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Engineering improved Rubisco for the enhancement of photosynthesis is challenged by the alternate locations of the chloroplast rbcL gene and nuclear RbcS genes. Here we develop an RNAi-RbcS tobacco (Nicotiana tabacum) master-line, tobRrΔS, for producing homogenous plant Rubisco by rbcL-rbcS operon chloroplast transformation. Four genotypes encoding alternative rbcS genes and adjoining 5′-intergenic sequences revealed that Rubisco production was highest (50% of the wild type) in the lines incorporating a rbcS gene whose codon use and 5′ untranslated-region matched rbcL. Additional tobacco genotypes produced here incorporated differing potato (Solanum tuberosum) rbcL-rbcS operons that either encoded one of three mesophyll small subunits (pS1, pS2, and pS3) or the potato trichome pS(T)-subunit. The pS3-subunit caused impairment of potato Rubisco production by ∼15% relative to the lines producing pS1, pS2, or pS(T). However, the βA-βB loop Asn-55-His and Lys-57-Ser substitutions in the pS3-subunit improved carboxylation rates by 13% and carboxylation efficiency (CE) by 17%, relative to potato Rubisco incorporating pS1 or pS2-subunits. Tobacco photosynthesis and growth were most impaired in lines producing potato Rubisco incorporating the pS(T)-subunit, which reduced CE and CO(2)/O(2) specificity 40% and 15%, respectively. Returning the rbcS gene to the plant plastome provides an effective bioengineering chassis for introduction and evaluation of novel homogeneous Rubisco complexes in a whole plant context.

Este artículo contiene 11 páginas, 4 figuras, 1 tabla., The CO2-fixing enzyme Ribulose bisphosphate carboxylase-oxygenase (Rubisco) links the inorganic and organic phases of the global carbon cycle. In aquatic systems, the catalytic adaptation of algae Rubiscos has been more expansive and followed an evolutionary pathway that appears distinct to terrestrial plant Rubisco. Here, we extend this survey to differing seagrass species of the genus Posidonia to reveal how their disjunctive geographical distribution and diverged phylogeny, along with their CO2 concentrating mechanisms (CCMs) effectiveness, have impacted their Rubisco kinetic properties. The Rubisco from Posidonia species showed lower carboxylation efficiencies and lower sensitivity to O2 inhibition than those measured for terrestrial C3 and C4-plant Rubiscos. Compared with the Australian Posidonia species, Rubisco from the Mediterranean Posidonia oceanica had 1.5–2-fold lower carboxylation and oxygenation efficiencies, coinciding with effective CCMs and five Rubisco large subunit amino acid substitutions. Among the Australian Posidonia species, CCM effectiveness was higher in Posidonia sinuosa and lower in the deep-living Posidonia angustifolia, likely related to the 20%–35% lower Rubisco carboxylation efficiency in P. sinuosa and the two-fold higher Rubisco content in P. angustifolia. Our results suggest that the catalytic evolution of Posidonia Rubisco has been impacted by the low CO2 availability and gas exchange properties of marine environments, but with contrasting Rubisco kinetics according to the time of diversification among the species. As a result, the relationships between maximum carboxylation rate and CO2- and O2-affinities of Posidonia Rubiscos follow an alternative path to that characteristic of terrestrial angiosperm Rubiscos., This work was financially supported by the Spanish Ministry of Sciences and Innovation (State Research Agency), and the European Regional Development Funds (project PGC2018- 094621-B-I00) funded to J.G., and by the Australian Research Council (ARC) Centre of Excellence for Translational Photosynthesis CE140100015 funded to S.W. S.C.-B. was supported by an FPU Grant from the Spanish Ministry of Education. C.I. was supported by a postdoctoral grant from the government of the Balearic Islands. O.S. was supported by I + D+ i projects RYC2019-027073-I and PIE HOLOCENO 20213AT014 funded by MCIN/AEI/10.13039/501100011033 and FEDER.

