tive disorders and the prevention of stroke (Chiaradonna, 2012; Huang et al., 2011; Dhawan et al., 2011). Currently, there are only two known glutaminase inhibi- tors: bis-2-(5-phenylacetamido-1,2,4-thiadiazol-2-yl)ethyl- sul!de (BPTES) and 6-diazo-5-oxo-L-norleucine (DON) (Hartwick, 2011). However, neither compound crosses the blood-brain barrier nor is neuroactive; thus, neither is suit- able for pharmacotherapy of schizophrenia. "e purpose of this study was to screen for PAG inhibitors in a library of 58,000 neuroactive compounds. Robotic processing with a #uorescence-based assay was used to assess inhibition of PAG activity in vitro. A second- ary assay was used to con!rm PAG-speci!city of apparent inhibitors, and subsequent kinetic analysis of the top tier of these hits was used to select two leads for further chemical optimization. Primary Screen A library of 58,000 neuroactive compounds was pur- chased from ChemBridge. Compounds were supplied at a concentration of 10-3 M in DMSO and were stored in 384- well plates at -80oC. Human PAG was synthesized and puri!ed by our lab using a plasmid provided by Professor Norman Curthoys (Colorado State University) as previously described in Ken- ny et al. (2003). "e #uorescence assay used for the screen was optimized from a commercially available kit (Amplex Red, Invitro- gen) and was used to measure PAG activity in the pres- ence of each library compound. Glutamate, the product of PAG catalysis, was converted to a #uorescent compound called resoru!n by the addition of a series of kit enzymes, including glutamate oxidase (GO), horseradish peroxidase (HRP), and the #uorogenic substrate Amplex Red (Figure 1). Because the #uorescent molecule resoru!n is dependent on glutamate production and glutamate production is the product of PAG catalysis, the rate of change in #uorescence is a measurement of PAG activity. Potent inhibitors of PAG would signi!cantly decrease the #uorescence compared to controls without inhibitor. "e assay was carried out in a 384-well plate, with 80 µL of total liquid volume per well. 320 wells were car- ried out under experimental conditions, where 20 µL of Amplex Red solution (itself containing 8 mL of Tris-HCl reaction bu$er, 60 µL of GO, 25 µL of HRP, and 80 µL of Amplex Red reagent), 40 µL of PAG solution (itself 2 µL of synthesized PAG in 32 mL of Tris-phosphate bu$er), 0.8 µL of one library compound (originally 10-3 M, but diluted to 10-4 M in well), and 20 µL of 40 µM glutamine solution were pipetted into each well. While kit enzyme concentrations were the same as those used in the Amplex Red kit protocol (so that all kit enzymes were in ex- cess), optimum glutamine and PAG concentrations were determined according to Michaelis-Menten ki- netics. "e concentration of glutamine was selected based on the previously determined value of the Km of PAG-catalyzed glutamine deamination. Km is de- !ned as the concentration of substrate (glutamine) required to reach one half of the maximal reaction velocity (vmax) for a particular enzyme-catalyzed re- action (Copeland, 2000). Control conditions were included in the remain- ing 64 wells of each plate. Positive control wells, rep- resenting 100% PAG activity (0% PAG inhibition), contained PAG, glutamine, and Amplex Red solu- tion. Negative control wells, representing 0% PAG activity (100% inhibition), contained glutamine and Amplex Red solution. 