|Home | About | Journals | Submit | Contact Us | Français|
Serotonin N-acetyltransferase (arylalkylamine N-acetyltransferase, AANAT) is a member of the GCN5 N-acetyltransferase (GNAT) superfamily and catalyzes the penultimate step in the biosynthesis of melatonin; a large daily rhythm in AANAT activity drives the daily rhythm in circulating melatonin. We have used a structure-based computational approach to identify the first drug-like and selective inhibitors of AANAT. Approximately 1.2 million compounds were virtually screened by 3D high-throughput docking into the active site of X-ray structures for AANAT and in total 241 compounds were tested as inhibitors. One compound class, containing a rhodanine scaffold, exhibited low micromolar competitive inhibition against acetyl-CoA (AcCoA), and proved effective in blocking melatonin production in pineal cells. Compounds from this class are predicted to bind as bisubstrate inhibitors through interactions with the AcCoA and serotonin binding sites. Overall, this study demonstrates the feasibility of using virtual screening (VS) to identify small molecules which are selective inhibitors of AANAT.
Melatonin is produced in the pineal gland on a circadian schedule and is involved in the regulation of the biological clock in vertebrate organisms.1,2 Circulating levels of melatonin rise and fall on a daily basis under the control of an endogenous circadian clock located in the suprachiasmatic nucleus. Light entrains the clock to a diurnal cycle, thus gating stimulation of the pineal gland. The biosynthesis of melatonin in the pineal gland involves the conversion of 5-hydroxytryptamine (serotonin)a to 5-hydroxy-N-acetyltryptamine (N-acetylserotonin), catalyzed by serotonin N-acetyltransferase (arylalkylamine N-acetyltransferase, AANAT); this is followed by O-methylation to 5-methoxy-N-acetyltryptamine (melatonin), which is catalyzed by 5-hydroxyindole O-methyltransferase (HIOMT). The rhythmic production of melatonin is controlled by large changes in the activity of AANAT; in contrast, HIOMT is constitutively active and does not regulate melatonin rhythm.3 Efforts to understand the function of melatonin and to explore its modulation therapeutically have led investigators to develop inhibitors of AANAT. Such inhibitors have the potential to be useful in the treatment of a variety of sleep and mood disorders.4
Two strategies to identify AANAT inhibitors have been reported previously. One approach involved high throughput screening, which resulted in moderately potent in vitro peptide-based inhibitors of AANAT;4f their utility remains to be established. A second approach, which is based on the enzyme mechanism of AANAT, focused on the development of bisubstrate inhibitors, a strategy which has been used successfully to develop inhibitors of other members of the superfamily to which AANAT belongs.5,6 In the case of AANAT, a bisubstrate inhibitor has been developed that mimics the transient Coenzyme A-S-acetyltryptamine (CoA-S-acetyltryptamine) complex that is thought to form during acetyl transfer (Figure 1). This compound is highly potent and selective for AANAT (Ki = 90 nM).4i Unfortunately, this compound exhibits no in vivo activity, because its multiple phosphate groups confer poor cell permeability and unfavorable pharmacological properties.4j To overcome this limitation, several pro-drug approaches have been devised in attempts to generate bisubstrate inhibitors in vivo within the cytoplasm.4,7 However, due to various technical limitations, these methods have met with mixed results.4,7
In the study presented here, a computational approach to the identification of AANAT inhibitors has been used, one which employs virtual screening (VS) to identify candidate inhibitors with properties similar to known drugs (drug-like).8 This approach exploits the reported structures of AANAT in complex with bisubstrate and other coenzyme A (CoA) analogs.9
AANAT belongs to the GCN5 N-acetyltransferase (GNAT) family of proteins, which share a conserved structural domain.6a This domain originally evolved to bind CoA through conserved backbone interactions and facilitate acetyl transfer to a substrate. The CoA binding site is composed of two binding elements. The first is the backbone amides of a loop, known as the P-loop, which interact with the pyrophosphate oxygen atoms of CoA; the second site is a V-shaped cavity created between two parallel strands of a β-sheet. The exposed amide backbone within this cavity coordinates to the β-alanyl pantetheine backbone of CoA. Interestingly, the adenine moiety of the cofactor is solvent-exposed and does not significantly contribute to binding with GNATs.6,9,10
This CoA binding site exhibits several positive attributes for binding drug-like small molecules. First, in contrast to many nucleotide dependent proteins, a small molecule ligand need not mimic adenine to bind to the cofactor site. Therefore, there is less risk of non-selective binding to the multitude of nucleotide binding proteins. Second, the conserved backbone interactions may be exploited for high affinity binding, utilizing a wide range of drug-like moieties such as carboxylate, amide or sulfonamide groups. Third, the V-shaped cavity is buried, and thus provides a hydrophobic environment that is conducive to binding small drug-like molecules.
