
• Publication Date: 2016-08
• Subjects: algorithm -- proteomic -- FTMS -- FT-ICR -- tandem mass spectrometry -- high resolution -- peptide identification -- bioinformatic tool -- database search -- de novo sequencing; Mass spectrometry -- Periodicals; Mass Spectrometry; Mass spectrometry; Periodicals; Periodicals; 543.6505
• DOI: 10.1255/ejms.1434
• Languages: English
• ISSNs: 1469-0667

Abstract

Sequence protein identification by a randomized sequence database and transcriptome mass spectrometry software package has been developed at the University of Basilicata in Potenza (Italy) and designed to facilitate the determination of the amino acid sequence of a peptide as well as an unequivocal identification of proteins in a high-throughput manner with enormous advantages of time, economical resource and expertise. The software package is a valid tool for the automation of a de novo sequencing approach, overcoming the main limits and a versatile platform useful in the proteomic field for an unequivocal identification of proteins, starting from tandem mass spectrometry data. The strength of this software is that it is a user-friendly and non-statistical approach, so protein identification can be considered unambiguous.