# A little walk from physical to biological complexity: protein folding and stability

## TL;DR

This paper explores how physics principles help understand protein folding and stability, and how this knowledge can be used to study diseases.

## Contribution

The paper introduces thermodynamics-based tools for predicting protein stability and resistance to amino acid changes.

## Key findings

- Statistical potentials derived from experimental structures predict protein stability.
- These methods help understand protein aggregation in neuronal diseases.
- Inverse Boltzmann law is used to develop knowledge-driven bioinformatics tools.

## Abstract

As an example of topic where biology and physics meet, we present the issue of protein folding and stability, and the development of thermodynamics-based bioinformatics tools that predict the stability and thermal resistance of proteins and the change of these quantities upon amino acid substitutions. These methods are based on knowledge-driven statistical potentials, derived from experimental protein structures using the inverse Boltzmann law. We also describe an application of these predictors, which contributed to the understanding of the mechanisms of aggregation of a particular protein known to cause a neuronal disease.