Electrolytes with moderate lithium polysulfide solubility for high-performance long-calendar-life lithium-sulfur batteries.

Lithium-sulfur (Li-S) batteries with high energy density and low cost are promising for next-generation energy storage. However, their cycling stability is plagued by the high solubility of lithium polysulfide (LiPS) intermediates, causing fast capacity decay and severe self-discharge. Exploring electrolytes with low LiPS solubility has shown promising results toward addressing these challenges. However, here, we report that electrolytes with moderate LiPS solubility are more effective for simultaneously limiting the shuttling effect and achieving good Li-S reaction kinetics. We explored a range of solubility from 37 to 1,100 mM (based on S atom, [S]) and found that a moderate solubility from 50 to 200 mM [S] performed the best. Using a series of electrolyte solvents with various degrees of fluorination, we formulated the Single-Solvent, Single-Salt, Standard Salt concentration with Moderate LiPSs solubility Electrolytes (termed S6MILE) for Li-S batteries. Among the designed electrolytes, Li-S cells using fluorinated-1,2-diethoxyethane S6MILE (F4DEE-S6MILE) showed the highest capacity of 1,160 mAh g-1 at 0.05 C at room temperature. At 60 °C, fluorinated-1,4-dimethoxybutane S6MILE (F4DMB-S6MILE) gave the highest capacity of 1,526 mAh g-1 at 0.05 C and an average CE of 99.89% for 150 cycles at 0.2 C under lean electrolyte conditions. This is a fivefold increase in cycle life compared with other conventional ether-based electrolytes. Moreover, we observed a long calendar aging life, with a capacity increase/recovery of 4.3% after resting for 30 d using F4DMB-S6MILE. Furthermore, the correlation between LiPS solubility, degree of fluorination of the electrolyte solvent, and battery performance was systematically investigated.

Sequence-based prediction of pH-dependent protein solubility using CamSol.

Solubility is a property of central importance for the use of proteins in research in molecular and cell biology and in applications in biotechnology and medicine. Since experimental methods for measuring protein solubility are material intensive and time consuming, computational methods have recently emerged to enable the rapid and inexpensive screening of solubility for large libraries of proteins, as it is routinely required in development pipelines. Here, we describe the development of one such method to include in the predictions the effect of the pH on solubility. We illustrate the resulting pH-dependent predictions on a variety of antibodies and other proteins to demonstrate that these predictions achieve an accuracy comparable with that of experimental methods. We make this method publicly available at https://www-cohsoftware.ch.cam.ac.uk/index.php/camsolph, as the version 3.0 of CamSol.

Chloroplastic ascorbate modifies plant metabolism and may act as a metabolite signal regardless of oxidative stress.

Ascorbate is a major plant metabolite that plays crucial roles in various processes, from reactive oxygen scavenging to epigenetic regulation. However, to what extent and how ascorbate modulates metabolism is largely unknown. We investigated the consequences of chloroplastic and total cellular ascorbate-deficiencies by studying chloroplastic ascorbate-transporter mutant lines lacking PHOSPHATE TRANSPORTER 4; 4 (PHT4; 4) , and the ascorbate-deficient vtc2-4 mutant of Arabidopsis (Arabidopsis thaliana). Under regular growth conditions, both ascorbate deficiencies caused minor alterations in photosynthesis, with no apparent signs of oxidative damage. In contrast, metabolomics analysis revealed global and largely overlapping alterations in the metabolome profiles of both ascorbate-deficiency mutants, suggesting that chloroplastic ascorbate modulates plant metabolism. We observed significant alterations in amino acid metabolism, particularly in arginine metabolism, activation of nucleotide salvage pathways, and changes in secondary metabolism. In addition, proteome-wide analysis of thermostability revealed that ascorbate may interact with enzymes involved in arginine metabolism, the Calvin-Benson cycle, and several photosynthetic electron transport components. Overall, our results suggest that, independently of oxidative stress, chloroplastic ascorbate modulates the activity of diverse metabolic pathways in vascular plants and may act as an internal metabolic signal.

ADAMTS-7 Modulates Atherosclerotic Plaque Formation by Degradation of TIMP-1.

