Cis-2-Decenoic Acid and Bupivacaine Delivered from Electrospun Chitosan Membranes Increase Cytokine Production in Dermal and Inflammatory Cell Lines.

Wound dressings serve to protect tissue from contamination, alleviate pain, and facilitate wound healing. The biopolymer chitosan is an exemplary choice in wound dressing material as it is biocompatible and has intrinsic antibacterial properties. Infection can be further prevented by loading dressings with cis-2-decenoic acid (C2DA), a non-antibiotic antimicrobial agent, as well as bupivacaine (BUP), a local anesthetic that also has antibacterial capabilities. This study utilized a series of assays to elucidate the responses of dermal cells to decanoic anhydride-modified electrospun chitosan membranes (DA-ESCMs) loaded with C2DA and/or BUP. Cytocompatibility studies determined the toxic loading ranges for C2DA, BUP, and combinations, revealing that higher concentrations (0.3 mg of C2DA and 1.0 mg of BUP) significantly decreased the viability of fibroblasts and keratinocytes. These high concentrations also inhibited collagen production by fibroblasts, with lower loading concentrations promoting collagen deposition. These findings provide insight into preliminary cellular responses to DA-ESCMs and can guide future research on their clinical application as wound dressings.

Building block aspect ratio controls assembly, architecture, and mechanics of synthetic and natural protein networks.

Fibrous networks constructed from high aspect ratio protein building blocks are ubiquitous in nature. Despite this ubiquity, the functional advantage of such building blocks over globular proteins is not understood. To answer this question, we engineered hydrogel network building blocks with varying numbers of protein L domains to control the aspect ratio. The mechanical and structural properties of photochemically crosslinked protein L networks were then characterised using shear rheology and small angle neutron scattering. We show that aspect ratio is a crucial property that defines network architecture and mechanics, by shifting the formation from translationally diffusion dominated to rotationally diffusion dominated. Additionally, we demonstrate that a similar transition is observed in the model living system: fibrin blood clot networks. The functional advantages of this transition are increased mechanical strength and the rapid assembly of homogenous networks above a critical protein concentration, crucial for in vivo biological processes such as blood clotting. In addition, manipulating aspect ratio also provides a parameter in the design of future bio-mimetic and bio-inspired materials.

Titanium coated with 2-decenoic analogs reduces bacterial and fungal biofilms.

AIMS: Due to antibiotic tolerance of microbes within biofilm, non-antibiotic methods for prevention and treatment of implant-related infections are preferable. The goal of this work is to evaluate a facile loading strategy for medium-chain fatty-acid signaling molecules 2-heptycyclopropane-1-carboxylic acid (2CP), cis-2-decenoic acid (C2DA), and trans-2-decenoic acid, which all act as diffusible signaling factors (DSFs), onto titanium surfaces for comparison of their antimicrobial efficacy. METHODS AND RESULTS: Titanium coupons were drop-coated with 0.75 mg of DSF in ethanol and dried. Surface characteristics and the presence of DSF were confirmed with Fourier Transform infrared spectroscopy, x-ray photoelectron spectroscopy, and water contact angle. Antimicrobial assays analyzing biofilm and planktonic Staphylococcus aureus, Escherichia coli, or Candida albicans viability showed that planktonic growth was reduced after 24-h incubation but only sustained through 72 h for S. aureus and C. albicans. Biofilm formation on the titanium coupons was also reduced for all strains at the 24-h time point, but not through 72 h for E. coli. Although ∼60% of the loaded DSF was released within the first 2 days, enough remained on the surface after 4 days of elution to significantly inhibit E. coli and C. albicans biofilm. Cytocompatibility evaluations with a fibroblast cell line showed that none of the DSF-loaded groups decreased viability, while C2DA and 2CP increased viability by up to 50%. CONCLUSIONS: In this study, we found that DSF-loaded titanium coupons can inhibit planktonic microbes and prevent biofilm attachment, without toxicity to mammalian cells.

Structure-based pharmacophore modeling 2. Developing a novel framework for structure-based pharmacophore model generation and selection.

