Abstract
Discovering the low-energy conformations of a molecule is of great interest to computational chemists, with applications in in silico materials design and drug discovery. In this paper, we propose a variable neighbourhood search heuristic for the conformational search problem. Using the structure of a molecule, neighbourhoods are chosen to allow for the efficient use of a binary quadratic optimizer for conformational search. The method is flexible with respect to the choice of molecular force field and the number of discretization levels in the search space, and can be further generalized to take advantage of higher-order binary polynomial optimizers. It is well-suited for the use of devices such as quantum annealers. After carefully defining neighbourhoods, the method easily adapts to the size and topology of these devices, allowing for seamless scaling alongside their future improvements.
Highlights
In medicinal chemistry, conformational analysis often involves identifying bioactive conformations of ligand molecules[1,2]
We present the results achieved by performing a local search heuristic (LS), and a hybrid of the two methods (LS–variable neighbourhood descent (VND)) in which a random conformation is first optimized using LS and passed to VND for further optimization
We present the VND results with the quantum annealer used as the underlying quadratic unconstrained binary optimization (QUBO) problem solver
Summary
Conformational analysis often involves identifying bioactive conformations of ligand molecules[1,2]. The geometrical differences between conformations result in different values for the molecular potential energy[5,6,7], which is a key factor for molecular stability and reactivity To this end, the problem of finding the conformations associated with the local minima of the potential energy surface (PES) of the molecule, referred to as the conformational search problem, has been of long-standing interest. One may be able to deterministically solve the conformational search problem via techniques such as branch and bound[12,13,14] This is impractical for even moderately sized molecules, as the size of the conformational search space grows exponentially with the number of rotatable bonds[15]. Our motivation was to develop such a formulation for the conformational search problem that avoids drastic compromises while producing good conformers
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