Direct Synthesis of 1-Butanol with High Faradaic Efficiency from CO2 Utilizing Cascade Catalysis at a Ni-Enhanced (Cr2O3)3Ga2O3 Electrocatalyst.

Electrochemical transformation of CO2 into energy-dense liquid fuels provides a viable solution to challenges regarding climate change and nonrenewable resource dependence. Here, we report on the modification of a Cr-Ga oxide electrocatalyst through the introduction of nickel to generate a catalyst that generates 1-butanol at unprecedented faradaic efficiencies (ξ = 42%). This faradaic efficiency occurs at -1.48 V vs Ag/AgCl, with 1-butanol production commencing at an overpotential of 320 mV. At this potential, minor products include formate, methanol, acetic acid, acetone, and 3-hydroxybutanal. At -1.0 and -1.4 V, 3-hydroxybutanal becomes the primary product. This is in contrast to the nickel-free (Cr2O3)3(Ga2O3) system, where neither 3-hydroxybutanal nor 1-butanol was detected. Mechanistic studies show that formate is the initial CO2 reduction product and identify acetaldehyde as the key intermediate. Nickel is found responsible for the coupling and reduction of acetaldehyde to generate the higher molecular weight carbon products observed. To the best of our knowledge, this is the first electrocatalyst to generate 1-butanol with high faradaic efficiency.

Iron-catalysed tritiation of pharmaceuticals.

A thorough understanding of the pharmacokinetic and pharmacodynamic properties of a drug in animal models is a critical component of drug discovery and development. Such studies are performed in vivo and in vitro at various stages of the development process--ranging from preclinical absorption, distribution, metabolism and excretion (ADME) studies to late-stage human clinical trials--to elucidate a drug molecule's metabolic profile and to assess its toxicity. Radiolabelled compounds, typically those that contain (14)C or (3)H isotopes, are one of the most powerful and widely deployed diagnostics for these studies. The introduction of radiolabels using synthetic chemistry enables the direct tracing of the drug molecule without substantially altering its structure or function. The ubiquity of C-H bonds in drugs and the relative ease and low cost associated with tritium ((3)H) make it an ideal radioisotope with which to conduct ADME studies early in the drug development process. Here we describe an iron-catalysed method for the direct (3)H labelling of pharmaceuticals by hydrogen isotope exchange, using tritium gas as the source of the radioisotope. The site selectivity of the iron catalyst is orthogonal to currently used iridium catalysts and allows isotopic labelling of complementary positions in drug molecules, providing a new diagnostic tool in drug development.

Fast Metabolite Identification in Nuclear Magnetic Resonance Metabolomic Studies: Statistical Peak Sorting and Peak Overlap Detection for More Reliable Database Queries.

A lot of time is spent by researchers in the identification of metabolites in NMR-based metabolomic studies. The usual metabolite identification starts employing public or commercial databases to match chemical shifts thought to belong to a given compound. Statistical total correlation spectroscopy (STOCSY), in use for more than a decade, speeds the process by finding statistical correlations among peaks, being able to create a better peak list as input for the database query. However, the (normally not automated) analysis becomes challenging due to the intrinsic issue of peak overlap, where correlations of more than one compound appear in the STOCSY trace. Here we present a fully automated methodology that analyzes all STOCSY traces at once (every peak is chosen as driver peak) and overcomes the peak overlap obstacle. Peak overlap detection by clustering analysis and sorting of traces (POD-CAST) first creates an overlap matrix from the STOCSY traces, then clusters the overlap traces based on their similarity and finally calculates a cumulative overlap index (COI) to account for both strong and intermediate correlations. This information is gathered in one plot to help the user identify the groups of peaks that would belong to a single molecule and perform a more reliable database query. The simultaneous examination of all traces reduces the time of analysis, compared to viewing STOCSY traces by pairs or small groups, and condenses the redundant information in the 2D STOCSY matrix into bands containing similar traces. The COI helps in the detection of overlapping peaks, which can be added to the peak list from another cross-correlated band. POD-CAST overcomes the generally overlooked and underestimated presence of overlapping peaks and it detects them to include them in the search of all compounds contributing to the peak overlap, enabling the user to accelerate the metabolite identification process with more successful database queries and searching all tentative compounds in the sample set.

Charting an Unexplored Streptococcal Biosynthetic Landscape Reveals a Unique Peptide Cyclization Motif.

