The Secret Behind Protein Folding

10 Aug 2025 GS 3 Science & Technology

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The Problem – How Do Proteins Get Their Shape?

Protein folding is the process by which a protein chain — made of amino acids linked like beads on a string — twists, bends, and folds into a specific three-dimensional shape.

The order and type of amino acids decide how the protein folds into its 3D shape.
Shape is crucial — if shape changes, the protein often stops working.

Why it happens

Proteins are made from 20 types of amino acids.
Each amino acid interacts differently with water and with other amino acids (hydrophobic ones hide from water, hydrophilic ones face water).
These interactions, along with chemical bonds, cause the protein to fold into the shape that is most stable in the watery environment of the cell.

Why it is important

Function depends on shape
- A protein’s shape determines what it can do — e.g., bind to another molecule, catalyse a reaction, or provide structure.
- If the folding goes wrong, the protein may not work at all.
Specificity
- The right shape ensures the protein interacts only with its correct targets (like a key fitting into the right lock).
Health implications
- Misfolded proteins can cause diseases such as Alzheimer’s, Parkinson’s, cystic fibrosis, and some cancers.
Biotechnology & Medicine

Understanding folding helps scientists design new proteins for drugs, enzymes, and vaccines.

Big question for decades: How does nature always make proteins fold into the right shape?

About 70% of the cell is made of water, the way the amino acids are arranged and how that arrangement interacts with water molecules is pivotal to how they fold

Kauzmann’s 1959 Idea

Amino acids behave differently with water:
- Hydrophilic (water-loving) → mix easily with water (e.g., lysine).
- Hydrophobic (water-hating) → avoid water, clump together (e.g., tryptophan).
Since the cell is ~70% water, proteins fold so that:
- Hydrophobic amino acids hide inside (core).
- Hydrophilic amino acids stay outside (surface).
This “hydrophobic core” idea was later proved correct with X-ray crystallography in the 1960s–70s.

Old Belief – Protein Cores Are Extremely Sensitive

The core amino acids were thought to be very sensitive to changes.
Even small changes → protein misfolds → doesn’t work.
Reason: Many core sequences are almost identical in different species → assumed changes were deadly.
But this made scientists wonder — if most combinations don’t work, how did evolution manage to find working ones among so many possibilities?

The Numbers Problem

For just a 60–amino-acid core: ~10⁷⁸ possible combinations.
That’s roughly equal to the number of atoms in the universe.
Yet nature found functional protein shapes for millions of different proteins.
How was this possible if cores were so fragile?

New Study (2025)

Institutions: Centre for Genomic Regulation (Spain) + Wellcome Sanger Institute (UK).
only tested a tiny fraction of possible changes earlier — and often changed just one part of the core without allowing other areas to adjust.
Method:
- Made 78,125 combinations of amino acids at 7 locations in the cores of 3 proteins:
  1. SH3 domain of human FYN tyrosine kinase
  2. CI-2A protein from barley
  3. CspA from E. coli bacterium
- Tested which combinations stayed stable (kept proper shape).

Key Findings

Most combinations are unstable.
But several thousand stayed stable.
SH3-FYN (human) → over 12,000 stable core shapes possible.
Conclusion: Protein cores are more tolerant to change than we thought.

Machine Learning Role

Fed the experimental data into a machine-learning algorithm.
Goal: Predict protein stability from sequence alone.
Tested on 51,159 natural SH3 sequences from all life forms in databases.
Result: Could accurately predict stability even when sequences were <25% similar to the human SH3 version.

Why This Matters

1. For Medicine & Protein Engineering

Many therapeutic proteins cause immune reactions in patients.
Earlier → Changing core amino acids was avoided for fear of instability → changes were slow, small.
Now → We can safely try bigger sequence changes and screen more combinations faster.
Could design safer, more effective proteins quickly.

2. For Evolutionary Biology

Shows evolution had more flexibility than we assumed.
Nature didn’t have to “luck out” in a tiny space — there were many possible stable solutions.
Suggests life is more adaptable at the molecular level than we imagined.

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