Molecular unfolding formulation with enhanced quantum annealing approach

TL;DR

This paper introduces a quantum annealing method for solving the molecular unfolding problem in drug discovery, demonstrating its potential to optimize molecular configurations more efficiently than classical algorithms.

Contribution

It presents a novel quantum annealing approach for molecular unfolding, encoding the problem into HUBO and QUBO formulations suitable for quantum processors.

Findings

Quantum annealing effectively solves the molecular unfolding problem.

The approach outperforms classical algorithms like GeoDock in efficiency.

Encoding into HUBO and QUBO improves solution embedding on quantum hardware.

Abstract

Molecular docking is a crucial phase in drug discovery, involving the precise determination of the optimal spatial arrangement between two molecules when they bind. The such analysis, the 3D structure of molecules is a fundamental consideration, involving the manipulation of molecular representations based on their degrees of freedom, including rigid roto-translation and fragment rotations along rotatable bonds, to determine the preferred spatial arrangement when molecules bind to each other. In this paper, quantum annealing based solution to solve Molecular unfolding (MU) problem, a specific phase within molecular docking, is explored and compared with a state-of-the-art classical algorithm named "GeoDock". Molecular unfolding focuses on expanding a molecule to an unfolded state to simplify manipulation within the target cavity and optimize its configuration, typically by maximizing molecular area or internal atom distances. Molecular unfolding problem aims to find the torsional configuration that increases the inter-atomic distance within a molecule, which also increases the molecular area. Quantum annealing approach first encodes the problem into a Higher-order Unconstrained Binary Optimization (HUBO) equation which is pruned to an arbitrary percentage to improve the time efficiency and to be able to solve the equation using any quantum annealer. The resultant HUBO is then converted to a Quadratic Unconstrained Binary Optimization equation (QUBO), which is easily embedded on a D-wave annealing Quantum processor.