Pharmacophore models are three-dimensional arrangements of molecular features required for biological activity that are used in ligand identification efforts for many biological targets, including G protein-coupled receptors (GPCR). Though GPCR are integral membrane proteins of considerable interest as targets for drug development, many of these receptors lack known ligands or experimentally determined structures necessary for ligand- or structure-based pharmacophore model generation, respectively. Thus, we here present a structure-based pharmacophore modeling approach that uses fragments placed with Multiple Copy Simultaneous Search (MCSS) to generate high-performing pharmacophore models in the context of experimentally determined, as well as modeled GPCR structures. Moreover, we have addressed the oft-neglected topic of pharmacophore model selection via development of a cluster-then-predict machine learning workflow. Herein score-based pharmacophore models were generated in experimentally determined and modeled structures of 13 class A GPCR and resulted in pharmacophore models exhibiting high enrichment factors when used to search a database containing 569 class A GPCR ligands. In addition, classification of pharmacophore models with the best performing cluster-then-predict logistic regression classifier resulted in positive predictive values (PPV) of 0.88 and 0.76 for selecting high enrichment pharmacophore models from among those generated in experimentally determined and modeled structures, respectively.

Structure-based pharmacophore modeling 1. Automated random pharmacophore model generation.

Pharmacophores are three-dimensional arrangements of molecular features required for biological activity that are often used in virtual screening efforts to prioritize ligands for experimental testing. G protein-coupled receptors (GPCR) are integral membrane proteins of considerable interest as targets for ligand discovery and drug development. Ligand-based pharmacophore models can be constructed to identify structural commonalities between known bioactive ligands for targets including GPCR. However, structure-based pharmacophores (which only require an experimentally determined or modeled structure for a protein target) have gained more attention to aid in virtual screening efforts as the number of publicly available experimentally determined GPCR structures have increased (140 unique GPCR represented as of October 24, 2022). Thus, the goal of this study was to develop a method of structure-based pharmacophore model generation applicable to ligand discovery for GPCR that have few known ligands. Pharmacophore models were generated within the active sites of 8 class A GPCR crystal structures via automated annotation of 5 randomly selected functional group fragments to sample diverse combinations of pharmacophore features. Each of the 5000 generated pharmacophores was then used to search a database containing active and decoy/inactive compounds for 30 class A GPCR and scored using enrichment factor and goodness-of-hit metrics to assess performance. Application of this method to the set of 8 class A GPCR produced pharmacophore models possessing the theoretical maximum enrichment factor value in both resolved structures (8 of 8 cases) and homology models (7 of 8 cases), indicating that generated pharmacophore models can prove useful in the context of virtual screening.

Application of computational methods for class A GPCR Ligand discovery.

G protein-coupled receptors (GPCR) are integral membrane proteins of considerable interest as targets for drug development due to their role in transmitting cellular signals in a multitude of biological processes. Of the six classes categorizing GPCR (A, B, C, D, E, and F), class A contains the largest number of therapeutically relevant GPCR. Despite their importance as drug targets, many challenges exist for the discovery of novel class A GPCR ligands serving as drug precursors. Though knowledge of the structural and functional characteristics of GPCR has grown significantly over the past 20 years, a large portion of GPCR lack reported, experimentally determined structures. Furthermore, many GPCR have no known endogenous and/or synthetic ligands, limiting further exploration of their biochemical, cellular, and physiological roles. While many successes in GPCR ligand discovery have resulted from experimental high-throughput screening, computational methods have played an increasingly important role in GPCR ligand identification in the past decade. Here we discuss computational techniques applied to GPCR ligand discovery. This review summarizes class A GPCR structure/function and provides an overview of many obstacles currently faced in GPCR ligand discovery. Furthermore, we discuss applications and recent successes of computational techniques used to predict GPCR structure as well as present a summary of ligand- and structure-based methods used to identify potential GPCR ligands. Finally, we discuss computational hit list generation and refinement and provide comprehensive workflows for GPCR ligand identification.

Polymorphism of a Highly Asymmetrical Triacylglycerol in Milk Fat: 1-Butyryl 2-Stearoyl 3-Palmitoyl-glycerol.

