Discrete Optimization of Electronic Hyperpolarizabilities in a Chemical Subspace.

We introduce a general optimization algorithm based on an interpolation of property values on a hypercube. Each vertex of the hypercube represents a molecule, while the interior of the interpolation represents a virtual superposition ("alchemical" mutation) of molecules. The resultant algorithm is similar to branch-and-bound/tree-search methods. We apply the algorithm to the optimization of the first electronic hyperpolarizability for several tolane libraries. The search includes structural and conformational information. Geometries were optimized using the AM1 Hamiltonian, and first hyperpolarizabilities were computed using the INDO/S method. Even for small libraries, a significant improvement of the hyperpolarizability, up to a factor of ca. 4, was achieved. The algorithm was validated for efficiency and reproduced known experimental results. The algorithm converges to a local optimum at a computational cost on the order of the logarithm of the library size, making large libraries accessible. For larger libraries, the improvement was accomplished by performing electronic structure calculations on less than 0.01% of the compounds in the larger libraries. Alternation of electron donating and accepting groups in the tolane scaffold was found to produce candidates with large hyperpolarizabilities consistently.