Partition coefficients describe the equilibrium partitioning of a single, defined charge state of a solute between two liquid phases in contact, typically a neutral solute. Octanol–water partition coefficients ($$K_{\rm ow}$$), or their logarithms (log P), are frequently used as a measure of lipophilicity in drug discovery. The partition coefficient is a physicochemical property that captures the thermodynamics of relative solvation between aqueous and nonpolar phases, and therefore provides an excellent test for physics-based computational models that predict properties of pharmaceutical relevance such as protein-ligand binding affinities or hydration/solvation free energies. The SAMPL6 Part II octanol–water partition coefficient prediction challenge used a subset of kinase inhibitor fragment-like compounds from the SAMPL6 $$\hbox {p}{K}_{{\rm a}}$$ prediction challenge in a blind experimental benchmark. Following experimental data collection, the partition coefficient dataset was kept blinded until all predictions were collected from participating computational chemistry groups. A total of 91 submissions were received from 27 participating research groups. This paper presents the octanol–water log P dataset for this SAMPL6 Part II partition coefficient challenge, which consisted of 11 compounds (six 4-aminoquinazolines, two benzimidazole, one pyrazolo[3,4-d]pyrimidine, one pyridine, one 2-oxoquinoline substructure containing compounds) with log P values in the range of 1.95–4.09. We describe the potentiometric log P measurement protocol used to collect this dataset using a Sirius T3, discuss the limitations of this experimental approach, and share suggestions for future log P data collection efforts for the evaluation of computational methods.

In pharmaceutical oral drug delivery development, about 90% of drugs in the pipeline have poor aqueous solubility leading to severe challenges with oral bioavailability and translation to effective and safe drug products. Amorphous solid dispersions (ASDs) have been utilized to enhance the oral bioavailability of poorly soluble active pharmaceutical ingredients (APIs). However, a limited selection of regulatory-approved polymer excipients exists for the development and further understanding of tailor-made ASDs. Thus, a significant need exists to better understand how polymers can be designed to interact with specific API moieties. Here, we demonstrate how an automated combinatorial library approach can be applied to the synthesis and screening of polymer excipients for the model drug probucol. We synthesized a library of 25 random heteropolymers containing one hydrophilic monomer (2-hydroxypropyl acrylate (HPA)) and four hydrophobic monomers at varied incorporation. The performance of ASDs made by a rapid film casting method was evaluated by dissolution using ultra-performance liquid chromatography (UPLC) sampling at various time points. This combinatorial library and rapid screening strategy enabled us to identify a relationship between polymer hydrophobicity, monomer hydrophobic side group geometry, and API dissolution performance. Remarkably, the most effective synthesized polymers displayed slower drug release kinetics compared to industry standard polymer excipients, showing the ability to modulate the drug release profile. Future coupling of high throughput polymer synthesis, high throughput screening (HTS), and quantitative modeling would enable specification of designer polymer excipients for specific API functionalities.

Directed enzyme evolution has led to significant application of biocatalysis for improved chemical transformations throughout the scientific and industrial communities. Biocatalytic reactions utilizing evolved enzymes immobilized within microporous supports have realized unique advantages, including notably higher enzyme stability, higher enzyme load, enzyme reusability, and efficient product-enzyme separation. To date, limited analytical methodology is available to discern the spatial and chemical distribution of immobilized enzymes, in which techniques for surface visualization, enzyme stability, or activity are instead employed. New analytical tools to investigate enzyme immobilization are therefore needed. In this work, development, application, and evaluation of an analytical methodology to study enzyme immobilization is presented. Specifically, Raman hyperspectral imaging with principal component analysis, a multivariate method, is demonstrated for the first time to investigate evolved enzymes immobilized onto microporous supports for biocatalysis. Herein we demonstrate the ability to spatially and spectrally resolve evolved pantothenate kinase (PanK) immobilized onto two commercially-available, chemically-diverse porous resins. This analytical methodology is able to chemically distinguish evolved enzyme, resin, and chemical species pertinent to immobilization. As such, a new analytical approach to study immobilized biocatalysts is demonstrated, offering potential wide application for analysis of protein or biomolecule immobilization.

