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The recognition of boron compounds is well developed as boronic acids but untapped as organotrifluoroborate anions (R−BF₃⁻). We are exploring the development of these and other designer anions as anion‐recognition motifs by considering them as substituted versions of the parent inorganic ion. To this end, we demonstrate strong and reliable binding of organic trifluoroborates, R−BF₃⁻, by cyanostar macrocycles that are size‐complementary to the inorganic BF₄⁻progenitors. We find that recognition is modulated by the substituent's sterics and that the affinities are retained using the common K⁺salts of R−BF₃⁻anions.

 

A new strategy for the synthesis of highly versatile cyclobutylboronates via the photosensitized [2+2]‐cycloaddition of alkenylboronates and alkenes is presented. The process is mechanistically different from other processes in that energy transfer occurs with the alkenylboronate as opposed to the other alkene. This strategy allows for the synthesis of an array of diverse cyclobutylboronates. The conversion of these adducts to other compounds as well as their utility in the synthesis of melicodenine C is demonstrated.

 

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.