Data Sheet 5_Integrative proteome-wide structural analysis and high-throughput docking ide

Anderson Pereira Soares constructed homology models of structural and nonstructural proteins from five flaviviruses: Zika, Yellow Fever, West Nile, Saint Louis Encephalitis, and Usutu. The dataset includes results from a standardized virtual screening pipeline applied to a focused library of 160 natural product scaffolds and repurposed antivirals, with 40 top-ranked compounds identified. The data was last updated on 2026-04-30 and is shared under a CC-BY-4.0 license.

Use Cases

• Virtual screening for broad-spectrum antiviral candidates based on homology models of flavivirus proteins.
• Ranking lead compounds by binding energy based on exhaustive docking results (2,000 runs per pocket).
• Identifying dual-site binding scaffolds based on comparative analyses (RMSD, PCA, RMSF) of conserved core folds.
• Prioritizing compounds for experimental validation based on pharmacokinetic filtering (Lipinski’s rules, ADMET).

Strengths

• Includes homology models for all structural and nonstructural proteins from five distinct flaviviruses.
• Virtual screening pipeline applied a focused library of 160 compounds with exhaustive docking (2,000 runs per pocket).
• Identifies 40 top-ranked scaffolds with specific estimated binding affinities (e.g., temoporfin Kd ≈ 1.2 nM).

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 pipeline used.

Provenance

Source

Anderson Pereira Soares via figshare.

Collection Method

Computational pipeline combining homology modeling, pocket prediction (Concavity), electrostatic profiling (APBS), pharmacokinetic filtering, and molecular docking (AutoDock4/Vina).

Freshness

Last updated 2026-04-30 05:24:56; freshness should be verified.