PROPKA 3

What is PROPKA?

PROPKA is an empirical software program for structure-based pKa prediction in proteins and protein-ligand complexes. It starts from a model pKa for each recognized ionizable group, then estimates how desolvation, hydrogen bonding, nearby charges, and other features of the three-dimensional environment shift that value.

The method was introduced as a fast way to predict and rationalize protein pKa values from atomic coordinates. PROPKA 3 replaced the earlier split between buried and surface residues with a continuous treatment of desolvation and dielectric response. PROPKA 3.1 and later also support recognized ionizable groups in bound ligands and identify potentially coupled titratable groups.

Core functionality

• Protein pKa prediction: Estimates pKa values for ASP, GLU, HIS, CYS, TYR, LYS, ARG, the N-terminus, and the C-terminus.
• Environmental shift analysis: Reports the total shift from each model pKa in the results table, while the native .pka report breaks that shift into its structural determinants.
• Protein-ligand analysis: Includes supported ionizable ligand groups when their chemistry can be recognized from the structure.
• Coupled-site detection: Flags interacting titratable groups for which alternative pKa assignments may need to be considered together.

Why it is used

Ionization states affect protein charge, hydrogen-bond patterns, catalytic chemistry, ligand binding, and the preparation of structures for docking or molecular simulation. PROPKA provides site-specific estimates quickly enough to compare related structures, inspect unusually shifted residues, and guide protonation-state choices before more expensive calculations.

The result is a structure-based estimate, not a direct measurement or a constant-pH simulation. A different conformation, missing atoms, alternate side-chain placement, or changed ligand chemistry can produce a different prediction.

How to use PROPKA online

ProteinIQ runs PROPKA 3.5.1 on one uploaded PDB or ENT structure or one structure fetched from RCSB PDB per job. Use Batch mode to analyze multiple files as separate jobs. Each completed job returns a searchable pKa table, a CSV file, and the native .pka report, with optional chain selection, residue targeting, and coupled-group reporting.

Inputs

Protein-ligand complexes can be submitted as a single PDB structure. Ligand rows are returned only for chemical groups that PROPKA recognizes and parameterizes. Molecular-dynamics PDB files that place charge notation in atom fields are rejected because that notation conflicts with standard PDB parsing.

Settings

An empty chain or residue field keeps the standard full-structure calculation. A residue selector must identify a group that PROPKA treats as titratable. Selecting an alanine or another unsupported site returns an input error rather than an empty result.

Results

The Results tab contains one row per reported protein residue, terminal group, or ligand-derived site.

In Batch mode, each structure runs as a separate job with its own results and status. A failed structure does not remove results from successful jobs.

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Interpreting PROPKA results

pKa, model pKa, and shift

The model pKa is a reference value for the isolated chemical group. The predicted pKa includes the effect of the submitted structure. A positive Shift means the environment raises the pKa relative to the model value; a negative Shift means it lowers it.

The magnitude of a shift is useful for prioritizing unusual sites, but there is no universal cutoff that proves catalytic or functional importance. Comparisons are strongest when the same residue is evaluated across structures prepared in the same way.

Protonation at a target pH

For a simple, uncoupled group, pH relative to pKa gives the dominant state:

• Acidic groups: Predominantly protonated and usually neutral when pH is below pKa; predominantly deprotonated and negatively charged when pH is above pKa.
• Basic groups: Predominantly protonated and positively charged when pH is below pKa; predominantly deprotonated and usually neutral when pH is above pKa.
• Near the pKa: Both states can have appreciable populations. A single dominant-state assignment becomes less secure.

PROPKA reports pKa values rather than a protonated coordinate file. For a PQR structure with atomic charges, radii, and protonation assigned at a chosen pH, PDB2PQR is the more direct workflow.

Coupled groups and ligand sites

Strongly interacting ionizable groups can have coupled protonation behavior. Enabling Show coupled residues asks PROPKA to include the alternative assignments and notes it detects in the native report. The results table preserves a coupling note only when one appears on the corresponding summary row. Coupled values should be considered together, not read as independent single-site measurements.

Ligand rows include the ligand residue name, atom label, model pKa, and a PROPKA ligand atom type such as NAR or N33. An absent ligand row does not prove that a ligand has no ionizable group. It can also mean that the relevant chemistry was not recognized from the submitted PDB bonding and atom records.