75%, 50%, and 25% inhibition controls were also used, obtained by creating a dilution series of the posi- tive control. Additionally, Amplex Red solution only con- trols were used as an additional negative control. In control wells, where necessary, Tris-HCl reaction bu$er was added to bring wells to the standard volume. Outlined in Figure 2 below is a typical assay plate setup. Fluorescence measurements were taken at baseline (im- mediately after glutamine was added to each well), and after a 60-minute incubation at 37 oC, by an Envision #uores- cence reader (Perkin Elmer). Pipetting was done by a Mini- Trak Robotic Liquid Handling System (Perkin Elmer) for speed and e%ciency. To calculate percent inhibition of PAG, GO, and HRP, the average negative control #uorescence was subtracted from the experimental group #uorescence and divided by the average positive control #uorescence. Subtracting per- cent activity from 100% gave percent inhibition. In the brain, phosphate-activated glutaminase catalyzes the recycling of glutamine back to glutamate for excitatory neurotransmis- sion. In mice, genetic knockdown of phosphate-activated glutaminase has been shown to confer resilience to schizophrenia-like symp- toms, suggesting that inhibition of glutaminase may have therapeutic potential for the pharmacotherapy of schizophrenia. As there are no known neuroactive inhibitors of glutaminase, i.e. inhibitors that get into the brain, high-throughput screening of a library of 58,000 QHXURDWLYH�FRPSRXQGV�ZDV�FRQGXFWHG�XVLQJ�D�ÀXRUHVFHQFH�EDVHG�DVVD\��WKLV�VFUHHQ�LGHQWL¿HG�����SRWHQWLDO�JOXWDPLQDVH�LQKLELWRUV�� $�VHFRQGDU\�VFUHHQ�ZDV�FDUULHG�RXW�WR�DVVHVV�VSHFL¿FLW\��WKLV�\LHOGHG����KLWV���8VLQJ�D�NLQHWLF�DQDO\VLV��WZR�OHDGV�ZLWK�ORZ�PLFURPRODU� activity were found. Columbia Undergraduate Science Journal Open-Access Publication | http://cusj.columbia.edu 3 cusjVolume 6Spring 2012 Columbia Undergraduate Sci J http://cusj.columbia.edu P S Y C H IA TR Y cusjcolumbia undergraduate science journal Research Articles 4cusj Volume 6Spring 2012 Columbia Undergraduate Sci J http://cusj.columbia.edu P S Y C H IATR Y Schizophrenia is a complex and diverse neuropsy- chiatric disorder that a$ects approximately one percent of the world population. Symptoms typically present in schizophrenia are placed into three categories: posi- tive, such as hallucinations, negative, such as paucity of speech and social withdrawal, and cognitive, such as conceptual disorganization and de!cits in working memory. "e treatment of schizophrenia has focused on tar- geting dopamine hyperactivity with anti-psychotic drugs. "e dopamine hypothesis, which attributes the symptoms of schizophrenia to hyperactive dopaminer- gic signal transduction in the striatum and, more broadly, the mesolimbic pathway, rose to prominence with the dis- covery that many common antipsychotic drugs, such as chlorpromazine and clozapine, work by binding to post- synaptic dopamine receptors, notably D2 receptors, and interfering with dopamine signal transduction (Creese, 1976; Seeman, 1975; Van Rossum, 1966; Matthyse, 1973). However, the dopamine hypothesis does not fully explain schizophrenia. One problem is that these dopamine recep- tor antagonists are largely ine$ective in treating the nega- tive and cognitive symptoms of schizophrenia, which sug- gests that dopaminergic hyperactivity may be unrelated to this class of symptoms (Davis, 1991; Javitt, 2010; Kellen- donk, 2006). Moreover, a signi!cant number of patients with schizophrenia do not respond to these drugs, which also may be due to the involvement of other neurochemical pathways (Davis 1991). More recently, abnormal glutamate transmission has been implicated in the pathophysiology of schizophrenia. Glutamate is the major excitatory neurotransmitter in the central nervous system. Under normal conditions it is pro- duced and maintained at a low extracellular concentration through the glutamate-glutamine cycle (Sanacora, 2008). "e importance of glutamate transmission in schizophrenia and psychosis was realized with the discovery that drugs like phencyclidine (PCP) cause symptoms that are nearly indistinguishable from those of schizophrenia by acting as an antagonist to N-methyl D-aspartate (NMDA) recep- tors to which glutamate is an agonist. Since then, many studies have shown that processes that modulate normal glutamatergic signaling may have bene!cial e$ects on posi- tive, negative, and cognitive symptoms of schizophrenia (Javitt 