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Large conjugated carbon framework has been incorporated as the diimine ligand for Re(α-diimine)(CO)3Cl complexes with a pyrazinyl linkage, either to increase energy efficiency or to turn them into heterogeneous catalysts for selective electrocatalytic CO2 reduction. However, there exists a nonmonotonic dependence of CO2 reduction overpotential on the conjugation size of the ligands. Understanding its origin could facilitate heterogenization of molecular catalysts with improved energy efficiency. Here, we show that the conjugated pyrazinyl moiety plays a crucial role in catalysis by enabling a proton-coupled, lower-energy pathway for CO2 reduction. With ligands of moderate size, the pathway leads to previously unknown intermediates and decreases CO2 reduction overpotential. Because the pathway hinges on the basicity of the pyrazinyl nitrogen, we propose that it imposes a limit on the conjugation size of the ligand for the pathway to be effective. 

Methods which accurately predict protein – ligand binding strengths are critical for drug discovery. In the last two decades, advances in chemical modelling have enabled steadily accelerating progress in the discovery and optimization of structure-based drug design. Most computational methods currently used in this context are based on molecular mechanics force fields that often have deficiencies in describing the quantum mechanical (QM) aspects of molecular binding. In this study, we show the competitiveness of our QM-based Molecules-in-Molecules (MIM) fragmentation method for characterizing binding energy trends for seven different datasets of protein – ligand complexes. By using molecular fragmentation, the MIM method allows for accelerated QM calculations. We demonstrate that for classes of structurally similar ligands bound to a common receptor, MIM provides excellent correlation to experiment, surpassing the more popular Molecular Mechanics Poisson-Boltzmann Surface Area (MM/PBSA) and Molecular Mechanics Generalized Born Surface Area (MM/GBSA) methods. The MIM method offers a relatively simple, well-defined protocol by which binding trends can be ascertained at the QM level and is suggested as a promising option for lead optimization in structure-based drug design. 

Electrochemical dehalogenation of polyhalogenated compounds is an inefficient process as the working electrode is passivated by the deposition of short-chain polymers that form during the early stages of electrolysis. Herein, we report the use of 1, 1, 1, 3, 3, 3-hexaflouroisopropanol (HFIP) as an efficient reagent to control C–H formation over the radical association. Debromination of 1,6-dibromohexane was examined in the presence of Ni(II) salen and HFIP as the electrocatalyst and hydrogen atom source, respectively. Electrolysis of 10 mM 1,6-dibromohexane and 2 mM Ni(II) salen in the absence of HFIP yields 50% unreacted 1,6-dibromohexane and ∼40% unaccounted for starting material, whereas electrolysis with 50 mM HFIP affords 65%n-hexane. The mechanism of hydrogen atom incorporation was examined via deuterium incorporation coupled with high-resolution mass spectrometry, and density functional theory (DFT) calculations. Deuterium incorporation analysis revealed that the hydrogen atom originated from the secondary carbon of HFIP. DFT calculations showed that the deprotonation of hydroxyl moiety of HFIP, prior to the hydrogen atom transfer, is a key step for C–H formation. The scope of electrochemical dehalogenation was examined by electrolysis of 10 halogenated compounds. Our results indicate that through the use of HFIP, the formation of short-chain polymers is no longer observed, and monomer formation is the dominant product.