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Gabapentin, a selective ligand for the α2δ subunit of voltage-dependent calcium channels, is an anticonvulsant medication used in the treatment of neuropathic pain, epilepsy, and other neurological conditions. We recently described two radiofluorinated derivatives of gabapentin ( trans- 4-[ 18 F]fluorogabapentin, [ 18 F]tGBP4F, and cis- 4-[ 18 F]fluorogabapentin, [ 18 F]cGBP4F) and showed that these compounds accumulate in the injured nerves in a rodent model of neuropathic pain. Given the use of gabapentin in brain diseases, here we investigate whether these radiofluorinated derivatives of gabapentin can be used for imaging α2δ receptors in the brain. Specifically, we developed automated radiosynthesis methods for [ 18 F]tGBP4F and [ 18 F]cGBP4F and conducted dynamic PET imaging in adult rhesus macaques with and without preadministration of pharmacological doses of gabapentin. Both radiotracers showed very high metabolic stability, negligible plasma protein binding, and slow accumulation in the brain. [ 18 F]tGBP4F, the isomer with higher binding affinity, showed low brain uptake and could not be displaced, whereas [ 18 F]cGBP4F showed moderate brain uptake and could be partially displaced. Kinetic modeling of brain regional time-activity curves using a metabolite-corrected arterial input function shows that a one-tissue compartment model accurately fits the data. Graphical analysis using Logan or multilinear analysis 1 produced similar results as compartmental modeling, indicating robust quantification. This study advances our understanding of how gabapentinoids work and provides an important advancement toward imaging α2δ receptors in the brain.

Demyelination, the loss of the insulating sheath of neurons, causes failed or slowed neuronal conduction and contributes to the neurological symptoms in multiple sclerosis, traumatic brain and spinal cord injuries, stroke, and dementia. In demyelinated neurons, the axonal potassium channels K v 1.1 and K v 1.2, generally under the myelin sheath, become exposed and upregulated. Therefore, imaging these channels using positron emission tomography can provide valuable information for disease diagnosis and monitoring. Here, we describe a novel tracer for K v 1 channels, [ 11 C]3-methyl-4-aminopyridine ([ 11 C]3Me4AP). [ 11 C]3Me4AP was efficiently synthesized via Pd(0)-Cu(I) comediated Stille cross-coupling of a stannyl precursor containing a free amino group. Evaluation of its imaging properties in rats and nonhuman primates showed that [ 11 C]3Me4AP has a moderate brain permeability and slow kinetics. Additional evaluation in monkeys showed that the tracer is metabolically stable and that a one-tissue compartment model can accurately model the regional brain time-activity curves. Compared to the related tracers [ 18 F]3-fluoro-4-aminopyridine ([ 18 F]3F4AP) and [ 11 C]3-methoxy-4-aminopyridine ([ 11 C]3MeO4AP), [ 11 C]3Me4AP shows lower initial brain uptake, which indicates reduced permeability to the blood-brain barrier and slower kinetics, suggesting higher binding affinity consistent with in vitro studies. While the slow kinetics and strong binding affinity resulted in a tracer with less favorable properties for imaging the brain than its predecessors, these properties may make 3Me4AP useful as a therapeutic.

Demyelination, the loss of the protecting sheath of neurons, contributes to disability in many neurological diseases. In order to fully understand its role in different diseases and to monitor treatments aiming at reversing this process, it would be valuable to have PET radiotracers that can detect and quantify molecular changes involved in demyelination such as the uncovering and upregulation of the axonal potassium channels K v 1.1 and K v 1.2. Carbon-11 labeled radiotracers present the advantage of allowing for multiple scans on the same subject in the same day. Here, we describe [ 11 C]3MeO4AP, a novel 11 C-labeled version of the K + channel tracer [ 18 F]3F4AP, and characterize its imaging properties in two non-human primates including a monkey with a focal brain injury sustained during a surgical procedure 3 years prior to imaging. Our findings show that [ 11 C]3MeO4AP is brain permeable, metabolically stable and has high plasma availability. When compared with [ 18 F]3F4AP, [ 11 C]3MeO4AP shows very high correlation in volumes of distribution ( V T ), confirming a common target. [ 11 C]3MeO4AP shows slower washout than [ 18 F]3F4AP, suggesting stronger binding. Finally, similar to [ 18 F]3F4AP, [ 11 C]3MeO4AP is highly sensitive to the focal brain injury. All these features make it a promising radioligand for imaging demyelinated lesions.