Partition coefficients describe the equilibrium partitioning of a single, defined charge state of a solute between two liquid phases in contact, typically a neutral solute. Octanol-water partition coefficients (Kow), or their logarithms (logP), are frequently used as a measure of lipophilicity in drug discovery. The partition coefficient is a physicochemical property that captures the thermodynamics of relative solvation between aqueous and nonpolar phases, and therefore provides an excellent test for physics-based computational models that predict properties of pharmaceutical relevance such as protein-ligand binding affinities or hydration/solvation free energies. The SAMPL6 Part II Octanol-Water Partition Coefficient Prediction Challenge used a subset of kinase inhibitor fragment-like compounds from the SAMPL6 pKaPrediction Challenge in a blind experimental benchmark. Following experimental data collection, the partition coefficient dataset was kept blinded until all predictions were collected from participating computational chemistry groups. A total of 91 submissions were received from 27 participating research groups. This paper presents the octanol-water logPdataset for this SAMPL6 Part II Partition Coefficient Challenge, which consisted of 11 compounds (six 4-aminoquinazolines, two benzimidazole, one pyrazolo[3,4-d]pyrimidine, one pyridine, one 2-oxoquinoline substructure containing compounds) with logPvalues in the range of 1.95–4.09. We describe the potentiometric logPmeasurement protocol used to collect this dataset using a Sirius T3, discuss the limitations of this experimental approach, and share suggestions for future logPdata collection efforts for the evaluation of computational methods.

Protocol for recombinant protein expression in E. coli for protein purification and subsequent enzyme assays, protein crystallography etc.

Determining the net charge and protonation states populated by a small molecule in an environment of interest or the cost of altering those protonation states upon transfer to another environment is a prerequisite for predicting its physicochemical and pharmaceutical properties. The environment of interest can be aqueous, an organic solvent, a protein binding site, or a lipid bilayer. Predicting the protonation state of a small molecule is essential to predicting its interactions with biological macromolecules using computational models. Incorrectly modeling the dominant protonation state, shifts in dominant protonation state, or the population of significant mixtures of protonation states can lead to large modeling errors that degrade the accuracy of physical modeling. Low accuracy hinders the use of physical modeling approaches for molecular design. For small molecules, the acid dissociation constant (pKa) is the primary quantity needed to determine the ionic states populated by a molecule in an aqueous solution at a given pH. As a part of SAMPL6 community challenge, we organized a blind pKa prediction component to assess the accuracy with which contemporary pKa prediction methods can predict this quantity, with the ultimate aim of assessing the expected impact on modeling errors this would induce. While a multitude of approaches for predicting pKa values currently exist, predicting the pKas of drug-like molecules can be difficult due to challenging properties such as multiple titratable sites, heterocycles, and tautomerization. For this challenge, we focused on set of 24 small molecules selected to resemble selective kinase inhibitors—an important class of therapeutics replete with titratable moieties. Using a Sirius T3 instrument that performs automated acid–base titrations, we used UV absorbance-based pKa measurements to construct a high-quality experimental reference dataset of macroscopic pKas for the evaluation of computational pKa prediction methodologies that was utilized in the SAMPL6 pKa challenge. For several compounds in which the microscopic protonation states associated with macroscopic pKas were ambiguous, we performed follow-up NMR experiments to disambiguate the microstates involved in the transition. This dataset provides a useful standard benchmark dataset for the evaluation of pKa prediction methodologies on kinase inhibitor-like compounds.

Protocol for recombinant protein expression in E. coli for protein purification and subsequent enzyme assays, protein crystallography etc.

It has been estimated that approximately 50% of all marketed drug molecules are manufactured and administered in the form of salts, often with the goal of improving solubility, dissolution rate, and efficacy of the drug. However, salt disproportionation during processing or storage is a common adverse effect in these formulations. Due to the heterogeneous nature of solid drug formulations, it is essential to characterize the drug substances noninvasively at micrometer resolution to understand the molecular mechanism of salt disproportionation. However, there is a lack of such capability with current characterization methods. In this study, we demonstrate that stimulated Raman scattering (SRS) microscopy can be used to provide sensitive and quantitative chemical imaging of the salt disproportionation reaction of pioglitazone hydrochloride (PIO-HCl) at a very low drug loading (1% w/w). Our findings illuminate a water mediated pathway of drug disproportionation and highlight the importance of noninvasive chemical imaging in a mechanistic study of solid-state chemical reactions.

