Configure inputs to begin
Set options on the left, then click “Generate Profile”.

Plot net charge vs pH for protein sequences. Visualize how protein charge changes across pH 0-14 and identify the isoelectric point (pI) where the net charge crosses zero.

Generate Kyte-Doolittle hydropathy plots to visualize hydrophobic and hydrophilic regions along protein sequences. Identify transmembrane domains and surface-exposed regions.

Generate hydrophobicity plots using 24 different amino acid scales. Visualize hydrophobic and hydrophilic regions for protein analysis, epitope prediction, and membrane protein studies.

Faithful static-mode Aggrescan3D tool for per-residue aggregation propensity analysis from a single protein structure.

Match experimental peptide masses against theoretical digest fragments of a protein sequence. Identify peptides from mass spectrometry data by peptide mass fingerprinting.

Predict protease and chemical cleavage sites across a protein sequence for up to 39 enzymes simultaneously. Identify where each enzyme cuts, the cleavage residue, and context window around each site.

Cleave a protein sequence with a chosen protease and compute the masses of the resulting peptides. Supports multiple enzymes, missed cleavages, chemical modifications, and different ion types for mass spectrometry experiment planning.

Predict pKa values of ionizable groups in proteins and protein-ligand complexes from 3D structure. PROPKA calculates environment-driven pKa shifts for standard ionizable residues, terminal groups, and supported ligand atom types.

Calculate protein parameters, including molecular weight, theoretical pI, extinction coefficients, aromaticity, secondary structure fractions, atomic composition, estimated half-life, and several indices, including instability, aliphatic index, and GRAVY.

Isoelectric Point Calculator 2.0 - Predict protein/peptide isoelectric point (pI) using 18+ validated pKa scales, SVR models, and deep learning. Supports proteins, peptides, and comprehensive analysis.
Protein Scale Profiler generates amino acid property profiles along a protein sequence using a sliding window average. It provides 42 different physicochemical scales spanning hydrophobicity, secondary structure propensity, flexibility, polarity, surface accessibility, antigenicity, charge, bulkiness, mutability, and residue composition — making it one of the most comprehensive amino acid scale tools available for sequence analysis.
Unlike single-purpose tools, Protein Scale Profiler unifies all major amino acid property scales in one interface. Scales can be switched instantly to compare different properties for the same sequence without re-entering data.
Each scale assigns a numeric value to every amino acid based on experimentally measured or statistically derived properties. A sliding window moves along the sequence, averaging the values at each position to reveal regional trends.
For a window of size centered at position , the smoothed value is:
where is the scale value for the amino acid at position . At sequence termini, the window is truncated and the average is computed over the available residues.
Smaller windows (5-7) retain local fluctuations useful for identifying individual residue effects. Larger windows (15-21) emphasize extended domains such as transmembrane helices or disordered regions.
The largest category, covering a range of experimental approaches:
Additional HPLC and partition-based scales include Wilson, Meek, Parker, Cowan-Whittaker (pH 3.4 and 7.5), Abraham-Leo, Roseman, Bull-Breese, Black-Mould, OMH Sweet-Eisenberg, Aboderin, and Manavalan-Ponnuswamy.
Sliding window: Controls the number of residues averaged at each position. The default value of 9 works well for most analyses. Use 5-7 for fine-grained local properties. Use 15-21 for detecting extended domains like transmembrane helices. Only odd numbers are accepted.
Property scale: Select the scale that matches your analysis objective. Refer to the scale selection guide below for recommendations.
The interactive chart plots the smoothed property values against sequence position. Hover over any point to see the exact position, residue identity (three-letter code), and calculated value.
A reference line at zero helps distinguish positive and negative regions. For most hydrophobicity scales, positive peaks indicate hydrophobic segments and negative valleys indicate hydrophilic segments. For inverted scales like Hopp-Woods, the convention is reversed.
The sidebar displays the selected scale name, category, a brief description, the per-amino-acid values sorted from highest to lowest, and the original literature reference.
Download results as CSV for further analysis in spreadsheet software or statistical packages. Export the chart as PNG or SVG for publication-quality figures.
| Analysis goal | Recommended scales | Window size |
|---|---|---|
| Transmembrane helix prediction | Eisenberg, Janin, Guy, Rao-Argos | 19 |
| Epitope prediction | Hopp-Woods, Kolaskar-Tongaonkar, Emini Surface | 7-9 |
| Surface accessibility | Emini Surface, Janin Surface | 9 |
| Secondary structure tendency | Chou-Fasman Helix/Sheet/Turn, Deleage-Roux Coil | 7-9 |
| Flexible/disordered regions | Karplus-Schulz | 7-9 |
| Charge distribution | Net Charge at pH 7.0 | 5-9 |
| General hydrophobicity | Eisenberg, Fauchere-Pliska | 9 |
| Evolutionary conservation | Dayhoff Relative Mutability | 9-11 |
Sliding window profiles assume that local sequence composition determines local properties. They do not account for three-dimensional structure, long-range interactions, post-translational modifications, or the influence of neighboring chains.
For dedicated transmembrane topology prediction, consider specialized tools that incorporate evolutionary profiles and hidden Markov models. For secondary structure prediction beyond Chou-Fasman propensities, tools like DSSP use actual 3D structure assignments.