Rational design of hydrogen-free catalytic active sites

Materials that are organic-based and exhibit oxidative catalytic activity, including free-radical pathways, while being refractory to the activated oxygen species are not known. The synthesis of several classes of such materials, their electronic and structural characterizations as well as catalytic properties are reported. Their rational molecular design and biologically inspired reactivity are based on enzymatic active sites, which are reengineered into robust metal-organic fluoroalkylated scaffolds that, for the first time, exhibit structural asymmetry and tunable π-π interactions both in solution and solid state. In these complexes, labile C-H bonds are replaced with chemically and thermally resistant C-F bonds to create a Teflon coating ; of the metal active site, keeping it open for catalysis while protecting the molecule against self-decomposition. The first part presents the synthesis, spectroscopic and X-ray structural characterization of new, mixed alkyl-perfluoroalkyl trispyrazolylborate (Tp) ligands and several of their sodium and silver derivatives. These complexes are subject to an N3-coordinating agent bearing a -1 charge. The metal is encapsulated in a fluorine-rich environment and exhibits a high Lewis acidity, allowing additional coordination by toluene, triphenylphosphine, methyldiphenylphosphine and triphenylphosphine oxide. X-ray crystallographic analysis of the new materials allows for the development of a structural model that predicts interatomic distances and the relative stability of this class of compounds. The balancing of electronic and steric effects of substituents on the Tp and additional ligands can lead to remarkably stable compounds in solution and the solid state, even when metals particularly prone to reduction (such as silver) are involved. Examples among the new complexes are provided. The second part describes the design of two new classes of macrocyclic organic chromophores with enhanced N4-coordinating ability and -2 charges, belonging to the family of fluoroalkylated phthalocyanines and produced as their zinc and cobalt complexes. The first class, bearing trifluoromethyl groups, exhibits reduced steric hindrance and solvent-dependent aggregation. A direct correlation between the degree of dimerization and the solvent\u27s hydrogen bond donor ability is established. The second class constitutes the first asymmetric perfluorinated phthalocyanines, a property imparted by a combination of fluorine atoms and perfluoroisopropyl groups. X-ray crystal structures reveal tunable π-π stacking in the solid state for representatives of both classes. The new compounds\u27 ability to catalytically activate oxygen from air and consequently oxidize substrates is tested on two processes of industrial importance: the environmentally benign conversion of corrosive thiols to disulfides and the photocatalytic oxidation of (S\u27)-citronellol. The extreme electronic deficiency imparted on the metal complexes supports a new strategy for broadening catalytic activity to include thiols with poor basicity, which under normal circumstances cannot be oxidized. Quantitative substrate conversion and virtual immunity of the catalysts to chemical attacks is demonstrated for the first time in a metal-organic assembly through oxygen consumption and stability studies, thus opening pathways for development of new materials

Reaction-Based Probes for Imaging Mobile Zinc in Live Cells and Tissues

Chelatable, or mobile, forms of zinc play critical signaling roles in numerous biological processes. Elucidating the action of mobile Zn(II) in complex biological environments requires sensitive tools for visualizing, tracking, and manipulating Zn(II) ions. A large toolbox of synthetic photoinduced electron transfer (PET)-based fluorescent Zn(II) sensors are available, but the applicability of many of these probes is limited by poor zinc sensitivity and low dynamic ranges owing to proton interference. We present here a general approach for acetylating PET-based probes containing a variety of fluorophores and zinc-binding units. The new sensors provide substantially improved zinc sensitivity and allow for incubation of live cells and tissue slices with nM probe concentrations, a significant improvement compared to the μM concentrations that are typically required for a measurable fluorescence signal. Acetylation effectively reduces or completely quenches background fluorescence in the metal-free sensor. Binding of Zn(II) selectively and quickly mediates hydrolytic cleavage of the acetyl groups, providing a large fluorescence response. An acetylated blue coumarin-based sensor was used to carry out detailed analyses of metal binding and metal-promoted acetyl hydrolysis. Acetylated benzoresorufin-based red-emitting probes with different zinc-binding sites are effective for sensing Zn(II) ions in live cells when applied at low concentrations (∼50–100 nM). We used green diacetylated Zinpyr1 (DA-ZP1) to image endogenous mobile Zn(II) in the molecular layer of mouse dorsal cochlear nucleus (DCN), confirming that acetylation is a suitable approach for preparing sensors that are highly specific and sensitive to mobile zinc in biological systems.National Institutes of Health (U.S.) (NIH grant GM065519)National Institutes of Health (U.S.) (NIH grant R01-DC007905)National Institutes of Health (U.S.) (NIH Fellowship (F32- EB019243))National Institutes of Health (U.S.) (NIH Fellowship (T32-DC011499))National Institutes of Health (U.S.) (NIH Fellowship (F32-DC013734)

Automated affinity selection for rapid discovery of peptide binders

This work reports an automated affinity selection-mass spectrometry (AS-MS) approach amenable to both de novo peptide binder discovery and affinity maturation of known binders in a high-throughput and selective manner.</jats:p

Solid-phase synthesis provides a modular, lysine-based platform for fluorescent discrimination of nitroxyl and biological thiols