PROPKA 3 examples

Ubiquitin complete pKa profile

The compact, single-chain ubiquitin structure demonstrates the standard full-structure workflow with no residue filter.

• Input: Ubiquitin from RCSB PDB 1UBQ, chain A
• Settings: Defaults

PROPKA returned 26 ionizable groups with predicted pKa values from 2.99 to 12.76. Asp58 appears at pKa 2.99 with a shift of -0.81. The values apply to the submitted crystal conformation and do not include conformational sampling.

Lysozyme Glu35 and Asp52 catalytic dyad

The targeted lysozyme run compares two well-known catalytic carboxylates while excluding other groups from titration.

• Input: Hen egg-white lysozyme from RCSB PDB 2LZT
• Non-default settings: Restrict to chains = A; Titrate only residues = A:35,A:52

Glu35 has a predicted pKa of 6.52, 2.02 units above its model pKa of 4.50. Asp52 is close to its model value at pKa 3.77 with a shift of -0.03. The contrast supports different modeled microenvironments, but it does not by itself establish a catalytic mechanism or experimental protonation state.

HIV-1 protease with the MK1 ligand

The HIV-1 protease complex shows protein groups from both chains together with supported ionizable atoms in a bound ligand.

• Input: HIV-1 protease with MK1 from RCSB PDB 1HSG, chains A and B
• Non-default setting: Show coupled residues = enabled

The complete result contains 48 groups. Asp25 is predicted at pKa 4.35 in chain A and 7.89 in chain B for this submitted structure. Because the two catalytic Asp25 residues interact across the dimer interface, these values should be examined together with the detailed native report rather than treated as independent, fixed solution states.

The ligand-derived rows report MK1 N3 at pKa 11.23 with atom type N33, and MK1 N5 at pKa 4.16 with atom type NAR. Coupling note is N/A for both rows, so PROPKA did not return an alternative coupling note for these sites even though coupled-residue reporting was enabled.

How PROPKA works

PROPKA starts from the model pKa of each recognized group and estimates an environmental perturbation from the submitted coordinates:

$\text{pKa} = \text{pKa}_{\text{model}} + \Delta\text{pKa}_{\text{environment}}$

Environmental contributions

• Desolvation: Burial removes favorable interaction with water. The effect depends on solvent exposure and depth in the protein.
• Backbone reorganization: Local backbone dipoles can stabilize a buried charge and offset part of the desolvation penalty.
• Hydrogen bonds: Geometry-dependent hydrogen bonds can stabilize one protonation state relative to another.
• Charge interactions: Nearby ionizable groups alter the relative stability of charged and neutral states.

PROPKA 3 replaced the older hard division between surface and buried groups with a continuous treatment of desolvation and dielectric response. In the original PROPKA 3 benchmark, root-mean-square deviations were 0.79 pKa units for Asp/Glu, 0.75 for Tyr, 0.65 for Lys, and 1.00 for His. Those dataset-level values describe benchmark performance, not an uncertainty interval for every row.

Ligands and coupling

PROPKA 3.1 extended the method to supported ionizable ligand groups, inductive interactions within ligands, interactions between multiple ligands, and detection of noncovalently coupled ionizable groups. ProteinIQ preserves the native ligand atom-type and coupling annotations in the result table and .pka report.

Choosing PROPKA or a different calculation

Limitations and structure checks

• Single conformation: PROPKA does not sample conformational dynamics. Alternate structures or side-chain arrangements can change a prediction.
• Input quality: Missing heavy atoms, unresolved side chains, alternate locations, and crystal contacts can distort the local environment.
• Hydrogen handling: The default discards input protons. Keep input protons should be used only when those atoms are deliberately prepared.
• Ligand perception: PDB files do not always encode bond orders unambiguously, and unsupported ligand chemistry may be typed incorrectly or omitted.
• Coupled sites: A single pKa can be an incomplete description when protonation states interact strongly.
• Empirical scope: Accuracy depends on the chemical group and structural environment represented by the parameterization. Unusual cofactors, buried waters, metals, and highly shifted sites merit additional validation.

Structures with missing atoms or incomplete residues should be repaired before the PROPKA run. When protonation choices affect docking, electrostatics, or simulation setup, the prediction should be checked against experimental evidence, alternative structures, or a higher-level pKa calculation.