Cycloleucine blocks NMDA responses in cultured hippocampal neurones under voltage clamp: antagonism at the strychnine-insensitive glycine receptor

Discovery and Characterization of Pyridoxal 5'-Phosphate-Dependent Cycloleucine Synthases

Pyridoxal 5'-phosphate (PLP)-dependent enzymes are the most versatile biocatalysts for synthesizing nonproteinogenic amino acids. α,α-Disubstituted quaternary amino acids, such as 1-aminocyclopentane-1-carboxylic acid (cycloleucine), are useful building blocks for pharmaceuticals. In this study, starting with the biosynthesis of fusarilin A, we discovered a family of PLP-dependent enzymes that can facilitate tandem carbon-carbon forming steps to catalyze an overall [3 + 2]-annulation. In the first step, the cycloleucine synthases use SAM as the latent electrophile and an in situ-generated enamine as the nucleophile for γ-substitution. Whereas previously characterized γ-replacement enzymes protonate the resulting α-carbon and release the acyclic amino acid, cycloleucine synthases can catalyze an additional, intramolecular aldol or Mannich reaction with the nucleophilic α-carbon to form the substituted cyclopentane. Overall, the net [3 + 2]-annulation reaction can lead to 2-hydroxy or 2-aminocycloleucine products. These studies further expand the biocatalytic scope of PLP-dependent enzymes.

Depression of Synaptic N-methyl-D-Aspartate Responses by Xenon and Nitrous Oxide

In "synapse bouton preparation" of rat hippocampal CA3 neurons, we examined how Xe and N₂O modulate N-methyl-D-aspartate (NMDA) receptor-mediated spontaneous and evoked excitatory post-synaptic currents (sEPSC_NMDA and eEPSC_NMDA). This preparation is a mechanically isolated single neuron attached with nerve endings (boutons) preserving normal physiologic function and promoting the exact evaluation of sEPSC_NMDA and eEPSC_NMDA responses without influence of extrasynaptic, glial, and other neuronal tonic currents. These sEPSCs and eEPSCs are elicited by spontaneous glutamate release from many homologous glutamatergic boutons and by focal paired-pulse electric stimulation of a single bouton, respectively. The s/eEPSC_AMPA/KA and s/eEPSC_NMDA were isolated pharmacologically by their specific antagonists. Thus, independent contributions of pre- and postsynaptic responses could also be quantified. All kinetic properties of s/eEPSC_AMPA/KA and s/eEPSC_NMDA were detected clearly. The s/eEPSC_NMDA showed smaller amplitude and slower rise and 1/e decay time constant (τ _Decay) than s/eEPSC_AMPA/KA Xe (70%) and N₂O (70%) significantly decreased the frequency and amplitude without altering the τ _Decay of sEPSC_NMDA They also decreased the amplitude but increased the Rf and PPR without altering the τ _Decay of the eEPSC_NMDA These data show clearly that "synapse bouton preparation" can be an accurate model for evaluating s/eEPSC_NMDA Such inhibitory effects of gas anesthetics are primarily due to presynaptic mechanisms. Present results may explain partially the powerful analgesic effects of Xe and N₂O. SIGNIFICANCE STATEMENT: We could record pharmacologically isolated NMDA receptor-mediated spontaneous and (action potential-evoked) excitatory postsynaptic currents (sEPSC_NMDA and eEPSC_NMDA) and clearly detect all kinetic parameters of sEPSC_NMDA and eEPSC_NMDA at synaptic levels by using "synapse bouton preparation" of rat hippocampal CA3 neurons. We found that Xe and N₂O clearly suppressed both sEPSC_NMDA and eEPSC_NMDA. Different from previous studies, present results suggest that Xe and N₂O predominantly inhibit the NMDA responses by presynaptic mechanisms.

Design, Synthesis, and Biological Activity of Novel Ferulic Amide Ac5c Derivatives

A total of 34 novel ferulic amide Ac5c derivatives were designed and synthesized and their antipest activities were investigated. The results showed that some compounds exhibited excellent in vitro antibacterial activity against Xanthomonas oryzae pv. oryzae (Xoo) and X. oryzae pv. oryzicola (Xoc), such as compounds 4q and 5n demonstrated excellent in vitro activity against Xoo, with EC₅₀ values of 4.0, and 1.9 μg/mL, respectively. Compounds 4c, 4h, 4m, 4p, 4q, and 5a had significant in vitro activities against Xoc, with EC₅₀ values of 12.5, 13.9, 9.8 15.0, 9.2, and 19.8 μg/mL, respectively. Moreover, the antibacterial activity in vivo against rice bacterial leaf blight was also evaluated. Scanning electron microscopy (SEM) showed that compound 5n significantly reduced the cell membrane of Xoo, and resulted in cell surface wilting, deformation, breakage, and increased porous attributes. In addition, some of the target compounds also showed moderate biological activity against fungi and acted as potential insecticides.

