Dataset Information

PIRSitePredict for protein functional site prediction using position-specific rules.

ABSTRACT: Methods focused on predicting 'global' annotations for proteins (such as molecular function, biological process and presence of domains or membership in a family) have reached a relatively mature stage. Methods to provide fine-grained 'local' annotation of functional sites (at the level of individual amino acid) are now coming to the forefront, especially in light of the rapid accumulation of genetic variant data. We have developed a computational method and workflow that predicts functional sites within proteins using position-specific conditional template annotation rules (namely PIR Site Rules or PIRSRs for short). Such rules are curated through review of known protein structural and other experimental data by structural biologists and are used to generate high-quality annotations for the UniProt Knowledgebase (UniProtKB) unreviewed section. To share the PIRSR functional site prediction method with the broader scientific community, we have streamlined our workflow and developed a stand-alone Java software package named PIRSitePredict. We demonstrate the use of PIRSitePredict for functional annotation of de novo assembled genome/transcriptome by annotating uncharacterized proteins from Trinity RNA-seq assembly of embryonic transcriptomes of the following three cartilaginous fishes: Leucoraja erinacea (Little Skate), Scyliorhinus canicula (Small-spotted Catshark) and Callorhinchus milii (Elephant Shark). On average about 1200 lines of annotations were predicted for each species.

SUBMITTER: Chen C

PROVIDER: S-EPMC6389862 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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PIRSitePredict for protein functional site prediction using position-specific rules.

Chen Chuming C Wang Qinghua Q Huang Hongzhan H Vinayaka Cholanayakanahalli R CR Garavelli John S JS Arighi Cecilia N CN Natale Darren A DA Wu Cathy H CH

Database : the journal of biological databases and curation 20190101

Methods focused on predicting 'global' annotations for proteins (such as molecular function, biological process and presence of domains or membership in a family) have reached a relatively mature stage. Methods to provide fine-grained 'local' annotation of functional sites (at the level of individual amino acid) are now coming to the forefront, especially in light of the rapid accumulation of genetic variant data. We have developed a computational method and workflow that predicts functional sit ...[more]

PMID: 30805646

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Project description:Site-specific protein labeling is an important technique in protein chemistry and is used for diverse applications ranging from creating protein conjugates to protein immobilization. Enzymatic reactions, including protein prenylation, have been widely exploited as methods to accomplish site-specific labeling. Enzymatic prenylation is catalyzed by prenyltransferases, including protein farnesyltransferase (PFTase) and geranylgeranyltransferase type I (GGTase-I), both of which recognize C-terminal CaaX motifs with different specificities and transfer prenyl groups from isoprenoid diphosphates to their respective target proteins. A number of isoprenoid analogues containing bioorthogonal functional groups have been used to label proteins of interest via PFTase-catalyzed reaction. In this study, we sought to expand the scope of prenyltransferase-mediated protein labeling by exploring the utility of rat GGTase-I (rGGTase-I). First, the isoprenoid specificity of rGGTase-I was evaluated by screening eight different analogues and it was found that those with bulky moieties and longer backbone length were recognized by rGGTase-I more efficiently. Taking advantage of the different substrate specificities of rat PFTase (rPFTase) and rGGTase-I, we then developed a simultaneous dual labeling method to selectively label two different proteins by using isoprenoid analogue and CaaX substrate pairs that were specific to only one of the prenyltransferases. Using two model proteins, green fluorescent protein with a C-terminal CVLL sequence (GFP-CVLL) and red fluorescent protein with a C-terminal CVIA sequence (RFP-CVIA), we demonstrated that when incubated together with both prenyltransferases and the selected isoprenoid analogues, GFP-CVLL was specifically modified with a ketone-functionalized analogue by rGGTase-I and RFP-CVIA was selectively labeled with an alkyne-containing analogue by rPFTase. By switching the ketone-containing analogue to an azide-containing analogue, it was possible to create protein tail-to-tail dimers in a one-pot procedure through the copper(I)-catalyzed alkyne-azide cycloaddition (CuAAC) reaction. Overall, with the flexibility of using different isoprenoid analogues, this system greatly extends the utility of protein labeling using prenyltransferases.

Dataset Information

PIRSitePredict for protein functional site prediction using position-specific rules.

Publications

PIRSitePredict for protein functional site prediction using position-specific rules.

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