BACKGROUND: The ADAMTS7 locus was genome-wide significantly associated with coronary artery disease. Lack of the ECM (extracellular matrix) protease ADAMTS-7 (A disintegrin and metalloproteinase-7) was shown to reduce atherosclerotic plaque formation. Here, we sought to identify molecular mechanisms and downstream targets of ADAMTS-7 mediating the risk of atherosclerosis. METHODS: Targets of ADAMTS-7 were identified by high-resolution mass spectrometry of atherosclerotic plaques from Apoe-/- and Apoe-/-Adamts7-/- mice. ECM proteins were identified using solubility profiling. Putative targets were validated using immunofluorescence, in vitro degradation assays, coimmunoprecipitation, and Förster resonance energy transfer-based protein-protein interaction assays. ADAMTS7 expression was measured in fibrous caps of human carotid artery plaques. RESULTS: In humans, ADAMTS7 expression was higher in caps of unstable as compared to stable carotid plaques. Compared to Apoe-/- mice, atherosclerotic aortas of Apoe-/- mice lacking Adamts-7 (Apoe-/-Adamts7-/-) contained higher protein levels of Timp-1 (tissue inhibitor of metalloprotease-1). In coimmunoprecipitation experiments, the catalytic domain of ADAMTS-7 bound to TIMP-1, which was degraded in the presence of ADAMTS-7 in vitro. ADAMTS-7 reduced the inhibitory capacity of TIMP-1 at its canonical target MMP-9 (matrix metalloprotease-9). As a downstream mechanism, we investigated collagen content in plaques of Apoe-/- and Apoe-/-Adamts7-/- mice after a Western diet. Picrosirius red staining of the aortic root revealed less collagen as a readout of higher MMP-9 activity in Apoe-/- as compared to Apoe-/- Adamts7-/- mice. To facilitate high-throughput screening for ADAMTS-7 inhibitors with the aim of decreasing TIMP-1 degradation, we designed a Förster resonance energy transfer-based assay targeting the ADAMTS-7 catalytic site. CONCLUSIONS: ADAMTS-7, which is induced in unstable atherosclerotic plaques, decreases TIMP-1 stability reducing its inhibitory effect on MMP-9, which is known to promote collagen degradation and is likewise associated with coronary artery disease. Disrupting the interaction of ADAMTS-7 and TIMP-1 might be a strategy to increase collagen content and plaque stability for the reduction of atherosclerosis-related events.

Ten Years of Extracellular Matrix Proteomics: Accomplishments, Challenges, and Future Perspectives.

The extracellular matrix (ECM) is a complex assembly of hundreds of proteins forming the architectural scaffold of multicellular organisms. In addition to its structural role, the ECM conveys signals orchestrating cellular phenotypes. Alterations of ECM composition, abundance, structure, or mechanics have been linked to diseases and disorders affecting all physiological systems, including fibrosis and cancer. Deciphering the protein composition of the ECM and how it changes in pathophysiological contexts is thus the first step toward understanding the roles of the ECM in health and disease and toward the development of therapeutic strategies to correct disease-causing ECM alterations. Potentially, the ECM also represents a vast, yet untapped reservoir of disease biomarkers. ECM proteins are characterized by unique biochemical properties that have hindered their study: they are large, heavily and uniquely posttranslationally modified, and highly insoluble. Overcoming these challenges, we and others have devised mass-spectrometry-based proteomic approaches to define the ECM composition, or "matrisome," of tissues. This first part of this review provides a historical overview of ECM proteomics research and presents the latest advances that now allow the profiling of the ECM of healthy and diseased tissues. The second part highlights recent examples illustrating how ECM proteomics has emerged as a powerful discovery pipeline to identify prognostic cancer biomarkers. The third part discusses remaining challenges limiting our ability to translate findings to clinical application and proposes approaches to overcome them. Lastly, the review introduces readers to resources available to facilitate the interpretation of ECM proteomics datasets. The ECM was once thought to be impenetrable. Mass spectrometry-based proteomics has proven to be a powerful tool to decode the ECM. In light of the progress made over the past decade, there are reasons to believe that the in-depth exploration of the matrisome is within reach and that we may soon witness the first translational application of ECM proteomics.

