The Use of Quantum Molecular Calculations to Guide a Genetic Algorithm: A Way to Search for New Chemistry

AbstractThe process of gene‐based molecular evolution has been simulated in silico by using massively parallel density functional theory quantum calculations, coupled with a genetic algorithm, to test for fitness with respect to a target chemical reaction in populations of genetically encoded molecules. The goal of this study was the identification of transition‐metal complexes capable of mediating a known reaction, namely the cleavage of N2 to give the metal nitride. Each complex within the search space was uniquely specified by a nanogene consisting of an eight‐digit number. Propagation of an individual nanogene into successive generations was determined by the fitness of its phenotypic molecule to perform the target reaction and new generations were created by recombination and mutation of surviving nanogenes. In its simplest implementation, the quantum‐directed genetic algorithm (QDGA) quickly located a local minimum on the evolutionary fitness hypersurface, but proved incapable of progressing towards the global minimum. A strategy for progressing beyond local minima consistent with the Darwinian paradigm by the use of environmental variations coupled with mass extinctions was