PREDICT: a method for inferring novel drug indications with application to personalized medicine

The authors present a new method, PREDICT, for the large-scale prediction of drug indications, and demonstrate its use on both approved drugs and novel molecules. They also provide a proof-of-concept for its potential utility in predicting patient-specific medications.

We present a novel method for the large-scale prediction of drug indications that can handle both approved drugs and novel molecules.

Our method utilizes multiple drug–drug and disease–disease similarity measures for the prediction task, obtaining high specificity and sensitivity rates (AUC=0.9).

Our drug repositioning predictions cover 27% of the indications currently tested on clinical trials (P<2 × 10⁻²²⁰).

We show comparable performance using a gene expression signature-based disease–disease similarity, laying the computational foundation for predicting patient-specific indications.

Predicting indications for new molecules or finding alternative indications for approved drugs is a laborious and costly process (DiMasi et al, 2003), calling for computational solutions that would minimize production time and development costs (Terstappen and Reggiani, 2001). Here, we present a novel method for predicting drug indications, PREDICT, capable of handling both approved drugs and novel molecules. Our method is based on the assumption that similar drugs are indicated for similar diseases. To score a possible drug–disease association, we compute its similarity to known associations by combining drug–drug and disease–disease similarity computations. This strategy achieves high specificity and sensitivity rates in a cross-validation setting, where part of the known associations are hidden and the method is assessed based on how well it can retrieve them based on the rest of the associations. Assessing its predictions of novel indications for existing drugs, we find that it covers a significant portion (27%, P<2 × 10⁻²²⁰) of drug indications currently tested on clinical trials. Examples of such predictions include: (i) Cabergoline, indicated for Hyperprolactinemia, which is predicted to treat Migrane, a prediction supported by two separate studies (Verhelst et al, 1999; Cavestro et al, 2006) and (ii) Progesterone, which is predicted to treat renal cell cancer, non-papillary (npRCC), supported by the study of Izumi et al (2007). In addition, we provide indication predictions for novel molecules. For example, Cycloleucine is predicted for the treatment of Alzheimer's disease (AD); indeed, Cycloleucine was found to be a potent and selective antagonist of NMDA receptor-mediated responses (Hershkowitz and Rogawski, 1989), a new promising class of chemicals for the treatment of AD (Farlow, 2004). As another example, Hyperforin, St John's wort extract, is predicted to treat hyperthermia. Interestingly, St John's wort extract was found to have anxiolytic effects on stress-induced hyperthermia in mice (Grundmann et al, 2006). We further introduce a disease–disease similarity measure based on disease-specific gene signatures and show that such a measure can be used by our method to accurately predict drug indications. Importantly, this suggests the potential utility of our approach also in a personalized medicine setting, whereby future gene expression signatures from individual patients would replace these disease-specific signatures.

Inferring potential drug indications, for either novel or approved drugs, is a key step in drug development. Previous computational methods in this domain have focused on either drug repositioning or matching drug and disease gene expression profiles. Here, we present a novel method for the large-scale prediction of drug indications (PREDICT) that can handle both approved drugs and novel molecules. Our method is based on the observation that similar drugs are indicated for similar diseases, and utilizes multiple drug–drug and disease–disease similarity measures for the prediction task. On cross-validation, it obtains high specificity and sensitivity (AUC=0.9) in predicting drug indications, surpassing existing methods. We validate our predictions by their overlap with drug indications that are currently under clinical trials, and by their agreement with tissue-specific expression information on the drug targets. We further show that disease-specific genetic signatures can be used to accurately predict drug indications for new diseases (AUC=0.92). This lays the computational foundation for future personalized drug treatments, where gene expression signatures from individual patients would replace the disease-specific signatures.

Alanine metabolism, transport, and cycling in the brain

Brain glutamate/glutamine cycling is incomplete without return of ammonia to glial cells. Previous studies suggest that alanine is an important carrier for ammonia transfer. In this study, we investigated alanine transport and metabolism in Guinea pig brain cortical tissue slices and prisms, in primary cultures of neurons and astrocytes, and in synaptosomes. Alanine uptake into astrocytes was largely mediated by system L isoform LAT2, whereas alanine uptake into neurons was mediated by Na(+)-dependent transporters with properties similar to system B(0) isoform B(0)AT2. To investigate the role of alanine transport in metabolism, its uptake was inhibited in cortical tissue slices under depolarizing conditions using the system L transport inhibitors 2-aminobicyclo[2.2.1]heptane-2-carboxylic acid and cycloleucine (1-aminocyclopentanecarboxylic acid; cLeu). The results indicated that alanine cycling occurs subsequent to glutamate/glutamine cycling and that a significant proportion of cycling occurs via amino acid transport system L. Our results show that system L isoform LAT2 is critical for alanine uptake into astrocytes. However, alanine does not provide any significant carbon for energy or neurotransmitter metabolism under the conditions studied.