Improved drug target deconvolution with PISA-DIA using an extended, overlapping temperature gradient.

Thermal proteome profiling (TPP) is a powerful tool for drug target deconvolution. Recently, data-independent acquisition mass spectrometry (DIA-MS) approaches have demonstrated significant improvements to depth and missingness in proteome data, but traditional TPP (a.k.a. CEllular Thermal Shift Assay "CETSA") workflows typically employ multiplexing reagents reliant on data-dependent acquisition (DDA). Herein, we introduce a new experimental design for the Proteome Integral Solubility Alteration via label-free DIA approach (PISA-DIA). We highlight the proteome coverage and sensitivity achieved by using multiple overlapping thermal gradients alongside DIA-MS, which maximizes efficiencies in PISA sample concatenation and safeguards against missing protein targets that exist at high melting temperatures. We demonstrate our extended PISA-DIA design has superior proteome coverage as compared to using tandem-mass tags (TMT) necessitating DDA-MS analysis. Importantly, we demonstrate our PISA-DIA approach has the quantitative and statistical rigor using A-1331852, a specific inhibitor of BCL-xL. Due to the high melt temperature of this protein target, we utilized our extended multiple gradient PISA-DIA workflow to identify BCL-xL. We assert our novel overlapping gradient PISA-DIA-MS approach is ideal for unbiased drug target deconvolution, spanning a large temperature range whilst minimizing target dropout between gradients, increasing the likelihood of resolving the protein targets of novel compounds.

GATSol, an enhanced predictor of protein solubility through the synergy of 3D structure graph and large language modeling.

BACKGROUND: Protein solubility is a critically important physicochemical property closely related to protein expression. For example, it is one of the main factors to be considered in the design and production of antibody drugs and a prerequisite for realizing various protein functions. Although several solubility prediction models have emerged in recent years, many of these models are limited to capturing information embedded in one-dimensional amino acid sequences, resulting in unsatisfactory predictive performance. RESULTS: In this study, we introduce a novel Graph Attention network-based protein Solubility model, GATSol, which represents the 3D structure of proteins as a protein graph. In addition to the node features of amino acids extracted by the state-of-the-art protein large language model, GATSol utilizes amino acid distance maps generated using the latest AlphaFold technology. Rigorous testing on independent eSOL and the Saccharomyces cerevisiae test datasets has shown that GATSol outperforms most recently introduced models, especially with respect to the coefficient of determination R2, which reaches 0.517 and 0.424, respectively. It outperforms the current state-of-the-art GraphSol by 18.4% on the S. cerevisiae_test set. CONCLUSIONS: GATSol captures 3D dimensional features of proteins by building protein graphs, which significantly improves the accuracy of protein solubility prediction. Recent advances in protein structure modeling allow our method to incorporate spatial structure features extracted from predicted structures into the model by relying only on the input of protein sequences, which simplifies the entire graph neural network prediction process, making it more user-friendly and efficient. As a result, GATSol may help prioritize highly soluble proteins, ultimately reducing the cost and effort of experimental work. The source code and data of the GATSol model are freely available at https://github.com/binbinbinv/GATSol .

Mechanochemical synthesis of novel metronidazole cocrystal: Structure characterization and pharmaceutical properties study.

A new cocrystalline form of metronidazole (MET) with propyl gallate (PRO), referred to as MET-PRO, has been successfully synthesized and characterized. Structural characterization reveals that MET and PRO are present in a 1:1 ratio within the cocrystal lattice, with one water molecule equivalent incorporated into the structure. This arrangement facilitates the formation of MET-PRO heterodimers and multiple stable units, collectively constructing a three-dimensional supramolecular network. The solubility and permeability of the current cocrystal, along with the parent drug MET, are evaluated under physiological pH conditions. Experimental findings reveal that MET within the cocrystal exhibits a 1.54-2.37 folds increase in solubility and approximately a threefold improvement in permeability compared to its standalone form. Intriguingly, these concurrent enhancements in the physicochemical properties of MET lead to augmented antibacterial activity in vitro, evidenced by a reduction in minimum inhibitory concentration. Even more intriguingly, the enhanced physicochemical properties observed in vitro for the current cocrystal translate into tangible pharmacokinetic benefits in vivo, characterized by prolonged half-life and enhanced bioavailability. Consequently, this research not only introduces a fresh crystal structure for antibacterial medication but also presents approach for optimizing drug properties across in vitro and in vivo settings, while concurrently bolstering the antibacterial effectiveness of MET through pharmaceutical cocrystallization techniques.