Whereas the CoA binding sites of GNAT superfamily members are similar, distinct structural differences exist in the substrate binding sites, since these regions have evolved to bind a broad range of acetyl-group acceptors, including proteins and small molecule substrates. A small molecule candidate inhibitor that binds here would impart selectivity, but, as is often the case, the cofactor binding site may enhance affinity. Thus, to gain selectivity over other homologous GNAT proteins that bind AcCoA, it is desirable for a potent and selective inhibitor of AANAT to span both sites. To this end, we describe in this report the successful use of VS to facilitate the discovery of novel inhibitors of AANAT.
Docking and screening procedures, referred to as VS, can select small sets of likely lead drug candidates from large libraries of commercially or synthetically available compounds.11 In the first stage, a non-redundant drug-like commercial database of 1.2 million fully flexible ligands was docked into a grid representation of AANAT. The docking pose was then scored to maximize the discrepancy between binders and non-binders and rank the interaction of the compound with the receptor. This score takes into account the ligand–receptor interaction energy, conformational strain energy of the ligand, conformational entropy loss, and desolvation effects.11c Computational analysis (see Materials And Methods) on the top scoring compounds resulted in the retention of a few thousand compounds. Given the expense of purchasing a few compounds from each vendor, for this proof-of-concept work we decided to limit the number of purchased compounds to those available from the Sigma-Aldrich library of rare chemicals (based on the price competitiveness of this vendor) and from the NCI repository (for which compounds are free), with a combined total of 234,501 compounds. Finally, selection based on visual inspection of the predicted docking pose resulted in 188 compounds being chosen for biological testing.
The 188-compound subset nominated by VS was tested for its ability to inhibit ovine AANAT (oAANAT). In the primary screen, compounds that showed greater than 40% inhibition at 100 μM in an α–ketoglutarate dehydrogenase (αKD)-coupled, spectrophotometric assay were assigned as potential hits.12 A product inhibitor, N-acetyltryptamine, was used as a positive control and exhibited an IC50 of 402 μM, which is consistent with the published value (Table 1).5 The primary screen resulted in the identification of 23 potential hits. An iterative approach was taken to identify false positives. This approach included doubling the amount of αKD (to identify inhibitors that act on the coupling enzyme), rescreening in the presence of 0.01% Triton X-100 (to identify inhibitors that work by non-specific mechanisms, such as aggregation)13, structural validation by electrospray mass spectrometry (ESI-ms) and 1H-NMR, and, finally, confirmation of inhibitor activity in a direct radioactive acetyltransferase assay (Figure 2).14 Of the 23 potential hits from the primary screen, the following 5 compounds were confirmed AANAT inhibitors (Table 1, Figure 2): 1B (L332631), 2B (R833789), 3B (R880868), 1C (R825190), 2C (R824682). These compounds fell into two classes, B (carboxylate) and C (sulfonate, Figure 3). For comparison, the bisubstrate inhibitor CoA-S-acetyltryptamine is shown in Figure 1, and the structures of the false positives are shown in Figure 4. Based on the structures of these hits, a second subset of 53 compounds was tested that further explored scaffolds B and C as well as close analogs of the other potential hits from the initial screen. In an attempt to identify more potent inhibitors, the secondary screen was conducted with a more stringent cutoff of 40% inhibition at 25 μM. This resulted in the identification of 8 potential candidates, of which only 4B (L332607) was verified as an AANAT inhibitor (Table 2, Figures 2--3).3). Again, the structures of the false positives are shown in Figure 4. In the primary and secondary screen, the confirmed hit rates were approximately 2.7% and 1.9%, respectively (5 of 188 and 1 of 53). This lower hit percentage most likely reflects the fact that only a subset of commercially available VS hits were chosen for biological evaluation, namely those available from Sigma-Aldrich or the NCI repository.