Milk fat has more than 200 triacylglycerols (TAGs), which play a pivotal role in its crystallization behavior. Asymmetrical TAGs containing short butyryl chains contribute to a significant portion of milk fat TAGs. This work aims to elucidate the crystallization behavior of asymmetrical milk fat TAGs by employing the pure compound of 1-butyryl 2-stearoyl 3-palmitoyl-glycerol (BuSP). The structural evolution of BuSP after being cooled down to 20 °C from the melt is evaluated by small- and wide-angle X-ray scattering (SAXS and WAXS) and differential scanning calorimetry (DSC). The temporal structural observation shows that BuSP crystallizes into the α-form with short and long spacings of 4.10 and 56.9 Å, respectively, during the first hour of isothermal hold at 20 °C. The polymorphic transformation of the α to ß' phase occurred after 4 h of isothermal hold, and the ß'- to α-form fraction ratio was about 70:30 at the end of the isothermal experiment (18 h). Pure ß'-form X-ray patterns are obtained from the BuSP powder with short spacings of 4.33, 4.14, and 3.80 Å, while the long spacing of 51.2 Å depicts a three-chain-length lamellar structure with a tilt angle of 32°. Corresponding DSC measurements display that BuSP crystallizes from the melt at 29.1 °C, whereas the melting of α- and ß'-forms was recorded at 30.3 and 47.8 °C, respectively. In the absence of the ß-form, the ß'-polymorph is the most stable observed form in BuSP. This work exemplarily explains the crystallization behavior of asymmetrical milk fat TAGs and thus provides new insights into their role in overall milk fat crystallization.

A study of the interaction between TMAO and urea in water using NMR spectroscopy.

Trimethylamine N-oxide (TMAO) and urea are small organic biological molecules. While TMAO is known as a protective osmolyte that promotes the native form of biomolecules, urea is a denaturant. An understanding of the impact of TMAO and urea on water structure may aid in uncovering the molecular mechanisms that underlie this activity. Here we investigate binary solutions of TMAO-water, urea-water and ternary solutions of TMAO-urea-water using NMR spectroscopy at 300 K. An enhancement of the total hydrogen bonding in water was found upon the addition of TMAO and this effect was neutralised by a mole ratio of 1-part TMAO to 4-parts urea. Urea was found to have little effect on the strength of water's hydrogen bonding network and the dynamics of water molecules. Evidence was found for a weak interaction between TMAO and urea. Taken together, these results suggest that TMAO's function as a protective osmolyte, and its counteraction of urea, may be driven by the strength of its hydrogen bond interactions with water, and by a secondary reinforcement of water's own hydrogen bond network. They also suggest that the TMAO-urea complex forms through the donation of a hydrogen bond by urea.

Self-docking and cross-docking simulations of G protein-coupled receptor-ligand complexes: Impact of ligand type and receptor activation state.

G protein-coupled receptors (GPCR) are the largest family of cell surface receptors in vertebrates. Their abundance and role in nearly all physiological systems make GPCR the largest protein family targeted for development of pharmaceuticals. Ligand discovery aimed at identification of chemical tools and drug leads is aided by molecular docking simulations that allow critical analysis of the potential interactions between small molecules and proteins in resulting complexes. However, blind assessments of ligand pose quality and affinity prediction have thus far not provided broadly generalizable performance expectations for docking into experimentally-characterized GPCR targets. Likewise, the relative importance of receptor activation state and ligand function differences have also not been systematically assessed. This study compares performance when docking ligands of varied function into varied GPCR activation states in the absence of extensive resampling of the input GPCR structure, and only limited sidechain flexibility after ligand placement. Simulations were performed using 37 experimental structures of 11 Class A GPCR crystallized in multiple activation states (giving rise to 37 self-docking and 68 cross docking simulations). Our results show that one specific subset of cross-docking simulations gave results of similar quality to self-docking. Median ligand RMSD values for top-scored poses were 1.2 Å and 2.0 Å for self-docking and StateMatch/FunctionMatch cross-docking, respectively. The distributions of ligand RMSD values were not statistically different for these two conditions, according to a Kolmogorov-Smirnov test. Therefore, docking performance against GPCR targets can be estimated in advance based on docking target structure activation states, with higher accuracy expected when docking agonists into active state structures and inverse agonists or antagonists into inactive state structures. Receptor conformational sampling in advance of docking or receptor conformational adjustment after docking are more likely to produce substantial improvements for other pairings of receptor activation state and ligand function.

