Compugen Announces Drug Discovery Platform to Predict Peptides that Block Disease-Associated Conformations of Proteins
Product News Mar 24, 2008
Compugen Ltd. announced the development and validation of its Blockers of Disease-Associated Conformation (DAC Blockers) platform, a new discovery platform for the identification of peptides that block proteins from adopting their disease-associated conformations.
To date, two of the predicted therapeutic peptide candidates from the pilot validation run of the platform have shown initial experimental verification, one with anti-inflammatory and the other with anti-cancer activities.
The DAC Blockers platform has been designed to identify segments in proteins of interest that, if introduced therapeutically as synthetic peptides, would block specific conformational changes of such proteins, and thereby prevent them from adopting disease-associated conformations and related activities. A key capability of the platform is that it enables the proteome-wide search for such conformational change blocking peptides in human, viral and bacterial proteomes.
An initial run of the discovery platform resulted in the in silico prediction of therapeutic peptide candidates for approximately 40 drug targets of interest with potential usage for various indications, including solid cancers, inflammatory diseases, septic shock and viral diseases. Seven of these drug targets were selected for initial experimental validation and peptide blockers were found for all seven targets.
In addition, to date, two of these peptides have shown biological efficacy in experimental models, further demonstrating both their potential therapeutic utility and the validity of the platform’s predictive capability.
“Attempting to prevent the disease-associated conformation of proteins has been an area of interest in pharmaceutical research, relying substantially on various experimental discovery methods,” said Yossi Cohen, M.D., Compugen’s Vice President of Research and Development.
“Therefore, we view our DAC Blockers platform as a major accomplishment in this field since it replaces a largely experimental and inefficient discovery process with a systematic and constantly improving process of in silico prediction followed by experimental validation,” Dr. Cohen continued.
“The initial results are extremely encouraging, both in terms of quality and quantity, and we are very pleased to now add this discovery platform -- the ninth platform announced to date -- to our rapidly expanding discovery infrastructure,” Dr. Cohen concluded.