We describe a modular, synthetically facile solid-phase approach aimed at separating the fluorescent reporter and binding unit of small-molecule metal-based sensors. The first representatives contain a lysine backbone functionalized with a tetramethylrhodamine fluorophore, and they operate by modulating the oxidation state of a copper ion ligated to an [N4] (cyclam) or an [N2O] (quinoline-phenolate) moiety. We demonstrate the selectivity of their Cu(II) complexes for sensing nitroxyl (HNO) and thiols (RSH), respectively, and investigate the mechanism responsible for the observed reactivity in each case. The two lysine conjugates are cell permeable in the active, Cu(II)-bound forms and retain their analyte selectivity intracellularly, even in the presence of interfering species such as nitric oxide, nitrosothiols, and hydrogen sulfide. Moreover, we apply the new probes to discriminate between distinct levels of intracellular HNO and RSH generated upon stimulation of live HeLa cells with ascorbate and hydrogen sulfide, respectively. The successful implementation of the lysine-based sensors to gain insight into biosynthetic pathways validates the method as a versatile tool for producing libraries of analogues with minimal synthetic effort.National Institutes of Health (U.S.) (NIH Grant 1S10RR13886-01)National Science Foundation (U.S.) (NSF Grant CHE-1265770

Linearizable Macrocyclic Peptide Libraries for Affinity Selection-Mass Spectrometry

Macrocyclic peptides are attractive for therapeutic development but have been limited in their application to combinatorial library selection from synthetic libraries. Here, we establish a synthetic approach based on split-pool chemistry to produce 100-million membered macrocyclic libraries containing natural and non-natural amino acids. Near-quantitative intramolecular disulfide formation is facilitated by rapid (<10 minute) oxidation by iodine to prepare macrocyclic synthetic libraries in solution. Treatment with dithiothreitol post-affinity selection enables near-quantitative reduction of the library members, rendering the linear analogs amenable to standard tandem mass spectrometry sequencing. We demonstrate the utility of these libraries to discover novel macrocyclic binders to cadherin-2 and the anti-hemagglutinin antibody clone 12ca5. The lead cadherin-binding peptide (CBP) is endowed with nanomolar binding affinity measured by biolayer interferometry (BLI, apparent dissociation constant KD = 53 nM). Structure-activity relationship (SAR) studies including alanine and D-amino acid scans reveal the amino acids responsible for driving affinity (hot-spots) and the positions tolerating mutagenesis (cold-spots). Informed by SAR data, two new macrocyclic libraries are designed to derivatize these positions with a variety of abiotic amino acids based on the hot- and cold-spots. Following affinity selection and experimental validation by BLI, 10 high-affinity ligands out of 10 discovered were identified from the library that derivatized the CBP cold-spots, while zero of the two peptide ligands discovered from the hot-spot library were high-affinity binders. Of these noncanonical CBPs (NCBP), NCBP-4 demonstrates improved affinity to cadherin-2 (KD = 29 nM). Overall, we expect that this work will pioneer the use of large-scale macrocyclic libraries to further catalyze therapeutic peptide discovery and development

Automated Flow Synthesis of Artificial Heme Enzymes for Enantioselective Biocatalysis

The remarkable efficiency with which enzymes catalyze small molecule reactions has driven their widespread application in organic chemistry. Here, we employ automated fast-flow solid-phase synthesis to access full-length enzymes without restrictions on the number and structure of non-canonical amino acids incorporated. We demonstrate the total syntheses of Fe-dependent Bacillus subtilis myoglobin (BsMb) and sperm whale myoglobin (SwMb), which displayed excellent enantioselectivity and yield in carbene transfer reactions. Absolute control over enantioselectivity in styrene cyclopropanation was achieved using L- and D-BsMb mutants which delivered each enantiomer of cyclopropane product in identical and opposite enantiomeric enrichment. BsMb mutants outfitted with non-canonical amino acids were used to facilitate detailed structure-activity relationship studies, revealing a previously unrecognized hydrogen-bonding interaction as the primary driver of enantioselectivity in styrene cyclopropanation

Deep Learning for Prediction and Optimization of Fast-Flow Peptide Synthesis

Chemical synthesis of polypeptides involves stepwise formation of amide bonds on an immobilized solid support. The high yields required for efficient incorporation of each individual amino acid in the growing chain are often impacted by sequence-dependent events such as aggregation. Here we apply deep learning over ultraviolet-visible (UV-Vis) analytical data collected from 35,485 individual fluorenylmethyloxycarbonyl (Fmoc) deprotection reactions performed with an automated fast-flow peptide synthesizer. The integral, height and width of these time-resolved UV-Vis deprotection traces indirectly allow for analysis of the iterative amide coupling cycles on resin. The computational model maps structural representations of amino acids and peptide sequences to experimental synthesis parameters and predicts the outcome of deprotection reactions with less than 4% error. Our deep learning approach enables experimentally-aware computational design for prediction of Fmoc deprotection efficiency and minimization of aggregation events, building the foundation for real-time optimization of peptide synthesis in flow.</p

Deep Learning for Prediction and Optimization of Fast-Flow Peptide Synthesis

© 2020 American Chemical Society. The chemical synthesis of polypeptides involves stepwise formation of amide bonds on an immobilized solid support. The high yields required for efficient incorporation of each individual amino acid in the growing chain are often impacted by sequence-dependent events such as aggregation. Here, we apply deep learning over ultraviolet-visible (UV-vis) analytical data collected from 35 »427 individual fluorenylmethyloxycarbonyl (Fmoc) deprotection reactions performed with an automated fast-flow peptide synthesizer. The integral, height, and width of these time-resolved UV-vis deprotection traces indirectly allow for analysis of the iterative amide coupling cycles on resin. The computational model maps structural representations of amino acids and peptide sequences to experimental synthesis parameters and predicts the outcome of deprotection reactions with less than 6% error. Our deep-learning approach enables experimentally aware computational design for prediction of Fmoc deprotection efficiency and minimization of aggregation events, building the foundation for real-time optimization of peptide synthesis in flow