Bridging Structure, Dynamics, and Thermodynamics: An Example Study on Aqueous Potassium Halides.

Aqueous salt systems are ubiquitous in all areas of life. The ions in these solutions impose important structural and dynamic perturbations to water. In this study, we employ a combined neutron scattering, nuclear magnetic resonance, and computational modeling approach to deconstruct ion-specific perturbations to water structure and dynamics and shed light on the molecular origins of bulk thermodynamic properties of the solutions. Our approach uses the atomistic scale resolution offered to us by neutron scattering and computational modeling to investigate how the properties of particular short-ranged microenvironments within aqueous systems can be related to bulk properties of the system. We find that by considering only the water molecules in the first hydration shell of the ions that the enthalpy of hydration can be determined. We also quantify the range over which ions perturb water structure by calculating the average enthalpic interaction between a central halide anion and the surrounding water molecules as a function of distance and find that the favorable anion-water enthalpic interactions only extend to ∼4 Å. We further validate this by showing that ions induce structure in their solvating water molecules by examining the distribution of dipole angles in the first hydration shell of the ions but that this perturbation does not extend into the bulk water. We then use these structural findings to justify mathematical models that allow us to examine perturbations to rotational and diffusive dynamics in the first hydration shell around the potassium halide ions from NMR measurements. This shows that as one moves down the halide series from fluorine to iodine, and ionic charge density is therefore reduced, that the enthalpy of hydration becomes less negative. The first hydration shell also becomes less well structured, and rotational and diffusive motions of the hydrating water molecules are increased. This reduction in structure and increase in dynamics are likely the origin of the previously observed increased entropy of hydration as one moves down the halide series. These results also suggest that simple monovalent potassium halide ions induce mostly local perturbations to water structure and dynamics.

Synthesis and Characterization of 2-Decenoic Acid Modified Chitosan for Infection Prevention and Tissue Engineering.

Chitosan nanofiber membranes are recognized as functional antimicrobial materials, as they can effectively provide a barrier that guides tissue growth and supports healing. Methods to stabilize nanofibers in aqueous solutions include acylation with fatty acids. Modification with fatty acids that also have antimicrobial and biofilm-resistant properties may be particularly beneficial in tissue regeneration applications. This study investigated the ability to customize the fatty acid attachment by acyl chlorides to include antimicrobial 2-decenoic acid. Synthesis of 2-decenoyl chloride was followed by acylation of electrospun chitosan membranes in pyridine. Physicochemical properties were characterized through scanning electron microscopy, FTIR, contact angle, and thermogravimetric analysis. The ability of membranes to resist biofilm formation by S. aureus and P. aeruginosa was evaluated by direct inoculation. Cytocompatibility was evaluated by adding membranes to cultures of NIH3T3 fibroblast cells. Acylation with chlorides stabilized nanofibers in aqueous media without significant swelling of fibers and increased hydrophobicity of the membranes. Acyl-modified membranes reduced both S. aureus and P.aeruginosa bacterial biofilm formation on membrane while also supporting fibroblast growth. Acylated chitosan membranes may be useful as wound dressings, guided regeneration scaffolds, local drug delivery, or filtration.

2-Heptylcyclopropane-1-Carboxylic Acid Disperses and Inhibits Bacterial Biofilms.

Fatty-acid signaling molecules can inhibit biofilm formation, signal dispersal events, and revert dormant cells within biofilms to a metabolically active state. We synthesized 2-heptylcyclopropane-1-carboxylic acid (2CP), an analog of cis-2-decenoic acid (C2DA), which contains a cyclopropanated bond that may lock the signaling factor in an active state and prevent isomerization to its least active trans-configuration (T2DA). 2CP was compared to C2DA and T2DA for ability to disperse biofilms formed by Staphylococcus aureus and Pseudomonas aeruginosa. 2CP at 125 µg/ml dispersed approximately 100% of S. aureus cells compared to 25% for C2DA; both 2CP and C2DA had significantly less S. aureus biofilm remaining compared to T2DA, which achieved no significant dispersal. 2CP at 125 µg/ml dispersed approximately 60% of P. aeruginosa biofilms, whereas C2DA and T2DA at the same concentration dispersed 40%. When combined with antibiotics tobramycin, tetracycline, or levofloxacin, 2CP decreased the minimum concentration required for biofilm inhibition and eradication, demonstrating synergistic and additive responses for certain combinations. Furthermore, 2CP supported fibroblast viability above 80% for concentrations below 1 mg/ml. This study demonstrates that 2CP shows similar or improved efficacy in biofilm dispersion, inhibition, and eradication compared to C2DA and T2DA and thus may be promising for use in preventing infection for healthcare applications.

