Dataset Information

RAId_DbS: mass-spectrometry based peptide identification web server with knowledge integration.

ABSTRACT: BACKGROUND:Existing scientific literature is a rich source of biological information such as disease markers. Integration of this information with data analysis may help researchers to identify possible controversies and to form useful hypotheses for further validations. In the context of proteomics studies, individualized proteomics era may be approached through consideration of amino acid substitutions/modifications as well as information from disease studies. Integration of such information with peptide searches facilitates speedy, dynamic information retrieval that may significantly benefit clinical laboratory studies. DESCRIPTION:We have integrated from various sources annotated single amino acid polymorphisms, post-translational modifications, and their documented disease associations (if they exist) into one enhanced database per organism. We have also augmented our peptide identification software RAId_DbS to take into account this information while analyzing a tandem mass spectrum. In principle, one may choose to respect or ignore the correlation of amino acid polymorphisms/modifications within each protein. The former leads to targeted searches and avoids scoring of unnecessary polymorphism/modification combinations; the latter explores possible polymorphisms in a controlled fashion. To facilitate new discoveries, RAId_DbS also allows users to conduct searches permitting novel polymorphisms as well as to search a knowledge database created by the users. CONCLUSION:We have finished constructing enhanced databases for 17 organisms. The web link to RAId_DbS and the enhanced databases is http://www.ncbi.nlm.nih.gov/CBBResearch/qmbp/RAId_DbS/index.html. The relevant databases and binaries of RAId_DbS for Linux, Windows, and Mac OS X are available for download from the same web page.

SUBMITTER: Alves G

PROVIDER: S-EPMC2605478 | biostudies-literature | 2008 Oct

REPOSITORIES: biostudies-literature

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RAId_DbS: mass-spectrometry based peptide identification web server with knowledge integration.

Alves Gelio G Ogurtsov Aleksey Y AY Yu Yi-Kuo YK

BMC genomics 20081027

<h4>Background</h4>Existing scientific literature is a rich source of biological information such as disease markers. Integration of this information with data analysis may help researchers to identify possible controversies and to form useful hypotheses for further validations. In the context of proteomics studies, individualized proteomics era may be approached through consideration of amino acid substitutions/modifications as well as information from disease studies. Integration of such infor ...[more]

PMID: 18954448

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Project description:In the rapidly expanding field of peptide therapeutics, the short in vivo half-life of peptides represents a considerable limitation for drug action. D-peptides, consisting entirely of the dextrorotatory enantiomers of naturally occurring levorotatory amino acids (AAs), do not suffer from these shortcomings as they are intrinsically resistant to proteolytic degradation, resulting in a favourable pharmacokinetic profile. To experimentally identify D-peptide binders to interesting therapeutic targets, so-called mirror-image phage display is typically performed, whereby the target is synthesized in D-form and L-peptide binders are screened as in conventional phage display. This technique is extremely powerful, but it requires the synthesis of the target in D-form, which is challenging for large proteins. Here we present finDr, a novel web server for the computational identification and optimization of D-peptide ligands to any protein structure (https://findr.biologie.uni-freiburg.de/). finDr performs molecular docking to virtually screen a library of helical 12-mer peptides extracted from the RCSB Protein Data Bank (PDB) for their ability to bind to the target. In a separate, heuristic approach to search the chemical space of 12-mer peptides, finDr executes a customizable evolutionary algorithm (EA) for the de novo identification or optimization of D-peptide ligands. As a proof of principle, we demonstrate the validity of our approach to predict optimal binders to the pharmacologically relevant target phenol soluble modulin alpha 3 (PSMα3), a toxin of methicillin-resistant Staphylococcus aureus (MRSA). We validate the predictions using in vitro binding assays, supporting the success of this approach. Compared to conventional methods, finDr provides a low cost and easy-to-use alternative for the identification of D-peptide ligands against protein targets of choice without size limitation. We believe finDr will facilitate D-peptide discovery with implications in biotechnology and biomedicine.

Dataset Information

RAId_DbS: mass-spectrometry based peptide identification web server with knowledge integration.

Publications

RAId_DbS: mass-spectrometry based peptide identification web server with knowledge integration.

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