Protein Isoelectric Point (pI) Calculator

How the pI is computed

• Net charge is the sum of ionizable groups using Henderson–Hasselbalch equations (acidic side chains & C-term vs. basic side chains & N-term).
• pI is the pH where net charge = 0, located via bisection in the range 0–14 with a tight tolerance.
• pKa sets: choose EMBOSS or Bjellqvist; or supply custom values for residues and termini.
• Plot: the mini-curve shows net charge vs. pH (0→14). Values are not smoothed.

Notes & Assumptions

• Scope: Uses free amino acid model (no microenvironment, PTMs, salt, or temperature corrections). Good for quick in-silico estimates.
• Input cleaning: FASTA headers (> lines), whitespace, numbers, and non-standard letters are removed.
• Termini: N- and C-termini are included; override their pKa to model blocked/modified termini.
• Optional stats: Molecular weight and ε₂₈₀ are reported as convenience estimates.

What is the isoelectric point (pI) and why does it matter?

The isoelectric point (pI) of a protein or peptide is the pH at which its net electrical charge is zero. Below the pI, the molecule is overall positively charged; above the pI, it is overall negatively charged. Knowing pI helps you choose appropriate buffers, predict solubility, optimize chromatography and electrophoresis conditions, and understand how a sequence may behave in different environments. In techniques like isoelectric focusing or 2D gel electrophoresis, proteins migrate within a pH gradient until they reach their pI, where net charge becomes zero and movement stops.

How this calculator estimates pI

This tool models ionizable groups using the Henderson–Hasselbalch framework. Each relevant residue side chain (Asp, Glu, Cys, Tyr, His, Lys, Arg) contributes a pH-dependent charge, as do the N-terminus and C-terminus. The app sums all contributions to compute net charge at any pH and then locates the isoelectric point where net charge crosses zero. You can choose between common pKa sets (e.g., EMBOSS or Bjellqvist) or provide custom pKa values to reflect experimental preferences or known modifications. Because everything runs in your browser, your sequences remain private.

Assumptions and real-world caveats

Any pI calculator is an approximation. The local microenvironment in real proteins can shift pKa values: coupling between nearby residues, salt concentration, temperature, ligand binding, and post-translational modifications (PTMs) such as phosphorylation, acetylation, amidation, or disulfide formation can all alter charge states. Likewise, proteins with structured domains versus intrinsically disordered regions may present different effective pKa behavior. This tool uses a uniform, sequence-only model that works well for screening, design, and education, but laboratory measurements (e.g., capillary IEF) are the gold standard for precise values.

Practical tips for using pI in the lab

• Buffer selection: For maximum solubility, work at least 1 pH unit away from the calculated pI to increase net charge and reduce aggregation.
• Purification planning: In ion-exchange chromatography, choose resin type based on charge sign at your working pH (below pI → cation exchange; above pI → anion exchange).
• Electrophoresis & IEF: Use the predicted pI to select narrow pH ranges for sharper focusing and better resolution.
• Design & mutagenesis: Substituting acidic (D/E) or basic (K/R/H) residues will shift pI. Small changes can significantly affect stability and solubility.
• Termini & PTMs: Blocked termini or modifications (e.g., N-acetylation, C-amidation, phosphorylation) change overall charge; adjust pKa values accordingly in the Custom panel.

Peptides vs. proteins

Short peptides are strongly influenced by the termini because they represent a larger fraction of ionizable groups. In large proteins, side-chain composition dominates the pI. If you compare sequences of different lengths, consider both residue counts and termini effects when interpreting results.

Summary: pI is a simple number with wide practical impact. Use it to guide buffer choice, separation methods, and construct design— and remember to validate critical decisions with experimental measurements whenever possible.