Gate-based quantum computing for protein design

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. Moreover, the algorithm’s oracle is designed to consist of only adder functions. Quantum computer simulators validate the practicality of our circuits, containing up to 234 qubits. However, a smaller circuit is implemented on real quantum devices. Our results show that using O(N) iterations, the circuits find the correct results among all N possibilities, providing the expected quadratic speed up of Grover’s algorithm over classical methods (i.e., O(N)).Author summary: Protein design aims to create novel proteins or enhance the functionality of existing proteins by tweaking their sequences through permuting amino acids. The number of possible configurations, N, grows exponentially as a function of the number of designable sites (s), i.e., N = As, where A is the number of different amino acids (A = 20 for canonical amino acids). The classical computation methods require O(N)) queries to search and find the low-energy configurations among N possible sequences. Searching among these possibilities becomes unattainable for large proteins, forcing the classical approaches to use sampling methods. Alternatively, quantum computing can promise quadratic speed-up in searching for answers in an unorganized list by employing Grover’s algorithm. Our work shows the implementation of this algorithm at the circuit level to solve protein design problems. We first focus on lattice model-like systems and then improve them to more realistic models (change in the energy as a function of distances). Our algorithms can implement various custom pair-wise energy tables and any protein structure models. We have used quantum computer simulators to validate the practicality of our circuits which require up to 234 qubits. We have also implemented a simple version of our circuits on real quantum devices. Our results show that our circuits provide the expected quadratic speed-up of Grover’s algorithm.