We report new SSTR5 antagonists with enhanced potency, subtype selectivity, and minimal off-target activities as compared to previously reported compounds. Starting from the reported SSTR5 antagonist 1 , we systematically surveyed changes in the central core and head piece while maintaining the diphenyl tail group constant. From this study the azaspirodecanone 10 emerged as a new highly potent and selective SSTR5 antagonist. Compound 10 lowered glucose excursion by 94% in an oral glucose tolerance test (OGTT) in mice following a 3 mg/kg oral dose. The compound increased both total and active circulating incretin hormone GLP-1 levels in mice at a dose of 10 mg/kg. A synergistic effect was also demonstrated when compound 10 was coadministered with a DPP-4 inhibitor, substantially increasing circulating active GLP-1[7-36] amide and insulin in response to a glucose challenge., Competing Interests: The authors declare no competing financial interest.

The imidazolyl-tetrahydro-β-carboline class of sstr3 antagonists have demonstrated efficacy in a murine model of glucose excursion and may have potential as a treatment for type 2 diabetes. The first candidate in this class caused unacceptable QTc interval prolongation in oral, telemetrized cardiovascular (CV) dogs. Herein, we describe our efforts to identify an acceptable candidate without CV effects. These efforts resulted in the identification of (1R,3R)-3-(4-(5-fluoropyridin-2-yl)-1H-imidazol-2-yl)-1-(1-ethyl-pyrazol-4-yl)-1-(3-methyl-1,3,4-oxadiazol-3H-2-one-5-yl)-2,3,4,9-tetrahydro-1H-β-carboline (17e, MK-1421).

We report a 2D layered metal-organic framework (MOF) with wide channels named NUS-1 and its activated analogue NUS-1a composed of Zn4O-like secondary building units and tetraphenylethene (TPE)-based ligand 4,4'-(2,2-diphenylethene-1,1-diyl)dibenzoic acid. Due to its special structure, NUS-1a exhibits unprecedented gas sorption behavior, glass-transition-like phase transition under cryogenic conditions, and responsive turn-on fluorescence to various volatile organic compounds. Our approach using angular ligand containing partially fixed TPE units paves a way toward highly porous MOFs with fluorescence turn-on response that will find wide applications in chemical sensing.

A novel class of small-molecule, highly potent, and subtype-selective somatostatin SST3 agonists was discovered through modification of a SST3 antagonist. As an example, (1R,2S)-9 demonstrated not only potent in vitro SST3 agonist activity but also in vivo SST3 agonist activity in a mouse oral glucose tolerance test (OGTT). These agonists may be useful reagents for studying the physiological roles of the SST3 receptor and may potentially be useful as therapeutic agents.

Antagonism of somatostatin subtype receptor 3 (sstr3) has emerged as a potential treatment of Type 2 diabetes. Unfortunately, the development of our first preclinical candidate, MK-4256, was discontinued due to a dose-dependent QTc (QT interval corrected for heart rate) prolongation observed in a conscious cardiovascular (CV) dog model. As the fate of the entire program rested on resolving this issue, it was imperative to determine whether the observed QTc prolongation was associated with hERG channel (the protein encoded by the human Ether-à-go-go-Related Gene) binding or was mechanism-based as a result of antagonizing sstr3. We investigated a structural series containing carboxylic acids to reduce the putative hERG off-target activity. A key tool compound, 3A, was identified from this SAR effort. As a potent sstr3 antagonist, 3A was shown to reduce glucose excursion in a mouse oGTT assay. Consistent with its minimal hERG activity from in vitro assays, 3A elicited little to no effect in an anesthetized, vagus-intact CV dog model at high plasma drug levels. These results afforded the critical conclusion that sstr3 antagonism is not responsible for the QTc effects and therefore cleared a path for the program to progress.