Peptide natural products are often used as signals or antibiotics and contain unusual structural modifications, thus providing opportunities for expanding our understanding of Nature's therapeutic and biosynthetic repertoires. Herein, we have investigated the under-explored biosynthetic potential of Streptococci, prevalent bacteria in mammalian microbiomes that include mutualistic, commensal, and pathogenic members. Using a new bioinformatic search strategy, in which we linked the versatile radical S-adenosylmethionine (RaS) enzyme superfamily to an emerging class of natural products in the context of quorum sensing control, we identified numerous, uncharted biosynthetic loci. Focusing on one such locus, we identified an unprecedented post-translational modification, consisting of a tetrahydro[5,6]benzindole cyclization motif in which four unactivated positions are linked by two C-C bonds in a regio- and stereospecific manner by a single RaS enzyme. Our results expand the scope of reactions that microbes have at their disposal in concocting complex ribosomal peptides.

Identifying and avoiding singularity-induced local traps over control landscapes of spin chain systems.

The wide success of quantum optimal control in experiments and simulations is attributed to the properties of the control landscape, defined by the objective value as a functional of the controls. Prior analysis has shown that on satisfaction of some underlying assumptions, the landscapes are free of suboptimal traps that could halt the search for a global optimum with gradient-based algorithms. However, violation of one particular assumption can give rise to a so-called singular control, possibly bringing about local traps on the corresponding landscapes in some particular situations. This paper theoretically and experimentally demonstrates the existence of singular traps on the landscape in linear spin-1/2 chains with Ising couplings between nearest neighbors and with certain field components set to zero. The results in a two-spin example show how a trap influences the search trajectories passing by it, and how to avoid encountering such traps in practice by choosing sufficiently strong initial control fields. The findings are also discussed in the context of the generally observed success of quantum control.

Precursor-centric genome-mining approach for lasso peptide discovery.

Lasso peptides are a class of ribosomally synthesized posttranslationally modified natural products found in bacteria. Currently known lasso peptides have a diverse set of pharmacologically relevant activities, including inhibition of bacterial growth, receptor antagonism, and enzyme inhibition. The biosynthesis of lasso peptides is specified by a cluster of three genes encoding a precursor protein and two enzymes. Here we develop a unique genome-mining algorithm to identify lasso peptide gene clusters in prokaryotes. Our approach involves pattern matching to a small number of conserved amino acids in precursor proteins, and thus allows for a more global survey of lasso peptide gene clusters than does homology-based genome mining. Of more than 3,000 currently sequenced prokaryotic genomes, we found 76 organisms that are putative lasso peptide producers. These organisms span nine bacterial phyla and an archaeal phylum. To provide validation of the genome-mining method, we focused on a single lasso peptide predicted to be produced by the freshwater bacterium Asticcacaulis excentricus. Heterologous expression of an engineered, minimal gene cluster in Escherichia coli led to the production of a unique lasso peptide, astexin-1. At 23 aa, astexin-1 is the largest lasso peptide isolated to date. It is also highly polar, in contrast to many lasso peptides that are primarily hydrophobic. Astexin-1 has modest antimicrobial activity against its phylogenetic relative Caulobacter crescentus. The solution structure of astexin-1 was determined revealing a unique topology that is stabilized by hydrogen bonding between segments of the peptide.

Metabolomic approach to human brain spectroscopy identifies associations between clinical features and the frontal lobe metabolome in multiple sclerosis.

Proton magnetic resonance spectroscopy ((1)H-MRS) is capable of noninvasively detecting metabolic changes that occur in the brain tissue in vivo. Its clinical utility has been limited so far, however, by analytic methods that focus on independently evaluated metabolites and require prior knowledge about which metabolites to examine. Here, we applied advanced computational methodologies from the field of metabolomics, specifically partial least squares discriminant analysis and orthogonal partial least squares, to in vivo (1)H-MRS from frontal lobe white matter of 27 patients with relapsing-remitting multiple sclerosis (RRMS) and 14 healthy controls. We chose RRMS, a chronic demyelinating disorder of the central nervous system, because its complex pathology and variable disease course make the need for reliable biomarkers of disease progression more pressing. We show that in vivo MRS data, when analyzed by multivariate statistical methods, can provide reliable, distinct profiles of MRS-detectable metabolites in different patient populations. Specifically, we find that brain tissue in RRMS patients deviates significantly in its metabolic profile from that of healthy controls, even though it appears normal by standard MRI techniques. We also identify, using statistical means, the metabolic signatures of certain clinical features common in RRMS, such as disability score, cognitive impairments, and response to stress. This approach to human in vivo MRS data should promote understanding of the specific metabolic changes accompanying disease pathogenesis, and could provide biomarkers of disease progression that would be useful in clinical trials.