Predicting the effects of mutations on protein solubility using graph convolution network and protein language model representation.

Solubility is one of the most important properties of protein. Protein solubility can be greatly changed by single amino acid mutations and the reduced protein solubility could lead to diseases. Since experimental methods to determine solubility are time-consuming and expensive, in-silico methods have been developed to predict the protein solubility changes caused by mutations mostly through protein evolution information. However, these methods are slow since it takes long time to obtain evolution information through multiple sequence alignment. In addition, these methods are of low performance because they do not fully utilize protein 3D structures due to a lack of experimental structures for most proteins. Here, we proposed a sequence-based method DeepMutSol to predict solubility change from residual mutations based on the Graph Convolutional Neural Network (GCN), where the protein graph was initiated according to predicted protein structure from Alphafold2, and the nodes (residues) were represented by protein language embeddings. To circumvent the small data of solubility changes, we further pretrained the model over absolute protein solubility. DeepMutSol was shown to outperform state-of-the-art methods in benchmark tests. In addition, we applied the method to clinically relevant genes from the ClinVar database and the predicted solubility changes were shown able to separate pathogenic mutations. All of the data sets and the source code are available at https://github.com/biomed-AI/DeepMutSol.

Soft-sphere continuum solvation models for nonaqueous solvents.

Solvation effects profoundly influence the characteristics and behavior of chemical systems in liquid solutions. The interaction between solute and solvent molecules intricately impacts solubility, reactivity, stability, and various chemical processes. Continuum solvation models gained prominence in quantum chemistry by implicitly capturing these interactions and enabling efficient investigations of diverse chemical systems in solution. In comparison, continuum solvation models in condensed matter simulation are very recent. Among these, the self-consistent continuum solvation (SCCS) and the soft-sphere continuum solvation models (SSCS) have been among the first to be successfully parameterized and extended to model periodic systems in aqueous solutions and electrolytes. As most continuum approaches, these models depend on a number of parameters that are linked to experimental or theoretical properties of the solvent, or that can be tuned based on reference data. Here, we present a systematic parameterization of the SSCS model for over 100 nonaqueous solvents. We validate the model's efficacy across diverse solvent environments by leveraging experimental solvation-free energies and partition coefficients from comprehensive databases. The average root means square error over all the solvents was calculated as 0.85 kcal/mol which is below the chemical accuracy (1 kcal/mol). Similarly to what has been reported by Hille et al. (J. Chem. Phys. 2019, 150, 041710.) for the SCCS model, a single-parameter model accurately reproduces experimental solvation energies, showcasing the transferability and predictive power of these continuum approaches. Our findings underscore the potential for a unified approach to predict solvation properties, paving the way for enhanced computational studies across various chemical environments.

Stability-based approaches in chemoproteomics.

Target deconvolution can help understand how compounds exert therapeutic effects and can accelerate drug discovery by helping optimise safety and efficacy, revealing mechanisms of action, anticipate off-target effects and identifying opportunities for therapeutic expansion. Chemoproteomics, a combination of chemical biology with mass spectrometry has transformed target deconvolution. This review discusses modification-free chemoproteomic approaches that leverage the change in protein thermodynamics induced by small molecule ligand binding. Unlike modification-based methods relying on enriching specific protein targets, these approaches offer proteome-wide evaluations, driven by advancements in mass spectrometry sensitivity, increasing proteome coverage and quantitation methods. Advances in methods based on denaturation/precipitation by thermal or chemical denaturation, or by protease degradation are evaluated, emphasising the evolving landscape of chemoproteomics and its potential impact on future drug-development strategies.

What Matters to Fabrication of Type II Porous Liquids: A Case Study on Metallocages and Bulky Ionic Liquid?

