Sage-N Research has announced the integration of a phosphorylation tool using mass spectrometry into its drug discovery platform to aid in the study of diseases such as cancer.
The phosphorylation algorithm measures the likelihood of correct phosphorylation site localisation, which is important for the study of many diseases.
The analysis of post-translational modifications (PTMs) is particularly important.
If alterations occur in the regulation of these protein modifications it can lead to diseases such as Alzheimer's and cancer.
PTMs such as phosphorylation are used as chemical switches in protein interactions, and as such their identification is essential as it leads to insights into the function and role of the protein in the biological system.
It is also useful in the development of new drugs for these hard-to-treat diseases, and with a third of all newly marketed drugs being phospho-proteins (kinase inhibitors), the need for a tool to identify if a protein has phosphorylated has never been more essential.
Sage-N has worked in collaboration with Prof Steve Gygi from Harvard Medical School, who is the developer of the first phosphorylation algorithm Ascore, to integrate the technology into its drug discovery platform.
The platform features post-processing tools with the Sorcerer Enterprise 4.0 software to provide a sensitive and accurate identification and characterisation of low-abundance phospho-proteins and PTMs important to cancer and stem-cell research.
The phosphorylation algorithm goes beyond the identification of proper peptide sequencing to provide information about the presence or absence of site-determining ions.
Sage-N has integrated the tool with the Sequest 3G search engine, developed in partnership with Prof John R Yates III of the Scripps Research Institute.
The phosphorylation algorithm generates a probability-based score from the outcome of the Sequest 3G data, which measures the probability of correct phosphorylation size localisation based on the presence and intensity of site-determining ions in MS/MS spectra.
It is now possible to identify and characterise proteins on a large scale, with multiple scores using mass spectrometry proteomics.
Standard search engines are only able to identify the sequence of a protein but fail to determine if the phosphorylation site is correct.
By integrating the phosphorylation tool with Sequest 3G, it processes the data and provides multiple sites and a probability score to maximise data sensitivity by efficiently distracting incorrect peptide spectral matches (PSMs).