Triiodide Attacks the Organic Cation in Hybrid Lead Halide Perovskites: Mechanism and Suppression.

Molecular I2 can be produced from iodide-based lead perovskites under thermal stress; triiodide, I3 - , is formed from this I2 and I- . Triiodide attacks protic cation MA+ - or FA+ -based lead halide perovskites (MA+ , methylammonium; FA+ , formamidinium) as explicated through solution-based nuclear magnetic resonance (NMR) studies: triiodide has strong hydrogen-bonding affinity for MA+ or FA+ , which leads to their deprotonation and perovskite decomposition. Triiodide is a catalyst for this decomposition that can be obviated through perovskite surface treatment with thiol reducing agents. In contrast to methods using thiol incorporation into perovskite precursor solutions, no penetration of the thiol into the bulk perovskite is observed, yet its surface application stabilizes the perovskite against triiodide-mediated thermal stress. Thiol applied to the interface between FAPbI3 and Spiro-OMeTAD ("Spiro") prevents oxidized iodine species penetration into Spiro and thus preserves its hole-transport efficacy. Surface-applied thiol affects the perovskite work function; it ameliorates hole injection into the Spiro overlayer, thus improving device performance. It helps to increase interfacial adhesion ("wetting"): fewer voids are observed at the Spiro/perovskite interface if thiols are applied. Perovskite solar cells (PSCs) incorporating interfacial thiol treatment maintain over 80% of their initial power conversion efficiency (PCE) after 300 h of 85 °C thermal stress.

NMR landscapes for chemical shift prediction.

The ability to reliably predict NMR chemical shifts plays an important role in elucidating the structure of organic molecules. Additionally, an intriguing question is how the multitude of variable factors (structural, electronic, and environmental) correlate with the actual electromagnetic shielding effect that determines the chemical shift value. This work presents NMRscape as a new tool for understanding these correlations by constructing the landscape that describes the relationship between the chemical shift value and the moieties bonded to a molecular scaffold. The scaffold may be as small as a single atom probed by NMR or a larger molecular framework containing the probed atom. NMRscape operates with only a list of the chemical moieties bonded to the scaffold, without utilizing any potentially biasing chemometric descriptors. The corresponding chemical shift landscape is constructed based on fundamental physical principles, which makes NMRscape a credible chemical shift prediction and analysis tool. As an illustration, we demonstrate that NMRscape can predict (13)C chemical shifts with an accuracy exceeding the substituent chemical shift (SCS) increment, hierarchical organization of spherical environments (HOSE), and neural networks (NN), methods for three distinct families of molecules sharing a common scaffold structure with moieties placed at two variable sites. The constructed NMR landscapes confirmed known empirical rules relating chemical shift values to the variation of chemical moieties on a scaffold, as well as uncovered hitherto hidden relationships. The practical importance of NMRscape is discussed.

Formulation of pH-Responsive Methacrylate-Based Polyelectrolyte-Stabilized Nanoparticles for Applications in Drug Delivery.

pH-responsive polyelectrolytes, including methacrylate-based anionic copolymers (MACs), are widely used as enteric coatings and matrices in oral drug delivery. Despite their widespread use in these macroscopic applications, the molecular understanding of their use as stabilizers for nanoparticles (NPs) is lacking. Here, we investigate how MACs can be used to create NPs for therapeutic drug delivery and the role of MAC molecular properties on the assembly of NPs via flash nanoprecipitation. The NP size is tuned from 59 to 454 nm by changing the degree of neutralization, ionic strength, total mass concentration, and the core-to-MAC ratio. The NP size is determined by the volume of hydrophilic domains on the surface relative to the volume of hydrophobic domains in the core. We calculate the dimensions of the hydrophobic NP core relative to the thickness of the polyelectrolyte layer over a range of ionizations. Importantly, the results are shown to apply to both high-molecular-weight polymers as core materials and small-molecule drugs. The pH responsiveness of MAC-stabilized NPs is also demonstrated. Future development of polyelectrolyte copolymer-stabilized nanomedicines will benefit from the guiding principles established in this study.

Untying the Cesium "Not": Cesium-Iodoplumbate Complexation in Perovskite Solution-Processing Inks Has Implications for Crystallization.