2010; Vinson and Conn 2011; Gaisler-Solomon et al., 2009). In particular, mice haploinsu%cient for phosphate-ac- tivated glutaminase (PAG) show a reduction in glutama- tergic synaptic transmission, are behaviorally quite normal, and are resilient to the e$ects of pro-psychotic drugs. PAG is an enzyme that catalyzes the presynaptic conversion of glutamine to glutamate in neuronal mitochondria, "ese !ndings suggest that the reduction of glutamate release through the genetic reduction of PAG confers resilience to a schizophrenia-like phenotype in mice, and that the inhibition of PAG may have therapeutic potential in the pharmacotherapy of schizophrenia (Gaisler-Solomon et al., 2009). PAG inhibition also appears to have therapeutic potential in several diseases beyond schizophrenia, such as in the treatment of cancer, and HIV-associated neurocogni- Identi!cation of Inhibitors of Phosphate-activated Glutaminase for the Pharmacotherapy of Schizophrenia Cristina Sorrento 1,3,* , Stephen Rayport 1,3 , Andra Mihali 1,3 , Genevieve Kaunitz 1,3 , Shreya Subramani 1,3 , Joanne Macdonald 2 , Francine Katz 2 Departments of Psychiatry1 and Medicine2, Columbia University, New York, NY 10032 Departments of Molecular Therapeutics3, New York State Psychiatric Insitute, New York, NY 10032 Copyright: © 2012 The Trustees of Columbia University, Columbia University Libraries, some rights reserved, Sorrento, et al. Received 1/1/2012. Accepted 2/1/2012. Published 1/1/12 *To whom correspondence should be addressed: Departments of Psychiatry and Medicine, Columbia University, New York, NY 10032 cristinasorrento75@gmail.com Abstract Introduction Figure 1 7KH�VWHSV�RI�WKH�ÀXRUHVFHQFH�EDVHG�DVVD\�IRU�VWXG\LQJ�WKH�DFWLYLW\� RI�SKRVSKDWH�DFWLYDWHG�JOXWDPLQDVH��3$*����5HVRUX¿Q�ÀXRUHV- cence is a measure of glutamate concentration and, therefore, 3$*�DFWLYLW\��0RGL¿HG�IURP�0F(OUR\�HW�DO���������� Methods varying concentrations. Additionally, !uorescence readings were taken every 10 minutes so that reaction rates could be calculated based on the slope of the graph of !uorescence versus time. GraphPad Prism 4 was used to transform the !uorescence data to "t a characteristic Michaelis-Menten curve and to calculate the IC50 value for the inhibitors. IC50 is a measure of inhibitory power; it is the concentration of inhibitor at which the reaction rate catalyzed by a par- ticular enzyme is halved. #e steps in the screening of the ChemBridge CNS- Set library are detailed in Figure 3. A visual basic loop program was used to rank in descending order and in terms of percent inhibition the 320 library compounds on each of the 180 plates. Because of variability in !uo- rescence values of the controls in di$erent plates, results of the primary screen were sorted based on their dynamic range. #e DR of !uorescence for a particular plate was de"ned using the control !uorescence values: DR = 100% * (positive control - negative control) (positive control) Plates were then placed into three categories: good Secondary Screen To select true inhibitors of PAG, it was necessary to eliminate the hits that were inhibitors of the kit enzymes GO and HRP. To eliminate GO/HRP inhibitors, another resoru"n assay was designed for this purpose. #is assay was similar to the original glutamine-glutamate Amplex Red assay except that glutamine was replaced by the GO/ HRP substrate glutamic acid, and PAG was not included. Because the conversion of glutamate to resoru"n is much faster than PAG-catalyzed glutamine deamination, it was necessary to determine optimal substrate and enzyme con- centrations that would produce a linear increase in product over a given time frame. Based on a preliminary kinetics assay, it was determined that replacing the 40 µM gluta- mine with 10 µM glutamic acid and maintaining previous kit enzyme concentrations produced a reaction where the concentration of product (resoru"n) increased linearly with time (and did not