Newly prepared gold(I) acetylide-based luminescent cation sensors 1c and 1d, which bear a novel three-armed flexible conformation, together with control molecule 2c, were synthesized in four steps. 1c and 1d exhibit the π → π* absorption of the acetylide ligands in fluid solutions and produce the (3)(ππ*) emission of the acetylide ligands in the solid state and degassed THF solution. The (3)(ππ*) emission of 1c in DMSO can be turned on upon addition of Ag(+). The binding ratio between 1c and Ag(+) as well as the binding constant log K were determined as 1:1 and 4.35 ± 0.12 respectively by UV-vis titration experiments. The formation of [1c·Ag](+) adduct, which leads to the appearance of new up-field peaks, was confirmed by (1)H NMR spectroscopic titrations. The control (1)H NMR titration experiments for the acetylide-free analogue 1a and single-armed analogue 2c indicate the acetylide groups and tripodal structures are responsible for the binding of Ag(+). The control experiment for tripodal gold(I) acetylide analogue 1d suggests the change of PPh3 with P(2-Py)Ph2 induces similar binding affinity toward Ag(+) but less selectivity toward Ag(+). Free 1c also exhibits the anion binding affinity toward F(-), but the Ag(+) adduct [1c·Ag](+) shows less affinity toward F(-).

A series of mononuclear gold(I) acetylide complexes with urea moiety, R'(3)PAuC≡CC(6)H(4)-4-NHC(O)NHC(6)H(4)-4-R (R' = cyclohexyl, R = NO(2) (2a), CF(3) (2b), Cl (2c), H (2d), CH(3) (2e), (t)Bu (2f), OCH(3) (2g); R' = phenyl, R = NO(2) (3a), OCH(3) (3b); R' = 4-methoxyphenyl, R = H (4a), OCH(3) (4b)), have been synthesized and characterized. The crystal structures of Ph(3)PAuC≡CC(6)H(4)-4-NHC(O)NHC(6)H(4)-4-NO(2) (3a) and (4-CH(3)OC(6)H(4))(3)PAuC≡CC(6)H(4)-4-NHC(O)NHC(6)H(5) (4a) have been determined by X-ray diffraction. Complexes 2a-2g, 3b, and 4a-4b show intense luminescence both in the solid state and in degassed THF solution at 298 K. Anion binding properties of complexes 2a-2g, 3a-3b, and 4a-4b have been studied by UV-vis and (1)H NMR titration experiments. In general, the log K values of 2a-2g with the same anion in THF depend on the substituent R on the acetylide ligand of 2a-2g: R = NO(2) (2a) > CF(3) (2b) ≥ Cl (2c) > H (2d) > CH(3) (2e) ≈ (t)Bu (2f) ≥ OCH(3) (2g). Complex 2a with NO(2) group shows the dramatic color change toward F(-) in DMSO, which provides an access of naked eye detection of F(-).

A structure-activity relationship study of the imidazolyl-β-tetrahydrocarboline series identified MK-4256 as a potent, selective SSTR3 antagonist, which demonstrated superior efficacy in a mouse oGTT model. MK-4256 reduced glucose excursion in a dose-dependent fashion with maximal efficacy achieved at doses as low as 0.03 mg/kg po. As compared with glipizide, MK-4256 showed a minimal hypoglycemia risk in mice.

This letter provides the first pharmacological proof of principle that the sst3 receptor mediates glucose-stimulated insulin secretion (GSIS) from pancreatic β-cells. To enable these studies, we identified the selective sst3 antagonist (1R,3R)-3-(5-phenyl-1H-imidazol-2-yl)-1-(tetrahydro-2H-pyran-4-yl)-2,3,4,9-tetrahydro-1H-β-carboline (5a), with improved ion channel selectivity and mouse pharmacokinetic properties as compared to previously described tetrahydro-β-carboline imidazole sst3 antagonists. We demonstrated that compound 5a enhances GSIS in pancreatic β-cells and blocks glucose excursion induced by dextrose challenge in ipGTT and OGTT models in mice. Finally, we provided strong evidence that these effects are mechanism-based in an ipGTT study, showing reduction of glucose excursion in wild-type but not sst3 knockout mice. Thus, we have shown that antagonism of sst3 represents a new mechanism with potential in treating type 2 diabetes mellitus.

A regression tree (RT) was extensively utilized in quantitative structure-activity relationship studies (QSAR), due to its inherently promising attributes. The issues of instability and inclination to overfitting and suboptima, however, often occur in RT. In the present study, a robust version of boosting was invoked to simultaneously improve the stability and generalization ability of RT, forming a new method called robust boosting regression tree (RBRT). RBRT works by sequentially employing the RT method to model the robustly reweighted versions of the original training set and then aggregating these resultant predictors via weighted median. The designed RBRT was applied to predict the bioactivities of flavoniod derivatives and the anti-HIV activities of HIV-1 inhibitors, compared with boosting RT (BRT) and RT. The results of these two data sets demonstrated that the introduction of robust boosting drastically enhances the stability and generalization ability of RT, and RBRT is superior to BRT in QSAR studies.

