Janaka C. Gamekkanda

Historically, many compelling therapeutic targets have been accessible only by injectable biologic drugs. Macrocyclic peptides, such as the proprotein convertase subtilisin/kexin type 9 inhibitor enlicitide for the treatment of atherosclerotic cardiovascular disease, are beginning to unlock these targets to orally administered therapies to enable broader patient access. We report the convergent biocatalytic assembly of enlicitide from simple building blocks enabled by a suite of engineered enzymes to catalyze selective peptide fragment formation, coupling, and macrocyclization in a protecting group–free manner. Together with efficient crystallizations that obviate the need for chromatography, this approach reduces the number of steps by greater than half compared with prior state-of-the-art methods, addressing long-standing synthetic challenges and offering a sustainable blueprint for the scalable development of complex peptide therapeutics.

Extracting quantitative information about highly scattering surfaces from an imaging system is challenging because the phase of the scattered light undergoes multiple folds upon propagation, resulting in complex speckle patterns. One specific application is the drying of wet powders in the pharmaceutical industry, where quantifying the particle size distribution (PSD) is of particular interest. A non-invasive and real-time monitoring probe in the drying process is required, but there is no suitable candidate for this purpose. In this report, we develop a theoretical relationship from the PSD to the speckle image and describe a physics-enhanced autocorrelation-based estimator (PEACE) machine learning algorithm for speckle analysis to measure the PSD of a powder surface. This method solves both the forward and inverse problems together and enjoys increased interpretability, since the machine learning approximator is regularized by the physical law.

Extracting quantitative information about highly scattering surfaces from an imaging system is challenging because the phase of the scattered light undergoes multiple folds upon propagation, resulting in complex speckle patterns. One specific application is the drying of wet powders in the pharmaceutical industry, where quantifying the particle size distribution (PSD) is of particular interest. A non-invasive and real-time monitoring probe in the drying process is required, but there is no suitable candidate for this purpose. In this report, we develop a theoretical relationship from the PSD to the speckle image and describe a physics-enhanced autocorrelation-based estimator (PEACE) machine learning algorithm for speckle analysis to measure the PSD of a powder surface. This method solves both the forward and inverse problems together and enjoys increased interpretability, since the machine learning approximator is regularized by the physical law.

The competition and balance between intermolecular hydrogen bonds (HBs) and halogen bonds (XBs) were explored by co-crystallizing tetra-functionalized (2 × HB (–OH) and 2 × XB (–CC–I)) molecules, trans-1,4-bis(iodoethynyl)cyclohexane-1,4-diol (D1) and cis-1,4-bis(iodoethynyl)cyclohexane-1,4-diol (D2), with six ditopic nitrogen based acceptor molecules. The crystal structures of both D1 and D2 showed non-covalent interactions between HB/XB donors and available acceptor sites (oxygen/triple bond/negative region of iodine). In three co-crystals of D1 the HB and XB donors act in similar ways as both activated iodine and hydroxyl hydrogen bind to the nitrogen acceptors in the solid state. In contrast, in a co-crystal of D2, a geometric isomer of D1, there were only hydrogen bonds to the co-former and the halogen-bond donor interacted with the hydroxyl oxygen atoms of D2. A stronger tendency for linear XB interactions (as well as greater van der Waals radii reduction) was observed with nitrogen atoms as acceptors (average reduction = 21%) compared to those involving an oxygen atom as an acceptor (average reduction = 16%). A control molecule, trans-1,4-diethynylcyclohexane-1,4-diol (D3), which has only HB donors (–OH and –CC–H) was also examined to get a better understanding of the balance between XB and HB intercations. The ethynyl hydrogen atom did not form hydrogen bonds to the nitrogen atoms in acceptors, and only O–H⋯N and –CC–H⋯O hydrogen bonds were observed in these structures.

In order to explore the use of non-covalent interactions in the deliberate assembly of metal-supramolecular architectures, a series of β-diketone based ligands capable of simultaneously acting as halogen-bond donors and chelating ligands were synthesized. The three ligands, L1, L2, and L3, carry ethynyl-activated chlorine, bromine, and iodine atoms, respectively and copper(II) complexes of all three ligands were crystallized from different solvents, acetonitrile, ethyl acetate, and nitromethane in order to study specific ligand-solvent interaction. The free ligands L2 and L3, with more polarizable halogen atoms, display C-X⋯O halogen bonds in the solid state, whereas the chloro-analogue (L1) does not engage in halogen bonding. Both acetonitrile and ethyl acetate act as halogen-bond acceptors in Cu(II)-complexes of L2 and L3 whereas nitromethane is present as a ‘space-filling’ guest without participating in any significant intermolecular interactions in Cu(II)-complexes of L2. L3, which is decorated with an iodoethynyl moiety and consistently engages in halogen-bonds with suitable acceptors. This systematic structural analysis allows us to rank the relative importance of a variety of electron-pair donors in these metal complexes.