The urge to discover selective fluorescent binders to G-quadruplexes (G4s) for rapid diagnosis must be linked to understand the effect that those have on the DNA photophysics. Herein, we report on the electronic excited states of a bound merocyanine dye to c-Myc G4 using extensive multiscale quantum mechanics/molecular mechanics calculations. We find that the absorption spectra of c-Myc G4, both without and with the intercalated dye, are mainly composed of exciton states and mixed local/charge-transfer states. The presence of merocyanine hardly affects the energy range of the guanine absorption or the number of guanines excited. However, it triggers a substantial amount (16%) of detrimental pure charge-transfer states involving oxidized guanines. We identify the rigidity introduced by the probe in G4, reducing the overlap among guanines, as the one responsible for the changes in the exciton and charge-transfer states, ultimately leading to a redshift of the absorption maximum.

A one-pot procedure for the aminoxylation of thioalkynes for the direct formation of α-functionalized thioesters under mild reaction conditions is reported. A ketenethionium ion is the key intermediate, which is generated in situ by Brønsted acid mediated protonation and undergoes a radical-polar crossover.

To achieve chemical accuracy in free energy calculations, it is necessary to accurately describe the system's potential energy surface and efficiently sample configurations from its Boltzmann distribution. While neural network potentials (NNPs) have shown significantly higher accuracy than classical molecular mechanics (MM) force fields, they have limited range of applicability and are significantly slower than MM potentials, often by orders of magnitude. To address this challenge, Rufa et al suggested a two-stage approach that uses a fast and established MM alchemical energy protocol, followed by reweighting the results using NNPs, known as endstate correction or indirect free energy calculation. In this study, we systematically investigate the accuracy, robustness, and efficiency of free energy calculations between a MM reference and a neural network target potential (ANI-2x) using free energy perturbation (FEP) and non-equilibrium (NEQ) switching simulation in vacuum. We investigate the influence of longer switching lengths and the impact of slow degrees of freedom on outliers in the work distribution. We compare the results to multistage equilibrium free energy calculations (MFES) for an established dataset. Our results demonstrate that free energy calculations between NNPs and MM potentials should not be performed using FEP but require NEQ switching simulations to obtain accurate free energy estimates. NEQ switching simulations between MM and NNPs are highly efficient, robust, and trivial to implement.