In vitro evaluation of loaded chitosan membranes for pain relief and infection prevention.

Wounds resulting from surgeries, implantation of medical devices, and musculoskeletal trauma result in pain and can also result in infection of damaged tissue. Up to 80% of these infections are due to biofilm formation either on the surface of implanted devices or on surrounding wounded tissue. Bacteria within a biofilm have intrinsic growth and development characteristics that allow them to withstand up to 1,000 times the minimum inhibitory concentration of antibiotics, demonstrating the need for new therapeutics to prevent and treat these infections. Cis-2-decenoic acid (C2DA) is known to disperse preformed biofilms and can prevent biofilm formation entirely for some strains of bacteria. Additionally, local anesthetics like bupivacaine have been shown to have antimicrobial effects against multiple bacterial strains. This study sought to evaluate hexanoic acid-treated electrospun chitosan membranes (HA-ESCM) as wound dressings that release C2DA and bupivacaine to simultaneously prevent infection and alleviate pain associated with musculoskeletal trauma. Release profiles of both therapeutics were evaluated, and membranes were tested in vitro against Methicillin-resistant Staphylococcus aureus (MRSA) to determine efficacy in preventing biofilm infection and bacterial growth. Results indicate that membranes release both therapeutics for 72 hr, and release profile can be tailored by loading concentration. Membranes were effective in preventing biofilm growth but were toxic to fibroblasts when loaded with 2.5 or 5 mg of bupivacaine.

Solute Specific Perturbations to Water Structure and Dynamics in Tertiary Aqueous Solution.

Liquid water is known as the "universal" solvent, capable of dissolving a wide variety of different solutes. While much is now understood about the impact of solutes on the water structure in binary solutions, it is much more challenging to deconvolute the potentially competing effects of more complex solutions. Here, we present a correlative NMR and neutron diffraction study to examine the solute induced perturbation of water structure and dynamics in a tertiary solution containing the naturally occurring osmolyte trimethylamine N-oxide (TMAO) and magnesium perchlorate (Mg(ClO4)2). We show that while TMAO and Mg(ClO4)2 perturb the water structure in an opposing manner, the two solutes slow water dynamics in an additive manner. We quantify the relative ability of each solute to perturb water by introducing a weighting parameter and show that TMAO is 1.54 times more effective at perturbing water structure and dynamics than Mg(ClO4)2. The combination of NMR, neutron diffraction, and computational modelling offers unprecedented access to the structure and dynamics of more complex aqueous solutions, permitting the deconvolution of solute specific perturbation of water. Such insight provides a new route to understand this universal solvent in the context of important and relevant aqueous environments.

Protein Microgel-Stabilized Pickering Liquid Crystal Emulsions Undergo Analyte-Triggered Configurational Transition.

Herein, we report a novel approach that involves Pickering stabilization of micometer-sized liquid crystal (LC) droplets with biocompatible soft materials such as a whey protein microgel (WPM) to facilitate the analysis of analyte-induced configurational transition of the LC droplets. The WPM particles were able to irreversibly adsorb at the LC-water interface, and the resulting WPM-stabilized LC droplets possessed a remarkable stability against coalescence over time. Although the LC droplets were successfully protected by a continuous network of the WPM layer, the LC-water interface was still accessible for small molecules such as sodium dodecyl sulfate (SDS) that could diffuse through the meshes of the adsorbed WPM network or through the interfacial pores and induce an LC response. This approach was exploited to investigate the dynamic range of the WPM-stabilized LC droplet response to SDS. Nevertheless, the presence of the unadsorbed WPM in the aqueous medium reduced the access of SDS molecules to the LC droplets, thus suppressing the configuration transition. An improved LC response to SDS with a lower detection limit was achieved after washing off the unadsorbed WPM. Interestingly, the LC exhibited a detection limit as low as ∼0.85 mM for SDS within the initial WPM concentration ranging from 0.005 to 0.1 wt %. Furthermore, we demonstrate that the dose-response behavior was strongly influenced by the number of droplets exposed to the aqueous analytes and the type of surfactants such as anionic SDS, cationic dodecyltrimethylammonium bromide (DTAB), and nonionic tetra(ethylene glycol)monododecyl ether (C12E4). Thus, our results address key issues associated with the quantification of aqueous analytes and provide a promising colloidal platform toward the development of new classes of biocompatible LC droplet-based optical sensors.