saturate). Once the glutamic acid assay parameters were deter- mined, the primary screen assay and glutamic acid assay were carried out in parallel on the primary screen hits. Per- cent inhibition of PAG, GO, and HRP (primary screen) and of GO and HRP (glutamaic acid assay) were deter- mined for each hit, and percent inhibition of PAG only was calculated by subtracting GO/HRP inhibition from PAG/ GO/HRP inhibition. ‘Hit’ Kinetics Analysis Of the compounds that were picked up in the second- ary screen, the ten with the highest percent PAG inhibi- tion were selected for kinetic analysis and purchased from ChemBridge. 0.1 M aliquots of each compound were pre- pared with DMSO and stored at -80oC. From these stock solutions, 10-fold dilution series ranging from 10-3 M to 10-8 M were prepared for each compound. #e same assay that was used in the primary screen was used for the kinetics analysis experiment, except that the inhibitors were used in Columbia Undergraduate Science Journal Open-Access Publication | http://cusj.columbia.edu 5 cusjVolume 6Spring 2012 Columbia Undergraduate Sci J http://cusj.columbia.edu P S Y C H IA TR Y cusjcolumbia undergraduate science journal Research Articles 6cusj Volume 6Spring 2012 Columbia Undergraduate http://cusj.columbia.edu Figure 2 A typical plate from the primary screen. Figure 4 Reaction rate vs. concentration plotted using Prism software. IC��� values are displayed in the table to the right Figure 3 $�VFKHPDWLF�GLDJUDP�RXWOLQLQJ�WKH�VFUHHQLQJ�SURFHVV�IRU�WKH�VHOHFWLRQ�RI�3$*�VSHFL¿F�LQKLELWRUV P S Y C H IATR Y Trial 1 2 3 4 Average ± SE IC50 (uM) 5.482 3.647 4.655 3.303 4.272 ± 0.572 R2 0.951 0.982 0.944 0.956 (DR=95-50%), low or extreme (DR<50% or DR>95%), and poor dynamic range (DR!0%). For plates with a good dynamic range, compounds that exhibited at least 90% in- hibition were selected. For plates with a low or extreme dynamic range or non-existent dynamic range, compounds were selected if they stood out in the plate distribution. Representative distributions of compound inhibition data for three plates in each of the three categories are shown in Figure 4. For plates with a good dynamic range, there were typically very few or no compounds with percent inhibition above 90%; however, for plates with a low or extreme dynamic range or a poor dy- namic range, there were signi"cantly more compounds whose percent inhibition was greater than 90%, and in fact, there were a signi"cant number of compounds with percent inhibition greater than 100%. #e hits picked up by this process were tested in the secondary screen to eliminate inhibitors of GO and HRP. #e compounds that had the least impact on GO and HRP were ranked based on their selective in- hibition of PAG. From this list of compounds, the top 10 were selected for kinetic analysis. For 2 of these 10 compounds, the inhibition curve "t Michaelis-Menten kinetics. Plots for these 2 compounds, 3D2 and 8O, of reaction velocity versus inhibitor concen- tration are shown below, and Figure 5 indicates the IC50 values 3D2 in four independent experiments. #e average IC50 value for 3D2 was 4.272 ± 0.572 µM. As indicated by the regression coe$cients of each experi- ment, the Michaelis-Menten model of enzyme kinetics was applicable to the activity of 3D2. Based on its average IC50 value, inhibitor 3D2 appears worthy of further investigation. Because combinatorial chemistry can be used to optimize inhibitory power by up to three orders of magnitude, it appears that optimization of 3D2 particularly would produce a compound that would inhibit PAG in the nanomolar range (Jorgensen, 2009). At concentrations lower than 10-4 M, 8O also exhibits similar dose-dependent behavior, but because of its unusual be- havior for concentrations greater than this, where reaction velocity appears to increase with greater concentrations of inhibitor, it is necessary to subject 8O to further kinetic scrutiny. For both compounds, before