A diverse set of drug and polymer combinations have been effectively evaluated utilizing a newly developed method called acoustic fusion to form amorphous solid dispersions (ASD) on the mg-scale, indicating that this approach is a general procedure that can be applied for ASD drug formulations. We have demonstrated the effectiveness of this acoustic fusion process by generating amorphous solid dispersions of various BCS class 2 and 4 drug candidates, including torcetrapib, itraconazole, and lopinavir, with a variety of polymer systems, including HPMCAS (L, M, and H), copovidone, Soluplus®, PEG1500, Vitamin-E TPGS, Kolliphor EL, and Eudragit, etc. Formulations of these ASD drug products demonstrated significantly elevated solubility of the drug substance compared to the solubility of the crystalline form of the drug. Acoustic fusion products using the model drug torcetrapib in either HPMCAS-LF, copovidone + Vitamin-E TPGS, or Soluplus®, exhibited enhanced supersaturation solubility in aqueous buffer in vitro compared to the drug in crystalline form, indicating that the acoustic fusion process resulted in an amorphous solid dispersion state similar to those formed in spray drying (SD) or hot melt extrusion (HME) processes. In vivo dosing of formulations of the acoustic fusion products in a rat pharmacokinetic study at a dose level of 10 mg/kg resulted in an improvement in exposures of approximately 8-fold by AUC(0–24) in comparison to a conventional suspension formulation of the drug material in crystalline form, thus validating the efficiency of this novel acoustic fusion approach for elevating the bioperformance in preclinical studies.

Localized drug delivery systems (DDSs) provide therapeutic levels of drug agent while mitigating side effects of systemic delivery. These systems offer controlled release over extended periods of time making them attractive therapies. Monitoring drug dissolution is vital for developing safe and effective means of drug delivery. Currently, dissolution characterization methods are limited to bulk analysis and cannot provide dissolution kinetics at high spatial resolution. However, dissolution rates of drug particles can be heterogeneous with influences from many factors. Insights into finer spatiotemporal dynamics of single particle dissolution could potentially improve pharmacokinetic modeling of dissolution for future drug development. In this work, we demonstrate high-resolution chemical mapping of entecavir, a hepatitis B antiviral drug, embedded in a slow release poly(d,l-lactic acid) formulation with stimulated Raman scattering (SRS) microscopy. By tracking the volume change of individual micron-sized drug particles within the polymer matrix, we establish an analytical protocol for quantitatively profiling dissolution of single crystalline particles in implant formulations in an in situ manner.

Determining the net charge and protonation states populated by a small molecule in an environment of interest or the cost of altering those protonation states upon transferto another environment is a prerequisite for predicting its physicochemical and pharmaceutical properties. The environment of interest can be aqueous, an organic solvent, a protein binding site, or a lipid bilayer. Predicting the protonation state of a small molecule is essential to predicting its interactions with biological macromolecules using computational models. Incorrectly modeling the dominant protonation state, shifts in dominant protonation state, or the population of significant mixtures of protonation states can lead to large modeling errors that degrade the accuracy of physical modeling. Low accuracy hinders the use of physical modeling approaches for molecular design. For small molecules, the acid dissociation constant (pK(a)) is the primary quantity needed to determine the ionic states populated by a molecule in an aqueous solution at a given pH. As a part of SAMPL6 community challenge, we organized a blind pK(a) prediction component to assess the accuracy with which contemporary pK(a) prediction methods can predict this quantity, with the ultimate aim of assessing the expected impact on modeling errors this would induce. While a multitude of approaches for predicting pK(a) values currently exist, predicting the pK(a)s of drug-like molecules can be difficult due to challenging properties such as multiple titratable sites, heterocycles, and tautomerization. For this challenge, we focused on set of 24 small molecules selected to resemble selective kinase inhibitors—an important class of therapeutics replete with titratable moieties. Using a Sirius T3 instrument that performs automated acid- base titrations, we used UV absorbance-based pK(a) measurements to construct a high-quality experimental reference dataset of macroscopic pK(a)s for the evaluation of computational pK(a) prediction methodologies that was utilized in the SAMPL6 pK(a) challenge. For several compounds in which the microscopic protonation states associated with macroscopic pK(a)s were ambiguous, we performed follow-up NMR experiments to disambiguate the microstates involved in the transition. This dataset provides a useful standard benchmark dataset for the evaluation of pK(a) prediction methodologies on kinase inhibitor-like compounds.

