Integrated computational protocol for sampling molecular databases towards allosteric inhi

A computational screening protocol applied to a library of approximately 60,000 ZINC compounds to identify potential allosteric inhibitors of the SARS-CoV-2 spike protein. The dataset, authored by Vanda Boršová and last updated on 2026-05-08, includes results from molecular dynamics and free-energy calculations on selected candidates. It provides a framework for analyzing small molecule effects on large conformational changes in viral fusion proteins.

Use Cases

• Identifying candidate small molecules for allosteric inhibition based on physicochemical and spatial screening criteria.
• Analyzing ligand stability and its effect on protein conformational changes using classical molecular dynamics simulation data.
• Quantifying the impact of compounds on protein activation pathways using free-energy profiles from umbrella sampling.
• Clustering and selecting representative compounds from a large initial library for detailed study.

Strengths

• Includes data from an initial screening library of approximately 60,000 ZINC compounds.
• Provides results from detailed computational methods, including molecular dynamics and steered simulations.
• Analysis includes free-energy profiles and conformational population density maps for selected ligands.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect methodological bias inherent to the specific computational protocols used.

Provenance

Source

figshare

Collection Method

Integrated computational approach including molecular dynamics, steered simulations, umbrella sampling, and principal component analysis.

Freshness

Last updated 2026-05-08 12:59:44; freshness should be verified.