they are to be op- timized, it is necessary to con"rm their inhibitory power through alternative assays and to increase the number of hits to be optimized. #e organization of the primary screen experiments into three categories based on the dynamic range of control %uorescence enabled comparison between plates and ap- propriate selection of hits. For plates with a good dynamic range, there were few or no compounds with greater than 90% inhibition. However, for plates with an extreme (low or high) or non-existent dynamic range, there were many compounds with greater than 90% inhibition and even some well above 100%. #is result most likely does not indicate a greater number of hits for these two categories of plates; indeed, the >100% inhibitors suggests that the large number of apparent hits with percent inhibition >90% is an artifact of an abnormal dynamic range. #erefore, the division of the plates into the three categories and the se- lection of outliers from the two categories of plates with abnormal values for dynamic range were used to correct this artifact so that only outliers were selected from every plate. #e secondary screen was designed to eliminate non- speci"c inhibitors and false positives from the screen. In testing for inhibition of glutamate oxidase and horseradish peroxidase, the secondary screen was able to exclude com- pounds that were potential inhibitors of these kit enzymes. In addition to this secondary assay, it is necessary to con"rm the inhibitory power of 3D2 using another assay without the use of Amplex Red; one such assay involves the direct determination of glutamate as a product of PAG catalysis. From the IC50 curve of 8O, it appears that for concen- trations of inhibitor greater than 10-4 M, the reaction rate is actually higher than it is for lower concentrations; oth- erwise, for concentrations below 10-4 M, 8O appears to adhere to the dose-dependent pattern normally seen with good inhibitors. A likely explanation for this unusual pat- tern is that 8O is itself %uorescent and enhances the %uores- cence signal at high concentrations. One caveat to Michalis-Menten kinetics determinations is that the value of the IC50 measurement is in itself limited; IC50 depends on the concentration of substrate, enzyme, and inhibitor, as well as other experimental conditions. Ki, the dissociation constant of the inhibitor to the enzyme, is a more valuable measurement because it is an intrinsic thermodynamic quantity independent of substrate concen- tration, but dependent on enzyme and inhibitor concentra- tions. For this reason, Ki measurements are more replicable across di&erent experimental methods (Cer, 2009). #ere are ways of measuring Ki based on IC50 values, one Columbia Undergraduate Science Journal Open-Access Publication | http://cusj.columbia.edu 7 cusjVolume 6Spring 2012 Columbia Undergraduate Sci J http://cusj.columbia.edu P S Y C H IA TR Y Figure 5 IC���YDOXHV�GHWHUPLQHG�IRU��'��ZLWK�FRUUHVSRQGLQJ�5 � values. �2�ZDV�QRW�WHVWHG�RQ����������� of which is the Cheng-Pruso& equation: Ki= IC50/(1+[S]/KM ) However, this equation is used to calculate Ki for inhibi- tors known to be competitive (Copeland, 2000). Another method that can be used to determine Ki is through the use of the Lineweaver-Burk plot, which Graph- pad Prism 4 can generate. #ese plots are obtained by vary- ing both inhibitor and enzyme concentration, and can both elucidate the nature of the inhibitor (competitive, non- competitive, or uncompetitive) and be used to calculate Ki (Copeland, 2000). Knowing the nature of the inhibitor will allow prioritization of the leads for optimization. Non- competitive inhibitors will be favored for optimization over competitive inhibitors. Competitive inhibitors, binding to the enzyme’s active site, are less likely to be speci"c to PAG, as they are also likely to bind to the active sites of other enzymes in the glutamate cycle. #erefore, since PAG- speci"city