Determining the net charge and protonation states populated by a small molecule in an environment of interest or the cost of altering those protonation states upon transfer to another environment is a prerequisite for predicting its physicochemical and pharmaceutical properties. The environment of interest can be aqueous, an organic solvent, a protein binding site, or a lipid bilayer. Predicting the protonation state of a small molecule is essential to predicting its interactions with biological macromolecules using computational models. Incorrectly modeling the dominant protonation state, shifts in dominant protonation state, or the population of significant mixtures of protonation states can lead to large modeling errors that degrade the accuracy of physical modeling. Low accuracy hinders the use of physical modeling approaches for molecular design. For small molecules, the acid dissociation constant (pKa) is the primary quantity needed to determine the ionic states populated by a molecule in an aqueous solution at a given pH. As a part of SAMPL6 community challenge, we organized a blind pKa prediction component to assess the accuracy with which contemporary pKa prediction methods can predict this quantity, with the ultimate aim of assessing the expected impact on modeling errors this would induce. While a multitude of approaches for predicting pKa values currently exist, predicting the pKas of drug-like molecules can be difficult due to challenging properties such as multiple titratable sites, heterocycles, and tautomerization. For this challenge, we focused on set of 24 small molecules selected to resemble selective kinase inhibitors—an important class of therapeutics replete with titratable moieties. Using a Sirius T3 instrument that performs automated acid-base titrations, we used UV absorbance-based pKa measurements to construct a high-quality experimental reference dataset of macroscopic pKas for the evaluation of computational pKa prediction methodologies that was utilized in the SAMPL6 pKa challenge. For several compounds in which the microscopic protonation states associated with macroscopic pKas were ambiguous, we performed follow-up NMR experiments to disambiguate the microstates involved in the transition. This dataset provides a useful standard benchmark dataset for the evaluation of pKa prediction methodologies on kinase inhibitor-like compounds.AbbreviationsSAMPLStatistical Assessment of the Modeling of Proteins and LigandspKa-log10 acid dissociation equilibrium constantpsKa-log10 apparent acid dissociation equilibrium constant in cosolventDMSODimethyl sulfoxideISAlonic-strength adjustedSEMStandard error of the meanTFATarget factor analysisLC-MSLiquid chromatography - mass spectrometryNMRNuclear magnetic resonance spectroscopyHMBCHeteronuclear Multiple-Bond CorrelationTFA-ddeutero-trifluoroacetic acid

Protocol for recombinant protein expression in E. coli for enzyme assays, protein crystallography etc.

Triboluminescence (TL) is shown to enable selective detection of trace crystallinity within nominally amorphous solid dispersions (ASDs). ASDs are increasingly used for the preparation of pharmaceutical formulations, the physical stability of which can be negatively impacted by trace crystallinity introduced during manufacturing or storage. In the present study, TL measurements of a model ASD consisting of griseofulvin in polyethylene glycol produced limits of detection of 140 ppm. Separate studies of the particle size dependence of sucrose crystals and the dependence on polymorphism in clopidogrel bisulfate particles are both consistent with a mechanism for TL closely linked to the piezoelectric response of the crystalline fraction. Whereas disordered polymeric materials cannot support piezoelectric activity, molecular crystals produced from homochiral molecules adopt crystal structures that are overwhelmingly symmetry-allowed for piezoelectricity. Consequently, TL may provide a broadly applicable and simple experimental route for sensitive detection of trace crystallinity within nominally amorphous materials.

Endopolyploidy occurs when DNA replication takes place without subsequent mitotic nuclear division, resulting in cell-specific ploidy levels within tissues. In plants, endopolyploidy plays an important role in sustaining growth and development, but only a few studies have demonstrated a role in abiotic stress response. In this study, we investigated the function of ploidy level and nuclear and cell size in leaf expansion throughout development and tracked cell type-specific ploidy in the halophyte Mesembryanthemum crystallinum In addition to developmental endopolyploidy, we examined the effects of salinity stress on ploidy level. We focused specifically on epidermal bladder cells (EBC), which are modified balloon-like trichomes, due to their large size and role in salt accumulation. Our results demonstrate that ploidy increases as the leaves expand in a similar manner for each leaf type, and ploidy levels up to 512C were recorded for nuclei in EBC of leaves of adult plants. Salt treatment led to a significant increase in ploidy levels in the EBC, and these cells showed spatially related differences in their ploidy and nuclear and cell size depending on the positions on the leaf and stem surface. Transcriptome analysis highlighted salinity-induced changes in genes involved in DNA replication, cell cycle, endoreduplication, and trichome development in EBC. The increase in cell size and ploidy observed in M. crystallinum under salinity stress may contribute to salt tolerance by increasing the storage capacity for sodium sequestration brought about by higher metabolic activity driving rapid cell enlargement in the leaf tissue and EBC.

