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Does anyone know if there is a program/library/script in R or Python that takes as input a list of proteins/peptides and a list of post-translational modifications (PTMs; like oxidation of methionine and acetylation of cysteine), and as output returns a matrix/list with the imported peptides and all possible locations of the selected modifications?

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    $\begingroup$ Why would you need that? Maybe you can work with Uniprot modifications listed at their webpage instead of creating "new" ones? $\endgroup$ – llrs Jul 8 '17 at 12:01
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I don't know of a tool that can do exactly what you want. However, there are various tools that can predict specific classes of post translational modifications. For example:

  1. Phosphorylation: GPS

    Computational prediction of phosphorylation sites with their cognate protein kinases (PKs) is greatly helpful for further experimental design. Although ~10 online predictors were developed, the PK classification and control of false positive rate (FPR) were not well addressed. Here we adopted a well-established rule to classify PKs into a hierarchical structure with four levels.

  2. Mitochondrial import: Mitoprot

    MitoProt calculates the N-terminal protein region that can support a Mitochondrial Targeting Sequence and the cleavage site. A complete description of the method to make the prediction is available in: M.G. Claros, P. Vincens. Computational method to predict mitochondrially imported proteins and their targeting sequences. Eur. J. Biochem. 241, 779-786 (1996).

  3. Acetylation: "PAIL: Prediction of Acetylation on Internal Lysines"

    In this work, we present a novel online predictor for protein acetylation sites prediction of PAIL, Prediction of Acetylation on Internal Lysines. We have manually mined scientific literature to collect 249 experimentally verified acetylation sites of 92 distinct proteins. Then the BDM (Bayesian Discriminant Method) algorithm has been employed.

You can use tools like the above and then combine the results to get the sort of matrix you are asking for.

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