8 research outputs found
MS/MS-Free Protein Identification in Complex Mixtures Using Multiple Enzymes with Complementary Specificity
In this work, we present the results
of evaluation of a workflow
that employs a multienzyme digestion strategy for MS1-based protein
identification in “shotgun” proteomic applications.
In the proposed strategy, several cleavage reagents of different specificity
were used for parallel digestion of the protein sample followed by
MS1 and retention time (RT) based search. Proof of principle for the
proposed strategy was performed using experimental data obtained for
the annotated 48-protein standard. By using the developed approach,
up to 90% of proteins from the standard were unambiguously identified.
The approach was further applied to HeLa proteome data. For the sample
of this complexity, the proposed MS1-only strategy determined correctly
up to 34% of all proteins identified using standard MS/MS-based database
search. It was also found that the results of MS1-only search were
independent of the chromatographic gradient time in a wide range of
gradients from 15–120 min. Potentially, rapid MS1-only proteome
characterization can be an alternative or complementary to the MS/MS-based
“shotgun” analyses in the studies, in which the experimental
time is more important than the depth of the proteome coverage
IdentiPy: An Extensible Search Engine for Protein Identification in Shotgun Proteomics
We
present an open-source, extensible search engine for shotgun
proteomics. Implemented in Python programming language, IdentiPy shows
competitive processing speed and sensitivity compared with the state-of-the-art
search engines. It is equipped with a user-friendly web interface,
IdentiPy Server, enabling the use of a single server installation
accessed from multiple workstations. Using a simplified version of
X!Tandem scoring algorithm and its novel “autotune”
feature, IdentiPy outperforms the popular alternatives on high-resolution
data sets. Autotune adjusts the search parameters for the particular
data set, resulting in improved search efficiency and simplifying
the user experience. IdentiPy with the autotune feature shows higher
sensitivity compared with the evaluated search engines. IdentiPy Server
has built-in postprocessing and protein inference procedures and provides
graphic visualization of the statistical properties of the data set
and the search results. It is open-source and can be freely extended
to use third-party scoring functions or processing algorithms and
allows customization of the search workflow for specialized applications
MS/MS-Free Protein Identification in Complex Mixtures Using Multiple Enzymes with Complementary Specificity
In this work, we present the results
of evaluation of a workflow
that employs a multienzyme digestion strategy for MS1-based protein
identification in “shotgun” proteomic applications.
In the proposed strategy, several cleavage reagents of different specificity
were used for parallel digestion of the protein sample followed by
MS1 and retention time (RT) based search. Proof of principle for the
proposed strategy was performed using experimental data obtained for
the annotated 48-protein standard. By using the developed approach,
up to 90% of proteins from the standard were unambiguously identified.
The approach was further applied to HeLa proteome data. For the sample
of this complexity, the proposed MS1-only strategy determined correctly
up to 34% of all proteins identified using standard MS/MS-based database
search. It was also found that the results of MS1-only search were
independent of the chromatographic gradient time in a wide range of
gradients from 15–120 min. Potentially, rapid MS1-only proteome
characterization can be an alternative or complementary to the MS/MS-based
“shotgun” analyses in the studies, in which the experimental
time is more important than the depth of the proteome coverage