Matrix-assisted laser desorption/ionization (MALDI) coupled with a time-of-flight (TOF) mass-spectrometry (MS) detector is acknowledged to be very useful for analysis of biological molecules. At the same time, hydrogen-deuterium exchange (HDX) is a well-known technique for studying protein higher-order structure. However, coupling MALDI with HDX has been challenging because of undesired back-exchange reactions during analysis. In this report, we survey an approach that utilizes MALDI coupled with an automated sample preparation to compare global conformational changes of proteins under different solution conditions using differential HDX. A nonaqueous matrix was proposed for MALDI sample preparation to minimize undesirable back-exchange. An automated experimental setup based on the use of a liquid-handling robot and automated data acquisition allowed for tracking protein conformational changes as a difference in the number of protons exchanged to deuterons at specified solution conditions. Experimental time points to study the deuteration-labeling kinetics were obtained in a fully automated manner. The use of a nonaqueous matrix solution allowed experimental error to be minimized to within 1% RSD. We applied this newly developed MALDI-HDX workflow to study the effect of several common excipients on insulin folding stability. The observed results were corroborated by literature data and were obtained in a high-throughput and automated manner. The proposed MALDI-HDX approach can also be applied in a high-throughput manner for batch-to-batch higher-order structure comparison, as well as for the optimization of protein chemical modification reactions.

We compare a coherent Raman imaging modality, broadband coherent anti-Stokes Raman scattering (BCARS) microscopy, with spontaneous Raman microscopy for quantitative and qualitative assessment of multicomponent pharmaceuticals. Indomethacin was used as a model active pharmaceutical ingredient (API) and was analyzed in a tabulated solid dosage form, embedded within commonly used excipients. In comparison with wide-field spontaneous Raman chemical imaging, BCARS acquired images 10× faster, at higher spatiochemical resolution and with spectra of much higher SNR, eliminating the need for multivariate methods to identify chemical components. The significant increase in spatiochemical resolution allowed identification of an unanticipated API phase that was missed by the spontaneous wide-field method and bulk Raman spectroscopy. We confirmed the presence of the unanticipated API phase using confocal spontaneous Raman, which provided spatiochemical resolution similar to BCARS but at 100× slower acquisition times.

Parenteral delivery remains a compelling drug delivery route for both large- and small-molecule drugs and can bypass issues encountered with oral absorption. For injectable drug products, there is a strong patient preference for subcutaneous administration due to its convenience over intravenous infusion. However, in subcutaneous injection, in contrast to intravenous administration, the formulation is in contact with an extracellular matrix environment that behaves more like a gel than a fluid. This can impact the expected performance of a formulation. Since typical bulk fluid dissolution studies do not accurately simulate the subcutaneous environment, improved in vitro models to help better predict the behavior of the formulation are critical. Herein, we detail the development of a new model system consisting of a more physiologically relevant gel phase to simulate the rate of drug release and diffusion from a subcutaneous injection site using agarose hydrogels as a tissue mimic. This is coupled with continuous real-time data collection to accurately monitor drug diffusion. We show how this in vitro model can be used as an in vivo performance differentiator for different formulations of both large and small molecules. Thus, this model system can be used to improve optimization and understanding of new parenteral drug formulations in a rapid and convenient manner.

Crassulacean acid metabolism (CAM) is an alternative carbon fixation pathway that imparts high water-use efficiency in plants adapted to warm, semiarid climates. With concerns that global warming will negatively influence crop production, turning agricultural focus towards CAM plants may provide a solution to increase productivity using either unconventional crops on marginal land or incorporating CAM molecular mechanisms into conventional crops and improving water-use efficiency. For this to be feasible, deeper insights into CAM pathway regulation are essential. To facilitate this research new tools which simplify procedures for detecting and measuring CAM are needed. Here we describe a non-invasive, non-destructive, simplified method using infrared thermography for monitoring CAM in the annual desert succulent Mesembryanthemum crystallinum L. via detection of changes in leaf temperature brought about by the absence of transpiration due to daytime reduction in stomatal conductance. This method is sensitive, measuring temperature differences of ± 1°C, can be used in both the field and green house and is not restricted by leaf architecture. It offers an alternative to the commonly used gas exchange methods to measure CAM that are technically difficult to acquire and require the use of expensive and cumbersome equipment.

