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Massively parallel interrogation of protein fragment secretability using SECRiFY reveals features influencing secretory system transit (preprint)
biorxiv; 2020.
Preprint
in English
| bioRxiv | ID: ppzbmed-10.1101.241349
ABSTRACT
While transcriptome- and proteome-wide technologies to assess processes in protein biogenesis are now widely available, we still lack global approaches to assay post-ribosomal biogenesis events, in particular those occurring in the eukaryotic secretory system. We here developed a method, SECRiFY, to simultaneously assess the secretability of >105 protein fragments by two yeast species, S. cerevisiae and P. pastoris, using custom fragment libraries, surface display and a sequencing-based readout. Screening human proteome fragments with a median size of 50 - 100 amino acids, we generated datasets that enable datamining into protein features underlying secretability, revealing a striking role for intrinsic disorder and chain flexibility. SECRiFY is the first methodology that generates sufficient amounts of annotated data for advanced machine learning methods to deduce secretability predictors. The finding that secretability is indeed a learnable feature of protein sequences is of significant impact in the broad area of recombinant protein expression and de novo protein design.
Full text:
Available
Collection:
Preprints
Database:
bioRxiv
Main subject:
Sleep Disorders, Intrinsic
Language:
English
Year:
2020
Document Type:
Preprint
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