A curated reference database of membrane-permeability annotations for biological dyes.

Area of Science:

• Biochemistry
• Chemical Biology
• Bioinformatics

Background:

• Cellular labeling, imaging, and functional assays rely heavily on fluorescent and chromogenic dyes.
• Existing data on dye membrane permeability is fragmented and inconsistently documented.
• A standardized resource is needed to consolidate this critical information.

Purpose of the Study:

• To create DyePermDB, a curated dataset of 251 biologically relevant dyes.
• To provide standardized chemical identifiers, literature-supported membrane permeability annotations, and structural information.
• To address the gap in consistent and accessible dye membrane permeability data.

Main Methods:

• Developed a two-level annotation framework for intrinsic permeability status and context-dependent permeability.
• Integrated structured annotation fields for chemical form, evidence, localization, and conditions.
• Standardized chemical structures using an RDKit-based workflow with quality control.
• Organized data into four linked datasets: core annotations, structure validation, supplementary data, and cross-references.

Main Results:

• Established DyePermDB with 251 dyes, including standard identifiers and permeability annotations.
• Implemented a detailed annotation framework capturing nuanced permeability contexts.
• Provided standardized structures with quality metadata for cheminformatics analysis.
• Validated the dataset's internal classification signal using FP4 fingerprint analyses.

Conclusions:

• DyePermDB offers a reusable resource for reviewing dye annotations and assessing structure quality.
• The database facilitates computational studies on membrane permeability.
• Integrating traceable evidence, standardized structures, and quality control enhances data reliability and usability.