is one of the selection criteria, and competitive inhibitors are unlikely to be PAG-speci"c, non-competitive inhibitors will be preferentially selected for optimization. Once these leads are optimized, they will be assessed for drug-like character and their suitability in the phar- macotherapy of schizophrenia. For example, PAG activity measurements in mice administerd the leads, electrophysi- ological recordings of their brain slices, and behavioral tests analyzing their response to amphetamine-induced hyperac- tivity can be used to assess the value of these leads in phar- macotherapy. Additionally, ADME-tox (Absorbtion, Dis- tribution, Metabolism, Excretion, and toxicity) analysis will be necessary in assessing suitability for drug development. CS thanks AM and GK for their guidance and encour- agement and SR for his mentorship, as well as all the col- laborators for their support and advice. Cer, R. Z., Mudunuri, U., Stephens, R., and Lebeda, F. J. (2009) NucleicAcids Res. 37, W441–W445 Copeland, Robert Allen. Enzymes: a Practical Introduction to Structure, Mechanism, and Data Analysis. New York: Wiley, 2000. Chiaradonna, F., R.m. Moresco, C. Airoldi, D. Gaglio, R. Palo- rini, F. Nicotra, C. Messa, and L. Alberghina. “From Cancer Me- tabolism to New Biomarkers and Drug Targets.” Biotechnology Ad- vances 30.1 (2012): 30-51. Creese, I., D. Burt, and S. Snyder. “Dopamine Receptor Binding Predicts Clinical and Pharmacological Potencies of Antischizophren- ic Drugs.” Science 192.4238 (1976): 481-83. Davis, Kenneth L., Rene S. Kahn, Grant Ko, and Michael David- son. “Dopamine in Schizophrenia: A Review and Reconceptualiza- tion.” Am J Psychiatry 148.11 (1991): 1474-486. Dhawan, J. “A New Look at Glutamate and Ischemia: NMDA Agonist Improves Long-term Functional Outcome in a Rat Model of Stroke.” Future Neurol. 6.6 (2011): 823-34 Gaisler-Salomon, Inna, Gretchen M. Miller, Nao Chuhma, Sooyeon Lee, Hong Zhang, Farhad Ghoddoussi, Nicole Lewan- dowski, Stephen Fairhurst, Yvonne Wang, Agnès Conjard-Duplany, Justine Masson, Peter Balsam, René Hen, Ottavio Arancio, Matthew P. Galloway, Holly M. Moore, Scott A. Small, and Stephen Rayport. “Glutaminase-De"cient Mice Display Hippocampal Hypoactivity, Insensitivity to Pro-Psychotic Drugs and Potentiated Latent Inhi- bition: Relevance to Schizophrenia.” Neuropsychopharmacology 34.10 (2009): 2305-322. Hartwick, E. W., and N. P. Curthoys. “BPTES Inhibition of HGA(124-551), a Truncated Form of Human Kidney- type Glutaminase.” J Enzyme Inhib Med Chem (2011). Huang, Y., L. Zhao, B. Jia, L. Wu, Y. Li, N. Curthoys, and J. C. Zheng. “Glutaminase Dysregulation in HIV-1-Infected Human Microglia Mediates Neurotoxicity: Relevant to HIV- 1-Associated Neurocognitive Disorders.” Journal of Neuro- science 31.42 (2011): 15195-5204. Javitt, Daniel C. “Glutamatergic #eories of Schizophre- nia.” Isr J Psychiatry Relat Sci 47.1 (2010): 4-16. Jorgensen WL. Acc Chem Res. 2009;42:724–733. Kellendonk C, Simpson EH, Polan HJ, Malleret G, Vronskaya S, Winiger V, Moore H, Kandel ER. Transient and selective over- expression of dopamine D2 receptors in the striatum causes per- sistent abnormalities in prefrontal cortex functioning. Neuron. 2006;49:603–615. Matthysse S. Antipsychotic drug actions: a clue to the neuropa- thology of schizophrenia.Federation Proc. 1973;32:200–208. McElroy, K. “Implementation of a Continuous, Enzyme-Cou- pled Fluorescence Assay for High-#roughput Analysis of Gluta- mate-Producing Enzymes.” Analytical Biochemistry 284.2 (2000): 382-87. Sanacora, Gerard, Carlos A. Zarate, John H. Krystal, and Hus- seini K. Manji. “Targeting the Glutamatergic System to Develop Novel, Improved #erapeutics for Mood Disorders.” Nature Re- views Drug Discovery 7.5 (2008): 426-37. cusjcolumbia undergraduate science journal Research Articles 8cusj Volume 6Spring 2012 Columbia Undergraduate Sci J http://cusj.columbia.edu P S Y C H IATR Y Discussion Acknowledgments References