Protein Folding Simulations on a Quantum Computer

This project explores the potential of quantum computing to address the complex problem of protein folding, a fundamental challenge in computational biology. Leveraging the capabilities of Qiskit’s protein folding module, we formulate the task as a combinatorial optimization problem, preserving critical topological constraints and hydrophobic-polar (HP) interactions.

We employ tetrahedral lattice encoding schemes to model realistic spatial configurations of proteins. Using Variational Quantum Algorithms (VQAs), we experiment with different ansatz designs and classical optimizers to benchmark their effect on energy minimization and convergence efficiency.

To ensure the scientific reliability of the approach, the quantum simulations are validated against classical results produced by GROMACS, a state-of-the-art molecular dynamics package. This hybrid quantum-classical setup provides valuable insights into the applicability of quantum resources to real-world biological systems and opens promising directions for future research in quantum bioinformatics.