Metadata-Version: 2.4
Name: qupepfold
Version: 0.8.0
Summary: QuPepFold: Quantum peptide folding simulations with Qiskit
Home-page: http://vidyaniranjan.co.in/?i=1
Author: Akshay Uttarkar, Vinay Kumar, Vidya Niranjan
Author-email: Akshay Uttarkar <akshayuttarkar@gmail.com>
License: MIT
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Quantum Computing
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: qiskit>=0.39
Requires-Dist: qiskit-aer
Requires-Dist: numpy
Requires-Dist: matplotlib
Requires-Dist: scipy
Dynamic: author
Dynamic: home-page
Dynamic: requires-python

# QuPepFold

QupepFold is a small, research-oriented toolkit that turns short amino-acid sequences into quantum bitstring encodings, optimizes them with a CVaR-VQE routine, and exports 3D PDB files (with CONECT records) for high-probability folds. It’s built to be easy to run, easy to inspect, and easy to tweak.

## Installation and easy way to use in CLI

pip3 install qupepfold
pip3 install pylatexenc

qupepfold --seq APRLFHG --tries 30 --alpha 0.025 --write-csv --out ./results

### What to expect in output in terminal

Qubit mapping (config/interaction/ancilla counts)
Best CVaR energy
Most probable bitstring (with probability)
Lowest-energy bitstring (with energy)

### Results in the output folder

1. output_summary.txt — quick result summary
2. optimal_circuit.png — ansatz diagram (no measurements)
2. cvar_scatter.png — CVaR value per multi-start iteration
2. bitstring_histogram.png — bar chart for states ≥ threshol
3. bitstring_summary.csv — [bitstring, cfg_bits, probability, energy, exported_PDB3D]
4. bitstring_summary_cvar.csv — same distribution (kept for continuity)
5. most_negative_energy_breakdown.png + .csv — component energies (backbone/MJ/distance/locality) for the lowest energy state
6. pdb3d/*.pdb — one PDB per exported bitstring, with CONECT bonds
7. pdb3d_bitstrings_ge_2pct.zip — bundle of those PDBs

### Uninstall

pip3 uninstall qupepfold





