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A comparative insight into peptide folding with quantum CVaR-VQE algorithm, MD simulations and structural alphabet analysis

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Abstract

Quantum computing in biology is one of the most rapidly evolving fields of technology. Protein folding is one of the key challenges which requires accurate and efficient algorithms with a quick computational time. Structural conformations of proteins with disordered regions need colossal amount of computational resource to map its least energy conformation state. In this regard, quantum algorithms like variational quantum eigensolver (VQE) are applied in the current research work to predict the lowest energy value of 50 peptides of seven amino acids each. VQE is initially used to calculate the energy values over which variational quantum optimization is applied via conditional value at risk (CVaR) over 100 iterations of 500,000 shots each to obtain least ground-state energy value. This is compared to the molecular dynamics-based simulations of 50 ns each to calculate the energy values along with the folding pattern. The results suggest efficient folding outcomes from CVaR-VQE compared to MD-based simulations and HMM-SA. With the ever-expanding quantum hardware and improving algorithms, the problem of protein folding can be resolved to obtain in-depth insights on the biological process and drug design.

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Acknowledgements

The authors thank Department of Computer Science and Engineering, the R V College of Engineering, Bangalore, for providing GPU (NVIDIA A100) computational support. The authors thank the support of Dr. Venugopal K, from the Department of Mathematics. A heartfelt thanks to Suman A for her unconditional support. A warm heartfelt thanks to the staff and administration at the R V College of Engineering for their support.

Funding

This research work was funded by Ministry of Electronics and Information Technology under the Meity QCaL Cohort-II which provides the access to Amazon Braket.

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  1. Department of Biotechnology, R V College of Engineering, (Affiliated to Visvesvaraya Technological University, Belagavi-590018), Bangalore, 560059, India

    Akshay Uttarkar & Vidya Niranjan

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  1. Akshay Uttarkar
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  2. Vidya Niranjan
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VN was in for ideation and conceptualization. AU contributed to the computational analysis and drafting the manuscript. Both the authors have read and agreed to the published version of the manuscript.

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Correspondence to Vidya Niranjan.

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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

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