Class B compounds contained a rhodanine scaffold with two sites of substitution on the indolinone (R1 and R2, Figure 3). With the exception of compound 4B, substitution at either of these positions did not significantly change the IC50 value (IC50 = 40-50 μM). With respect to compound 4B, acetylation of the indolinone nitrogen (R1) resulted in an approximately 2-fold decrease in IC50 (40-50 μM to 25 μM). Interestingly, carboxymethylation of this nitrogen (compound 22A) eliminates inhibitory activity of the compound suggesting that negatively charged substituents at this position are not tolerated. It is possible that acetylation at R1 in combination with another substitution will yield even more potent Class B compounds. Class C compounds contain a similar pharmacophore as Class B compounds, except that they have a shorter alkyl arm that terminates with a sulfonate instead of a carboxylate. In general, Class C compounds were more potent than Class B compounds; however, the presence of the sulfonate will require a pro-drug strategy to improve drug-likeness. With respect to this class of compounds, a larger substitution on the indolinone nitrogen (R1) yielded a more potent compound (compare 1C to 2C). The possibility for expansion with respect to the rhodanine scaffold is virtually limitless and largely unexplored. One can even imagine creating hybrid classes of compounds from these two scaffolds. For example, two additional classes can be created by substituting the acid in Class B with a sulfonate and substituting the sulfonate in Class C with an acid.
As one of the goals of this project was to identify cell permeable inhibitors of melatonin biosynthesis, one inhibitor from each class (2B and 1C) was selected for ex vivo evaluation in a rat pinealocyte based assay.15 Of these compounds, only 2B was able to inhibit melatonin biosynthesis and inhibition was reversed upon removal of the drug from the medium (Figure 5A, compare bars 3 and 5). More extensive analysis of 2B in this assay showed that the compound inhibited melatonin biosynthesis in a dose dependent manner, yielding an IC50 in the cell based assay of ~100 μM (Figure 5B). Furthermore, compound 2B did not appear to be non-specifically toxic to the cells, because the amount of cellular AANAT was not altered when the concentration of 2B was increased (Figure 5C).
The mechanism of inhibition for Class B compounds was probed by comparing IC50 values under different assay conditions. Compound 2B was selected as the prototype for this analysis, since it showed efficacy in the cell based assay. For this analysis, the IC50 was determined under three conditions using the αKD-coupled spectrophotometric assay: (i) At Km for each substrate; (ii) at saturating tryptamine (TrpNH2, 5× Km) and Km for AcCoA; and (iii) at saturating AcCoA (5× Km) and Km for TrpNH2. The following relationships were used to predict the effects of varying substrate concentrations on IC50 and deduce the mechanism of inhibition:16
For competitive inhibition, the IC50 should shift to be 3-fold less potent (to the right) when the substrate concentration is increased from Km to 5× Km. For noncompetitive inhibition, the IC50 should be independent of substrate concentration, and for uncompetitive inhibition the IC50 should shift to be 1.7-fold more potent (to the left) when the substrate concentration is increased from Km to 5× Km. As seen in Figure 6, IC50 was independent of the TrpNH2 concentration and dependent on the AcCoA concentration. Furthermore, ΔIC50 was 2.6-fold (less potent) which is close to the predicted 3-fold change. Taken together, it is reasonable to conclude that Class B compounds are competitive with respect to AcCoA and noncompetitive with respect to TrpNH2. These results are consistent with Class B compounds acting either as pure competitive inhibitors of AcCoA or as bisubstrate inhibitors.17 However, in this analysis it is impossible to tell the former from the latter. It should be noted that Class B compounds were predicted to be bisubstrate inhibitors of AANAT. As modeled in Figure 7A, the p-fluorophenyl (R1) of compound 2B docks in the serotonin binding site, and the remainder of the hydrophobic pocket is filled by the indolinone moiety. Furthermore, the thiazolidinone carbonyl is hydrogen bonded to the side chain of the proposed catalytic Y168. The 6-carbon aliphatic linker spans the AcCoA binding site where the carboxylate is anchored by hydrogen bonding with the backbone amide nitrogens of Q132, G136, and K135. In this manner, 2B exploits the same backbone interactions as the β-phosphate of AcCoA.9 As a comparison, the structure of CoA-S-acetyltryptamine bound to AANAT is shown in Figure 7B.