The configuration of classification and regression trees (CART) used to include tree-growing by greedy recursive partitioning, which selects the splitting parameters (i.e., splitting variables and values) involved in tree, and tree-pruning, which aims to obtain a final tree of right size. This method is successful for most applications; however, it presents some well-known limitations and drawbacks, such as, less comprehensibility, inclination to overfitting, and suboptima. In the present study, the modified discrete particle swarm optimization method was invoked to adaptively configure the globally optimal CART (MPSOCART) via simultaneously selecting the optimal splitting parameters in CART and the appropriate structure of CART. A new objective function was formulated to decide the appropriate CART architecture and the optimum splitting parameters. The proposed MPSOCART was applied to predict the bioactivities of flavonoid derivatives and inhibitory activities of inhibitors of epidermal growth factor receptor tyrosine kinase, compared with partial least-squares and CART induced by greedy recursive partitioning. The comparison revealed that MPSO was a useful tool for inducing a globally optimal CART, which converges fast to the optimal solution and avoid overfitting in great extent.

The support vector machine (SVM) has been receiving increasing interest in an area of QSAR study for its ability in function approximation and remarkable generalization performance. However, selection of support vectors and intensive optimization of kernel width of a nonlinear SVM are inclined to get trapped into local optima, leading to an increased risk of underfitting or overfitting. To overcome these problems, a new nonlinear SVM algorithm is proposed using adaptive kernel transform based on a radial basis function network (RBFN) as optimized by particle swarm optimization (PSO). The new algorithm incorporates a nonlinear transform of the original variables to feature space via a RBFN with one input and one hidden layer. Such a transform intrinsically yields a kernel transform of the original variables. A synergetic optimization of all parameters including kernel centers and kernel widths as well as SVM model coefficients using PSO enables the determination of a flexible kernel transform according to the performance of the total model. The implementation of PSO demonstrates a relatively high efficiency in convergence to a desired optimum. Applications of the proposed algorithm to QSAR studies of binding affinity of HIV-1 reverse transcriptase inhibitors and activity of 1-phenylbenzimidazoles reveal that the new algorithm provides superior performance to the backpropagation neural network and a conventional nonlinear SVM, indicating that this algorithm holds great promise in nonlinear SVM learning.

The equilibrium and dynamic adsorption data of H(2) and D(2) on different micro- and mesoporous adsorbents with orderly structure including 3A, 4A, 5A, Y, and 10X zeolites; carbon CMK-3; silica SBA-15; and so forth were collected. Critical effect of the nanodimension of adsorbents on the adsorption behavior of hydrogen and its isotopes is shown. The highest adsorption capacity was observed at pore size 0.7 nm, but equal or even larger isotope difference in the equilibrium adsorption was observed at larger pore sizes, whereas the largest isotope difference in the dynamic adsorption was observed at 0.5 nm. The adsorption rate of D(2) is larger than that of H(2) in microporous adsorbents, but the sequence could be switched over in mesoporous materials. Linear relationship was observed between the adsorption capacity for hydrogen and the specific surface area of adsorbents although the adsorbents are made of different material, which provides a convincing proof of the monolayer mechanism of hydrogen adsorption. The linear plot for microporous adsorbents has a larger slope than that for mesoporous adsorbents, which is attributed to the stronger adsorption potential in micropores.

The configuring of a radial basis function network (RBFN) consists of selecting the network parameters (centers and widths in RBF units and weights between the hidden and output layers) and network architecture. The issues of suboptimum and overfitting, however, often occur in RBFN configuring. This paper presented a hybrid particle swarm optimization (HPSO) algorithm to simultaneously search the optimal network structure and parameters involved in the RBFN (HPSORBFN) with an ellipsoidal Gaussian function as a basis function. The continuous version of PSO was used for parameter training, while the modified discrete PSO was employed to determine the appropriate network topology. The proposed HPSORBFN algorithm was applied to modeling the inhibitory activities of substituted bis[(acridine-4-carboxamide)propyl]methylamines to murine P388 leukemia cells and the bioactivities of COX-2 inhibitors. The results were compared with those obtained from RBFNs with the parameters optimized by continuous PSO and by conventionally RBFN training the algorithm for a fixed network topology, indicating that the HPSO was competent for RBFN configuring in that it converged quickly toward the optimal solution and avoided overfitting.