Photophysical Properties of Ruthenium(II) Polypyridyl DNA Intercalators: Effects of the Molecular Surroundings Investigated by Theory

The environmental effects on the structural and photophysical properties of [Ru(L)₂(dppz)]²⁺ complexes (L=bpy=2,2′‐bipyridine, phen=1,10‐phenanthroline, tap=1,4,5,8‐tetraazaphenanthrene; dppz=dipyrido[3,3‐a:2′,3′‐c]phenazine), used as DNA intercalators, have been studied by means of DFT, time‐dependent DFT, and quantum mechanics/molecular mechanics calculations. The electronic characteristics of the low‐lying triplet excited states in water, acetonitrile, and DNA have been investigated to decipher the influence of the environment on the luminescent behavior of this class of molecules. The lowest triplet intra‐ligand (IL) excited state calculated at λ≈800 nm for the three complexes and localized on the dppz ligand is not very sensitive to the environment and is available for electron transfer from a guanine nucleobase. Whereas the lowest triplet metal‐to‐ligand charge‐transfer (³MLCT) states remain localized on the ancillary ligand (tap) in [Ru(tap)₂(dppz)]²⁺, regardless of the environment, their character is drastically modified in the other complexes [Ru(phen)₂(dppz)]²⁺ and [Ru(bpy)₂(dppz)]²⁺ upon going from acetonitrile (MLCT_dppz/phen or MLCT_dppz/bpy) to water (MLCT_dppz) and DNA (MLCT_phen and MLCT_bpy). The change in the character of the low‐lying ³MLCT states accompanying nuclear relaxation in the excited state controls the emissive properties of the complexes in water, acetonitrile, and DNA. The light‐switching effect has been rationalized on the basis of environment‐induced control of the electronic density distributed in the lowest triplet excited states.     

A simple and effective metaheuristic for the Minimum Latency Problem

The Minimum Latency Problem (MLP) is a variant of the Traveling Salesman Problem which aims to minimize the sum of arrival times at vertices. The problem arises in a number of practical applications such as logistics for relief supply, scheduling and data retrieval in computer networks. This paper introduces a simple metaheuristic for the MLP, based on a greedy randomized approach for solution construction and iterated variable neighborhood descent with random neighborhood ordering for solution improvement. Extensive computational experiments on nine sets of benchmark instances involving up to 1000 customers demonstrate the good performance of the method, which yields solutions of higher quality in less computational time when compared to the current best approaches from the literature. Optimal solutions, known for problems with up to 50 customers, are also systematically obtained in a fraction of seconds.