# Energy Landscape and Kinetic Analysis of Molecular Dynamics Simulations for Intrinsically Disordered Proteins

## TL;DR

This paper introduces a method to analyze molecular dynamics simulations of disordered proteins by mapping their energy landscapes and kinetic behavior.

## Contribution

A modular framework combining DRIDmetric and freenet for energy landscape and kinetic analysis of IDPs is presented.

## Key findings

- The workflow computes free energy surfaces and transition state barriers from MD simulations.
- The method is demonstrated on Alzheimer’s amyloid-β peptide simulations in physiological environments.
- The approach provides interpretable thermodynamic and kinetic insights for intrinsically disordered proteins.

## Abstract

Understanding the
conformational dynamics of biomolecules
requires
methods that go beyond structural sampling and provide a quantitative
description of thermodynamics and kinetics. For intrinsically disordered
proteins (IDPs), energy landscape characterization is particularly
crucial to unravel their complex conformational behavior. Here, we
present a comprehensive protocol for analyzing molecular dynamics
(MD) simulations in terms of energy landscapes, metastable states,
and transition pathways. Our approach is based on the distribution
of reciprocal interatomic distances (DRID) for dimensionality reduction,
followed by clustering and kinetic modeling. Free energy surfaces
and transition state barriers are computed directly from the simulation
data and visualized using disconnectivity graphs. The method integrates
two Python packages, DRIDmetric and freenet, with standard energy landscape tools based on
kinetic transition networks, including PATHSAMPLE and disconnectionDPS. We demonstrate this
workflow for simulations of the intrinsically disordered, aggregation-prone
Alzheimer’s amyloid-β peptide in physiologically relevant
environments. This modular framework offers a robust and interpretable
way to extract thermodynamic and kinetic insights from MD data and
is especially valuable for characterizing the diverse conformational
states of IDPs.