A streamlined methodology for cocrystal screening and scale-up has been developed. There are two parts to this procedure: (1) a high throughput screening approach for the rapid identification of potential cocrystal leads and (2) a new procedure for solvent selection, rapidly mapping the critical region in the ternary phase diagram, and determining a cocrystallization procedure for scale-up. Using this approach, we have discovered and scaled-up two new cocrystal forms of the pharmaceutically active compound 1 for the treatment of type II diabetes. This approach provided more than 2 g of cocrystal material suitable for biopharmaceutical evaluation. The physicochemical characterization and single crystal X-ray diffraction data of these cocrystals are also presented and discussed.

This study was conducted to evaluate the aggregation properties of an amphiphilic drug.Aggregation of the drug was studied by various methods including phase-contrast and polarized microscopy, spectrophotometry, surface tensiometry, atomic force microscopy, and dynamic light scattering. Lymph-cannulated rats were used to assess fractions of drug that were absorbed into lymphatics.During the pharmaceutical development of an alpha/gamma dual PPAR agonist, a derivative of a chromane-2-carboxylic acid (compound 1), it was discovered that the compound was able to form various aggregates in aqueous media from pH 6.5 to 7.1, whereas aggregating predominantly into micelles at higher pH values. Critical micelle concentrations seemed to be quite low, about 0.25 mM (0.17 mg/mL) in deionized water as determined by spectrophotometric (dye) and surface tensiometry (du Nuoy) methods. Aggregation of compound 1 into large supramolecular aggregates was visualized via phase-contrast microscopy and atomic force microscopy. The observed aggregates ranged from 250 nm to greater than 10 microm in size. Formation of liquid crystalline phases was observed by polarized microscopy as the material was gradually hydrated with water. Lymph studies in rats indicated that up to 6.9% of the orally administered dose of compound 1 in pH 6.5 buffer appeared in lymph, suggesting that supramolecular aggregation may also occur in vivo leading to partitioning between the portal and the lymph routes.The aforementioned supramolecular aggregation was found to have a profound effect on the pharmaceutical development of the drug and potentially on in vivo absorption of the drug.

Drug discovery and development is a challenging area. During the drug optimization process, available drug compounds often have poor physicochemical and biopharmaceutical properties, making the proper in vivo evaluation of these compounds difficult. To address these challenges, drug nanoparticles of poorly soluble compounds have emerged as a promising formulation approach. Herein, we report on a new drug sparing technology utilizing low shear acoustic mixing to rapidly identify optimized nanosuspension formulations for a wide range of compounds with dramatically improved material and time efficiencies. This approach has several key advantages over typical methods of preparing nanoparticles, including miniaturization of the milling process, the ability to evaluate multiple formulation conditions in a high throughput manner, and direct translation to optimized formulation scale-up for in vivo studies. Furthermore, there are additional benefits obtained with this new approach resulting in nanosuspension formulations with significant stability and physical property enhancements over those obtained using traditional media milling techniques. These advantages make this approach highly suitable for the rapid evaluation of potential drug candidates in the discovery and development space.

The synthesis of a new, noncovalent anthracene-dimethylaniline dyad (ensemble I) held together via guanosine-cytidine Watson-Crick base-pairing interactions is reported. Upon excitation at 420 nm, photoinduced electron-transfer from the dimethylaniline donor to the singlet excited state of the anthracene acceptor occurs, as inferred from a combination of time-resolved fluorescence quenching and transient absorption measurements. In toluene at room temperature, the rate constants for photoinduced intraensemble electron-transfer and subsequent back-electron-transfer (charge recombination) are k(CS) = (3.5 +/- 0.03) x 10(10) s(-1) and k(CR) = (1.42 +/- 0.03) x 10(9) s(-1), respectively.

A new fiber-optic high-pressure cell for time-resolved absorbance and fluorescence measurements in near- and supercritical solvents is presented. It consists entirely of commercial components, thus facilitating ease of construction and maintenance and facilitating component exchange to incorporate materials that can withstand a broad range of pressures and temperatures. The adaptability of the cell and the applicability of the pressure-sealing technique to a variety of emission and fast kinetic measurements are discussed.