We illustrate the critical importance of the energetics of cation-solvent versus cation-iodoplumbate interactions in determining the stability of ABX3 perovskite precursors in a dimethylformamide (DMF) solvent medium. We have shown, through a complementary suite of nuclear magnetic resonance (NMR) and computational studies, that Cs+ exhibits significantly different solvent vs iodoplumbate interactions compared to organic A+-site cations such as CH3NH3+ (MA+). Two NMR studies were conducted: 133Cs NMR analysis shows that Cs+ and MA+ compete for coordination with PbI3- in DMF. 207Pb NMR studies of PbI2 with cationic iodides show that perovskite-forming Cs+ (and, somewhat, Rb+) do not comport with the 207Pb chemical shift trend found for Li+, Na+, and K+. Three independent computational approaches (density functional theory (DFT), ab initio Molecular Dynamics (AIMD), and a polarizable force field within Molecular Dynamics) yielded strikingly similar results: Cs+ interacts more strongly with the PbI3- iodoplumbate than does MA+ in a polar solvent environment like DMF. The stronger energy preference for PbI3- coordination of Cs+ vs MA+ in DMF demonstrates that Cs+ is not simply a postcrystallization cation "fit" for the perovskite A+-site. Instead, it may facilitate preorganization of the framework precursor that eventually transforms into the crystalline perovskite structure.

Optimized preprocessing of ultra-performance liquid chromatography/mass spectrometry urinary metabolic profiles for improved information recovery.

Ultra-performance liquid chromatography coupled to mass spectrometry (UPLC/MS) has been used increasingly for measuring changes of low molecular weight metabolites in biofluids/tissues in response to biological challenges such as drug toxicity and disease processes. Typically samples show high variability in concentration, and the derived metabolic profiles have a heteroscedastic noise structure characterized by increasing variance as a function of increased signal intensity. These sources of experimental and instrumental noise substantially complicate information recovery when statistical tools are used. We apply and compare several preprocessing procedures and introduce a statistical error model to account for these bioanalytical complexities. In particular, the use of total intensity, median fold change, locally weighted scatter plot smoothing, and quantile normalizations to reduce extraneous variance induced by sample dilution were compared. We demonstrate that the UPLC/MS peak intensities of urine samples should respond linearly to variable sample dilution across the intensity range. While all four studied normalization methods performed reasonably well in reducing dilution-induced variation of urine samples in the absence of biological variation, the median fold change normalization is least compromised by the biologically relevant changes in mixture components and is thus preferable. Additionally, the application of a subsequent log-based transformation was successful in stabilizing the variance with respect to peak intensity, confirming the predominant influence of multiplicative noise in peak intensities from UPLC/MS-derived metabolic profile data sets. We demonstrate that variance-stabilizing transformation and normalization are critical preprocessing steps that can benefit greatly metabolic information recovery from such data sets when widely applied chemometric methods are used.

Saccharomyces cerevisiae Requires CFF1 To Produce 4-Hydroxy-5-Methylfuran-3(2H)-One, a Mimic of the Bacterial Quorum-Sensing Autoinducer AI-2.

Quorum sensing is a process of cell-to-cell communication that bacteria use to orchestrate collective behaviors. Quorum sensing depends on the production, release, and detection of extracellular signal molecules called autoinducers (AIs) that accumulate with increasing cell density. While most AIs are species specific, the AI called AI-2 is produced and detected by diverse bacterial species, and it mediates interspecies communication. We recently reported that mammalian cells produce an AI-2 mimic that can be detected by bacteria through the AI-2 receptor LuxP, potentially expanding the role of the AI-2 system to interdomain communication. Here, we describe a second molecule capable of interdomain signaling through LuxP, 4-hydroxy-5-methylfuran-3(2H)-one (MHF), that is produced by the yeast Saccharomyces cerevisiae Screening the S. cerevisiae deletion collection revealed Cff1p, a protein with no known role, to be required for MHF production. Cff1p is proposed to be an enzyme, with structural similarity to sugar isomerases and epimerases, and substitution at the putative catalytic residue eliminated MHF production in S. cerevisiae Sequence analysis uncovered Cff1p homologs in many species, primarily bacterial and fungal, but also viral, archaeal, and higher eukaryotic. Cff1p homologs from organisms from all domains can complement a cff1ΔS. cerevisiae mutant and restore MHF production. In all cases tested, the identified catalytic residue is conserved and required for MHF to be produced. These findings increase the scope of possibilities for interdomain interactions via AI-2 and AI-2 mimics, highlighting the breadth of molecules and organisms that could participate in quorum sensing.IMPORTANCE Quorum sensing is a cell-to-cell communication process that bacteria use to monitor local population density. Quorum sensing relies on extracellular signal molecules called autoinducers (AIs). One AI called AI-2 is broadly made by bacteria and used for interspecies communication. Here, we describe a eukaryotic AI-2 mimic, 4-hydroxy-5-methylfuran-3(2H)-one, (MHF), that is made by the yeast Saccharomyces cerevisiae, and we identify the Cff1p protein as essential for MHF production. Hundreds of viral, archaeal, bacterial, and eukaryotic organisms possess Cff1p homologs. This finding, combined with our results showing that homologs from all domains can replace S. cerevisiae Cff1p, suggests that like AI-2, MHF is widely produced. Our results expand the breadth of organisms that may participate in quorum-sensing-mediated interactions.

