Peptoscope

To specifically detect PTMs we have developed Peptoscope.

Peptoscope is the computational platform generating a mass distance fingerprint (MDF) from high-accuracy peptide masses. It has been shown to detect a number of abundant peptide modifications with high accuracy and statistical significance. Peptoscope is used for quality control of experiments, PTM detection and to drive search engines. It also characterizes elution characteristics of chemical peptide modifications like e.g. ICAT.

Peptoscope is a simple statistical algorithm meant to detect common peptide precursor mass differences. These mass differences often correspond to post-translational modifications. Peptoscope requires high-accuracy mass spectrometry data as input, such as that generated by LTQ-FTs.

Figure: Illustration of the method. Red curve: R(Δm) having width σR. Green curve: the modification induced part having width σj . The red curve seems flat because σR >> σj This peak close to δm = 58.005 Da is induced by a modification. The area between the green and the red curve corresponds to the estimated number of true pairs. 95 percent of these true pairs are within ±2σj distance from 58.005 Da. The ±2σj boundaries are shown with blue lines.

Figure: Illustration of the MDF concept, mass distances ranging from 8 to 10 Da. Red curve: the measured MDH(Δm). Blue curve: R(Δm) with σR = 0.055 Da. Green curve: signal used for deriving the Mass Distance Fingerprint. In this case, Peptoscope finds a modification at Δm = 9.02967 Da which is 0.00052 Da off from the theoretical value of the cleavable ICAT modification Δm of 9.03019 Da.

For the datasets used in our study, Peptoscope was able to detect post-translational modifications at electron-mass accuracy or better. The method is used for automating a search engine with respect to variable modifications settings. Peptoscope is publicly available at www.peptoscope.ms.

Together with specific tools like the currently being developed Peptoscope application for the automated detection of post-translational modifications in high-accuracy data sets, the new bioinformatics tools will allow for an efficient processing and exploitation of proteomics data.

Publication

Potthast et.al, Chromatogr B. 2007 Jul 1;854(1-2):173-82

Contact

Dorothea Rutishauser