SuCOS

SuCOS quantifies the overlap of volumetric shape and pharmacophoric chemical features to assess binding-mode similarity between molecular fragments for structure-based drug discovery.

Key Features:

• Shape and Pharmacophoric Feature Integration: Combines volumetric shape with pharmacophoric chemical features to produce a single measure of molecular binding-mode similarity.
• RDKit-based implementation: Implements RDKit-based algorithms to calculate shape and chemical feature overlaps.
• Unified overlap score: Produces a unified overlap score that integrates both volumetric and pharmacophoric information.
• Relation to existing metrics: Presents a metric analogous to OpenEye's Tversky Combo and Malhotra and Karanicolas' COS measure.
• Redocking performance: Demonstrates fewer false positives and false negatives than RMSD and PLIF in redocking comparisons.
• Cross-docking performance: Distinguishes experimentally observed binding modes of elaborated molecules based on their non-elaborated counterparts in cross-docking scenarios.
• Virtual screening differentiation: Shows improved differentiation of actives versus decoys in evaluations using the DUD-E dataset compared with AutoDock Vina.

Scientific Applications:

• Fragment-based drug discovery: Assess preservation of fragment binding modes during molecular elaboration and lead optimization.
• Docking pose assessment: Evaluate and compare predicted docking poses in redocking and cross-docking studies.
• Virtual screening benchmarking: Benchmark actives versus decoys using datasets such as DUD-E and compare scoring performance to tools like AutoDock Vina.

Methodology:

Calculates a unified overlap score by combining volumetric shape and pharmacophoric features using RDKit-based algorithms.