As the results have shown, Class B compounds are cell permeable inhibitors of melatonin biosynthesis that presumably act at the level of AANAT. Furthermore, these compounds are competitive with AcCoA. To examine the specificity of Class B compounds, a prototype compound (2B) was evaluated for inhibition against another GNAT family member, p300/CBP-associated factor histone acetyltransferase (PCAF HAT), which binds and utilizes AcCoA in a similar manner. As demonstrated in Figure 8, compound 2B did not inhibit PCAF at concentrations as high as 50 μM, suggesting that this scaffold imparts selectivity toward the unique substrate (i.e. serotonin) binding site of AANAT.
As a final verification of inhibitor potency, we elected to determine the IC50 of 2B and 4B in the direct radioactive acetyltransferase assay (Figure 9).14 The results confirmed that both compounds inhibited AANAT activity. In this assay, these inhibitors appeared to be approximately 4-fold more potent than in the αKD-coupled assay. This presumably reflects the lower concentration of AcCoA in the radiochemical assay. In addition, the presence of coupling enzyme and cofactors/cosubstrates for the coupling enzyme may contribute to inhibitors appearing somewhat less potent in the spectrophotometric assay. From this analysis, the most potent Class B compound was compound 4B, which had an IC50 of 6.8 μM, whereas compound 2B had an IC50 of 11.1 μM. This class of compounds thus represents a promising lead for further medicinal chemical development.
As demonstrated with AANAT, it is possible to select, through VS, small molecule inhibitors with selectivity and affinity. In this proof-of-concept work we selected from a subset (1.2 million / 230K = 1/5) of total available commercial compounds and were able to identify a scaffold for lead-optimization. The rhodanine nucleus identified here has also been observed to inhibit other enzymes of interest, although in these cases it is decorated with alternative modifications.18 In follow-up studies, we have the option to identify more inhibitor classes through selecting from other vendors represented in the virtual screen or to optimize the scaffold identified in this work, as well as establish specificity versus a broader array of protein targets. The resulting AANAT inhibitors may eventually lead to development of a drug that would be useful in circadian biology research and in the treatment of sleep and mood disorders. In the future, it would be interesting to evaluate these inhibitors against the AANAT: 14-3-3ζ complex, since this complex is stable to proteolysis in vivo and ultimately responsible for elevated nighttime melatonin biosynthesis.9e,14,19,20
Whatman LK6D (channeled, silica gel) TLC plates and DMSO (molecular biology grade) were from Fisher Scientific. AcCoA and [14-C]-AcCoA were from GE Healthcare. Fetal calf serum (dialyzed), bovine serum albumin (BSA), thiamine pyrophosphate (TPP), dithiothreitol (DTT), β-nicotinamide adenosine diphosphate (β-NAD), α-ketoglutaric acid, αKD (porcine heart), TrpNH2, and N-acetyltryptamine were from Sigma-Aldrich. Papain and DNase I were from Worthington Biochemicals. Protease inhibitor cocktail was from Roche Applied Science. [14C]-BSA was from NEN Life Science Products. All inhibitors were purchased either from the Sigma-Aldrich rare chemical library or the NCI repository.
