Serine Protease Data for PLA Depolymerization Discovery and ML Design

Bin Xie's dataset contains raw and supporting data for a study on discovering and engineering a serine protease to degrade polylactic acid (PLA). The 1.3 MB collection includes enzyme activity measurements, lactic acid release profiles, and depolymerization efficiency calculations. It was last updated on May 21, 2026, and supports the reproducibility of structure-based discovery and machine learning-aided protein engineering.

Use Cases

• Training machine learning models for protein engineering based on mutant activity and thermostability data.
• Analyzing enzyme performance for plastic degradation based on lactic acid release profiles and depolymerization efficiency.
• Benchmarking computational protein design methods using structure-based discovery and experimental validation results.
• Reproducing analyses for high-substrate-loading reactions and commercial PLA product depolymerization assays.

Strengths

• Data is directly linked to a published manuscript, providing context for analysis and validation.
• Includes results for multiple experimental phases: discovery, engineering, and application testing on commercial products.
• Files are provided in the XLSX format, which is widely accessible for analysis.
• Released under a permissive CC-BY-4.0 license, allowing for broad reuse with attribution.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for large-scale ML training.
• The dataset is small at 1.3 MB, which may indicate a limited scope or sample size.

Provenance

Source

figshare, associated with a specific research manuscript.

Collection Method

Likely contains experimental measurements from enzyme activity assays, depolymerization tests, and computational analysis results.

Freshness

Last updated 2026-05-21 10:26:02; freshness should be verified.