Mohammad Hassan Khatami, Udson C. Mendes, Nathan Wiebe, Philip M. Kim.
Abstract
Protein design is a technique to engineer proteins by permuting amino acids in the sequence to obtain novel functionalities. However, exploring all possible combinations of amino acids is generally impossible due to the exponential growth of possibilities with the number of designable sites. The present work introduces circuits implementing a pure quantum approach, Grover’s algorithm, to solve protein design problems. Our algorithms can adjust to implement any custom pair-wise energy tables and protein structure models.
Introduction:
Protein design is a procedure to construct proteins with certain configurations to achieve novel functionality. In this regard, amino acids are mutated in the protein’s sequence to find sets of residues that provide the lowest energy of the protein in the expected configuration.
Methods:
System setup & simulations
Following the Grover’s algorithm, after the initialization, the oracle is programmed to implement energies and conduct required calculations to find and mark the answer states. The oracle has different sub-steps associated with it.
Real quantum devices and noise-containing simulators
The quantum circuits in this work are composed of several single-qubit and multi-qubit (including two or more qubits) gates. Generally, several single-qubit and multi-qubit gates with low complexities are predefined in quantum computer simulators (details vary by simulator packages).
Discussion:
This work studies developing gate-based circuits to address protein design problems by implementing a pure quantum computing algorithm, i.e., Grover’s algorithm. Using ideal quantum computer simulators shows that our quantum circuits can find the M desired answer states among N total states for systems with different complexities.
Acknowledgments:
The authors would like to thank WestGrid (www.westgrid.ca) and Compute Canada (www.computecanada.ca) for providing computational resources for this project.
We acknowledge the use of IBM Quantum services for this work. The views expressed are those of the authors, and do not reflect the official policy or position of IBM or the IBM Quantum team.
We also would like to acknowledge CMC Microsystems for facilitating this research, specifically through their member access to the IBM Quantum Hub at Institut quantique.
Citation: Khatami MH, Mendes UC, Wiebe N, Kim PM (2023) Gate-based quantum computing for protein design. PLoS Comput Biol 19(4): e1011033. https://doi.org/10.1371/journal.pcbi.1011033
Editor: Nir Ben-Tal, Tel Aviv University, ISRAEL
Received: November 22, 2022; Accepted: March 17, 2023; Published: April 12, 2023.
Copyright: © 2023 Khatami et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information file. The codes to create the circuits in the MR and SP models in this study are available on Zenodo at https://zenodo.org/record/7344649 and are available on GitHub at https://github.com/Mohammad-Khatami/grover-protein-desing.
Funding: PMK received a Canadian Institutes of Health Research (CIHR) grant PJT-159750, which supported this project. (https://cihr-irsc.gc.ca) MHK's salary was partially funded by Canadian Institutes of Health Research (CIHR) grant PJT-159750. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: UCM is the leader of the quantum computing team at CMC Microsystems. PMK is a co-founder and consultant to multiple companies, including Oracle Therapeutics and TBG Therapeutics, and serves on the scientific advisory board of ProteinQure. MHK and NW declare no Competing Financial or Non-Financial Interests.