Porosity in bulky solvents can be created by the methods of dispersing and dissolving porous hosts or by their chemical adornment. And the ensuing liquids with cavities offer requisite high gas uptakes. Intriguingly, metal-organic cages (MOCs) as discrete nanoporous hosts have been utilized recently as soluble entities to obtain a series of interesting type II porous liquids (PLs). Yet, factors affecting the fabrication of type II PLs have not been disclosed. Herein, three metallocages (NUT-101, ZrT-1-NH2, and ZrT-1) with the same zirconocene nodes but different organic ligands are chosen as porous hosts and a polyethylene-glycol (PEG) linked bis-imidazolium based IL, IL(NTf2), is used as a bulky solvent. It is revealed for the first time that the generation of type II PL depends upon the flexibility of MOCs and the interaction between MOCs and solvent molecules. The maximum solubility is observed with NUT-101 (5%) in IL(NTf2) while ZrT-1-NH2 and ZrT-1 remain least soluble (0.5% and 0.2%). As a result, PL-NUT-101-5% with most intrinsic cavities shows higher CO2 uptake (0.576 mmol g-1) than PL-ZrT-1-NH2-0.5% and PL-ZrT-1-0.2% as well as those reported type II PLs.

Grinding-Induced Water Solubility Exhibited by Mechanochromic Luminescent Supramolecular Fibers.

Most mechanochromic luminescent compounds are crystalline and highly hydrophobic; however, mechanochromic luminescent molecular assemblies comprising amphiphilic molecules have rarely been explored. This study investigated mechanochromic luminescent supramolecular fibers composed of dumbbell-shaped 9,10-bis(phenylethynyl)anthracene-based amphiphiles without any tetraethylene glycol (TEG) substituents or with two TEG substituents. Both amphiphiles formed water-insoluble supramolecular fibers via linear hydrogen bond formation. Both compounds acquired water solubility when solid samples composed of supramolecular fibers are ground. Grinding induces the conversion of 1D supramolecular fibers into micellar assemblies where fluorophores can form excimers, thereby resulting in a large redshift in the fluorescence spectra. Excimer emission from the ground amphiphile without TEG chains is retained after dissolution in water. The micelles are stable in water because hydrophilic dendrons surround the hydrophobic luminophores. By contrast, when water is added to a ground amphiphile having TEG substituents, fragmented supramolecular fibers with the same molecular arrangement as the initial supramolecular fibers are observed, because fragmented fibers are thermodynamically preferable to micelles as the hydrophobic arrays of fluorophores are covered with hydrophilic TEG chains. This leads to the recovery of the initial fluorescent properties for the latter amphiphile. These supramolecular fibers can be used as practical mechanosensors to detect forces at the mesoscale.

Investigating Protein Binding with the Isothermal Ligand-induced Resolubilization Assay.

Target engagement assays typically detect and quantify the direct physical interaction of a protein of interest and its ligand through stability changes upon ligand binding. Commonly used target engagement methods detect ligand-induced stability by subjecting samples to thermal or proteolytic stress. Here we describe a new variation to these approaches called Isothermal Ligand-induced Resolubilization Assay (ILIRA), which utilizes lyotropic solubility stress to measure ligand binding through changes in target protein solubility. We identified distinct buffer systems and salt concentrations that compromised protein solubility for four diverse proteins: dihydrofolate reductase (DHFR), nucleoside diphosphate-linked moiety X motif 5 (NUDT5), poly [ADP-ribose] polymerase 1 (PARP1), and protein arginine N-methyltransferase 1 (PRMT1). Ligand-induced solubility rescue was demonstrated for these proteins, suggesting that ILIRA can be used as an additional target engagement technique. Differences in ligand-induced protein solubility were assessed by Coomassie blue staining for SDS-PAGE and dot blot, as well as by NanoOrange, Thioflavin T, and Proteostat fluorescence, thus offering flexibility for readout and assay throughput.

A spectrophotometric analysis of extracted water-soluble phenolic metabolites of lichens.

