QuPepFold: A Quantum Simulator for Peptide Folding QuPepFold is a command-line tool leveraging the power of quantum computing, built on the Qiskit framework, to simulate the folding of short peptides (2–10 amino acids). This innovative simulator explores the conformational landscape of peptides by employing quantum algorithms. Given a protein sequence, QuPepFold performs the following key steps: Quantum Encoding of Conformational Space: It generates a turn-to-qubit mapping, effectively translating the degrees of freedom associated with peptide folding into the quantum realm. Energy Landscape Modeling: It constructs a Miyazawa–Jernigan interaction matrix directly from the input amino acid sequence, capturing the energy preferences between different residues. Variational Quantum Ansatz: QuPepFold defines a parameterized quantum circuit (ansatz) composed of single-qubit rotations and entangling CX gates. This circuit is designed to explore the possible folded states of the peptide. Quantum Optimization for Ground State: It employs a CVaR (Conditional Value at Risk)-based Variational Quantum Eigensolver (VQE) to find the minimum energy conformation. The optimization is performed using SciPy's COBYLA algorithm. Users can configure the number of quantum measurements (shot count, default: 1024) and the maximum number of optimization steps (iteration limit, default: 50). Comprehensive Output: Upon completion, QuPepFold provides the following insightful results: A concise text summary detailing the minimum calculated CVaR energy and the corresponding qubit configuration representing the predicted fold. A visual representation of the optimized quantum circuit as a PNG image. A convergence scatter plot illustrating how the CVaR energy evolves across the optimization iterations. A histogram highlighting the bitstrings (representing different conformations) with a significant probability (≥2%). All output files are conveniently saved within a user-specified directory, with ./results as the default location. Under the hood, QuPepFold harnesses the speed and efficiency of the Qiskit Aer simulator for local quantum computations and utilizes Matplotlib for generating informative visualizations. The utils installed automatically are typing-extensions, stevedore, rustworkx, psutil, dill, qiskit, qiskit-aer. Please install pylatexenc via (pip3 install pylatexenc) for plots. This tool offers a powerful platform for researchers to explore the application of near-term quantum computing to the fundamental problem of peptide folding.

Our previously published research works: Akshay Uttarkar, Vidya Niranjan (2024). Quantum synergy in peptide folding: A comparative study of CVaR-variational quantum eigensolver and molecular dynamics simulation. International Journal of Biological Macromolecules. Volume 273, Part 1, 2024, 133033, ISSN 0141-8130, https://doi.org/10.1016/j.ijbiomac.2024.133033 Uttarkar, A., Niranjan, V. A comparative insight into peptide folding with quantum CVaR-VQE algorithm, MD simulations and structural alphabet analysis. Quantum Inf Process 23, 48 (2024). https://doi.org/10.1007/s11128-024-04261-9 A. Uttarkar, A. S. Setlur and V. Niranjan, "T-Gate Enabled Fault-Tolerant Ansatz Circuit Design for Variational Quantum Algorithms in Peptide Folding on Aria-1," 2024 International Conference on Artificial Intelligence and Emerging Technology (Global AI Summit), Greater Noida, India, 2024, pp. 1271-1276, doi: 10.1109/GlobalAISummit62156.2024.10947993 A. Uttarkar and V. Niranjan, "Quantum Enabled Protein Folding of Disordered Regions in Ubiquitin C Via Error Mitigated VQE Benchamrked on Tensor Network Simulator and Aria 1," in IEEE Transactions on Molecular, Biological, and Multi-Scale Communications, doi: 10.1109/TMBMC.2025.3600516