All computational techniques were performed using the ICM (Internal Coordinate Mechanics) software suite under a Linux environment. The coordinates of the protein were taken from the RCSB Protein Data Bank. Hydrogen and missing heavy atoms were added to the receptor structure, followed by local minimization to resolve clashes and to correct chemistry, using a conjugate gradient algorithm and analytical derivatives in internal coordinate space.21 Water molecules were replaced by a continuous dielectric, and the orientation of asparagine and glutamine side chains as well as the tautomeric state of histidine residues were optimized. Seven x-ray crystal structures are reported in the PDB for mammalian AANAT (six of ovine and one of human AANAT). The three liganded structures with the highest crystallographic resolution (PDB codes 1CJW, 1KUV and 1KUX) were chosen for VS.9a,9c All three structures contain potent bisubstrate inhibitors of AANAT. Interestingly, comparison to the unliganded (apo) structure (PDB code 1B6B)9d shows major ligand-induced changes in the active site. For this reason, the apo-structure was not used for VS.
Cheminformatics manipulations and analysis was performed with ICM. Ten databases, from the vendors Asinex (Russia), BioNet (England), Chembridge (USA), Chemical Diversity (USA), IBS (Russia), Maybridge (USA), Sigma-Aldrich (USA), Specs (Netherlands), Tripos (USA) and TimTec (Russia), in 2D SDF format and totaling 2.05 million commercially available compounds were collated. Compounds common to more than one source (redundant) or nondrug-like (likely nonspecific inhibitors) were removed.22 The following criteria were imposed to compile the non-redundant and drug-like commercial database: (i) predicted solubility in water better than 1 μM; (ii) molecular weight less than 650; (iii) no atoms heavier than bromine. A library of 1.2 million compounds, stored as a single 2D SDF file, resulted from this process.
VS was performed with the ICM-Docking and ICM-VLS modules within ICM. The bisubstrate inhibitor was removed from the complexes available from the PDB and the non-redundant drug-like library was high-throughput docked. High-throughput docking and scoring calculations were performed on a Linux cluster (up to 200-Intel Xeon processors simultaneously) at the Scripps Research Institute. An important benefit in performing VS is that a wide range of 3D descriptors is generated from the docked complex. These descriptors can then be used, in conjunction with the docking score, to improve discrimination between true binders and false positives. To implement this approach, VS results were ranked by their ICM score. The ICM scoring function includes the terms for van der Waals interactions, hydrogen bonding, electrostatics, hydrophobic interactions, desolvation and ligand entropy loss.23 The term weights were optimized for maximal separation of binders and non-binders on a binding benchmark. The following three conditions were then imposed to nominate compounds for biological testing. First, a permissive cutoff score was imposed that resulted in only the top 1% of top scoring compounds being retained. Second, the location of the ligand in the pocket was considered, as the AANAT active site contains sub-sites for binding of cofactor (i.e. AcCoA) and substrate (i.e. serotonin). Bisubstrate ligands or ligands that occupy the serotonin binding site were preferred, since they are more likely to show high affinity and selectivity for AANAT over other members of the GNAT family. Third, the ligand should make at least one hydrogen bond with the protein. Furthermore, a conserved backbone hydrogen bond interaction with the oxygen atoms of the pyrophosphate moiety of AcCoA is characteristic for cofactor binding. Small molecules that exploit this conserved backbone interaction are preferred, as they are likely to bind with higher affinity.
