LLPSDB

LLPSDB provides a curated repository of proteins and detailed experimental conditions for studying liquid–liquid phase separation (LLPS) in vitro.

Key Features:

• Literature-curated dataset: Manually curated from published literature and containing 1182 entries covering 273 independent proteins and 2394 specific experimental conditions.
• Protein annotations: Includes protein sequences, modifications, and associated nucleic acids.
• Phase behavior annotations: Records experimental conditions and observed phase behaviors for entries.
• Micro-environmental influence: Emphasizes how micro-environmental conditions affect protein phase behavior beyond sequence-based predictions.
• Support for predictive method development: Provides data and annotations useful for developing and validating predictive methods for phase separation.

Scientific Applications:

• Studying in vitro LLPS: Enables analysis of proteins and conditions that drive liquid–liquid phase separation in vitro.
• Relating sequence and environment: Facilitates exploration of how protein characteristics and micro-environmental conditions influence propensity for phase separation.
• Developing predictive models: Supplies curated data to support development and validation of predictive methods for LLPS.
• Investigating cellular functions and disease: Provides annotations relevant to understanding LLPS mechanisms in cellular functions and related pathological conditions.

Methodology:

Data were manually curated from published literature.