SoluProtMutsupDB

SoluProtMutsupDB provides a manually curated database of experimental measurements linking protein sequence mutations to changes in protein solubility for analysis and predictive model development.

Key Features:

• Extensive Data Collection: Contains over 33,000 measurements across 17,000 protein variants in 103 proteins, integrating previously published solubility data and thousands of new data points, including deep mutational scanning experiments.
• Manual Curation: Datasets have undergone meticulous manual curation and substantial corrections to improve accuracy and reliability.
• Experimental Conditions: Records include a variety of experimental conditions known to influence protein solubility, providing context-rich measurements.
• Machine Learning-ready Datasets: Curated and corrected data are suitable for developing predictive machine learning models of mutational effects on solubility.

Scientific Applications:

• Protein Engineering: Enables rational design of protein variants with improved solubility to enhance yields in protein production and manufacturing.
• Disease Research: Supports investigation of connections between mutational changes in solubility, protein aggregation, and human diseases for therapeutic research.
• Machine Learning Development: Provides curated datasets for training and validating predictive models that forecast the impacts of mutations on protein solubility.

Methodology:

Compiles and integrates data from published sources, including historical and contemporary studies and deep mutational scanning datasets, followed by manual curation and corrective edits to the entries.