MAIN CONCLUSION: Rainwater most probably constitutes a relatively effective solvent for lichen substances in nature which have the potential to provide for human and environmental needs in the future. The aims were (i) to test the hypothesis on the potential solubility of lichen phenolic compounds using rainwater under conditions that partly reflect the natural environment and (ii) to propose new and effective methods for the water extraction of lichen substances. The results of spectrophotometric analyses of total phenolic metabolites in rainwater-based extracts from epigeic and epiphytic lichens, employing the Folin-Ciocalteu (F.-C.) method, are presented. The water solvent was tested at three pH levels: natural, 3, and 9. Extraction methods were undertaken from two perspectives: the partial imitation of natural environmental conditions and the potential use of extraction for economic purposes. From an ecological perspective, room-temperature water extraction ('cold' method) was used for 10-, 60-, and 120-min extraction periods. A variant of water extraction at analogous time intervals was an 'insolation' with a 100W light bulb to simulate the heat energy of the sun. For economic purposes, the water extraction method used the Soxhlet apparatus and its modified version, the 'tea-extraction' method ('hot' ones). The results showed that those extractions without an external heat source were almost ineffective, but insolation over 60- and 120-min periods proved to be more effective. Both tested 'hot' methods also proved to be effective, especially the 'tea-extraction' one. Generally, an increase in the concentration of phenolic compounds in water extracts resulted from an increasing solvent pH. The results show the probable involvement of lichen substances in biogeochemical processes in nature and their promising use for a variety of human necessities.

Benzo-Crown-Ether Functionalized O-BODIPY Probes for Cations - A Selective Fluorescent Probe for Ba2.

Herein, we report the synthesis and sensing characteristics of 4,4'-methoxy-substituted BODIPY fluorescent probes (O-BODIPYs) 3, 4 and 5 equipped with differently sized benzo-crown ethers (cf. Scheme 1, 3 (benzo-15-crown-5), 4 (benzo-18-crown-6) and 5 (benzo-21-crown7)). O-BODIPYs 3, 4 and 5 exhibited in comparison to their known F-BODIPY analogues 3a, 4a and 5a (cf. Scheme 1) an improved solubility in aqueous medium and higher fluorescence quantum yields. Fluorometric study in aqueous solutions of 3, 4 and 5 in the presence of different cations show cation induced fluorescence enhancements (FE). Compared to the benzo-crown ether substituted F-BODIPY analogues 3a, 4a and 5a, we found for the free O-BODIPYs 3, 4 and 5 higher fluorescence quantum yields (φf) but lower cation induced FEs. We show that in aqueous medium the fluorescence quenching process (OFF switching), a photoinduced electron transfer, in O-BODIPYs 3, 4 and 5 is less effective and consequently sensitive and selective ON switching of the fluorescence by cations, too. Albeit these observations the novel benzo-21-crown-7 equipped fluorescent probe 5 exhibits a good fluorometric Ba2+ selectivity and Ba2+ sensitivity in conjunction to their aqueous solubility.

Insights into Hildebrand Solubility Parameters - Contributions from Cohesive Energies or Electrophilicity Densities?

We introduce certain concepts and expressions from conceptual density functional theory (DFT) to study the properties of the Hildebrand solubility parameter. The original form of the Hildebrand solubility parameter is used to qualitatively estimate solubilities for various apolar and aprotic substances and solvents and is based on the square root of the cohesive energy density. Our results show that a revised expression allows the replacement of cohesive energy densities by electrophilicity densities, which are numerically accessible by simple DFT calculations. As an extension, the reformulated expression provides a deeper interpretation of the main contributions and, in particular, emphasizes the importance of charge transfer mechanisms. All calculated values of the Hildebrand parameters for a large number of common solvents are compared with experimental values and show good agreement for non- or moderately polar aprotic solvents in agreement with the original formulation of the Hildebrand solubility parameters. The observed deviations for more polar and protic solvents define robust limits from the original formulation which remain valid. Likewise, we show that the use of machine learning methods leads to only slightly better predictability.

Interplay of Drug-Polymer Interactions and Release Performance for HPMCAS-Based Amorphous Solid Dispersions.

