fpocket

What is fpocket?

fpocket is an open-source protein pocket detection algorithm that identifies ligand binding sites using Voronoi tessellation and alpha sphere geometry.

The software analyzes protein structures to locate and characterize cavities and clefts where small molecules can bind. The algorithm ranks detected pockets by druggability and provides geometric and physicochemical descriptors.

Traditional binding site detection methods often rely on grid-based approaches or require ligand-bound structures as templates. fpocket instead uses geometric principles to identify pockets directly from protein coordinates, making it applicable to both bound and unbound (apo) protein structures.

The algorithm achieves 94% detection accuracy within the top three ranked pockets while executing in under 3 seconds per structure.

Applications

• Virtual screening: Identifying druggable pockets before molecular docking campaigns
• Cryptic pocket discovery: Detecting transient or induced-fit binding sites in apo structures
• Protein function annotation: Predicting functionally important cavities in novel protein structures
• Structure-based design: Guiding where to position ligands for AutoDock Vina or GNINA docking studies

How to use fpocket online

ProteinIQ runs fpocket 4.2.3 through a web interface without command-line installation. You upload a protein structure or enter a PDB ID, and the tool returns ranked pockets with geometric and chemical descriptors.

Inputs

Settings

The default settings run automatic fpocket pocket detection. Optional controls can focus the analysis on known sites, selected chains, or adjusted alpha-sphere clustering parameters.

Results

fpocket returns a ranked table of detected pockets with the standard descriptors written to the *_info.txt report.

The Files tab includes the fpocket-generated artifacts for the run, including the *_info.txt report, combined pocket structures, per-pocket coordinate files, visualization scripts, and a CSV export of the spreadsheet values.

Interpreting druggability scores

The druggability score is a value from 0 to 1 calculated by fpocket 4.2.3 with a logistic function over selected pocket descriptors. A value above 0.5 indicates that binding by a drug-like molecule may be plausible; it is not a validated target classification or an affinity prediction. A low score does not mean that peptides, cofactors, or other molecule classes cannot bind.

Interpret the score alongside pocket geometry, chemistry, structural context, and experimental evidence. Changing fpocket's default detection parameters can also reduce the applicability of the trained druggability model.

How does fpocket work?

fpocket employs alpha sphere theory based on computational geometry. An alpha sphere is defined as a sphere that touches exactly four protein atoms on its boundary while containing no atoms in its interior. These spheres naturally concentrate in protein cavities and clefts, making them ideal markers for binding site detection.

Voronoi tessellation

The algorithm begins by computing a Voronoi decomposition of 3D space around the protein using the Qhull library. Voronoi vertices—points equidistant from four neighboring atoms—correspond to potential alpha sphere centers. fpocket filters these vertices by radius, discarding spheres too small (tight atomic packing in the protein core) or too large (solvent-exposed surface regions).

The default radius range is 3.4–6.2 Å, optimized for typical small molecule binding sites. This geometric criterion eliminates ~80% of candidate spheres before clustering.

Clustering algorithm

fpocket groups neighboring alpha spheres into pockets using a three-pass clustering procedure:

1. Rough segmentation: Initial clusters form from spheres within 3.3 Å of each other
2. Center-of-mass aggregation: Small clusters merge if their centers lie within 4.5 Å
3. Multiple linkage: Final refinement connects clusters sharing boundary spheres

This hierarchical approach handles irregular pocket geometries better than single-threshold methods. The algorithm leverages Qhull's neighbor lists to avoid pairwise distance calculations, achieving near-linear runtime scaling.

Scoring function

fpocket 4.2.3 calculates the pocket-ranking score as a signed linear combination of five descriptors:

The source formula also includes an intercept of -0.65784. These coefficients explain the ordering produced by this release; they should not be treated as independent biological effect sizes.

Descriptor calculation

Beyond the scoring function, fpocket computes additional physicochemical properties:

• Volume: Calculated from the union of alpha spheres using numerical integration
• SASA decomposition: Solvent-accessible surface area partitioned by residue hydrophobicity
• Charge: Net electrostatic character from charged residue contributions
• Residue composition: Count of each amino acid type lining the pocket

These descriptors enable users to assess pockets beyond the druggability score alone.

Performance characteristics

Benchmark studies on the PocketPicker dataset (48 diverse proteins) demonstrate:

• Bound structures: 83% rank-1 accuracy, 92% rank-3 accuracy
• Unbound structures: 69% rank-1 accuracy, 94% rank-3 accuracy
• Speed: Under 3 seconds per structure on a single CPU core

On the Astex Diverse set (85 high-quality pharmaceutical complexes):

• Rank-1 detection: 67–73% depending on pocket size
• Rank-3 detection: 82–88%

The algorithm outperforms CAST, PASS, SURFNET, and LIGSITE at rank-3 while executing 10–100× faster than grid-based competitors. This speed advantage enables proteome-scale screening applications.

Limitations

• Shallow pockets: Surface grooves lacking depth may score poorly despite biological relevance
• Induced-fit sites: Pockets requiring significant backbone rearrangement upon ligand binding may remain undetected in apo structures
• Allosteric sites: Cryptic pockets distant from the protein surface often fall below detection thresholds
• Protein-protein interfaces: Extended, relatively flat interaction surfaces score lower than compact small molecule binding sites