Consensus Scoring Results for Molecular Docking Analysis from Seven Algorithms

Rank-by-rank consensus scoring results for molecular docking analysis. Individual rankings from seven docking algorithms were combined using radar plot area calculations, where smaller areas indicate better overall performance. The dataset, created by Neha Sharma and last updated on April 22, 2026, contains a final ranking representing consensus performance across all methods, with rank 1 being the best.

Use Cases

• Ranking compound performance based on consensus scores from seven docking algorithms.
• Selecting top candidate compounds for further experimental analysis based on highlighted rankings.
• Comparing the agreement or divergence between different molecular docking scoring methods.
• Validating docking algorithms by analyzing their collective ranking of a set of compounds.

Strengths

• Consensus ranking derived from seven distinct docking algorithms, potentially reducing method-specific bias.
• Results are structured in an XLS file, a widely accessible format for analysis.
• Dataset is licensed under CC-BY-4.0, permitting reuse with attribution.

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 very small (9.5 KB), indicating a limited scope of compounds analyzed.

Provenance

Source

figshare

Collection Method

Individual rankings from seven docking algorithms were combined using radar plot area calculations.

Time Range

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Freshness

Last updated 2026-04-22 17:30:13; freshness should be verified.

Geography

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