Stability of Protein Structure during Nanocarrier Encapsulation: Insights on Solvent Effects from Simulations and Spectroscopic Analysis.

The dosing of peptide and protein therapeutics is complicated by rapid clearance from the blood pool and poor cellular membrane permeability. Encapsulation into nanocarriers such as liposomes or polymersomes has long been explored to overcome these limitations, but manufacturing challenges have limited clinical translation by these approaches. Recently, inverse Flash NanoPrecipitation (iFNP) has been developed to produce highly loaded polymeric nanocarriers with the peptide or protein contained within a hydrophilic core, stabilized by a hydrophobic polymer shell. Encapsulation of proteins with higher-order structure requires understanding how processing may affect their conformational state. We demonstrate a combined experimental/simulation approach to characterize protein behavior during iFNP processing steps using the Trp-cage protein TC5b as a model. Explicit-solvent fully atomistic molecular dynamics simulations with enhanced sampling techniques are coupled with two-dimensional heteronuclear multiple-quantum coherence nuclear magnetic resonance spectroscopy (2D-HMQC NMR) and circular dichroism to determine the structure of TC5b during mixed-solvent exposure encountered in iFNP processing. The simulations involve atomistic models of mixed solvents and protein to capture the complexity of the hydrogen bonding and hydrophobic interactions between water, dimethylsulfoxide (DMSO), and the protein. The combined analyses reveal structural unfolding of the protein in 11 M DMSO but confirm complete refolding after release from the polymeric nanocarrier back into an aqueous phase. These results highlight the insights that simulations and NMR provide for the formulation of proteins in nanocarriers.

Identification and quantification of water-soluble metabolites by cryoprobe-assisted nuclear magnetic resonance spectroscopy applied to microbial fermentation.

We highlight a range of cryoprobe-assisted NMR methods for studying metabolite production by cyanobacteria, which should be valuable for a wide range of biological applications requiring ultrasensitivity and precise concentration determination over a large dynamic range. Cyroprobe-assisted (1)H and (13)C NMR have been applied to precise determination of metabolic products excreted during autofermentation in two cyanobacterial species: filamentous Arthrospira (Spirulina) maxima CS-328 and unicellular Synechococcus sp. PCC 7002. Several fermentative end products were identified and quantified in concentrations ranging from 50 to 3000 microM in cell-free media (a direct measurement of native-like samples) with less than 5.5% relative error in under 10 min of acquisition per sample with the assistance of an efficient water-suppression protocol. Relaxation times (T1) of these metabolites in aqueous ((1)H(2)O) solution were measured and found to vary by nearly threefold, necessitating generation of individual calibration curves for each species for highest precision. However, using a 4.5 x longer overall recycle delay between scans, the metabolite concentrations can be predicted within 25% error by calibrating only to a single calibration standard (succinate); other metabolites are then calculated on the basis of their signal integrals and known proton degeneracies. Precise ratios of concentrations of (13)C-labeled versus unlabeled metabolites were determined from integral ratios of (1)H peaks that exhibit (13)C-(1)H J-couplings and independently confirmed by direct measurement of areas of corresponding (13)C resonances. (13)C NMR was used to identify and quantify production of osmolytes, trehalose, and glucosylglycerol by A. maxima.

PBLG as a versatile liquid crystalline medium for anisotropic NMR data acquisition.

Anisotropic NMR of small molecules has thus far utilized different solvent systems and alignment media to analyze molecules of different polarities. The value of utilizing PBLG liquid crystalline phase in a co-solvent system, expanding its range as a versatile alignment medium, is shown with three molecules of different polarities: strychnine, parthenolide, and sucrose.

