Integrative Proteome-Wide Virtual Screening for Pan-Flaviviral Antiviral Scaffolds

A 2026 dataset by Anderson Pereira Soares presents results from an integrative computational pipeline for discovering broad-spectrum antivirals against five flaviviruses. The work generated homology models of structural and nonstructural proteins from Zika, Yellow Fever, West Nile, Saint Louis Encephalitis, and Usutu viruses. A focused library of 160 natural product scaffolds and repurposed antivirals was exhaustively docked, identifying 40 top-ranked candidates with estimated binding affinities.

Use Cases

• Prioritizing lead compounds for experimental validation based on estimated binding energies (Kd) and multitarget profiles.
• Analyzing conserved binding sites across flavivirus proteins, such as the NS5 polymerase and E glycoprotein.
• Evaluating the pharmacokinetic properties of candidate scaffolds using filtered results from Lipinski's rules and ADMET predictions.
• Comparing virus-specific surface signatures and conserved core folds through structural analyses (RMSD, PCA, RMSF).

Strengths

• The dataset is the product of a standardized pipeline combining sequence and structure-based pocket prediction, electrostatic profiling, and pharmacokinetic filtering.
• Exhaustive docking was performed with 2,000 runs per pocket for a focused library of 160 compounds.
• Results include specific estimated binding affinities (Kd) for lead compounds like myricetin (≈1.9 µM) and temoporfin (≈1.2 nM).
• The analysis covers proteins from five distinct flaviviruses, enabling comparative studies.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset's 18.6 MB size suggests it is relatively small, potentially containing summary results rather than raw docking data.

Provenance

Source

figshare, authored by Anderson Pereira Soares.

Collection Method

Computational pipeline involving homology modeling, pocket prediction (Concavity), electrostatic profiling (APBS), pharmacokinetic filtering, and high-throughput docking (AutoDock4/Vina).

Freshness

Last updated 2026-04-30 05:24:57.