Benchmarking GPCR homology model template selection in combination with de novo loop generation.

G protein-coupled receptors (GPCR) comprise the largest family of membrane proteins and are of considerable interest as targets for drug development. However, many GPCR structures remain unsolved. To address the structural ambiguity of these receptors, computational tools such as homology modeling and loop modeling are often employed to generate predictive receptor structures. Here we combined both methods to benchmark a protocol incorporating homology modeling based on a locally selected template and extracellular loop modeling that additionally evaluates the presence of template ligands during these modeling steps. Ligands were also docked using three docking methods and two pose selection methods to elucidate an optimal ligand pose selection method. Results suggest that local template-based homology models followed by loop modeling produce more accurate and predictive receptor models than models produced without loop modeling, with decreases in average receptor and ligand RMSD of 0.54 Å and 2.91 Å, respectively. Ligand docking results showcased the ability of MOE induced fit docking to produce ligand poses with atom root-mean-square deviation (RMSD) values at least 0.20 Å lower (on average) than the other two methods benchmarked in this study. In addition, pose selection methods (software-based scoring, ligand complementation) selected lower RMSD poses with MOE induced fit docking than either of the other methods (averaging at least 1.57 Å lower), indicating that MOE induced fit docking is most suited for docking into GPCR homology models in our hands. In addition, target receptor models produced with a template ligand present throughout the modeling process most often produced target ligand poses with RMSD values ≤ 4.5 Å and Tanimoto coefficients > 0.6 after selection based on ligand complementation than target receptor models produced in the absence of template ligands. Overall, the findings produced by this study support the use of local template homology modeling in combination with de novo ECL2 modeling in the presence of a ligand from the template crystal structure to generate GPCR models intended to study ligand binding interactions.

A benchmark study of loop modeling methods applied to G protein-coupled receptors.

G protein-coupled receptors (GPCR) are important drug discovery targets. Despite progress, many GPCR structures have not yet been solved. For these targets, comparative modeling is used in virtual ligand screening to prioritize experimental efforts. However, the structure of extracellular loop 2 (ECL2) is often poorly predicted. This is significant due to involvement of ECL2 in ligand binding for many Class A GPCR. Here we examine the performance of loop modeling protocols available in the Rosetta (cyclic coordinate descent [CCD], KIC with fragments [KICF] and next generation KIC [NGK]) and Molecular Operating Environment (MOE) software suites (de novo search). ECL2 from GPCR crystal structures served as the structure prediction targets and were divided into four sets depending on loop length. Results suggest that KICF and NGK sampled and scored more loop models with sub-angstrom and near-atomic accuracy than CCD or de novo search for loops of 24 or fewer residues. None of the methods were able to sample loop conformations with near-atomic accuracy for the longest targets ranging from 25 to 32 residues based on 1000 models generated. For these long loop targets, increased conformational sampling is necessary. The strongly conserved disulfide bond between Cys3.25 and Cys45.50 in ECL2 proved an effective filter. Setting an upper limit of 5.1 Å on the S-S distance improved the lowest RMSD model included in the top 10 scored structures in Groups 1-4 on average between 0.33 and 1.27 Å. Disulfide bond formation and geometry optimization of ECL2 provided an additional incremental benefit in structure quality.

GPCR homology model template selection benchmarking: Global versus local similarity measures.