Feeding Immunity: Physiological and Behavioral Responses to Infection and Resource Limitation.

Resources are a core currency of species interactions and ecology in general (e.g., think of food webs or competition). Within parasite-infected hosts, resources are divided among the competing demands of host immunity and growth as well as parasite reproduction and growth. Effects of resources on immune responses are increasingly understood at the cellular level (e.g., metabolic predictors of effector function), but there has been limited consideration of how these effects scale up to affect individual energetic regimes (e.g., allocation trade-offs), susceptibility to infection, and feeding behavior (e.g., responses to local resource quality and quantity). We experimentally rewilded laboratory mice (strain C57BL/6) in semi-natural enclosures to investigate the effects of dietary protein and gastrointestinal nematode (Trichuris muris) infection on individual-level immunity, activity, and behavior. The scale and realism of this field experiment, as well as the multiple physiological assays developed for laboratory mice, enabled us to detect costs, trade-offs, and potential compensatory mechanisms that mice employ to battle infection under different resource conditions. We found that mice on a low-protein diet spent more time feeding, which led to higher body fat stores (i.e., concentration of a satiety hormone, leptin) and altered metabolite profiles, but which did not fully compensate for the effects of poor nutrition on albumin or immune defenses. Specifically, immune defenses measured as interleukin 13 (IL13) (a primary cytokine coordinating defense against T. muris) and as T. muris-specific IgG1 titers were lower in mice on the low-protein diet. However, these reduced defenses did not result in higher worm counts in mice with poorer diets. The lab mice, living outside for the first time in thousands of generations, also consumed at least 26 wild plant species occurring in the enclosures, and DNA metabarcoding revealed that the consumption of different wild foods may be associated with differences in leptin concentrations. When individual foraging behavior was accounted for, worm infection significantly reduced rates of host weight gain. Housing laboratory mice in outdoor enclosures provided new insights into the resource costs of immune defense to helminth infection and how hosts modify their behavior to compensate for those costs.

High-resolution NMR for metabomics.

NMR spectroscopy has become a powerful tool for extensive qualitative and quantitative analysis, including temporal variations and system-wide assessment of all metabolites and small molecular components in complex mixtures of biological origin. In combination with additional analytical techniques, primarily mass spectrometry and chromatography methods, and with the support of involved statistical and other data analysis tools, NMR offers unprecedented insight into the biochemistry of living systems, and provides an outstanding tool for toxicology, disease diagnostics and risk assessment.

Stably folded de novo proteins from a designed combinatorial library.

Binary patterning of polar and nonpolar amino acids has been used as the key design feature for constructing large combinatorial libraries of de novo proteins. Each position in a binary patterned sequence is designed explicitly to be either polar or nonpolar; however, the precise identities of these amino acids are varied extensively. The combinatorial underpinnings of the "binary code" strategy preclude explicit design of particular side chains at specified positions. Therefore, packing interactions cannot be specified a priori. To assess whether the binary code strategy can nonetheless produce well-folded de novo proteins, we constructed a second-generation library based upon a new structural scaffold designed to fold into 102-residue four-helix bundles. Characterization of five proteins chosen arbitrarily from this new library revealed that (1) all are alpha-helical and quite stable; (2) four of the five contain an abundance of tertiary interactions indicative of well-ordered structures; and (3) one protein forms a well-folded structure with native-like features. The proteins from this new 102-residue library are substantially more stable and dramatically more native-like than those from an earlier binary patterned library of 74-residue sequences. These findings demonstrate that chain length is a crucial determinant of structural order in libraries of de novo four-helix bundles. Moreover, these results show that the binary code strategy--if applied to an appropriately designed structural scaffold--can generate large collections of stably folded and/or native-like proteins.

Changes in drug 13C NMR chemical shifts as a tool for monitoring interactions with DNA.

The antibiotic drug, netropsin, was complexed with the DNA oligonucleotide duplex [d(GGTATACC)]2 to monitor drug 13C NMR chemical shifts changes. The binding mode of netropsin to the minor groove of DNA is well-known, and served as a good model for evaluating the relative sensitivity of 13C chemical shifts to hydrogen bonding. Large downfield shifts were observed for four resonances of carbons that neighbor sites which are known to form hydrogen bond interactions with the DNA minor groove. Many of the remaining resonances of netropsin exhibit shielding or relatively smaller deshielding changes. Based on the model system presented here, large deshielding NMR shift changes of a ligand upon macromolecule binding can likely be attributed to hydrogen bond formation at nearby sites.