dbMisLoc: A Manually Curated Database of Conditional Protein Mis-localization Events

Area of Science:

• Molecular Biology
• Bioinformatics
• Genomics

Background:

• Protein mis-localization is increasingly reported in various conditions, including complex disorders.
• Existing models lack a comprehensive, centralized database for experimentally validated protein mis-localization events.
• Data on protein mis-localization is scattered across scientific literature.

Purpose of the Study:

• To create a comprehensive database resource for conditional protein mis-localization events.
• To facilitate the study of protein mis-localization and its link to complex disorders.
• To provide a centralized platform for accessing and analyzing protein mis-localization data.

Main Methods:

• Manual curation of conditional protein mis-localization events from diverse scientific literature.
• Development of the dbMisLoc database to store protein localization, mis-localization, and associated conditions.
• Integration of a BLAST search engine for similarity searches of mis-localized proteins.

Main Results:

• The dbMisLoc database has been established, containing manually curated protein mis-localization events.
• The database covers 14 categories of conditions, including diseases, drug treatments, and environmental stresses.
• dbMisLoc offers intuitive viewing, searching, visualization, and downloading of protein mis-localization records.

Conclusions:

• dbMisLoc provides a valuable, centralized resource for researchers studying protein mis-localization.
• The database supports the investigation of protein mis-localization's role in complex disorders.
• dbMisLoc is publicly accessible and its source code is available for user-hosted mirrors.