The exponential series method of analysis is applied to single photon counting measurements of phenanthrene fluorescence decay in supercritical carbon dioxide at 32 and 35 °C and at pressures ranging from 76 to 207 bar for chromophore concentrations between 5 × 10-5 and 5 × 10-6 M. The analysis revealed trimodal fluorescence lifetime distributions near the critical temperature which can be explained by the presence of solvent−solute and solute−solute clustering. This local aggregation causes an increase in nonradiative relaxations and, therefore, a decrease in the observed fluorescence lifetimes. Concentration and density gradients are responsible for these three unique lifetimes (trimodal) in the supercritical fluid, as contrasted with the single lifetime observed in a typical organic solvent. An increase in temperature to 35 °C induces no change in lifetime distributions at high chromophore concentration, but the trimodal distribution collapses to a single mode at lower concentrations, indicating that t...

Contrary to a previous report, it is concluded that formation of methanol adducts to 3-methyl-2-cyclohexenones and of deconjugated enones on irradiation of the enones in acidified solutions proceeds via protonation of the intermediate enone π,π* triplet excited state and not by protonation of a relatively long-lived ground state trans-cyclohexenone. A rate constant for protonation of the triplet state of 3-methyl-2-cyclohexenone by sulfuric acid of 1.7 × 109 M−1 s−1 was determined by laser flash photolysis in ethyl acetate. Based on quantum efficiencies of product formation, a rate constant of ca. 108 M−1 s−1 was estimated for protonation of the enone triplet by acetic acid, which is too small to cause measurable reduction in the triplet state lifetime in the mM concentration range used in the preparative studies. The intermediate carbocation can be trapped by methanol, or revert to starting enone or the exocyclic deconjugated enone by loss of a proton. Since products revert to starting materials in an acid-catalyzed process, there is an acid concentration at which the yields of products are optimal. This concentration is ca. 6 mM for acetic acid, but is only 0.1 mM for p-toluenesulfonic or sulfuric acids. Product formation could be quenched using 1-methylnaphthalene and cyclopentene as triplet quenchers; in the latter case, formation of [2 + 2] photoadducts was observed to compete with formation of methanol adducts. Quenching rate constants were determined by laser flash studies. Keywords: laser flash photolysis, kinetic absorption spectroscopy (KAS), photoacoustic calorimetry (PAC), protonation of triplet states, trans-cyclohexenones.

The thermal diffusivity of a thin organic dye layer deposited atop thin films of the high temperature superconductor YBa2Cu3O7−δ is measured using a pulsed laser flash method. Here, the underlying superconductor acts as a highly sensitive temperature transducer after appropriate conversion of the transient voltage response from 7 ns optical pulses. Film surface temperature decays for several thicknesses of the dye layers were evaluated; these decays exhibited a linear dependence of the time at half temperature maximum versus thickness squared. Three dimensional finite difference modeling was used to study and extract the thermal diffusivity values of the thin organic layers as well as to investigate the transient temperature distributions within the dye and superconductor areas.

Rubisco assimilates CO2 to form the sugars that fuel life on earth. Correlations between rubisco kinetic traits across species have led to the proposition that rubisco adaptation is highly constrained by catalytic trade-offs. However, these analyses did not consider the phylogenetic context of the enzymes that were analysed. Thus, it is possible that the correlations observed were an artefact of the presence of phylogenetic signal in rubisco kinetics and the phylogenetic relationship between the species that were sampled. Here, we conducted a phylogenetically-resolved analysis of rubisco kinetics and show that there is a significant phylogenetic signal in rubisco kinetic traits. We re-evaluated the extent of catalytic trade-offs accounting for this phylogenetic signal and found that all were attenuated. Following phylogenetic correction, the largest catalytic trade-offs were observed between the Michaelis constant for CO2 and carboxylase turnover (∼21-37 %), and between the Michaelis constants for CO2 and O2 (∼9-19 %), respectively. All other catalytic trade-offs were substantially attenuated such that they were marginal (4 photosynthesis. Finally, we show that phylogenetic constraints (most likely caused by a slow rate of molecular evolution) have played a larger role than catalytic trade-offs in limiting the evolution of rubisco kinetics. Thus, although there is strong evidence for some catalytic trade-offs, rubisco adaptation has been more limited by phylogenetic constraint than by the combined action of all such trade-offs.