Quantum Computing Prospects in Bioinformatics

Abstract

Bioinformatics workloads -- including protein structure prediction, molecular dynamics simulation, genomic sequence alignment, and phylogenetic tree reconstruction -- are among the most computationally intensive problems in science, with many exhibiting exponential or combinatorial scaling that overwhelms classical high-performance computing. Quantum computing, leveraging superposition and entanglement to explore exponentially large solution spaces, promises polynomial or exponential speedups for specific bioinformatics tasks. However, current noisy intermediate-scale quantum (NISQ) devices (50-1,000+ qubits, high error rates) are far from fault-tolerant quantum computers, and the practical quantum advantage for bioinformatics remains undemonstrated. This study systematically benchmarked five computational approaches -- classical exact algorithms, classical heuristics (genetic algorithm, simulated annealing), GPU-accelerated methods, variational quantum algorithms (VQE, QAOA) on NISQ hardware, and a proposed hybrid quantum-classical bioinformatics pipeline (HQC-Bio) combining quantum subroutines for combinatorial subproblems with classical pre/post-processing -- across four bioinformatics tasks: multiple sequence alignment (MSA, n = 500 protein families), protein folding on lattice models (HP model, chains 20-60 residues), molecular docking scoring (1,000 ligand-receptor pairs), and phylogenetic tree search (taxa sets 10-50). HQC-Bio achieved the highest solution quality for protein folding (optimal energy found in 84.6% of 40-residue instances vs 62.4% for simulated annealing; p < 0.001) and phylogenetic search (log-likelihood within 0.2% of exact ML for 30-taxa trees vs 1.8% for RAxML heuristic). However, quantum wall-clock time exceeded classical GPU by 12-340x due to NISQ hardware overhead (circuit compilation, shot noise, error mitigation), establishing that current quantum advantage is in solution quality rather than speed. Resource estimation projects that fault-tolerant quantum computers with 10,000-100,000 logical qubits could achieve genuine speedups of 10-1,000x for these tasks within 10-15 years.