The interplay between drug and polymer chemistry and its impact on drug release from an amorphous solid dispersion (ASD) is a relatively underexplored area. Herein, the release rates of several drugs of diverse chemistry from hydroxypropyl methylcellulose acetate succinate (HPMCAS)-based ASDs were explored using surface area normalized dissolution. The tendency of the drug to form an insoluble complex with HPMCAS was determined through coprecipitation experiments. The role of pH and the extent of drug ionization were probed to evaluate the role of electrostatic interactions in complex formation. Relationships between the extent of complexation and the drug release rate from an ASD were observed, whereby the drugs could be divided into two groups. Drugs with a low extent of insoluble complex formation with HPMCAS tended to be neutral or anionic and showed reasonable release at pH 6.8 even at higher drug loadings. Cationic drugs formed insoluble complexes with HPMCAS and showed poor release when formulated as an ASD. Thus, and somewhat counterintuitively, a weakly basic drug showed a reduced release rate from an ASD at a bulk solution pH where it was ionized, relative to when unionized. The opposite trend was observed in the absence of polymer for the neat amorphous drug. In conclusion, electrostatic interactions between HPMCAS and lipophilic cationic drugs led to insoluble complex formation, which in turn resulted in ASDs with poor release performance.

Preparation and Characterization of a Rifampicin Coamorphous Material with Tromethamine Coformer: An Experimental-Theoretical Study.

Rifampicin (RIF) is an antibiotic used to treat tuberculosis and leprosy. Even though RIF is a market-available drug, it has a low aqueous solubility, hindering its bioavailability. Among the strategies for bioavailability improvement of poorly soluble drugs, coamorphous systems have been revealed as an alternative in the increase of the aqueous solubility of drug systems and at the same time also increasing the amorphous state stability and dissolution rate when compared with the neat drug. In this work, a new coamorphous form from RIF and tromethamine (TRIS) was synthesized by slow evaporation. Structural, electronic, and thermodynamic properties and solvation effects, as well as drug-coformer intermolecular interactions, were studied through density functional theory (DFT) calculations. Powder X-ray diffraction (PXRD) data allowed us to verify the formation of a new coamorphous. In addition, the DFT study indicates a possible intermolecular interaction by hydrogen bonds between the available amino and carbonyl groups of RIF and the hydroxyl and amino groups of TRIS. The theoretical spectra obtained are in good agreement with the experimental data, suggesting the main interactions occurring in the formation of the coamorphous system. PXRD was used to study the physical stability of the coamorphous system under accelerated ICH conditions (40 °C and 75% RH), indicating that the material remained in an amorphous state up to 180 days. The thermogravimetry result of this material showed a good thermal stability up to 153 °C, and differential scanning calorimetry showed that the glass temperature (Tg) was at 70.0 °C. Solubility studies demonstrated an increase in the solubility of RIF by 5.5-fold when compared with its crystalline counterpart. Therefore, this new material presents critical parameters that can be considered in the development of new coamorphous formulations.

Highly Soluble Dacarbazine Multicomponent Crystals Less Prone to Photodegradation.

Dacarbazine (DTIC) is a widely prescribed oncolytic agent to treat advanced malignant melanomas. Nevertheless, the drug is known for exhibiting low and pH-dependent solubility, in addition to being photosensitive. These features imply the formation of the inactive photodegradation product 2-azahypoxanthine (2-AZA) during pharmaceutical manufacturing and even drug administration. We have focused on developing novel DTIC salt/cocrystal forms with enhanced solubility and dissolution behaviors to overcome or minimize this undesirable biopharmaceutical profile. By cocrystallization techniques, two salts, two cocrystals, and one salt-cocrystal have been successfully prepared through reactions with aliphatic carboxylic acids. A detailed structural study of these new multicomponent crystals was conducted using X-ray diffraction (SCXRD, PXRD), spectroscopic (FT-IR and 1H NMR), and thermal (TG and DSC) analyses. Most DTIC crystal forms reported display substantial enhancements in solubility (up to 19-fold), with faster intrinsic dissolution rates (from 1.3 to 22-fold), contributing positively to reducing the photodegradation of DTIC in solution. These findings reinforce the potential of these new solid forms to enhance the limited DTIC biopharmaceutical profile.