Conformer Generation Workflows for COSMO-RS Solubility Predictions

André M. M. Gomes published a dataset on figshare on 2026-05-15 evaluating four conformer-generation workflows for COSMO-RS solubility predictions. It contains a curated set of 926 experimental solubility values and 405 free energies of solvation. The analysis compares RDKit-based, semiempirical, and DFT-based pipelines to assess their influence on prediction accuracy.

Use Cases

• Benchmarking conformer-generation workflows based on the described RDKit, semiempirical, and DFT pipelines.
• Improving solvent-aware single-conformer selection for molecules with intramolecular hydrogen bonds.
• Assessing prediction accuracy in the low-solubility regime using the provided experimental solubility data.

Strengths

• Curated data set comprising 926 experimental solubility values and 405 free energies of solvation.
• Systematic evaluation of four distinct conformer-generation workflows on a chemically diverse data set.
• Mean absolute errors close to one logarithmic unit reported for the full data set.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is small, with a file size of 128.9 KB.

Provenance

Source

André M. M. Gomes via figshare

Collection Method

Curated experimental data used to evaluate computational workflows.

Freshness

Last updated 2026-05-15 02:06:06; freshness should be verified.