G protein-coupled receptors (GPCR) are integral membrane proteins of considerable interest as targets for drug development. GPCR ligand interaction studies often have a starting point with either crystal structures or comparative models. The majority of GPCR do not have experimentally-characterized 3-dimensional structures, so comparative modeling, also called homology modeling, is a good structure-based starting point. Comparative modeling is a widely used method for generating models of proteins with unknown structures by analogy to crystallized proteins that are expected to exhibit structural conservation. Traditionally, comparative modeling template selection is based on global sequence identity and shared function. However high sequence identity localized to the ligand binding pocket may produce better models to examine protein-ligand interactions. This in silico benchmark study examined the performance of a global versus local similarity measure applied to comparative modeling template selection for 6 previously crystallized, class A GCPR (CXCR4, FFAR1, NOP, P2Y12, OPRK, and M1) with the long-term goal of optimizing GPCR ligand identification efforts. Comparative models were generated from templates selected using both global and local similarity measures. Similarity to reference crystal structures was reflected in RMSD values between atom positions throughout the structure or localized to the ligand binding pocket. Overall, models deviated from the reference crystal structure to a similar degree regardless of whether the template was selected using a global or local similarity measure. Ligand docking simulations were performed to assess relative performance in predicting protein-ligand complex structures and interaction networks. Calculated RMSD values between ligand poses from docking simulations and crystal structures indicate that models based on locally selected templates give docked poses that better mimic crystallographic ligand positions than those based on globally-selected templates in five of the six benchmark cases. However, protein model refinement strategies in advance of ligand docking applications are clearly essential as the average RMSD between crystallographic poses and poses docked into local template models was 9.7 Šand typically less than half of the ligand interaction sites are shared between the docked and crystallographic poses. These data support the utilization of local similarity measures to guide template selection in protocols using comparative models to investigate ligand-receptor interactions.

Abiotic reduction of Cr(VI) by humic acids derived from peat and lignite: kinetics and removal mechanism.

Hexavalent chromium contamination of groundwater is a worldwide problem caused by anthropogenic and natural processes. We report the rate of Cr(VI) removal by two humic acids (extracted from Miocene age lignite and younger peat soil) in aqueous suspensions across a pH range likely to be encountered in terrestrial environments. Cr(VI) was reduced to Cr(III) in a first-order reaction with respect Cr(VI) concentration, but exhibited a partial order (~ 0.5) with respect to [H+]. This reaction was more rapid with the peat humic acid, where Cr(VI) reduction was observed at all pH values investigated (3.7 ≤ pH ≤ 10.5). 13C NMR and pyrolysis GC-MS spectroscopy indicate that the reaction results in loss of substituted phenolic moieties and hydroxyl groups from the humic acids. X-ray absorption spectroscopy indicated that at all pH values the resulting Cr(III) was associated with the partially degraded humic acid in an inner-sphere adsorption complex. The reaction mechanism is likely to be controlled by ester formation between Cr(VI) and phenolic/hydroxyl moieties, as this initial step is rapid in acidic systems but far less favourable in alkaline conditions. Our findings highlight the potential of humic acid to reduce and remove Cr(VI) from solution in a range of environmental conditions.

Highly Potent Non-Carboxylic Acid Autotaxin Inhibitors Reduce Melanoma Metastasis and Chemotherapeutic Resistance of Breast Cancer Stem Cells.

Autotaxin (ATX, aka. ENPP2) is the main source of the lipid mediator lysophosphatidic acid (LPA) in biological fluids. This study reports on inhibitors of ATX derived by lead optimization of the benzene-sulfonamide in silico hit compound 3. The new analogues provide a comprehensive structure-activity relationship of the benzene-sulfonamide scaffold that yielded a series of highly potent ATX inhibitors. The three most potent analogues (3a, IC50 ∼ 32 nM; 3b, IC50 ∼ 9 nM; and 14, IC50 ∼ 35 nM) inhibit ATX-dependent invasion of A2058 human melanoma cells in vitro. Two of the most potent compounds, 3b and 3f (IC50 ∼ 84 nM), lack inhibitory action on ENPP6 and ENPP7 but possess weak antagonist action specific to the LPA1 G protein-coupled receptor. In particular, compound 3b potently reduced in vitro chemotherapeutic resistance of 4T1 breast cancer stem-like cells to paclitaxel and significantly reduced B16 melanoma metastasis in vivo.