Journal:Laboratory information management software for engineered mini-protein therapeutic workflow

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Full article title Laboratory information management software for engineered mini-protein therapeutic workflow
Journal BMC Bioinformatics
Author(s) Brusniak, Mi-Youn; Ramos, Hector; Lee, Bernard; Olson, James M.
Author affiliation(s) Fred Hutchinson Cancer Research Center
Primary contact Email: mbrusnia at fredhutch dot org
Year published 2019
Volume and issue 20
Page(s) 343
DOI 10.1186/s12859-019-2935-x
ISSN 1471-2105
Distribution license Creative Commons Attribution 4.0 International
Website https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2935-x
Download https://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/s12859-019-2935-x (PDF)

Abstract

Background: Protein-based therapeutics are one of the fastest growing classes of novel medical interventions in areas such as cancer, infectious disease, and inflammation. Protein engineering plays an important role in the optimization of desired therapeutic properties such as reducing immunogenicity, increasing stability for storage, increasing target specificity, etc. One category of protein therapeutics is nature-inspired bioengineered cystine-dense peptides (CDPs) for various biological targets. These engineered proteins are often further modified by synthetic chemistry. For example, candidate mini-proteins can be conjugated into active small molecule drugs. We refer to modified mini-proteins as "optides" (optimized peptides). To efficiently serve the multidisciplinary lab scientists with varied therapeutic portfolio research goals in a non-commercial setting, a cost-effective, extendable laboratory information management system (LIMS) is/was needed.

Results: We have developed a LIMS named Optide-Hunter for a generalized engineered protein compounds workflow that tracks entities and assays from creation to preclinical experiments. The implementation and custom modules are built using LabKey Server, which is an open-source platform for scientific data integration and analysis. Optide-Hunter contains a compound registry, in-silico assays, high-throughput production, large-scale production, in vivo assays, and data extraction from a specimen-tracking database. It is used to store, extract, and view data for various therapeutics projects. Optide-Hunter also includes stand-alone external processing software (HPLCPeakClassifierApp) for automated chromatogram classification. The HPLCPeakClassifierApp is used for pre-processing of high-performance liquid chromatography (HPLC) data prior to loading to Optide-Hunter. The custom implementation is done using data transformation modules in R, SQL, JavaScript, and Java, while being open-source to assist new users in customizing it for their unique workflows. (Instructions for exploring a deployed version of Optide-Hunter can be found on the LabKey website.)

Conclusion: The Optide-Hunter LIMS system is designed and built to track the processes of engineering, producing, and prioritizing protein therapeutic candidates. It can be easily adapted and extended for use in small or large research laboratories where multidisciplinary scientists are collaborating to engineer compounds for potential therapeutic or protein science applications. Exploration of open-source Optide-Hunter can help any bioinformatics scientist adapt, extend, and deploy an equivalent system tailored to each laboratory’s workflow.

Keywords: laboratory information management system, therapeutic protein, HPLC/UPLC peak classification, protein engineering, LabKey software

References

Notes

This presentation is faithful to the original, with only a few minor changes to presentation, spelling, and grammar. We also added PMCID and DOI when they were missing from the original reference.