Towards automatic derivation of geometry-based descriptors as surrogates for complex structural approaches in enzyme-substrate prediction
<p>Dataset produced for the Project PRELUDIUM19 2020/37/N/NZ2/00967 entitled: "Towards automatic derivation of geometry-based descriptors as surrogates for complex structural approaches in enzyme-substrate prediction"</p> <p>The dataset counts with the three families of enzymes used: dehalogenase, aldehyde reductase and nitrilase.</p> <p>For each enzyme, the docked structures, docked parameters and scripts to analyze them further are present. Moreover, the protocol that derives geometric descriptors from docked structures is also present.</p> <p>This work was supported by the National Science Centre, Poland (grant no. 2020/37/N/NZ2/00967)</p>
ShareScore
36/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 4