Optimizing Discovery of Therapeutic Proteins: AlgoNomics Offers In Silico Support
Author: Adis International Limited,
Source: Pharmaceutical & Diagnostic Innovation, Volume 4, Number 9, 2006 , pp. 12-13(2)
Publisher: Adis International
Key:
- Free Content
- New Content
- Subscribed Content
- Free Trial Content
- Free Content
- New Content
- Subscribed Content
- Free Trial Content
Abstract:
Identifying whether a therapeutic protein candidate could trigger adverse immune reactions is an important part of the development process. Conversely, selecting proteins with high immunogenicity is vital in vaccine discovery. Until recently, choosing candidate proteins with appropriate immunogenicity for further development relied on lengthy experiments and computer-based analysis of protein sequence. However, the Belgian company AlgoNomics has developed a structure-based algorithm that enables rapid and efficient determination of the immunogenicity of proteins. Epibase® can be used to select protein candidates with minimal immunogenicity for use as therapeutics, or those with high immunogenicity for formulation into vaccines.The potential impact of this in silico tool in protein drug discovery was recognized when AlgoNomics became the recipient of the 2006 Frost & Sullivan Award for Technology Innovation. AlgoNomics has also developed a structural bioinformatics tool for designing therapeutic peptides, Tripole®, and many biotech and pharma companies have licensed the use of these technology platforms to support their in-house protein drug discovery programs.Keywords: Bioinformatics; Drug Innovation and Design; Genomics; Recombinant proteins; Research and development; Vaccines
Document Type: Research article
Key:
- Free Content
- New Content
- Subscribed Content
- Free Trial Content
- Free Content
- New Content
- Subscribed Content
- Free Trial Content
Click here for Page Help