Instability Index

What is the instability index?

The instability index (II) predicts whether a protein will be stable in a test tube based on its amino acid sequence. Developed by Guruprasad and colleagues in 1990, it remains one of the most widely used sequence-based stability predictors in protein science.

The method works by analyzing dipeptide patterns—pairs of consecutive amino acids—that occur more frequently in unstable proteins. A low instability index suggests the protein will remain intact during expression, purification, and storage. A high value warns that the protein may degrade quickly.

For a comprehensive analysis that includes instability index along with molecular weight, pI, and other properties, use our Protein Parameters calculator.

How does the instability index work?

The calculation assigns a weight value to each of the 400 possible dipeptide combinations based on how often they appear in unstable versus stable proteins. These weights are called Dipeptide Instability Weight Values (DIWV).

The formula

The instability index is computed as:

$$II = \frac{10}{L} \sum_{i=1}^{L-1} DIWV(x_i x_{i+1})$$

Where $L$ is the sequence length and $DIWV(x_i x_{i+1})$ is the instability weight for the dipeptide at position $i$.

Dipeptide weights

The DIWV values were derived from statistical analysis of 12 unstable and 32 stable proteins. Dipeptides that appeared significantly more often in unstable proteins received higher weight values.

Some dipeptides strongly destabilize proteins (high DIWV), while others are neutral or stabilizing (low or negative DIWV). The sum of all dipeptide contributions, normalized by sequence length, produces the final index.

Understanding the results

The output table shows one row per input sequence with columns for protein ID, sequence length, and instability index.

The threshold of 40 separates stable from unstable predictions:

• II < 40: Protein is predicted to be stable in vitro
• II ≥ 40: Protein may be unstable with a short half-life

Most well-folded globular proteins have instability indices between 20 and 40. Values below 20 suggest very stable proteins, while values above 50 indicate likely degradation issues.

Input requirements

• Protein sequences: Enter one or more sequences in FASTA format
• Supports batch processing of multiple sequences
• Accepts .fasta, .fa, .fas, .pdb, .csv, and .txt file uploads
• Can fetch sequences directly from RCSB PDB

Use cases

The instability index helps guide protein production and engineering decisions:

• Expression screening: Prioritize protein variants predicted to be stable for recombinant production
• Mutation analysis: Compare wild-type and mutant proteins to identify destabilizing substitutions
• Protein engineering: Guide design of stabilizing mutations by tracking II changes
• Shelf-life prediction: Estimate whether purified proteins will remain stable during storage

Limitations

The instability index was developed from a small dataset (44 proteins) and is based on in vivo stability data. Keep these limitations in mind:

• In vitro conditions differ from the cellular environment where the training data originated
• Buffer composition, pH, temperature, and additives affect actual stability but are not captured by the index
• The method cannot account for post-translational modifications or cofactor binding
• Very short sequences may give unreliable predictions due to limited dipeptide sampling

We recommend using the instability index as one factor among several when evaluating protein stability. Experimental validation remains essential for critical applications.

Related tools

• Protein Parameters — Calculates instability index along with molecular weight, pI, GRAVY, extinction coefficient, and aliphatic index
• Aliphatic Index — Predicts thermostability from aliphatic amino acid content
• GRAVY — Quantifies hydrophobicity, which influences folding and solubility
• Protein Stability — Machine learning-based stability prediction using ESM embeddings
• Amino Acid Composition — View the full amino acid breakdown that underlies stability predictions

Based on: Guruprasad K, Reddy BV, Pandit MW (1990). Correlation between stability of a protein and its dipeptide composition: a novel approach for predicting in vivo stability of a protein from its primary sequence. Protein Engineering, 4(2):155-61.