From Static to Dynamic: The Future of Protein Modelling

The Static Problem

AlphaFold2 revolutionized structural biology—but it shows us only one frozen moment. Proteins are dynamic machines, constantly breathing and moving.

What Static Models Miss

• Conformational diversity across states
• Allosteric communication pathways
• Mutation-induced flexibility changes

Dynamic Modelling Captures

• Ensemble of biologically relevant states
• Cryptic binding pockets
• Functional motion mechanisms

Figure: ReFOLD4 protocol refining static predictions into dynamic ensembles

The Vision

Transform protein structure prediction from static snapshots to dynamic movies. By integrating AI with Molecular Dynamics, we capture the breathing motions essential for understanding mutations, de novo designs, and drug resistance.

Figure: End-to-end pipeline for dynamic protein modelling

Impact

10x

Better mutation modeling

100+

Conformational states captured

∞

Possibilities for drug discovery