Dataset Information

XComb: a cross-linked peptide database approach to protein-protein interaction analysis.

ABSTRACT: We developed an informatic method to identify tandem mass spectra composed of chemically cross-linked peptides from those of linear peptides and to assign sequence to each of the two unique peptide sequences. For a given set of proteins the key software tool, xComb, combs through all theoretically feasible cross-linked peptides to create a database consisting of a subset of all combinations represented as peptide FASTA files. The xComb library of select theoretical cross-linked peptides may then be used as a database that is examined by a standard proteomic search engine to match tandem mass spectral data sets to identify cross-linked peptides. The database search may be conducted against as many as 50 proteins with a number of common proteomic search engines, e.g. Phenyx, Sequest, OMSSA, Mascot and X!Tandem. By searching against a peptide library of linearized, cross-linked peptides, rather than a linearized protein library, search times are decreased and the process is decoupled from any specific search engine. A further benefit of decoupling from the search engine is that protein cross-linking studies may be conducted with readily available informatics tools for which scoring routines already exist within the proteomic community.

SUBMITTER: Panchaud A

PROVIDER: S-EPMC2884221 | biostudies-literature | 2010 May

REPOSITORIES: biostudies-literature

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xComb: a cross-linked peptide database approach to protein-protein interaction analysis.

Panchaud Alexandre A Singh Pragya P Shaffer Scott A SA Goodlett David R DR

Journal of proteome research 20100501 5

We developed an informatic method to identify tandem mass spectra composed of chemically cross-linked peptides from those of linear peptides and to assign sequence to each of the two unique peptide sequences. For a given set of proteins the key software tool, xComb, combs through all theoretically feasible cross-linked peptides to create a database consisting of a subset of all combinations represented as peptide FASTA files. The xComb library of select theoretical cross-linked peptides may then ...[more]

PMID: 20302351

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Project description:Snakebite envenoming is a major neglected tropical disease that affects millions of people every year. The only effective treatment against snakebite envenoming consists of unspecified cocktails of polyclonal antibodies purified from the plasma of immunized production animals. Currently, little data exists on the molecular interactions between venom-toxin epitopes and antivenom-antibody paratopes. To address this issue, high-density peptide microarray (hdpm) technology has recently been adapted to the field of toxinology. However, analysis of such valuable datasets requires expert understanding and, thus, complicates its broad application within the field. In the present study, we developed a user-friendly, and high-throughput web application named "Snake Toxin and Antivenom Binding Profiles" (STAB Profiles), to allow straight-forward analysis of hdpm datasets. To test our tool and evaluate its performance with a large dataset, we conducted hdpm assays using all African snake toxin protein sequences available in the UniProt database at the time of study design, together with eight commercial antivenoms in clinical use in Africa, thus representing the largest venom-antivenom dataset to date. Furthermore, we introduced a novel method for evaluating raw signals from a peptide microarray experiment and a data normalization protocol enabling intra-microarray and even inter-microarray chip comparisons. Finally, these data, alongside all the data from previous similar studies by Engmark et al., were preprocessed according to our newly developed protocol and made publicly available for download through the STAB Profiles web application (http://tropicalpharmacology.com/tools/stab-profiles/). With these data and our tool, we were able to gain key insights into toxin-antivenom interactions and were able to differentiate the ability of different antivenoms to interact with certain toxins of interest. The data, as well as the web application, we present in this article should be of significant value to the venom-antivenom research community. Knowledge gained from our current and future analyses of this dataset carry the potential to guide the improvement and optimization of current antivenoms for maximum patient benefit, as well as aid the development of next-generation antivenoms.

Dataset Information

XComb: a cross-linked peptide database approach to protein-protein interaction analysis.

Publications

xComb: a cross-linked peptide database approach to protein-protein interaction analysis.

Similar Datasets

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