Systematic Protein Prioritization for Targeted Proteomics Studies through Literature Mining

There
are more than 3.7 million published articles on the biological
functions or disease implications of proteins, constituting an important
resource of proteomics knowledge. However, it is difficult to summarize
the millions of proteomics findings in the literature manually and
quantify their relevance to the biology and diseases of interest.
We developed a fully automated bioinformatics framework to identify
and prioritize proteins associated with any biological entity. We
used the 22 targeted areas of the Biology/Disease-driven (B/D)-Human
Proteome Project (HPP) as examples, prioritized the relevant proteins
through their Protein Universal Reference Publication-Originated Search
Engine (PURPOSE) scores, validated the relevance of the score by comparing
the protein prioritization results with a curated database, computed
the scores of proteins across the topics of B/D-HPP, and characterized
the top proteins in the common model organisms. We further extended
the bioinformatics workflow to identify the relevant proteins in all
organ systems and human diseases and deployed a cloud-based tool to
prioritize proteins related to any custom search terms in real time.
Our tool can facilitate the prioritization of proteins for any organ
system or disease of interest and can contribute to the development
of targeted proteomic studies for precision medicine.