Literature DB >> 17022629

A new approach for the detection and identification of protein impurities using combinatorial solid phase ligand libraries.

Fréderic Fortis1, Luc Guerrier, Liliana B Areces, Paolo Antonioli, Tim Hayes, Kevin Carrick, David Hammond, Egisto Boschetti, Pier Giorgio Righetti.   

Abstract

We propose a novel method for detection of protein impurities present in plasma-derived and recombinant purified injectable biopharmaceuticals by enhancing the concentration of protein impurities, in essence "amplifying" their presence to detectable levels. The method is based on the capture of proteins using a combinatorial solid-phase hexapeptides ligand library previously described for the reduction of protein concentration difference in biological fluids. Three proteins have been investigated: Staphylococcus aureus Protein A, expressed in Escherichia coli and supplied as 99% pure, recombinant human albumin, expressed in Pichia pastoris and certified as 95% pure, and therapeutic albumin supplied as 96-98% pure injectable solution. In all cases, after treatment with the ligand libraries, a number of additional polypeptide chains, not visible in the control, could be detected and obtained in sufficient amounts for MS analysis. In the cases of the two recombinant proteins, it could be demonstrated that a number of these polypeptide chains were host cell proteins still present in the purified product. In addition, a substantial number of these spots were found to be cleavage products of the original recombinant DNA species. Such cleavage products were particularly abundant in the recombinant human albumin preparation. From pure injectable serum albumin, a number of human plasma protein impurities were also identified by LC-MS/MS analysis. Treatment with ligand libraries of purified proteins is thus seen as a very powerful method of capture and concentration of host proteins and cleaved products for further analysis to control better the quality of industrial biotechnology products.

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Year:  2006        PMID: 17022629     DOI: 10.1021/pr060090s

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  8 in total

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8.  Proteomic analysis for finding serum pathogenic factors and potential biomarkers in multiple myeloma.

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  8 in total

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