Full length (1-207) oAANAT was prepared by expressed protein ligation (EPL) as previously described.19 oAANAT purified via this method was > 90% pure by SDS-PAGE analysis, and contained a single mutation (Ala200Cys) that was necessary for the EPL reaction but did not affect enzyme activity. Protein mass was confirmed (22,976 ± 60 Da) by matrix-assisted-laser-desorption-ionization (MALDI) mass spectrometry. PCAF HAT catalytic domain was purified as previously described to > 90% purity by SDS-PAGE analysis.24
Initial screening was done by continually monitoring oAANAT acetyltransferase activity on a Beckman DU-640 spectrophotometer equipped with a thermostated cell holder (T = 25 °C), using the αKD-coupled assay as described by Kim et al.12 This assay couples the formation of CoA to reduction of β-NAD to β-NADH (E340 nm = 6230 M-1cm-1) using αKD. Reactions (150 μL) were done in 0.1 M ammonium acetate (pH 6.8) and contained 50 mM NaCl, 0.2 mM β-NAD, 0.2 mM TPP, 5 mM MgCl2, 1 mM DTT, 2.4 mM α-ketoglutaric acid, 0.2 mM AcCoA (Km = 0.212 mM)5, 0.2 mM TrpNH2 (Km = 0.147 mM)5, 50 μg/mL BSA, and 0.1 Units αKD. Assays were initiated by addition of oAANAT (75 nM). Product formation (β-NADH) was monitored at 340 nm and initial velocities (≤ 10% complete) were determined by linear regression to progress curves. Progress curves were linear to 10% complete and initial velocities were linear with respect to oAANAT concentration to 150 nM. When evaluating inhibitors, the DMSO concentration was held constant at 3.3%. IC50s for all validated hits were determined using the following equation:
oAANAT acetyltransferase activity was directly monitored in a TLC-based radioactive assay that was adopted from Ganguly et al.14 Reactions (100 μL) were done at 25 °C in 0.1 M ammonium acetate (pH 6.8) and contained 50 mM NaCl, 50 μg/mL BSA, 1 mM DTT, 0.1 mM TrpNH2, 0.1 mM [14C]-AcCoA, and were initiated by addition of oAANAT (3.5 nM). After 10 min the reactions were quenched by the addition of ethyl acetate (EtOAc, 4 volumes) and vortexing (30 sec). The organic phase, which contained the reaction product (N-acetyltryptamine), was removed to a fresh tube and the extraction was repeated. The pooled organic extracts were then dried in vacuo, resuspended in EtOAc (75 μL), spotted on Whatman LK6D TLC plates (25 μL), and developed in CHCl3:methanol:acetic acid (90:10:1 v/v/v). Radioactivity was quantified by PhosphorImage analysis (Molecular Dynamics). Reactions did not exceed 10% completion. Product formation was linear over the course of the reaction and with respect to oAANAT concentration to 10 nM. When evaluating inhibitors, the DMSO concentration was held constant at 3.3%. IC50 of selected compounds (2B and 4B) were determined in this assay using Eq. 4.
Pinealocytes were prepared from rat pineal glands as described previously.15 Briefly, pineal glands were incubated (1 h, 37°C) with 20 units/mL papain and 200 units/mL DNase I in Earle's Balanced Salt Solution (EBSS). Subsequently, glands were triturated and the resulting preparation was passed through a 40 μm cell strainer (BD Falcon). The pinealocytes were harvested, washed and suspended in Dulbecco's modified Eagle's medium (DMEM) supplemented with 10% fetal calf serum, 2 mM glutamine, 100 units/mL penicillin, and 100 μg/mL streptomycin and incubated overnight at 37 °C (air / CO2, 95%:5%). The following day, the cells were distributed in separate tubes (200,000 cells/250μL) for drug treatments. Cells were first treated with drug (2B or 1C) or 4% DMSO for 1 h. After 1 hour, norepinephrine (NE, 1μM) alone or in combination with drug was added to the desired tubes and incubated for an additional 5 hours.
Melatonin production from the pinealocytes was estimated by a liquid chromatography-quadrupole linear ion trap mass spectrometer system (Q TRAP®, Applied Biosystems).7b The system was connected on-line to SB-C18 column (Zorbax, 3.5 μm, Agilent), and the data were acquired by using Analyst 1.4 software. Q TRAP® was operated in positive mode with the curtain gas set to 35 (arbitrary units), and the source temperature was 350 °C. A multiple reaction monitoring (MRM) transition was selected from the list of parameters obtained after quantitative optimization of melatonin (positive mode mass 233.2). The detection method was developed by selecting parameters for a product ion (mass 174) with highest intensity value. Optimized values of the parameters used are as follows: declustering potential − 411 volts, entrance potential − 10 volts, collision cell entrance potential − 20 volts, and collision cell exit potential − 4.0 volts.
For melatonin measurement in the media (250 μL), the cells were first removed by centrifugation at 10,000 × g for 10 min and the supernatants were collected and mixed with an equal volume of methanol. The supernatants were clarified by centrifugation (10,000 × g, 20 min), taken to dryness, and the residue was resuspended in 60 μL of 50% aqueous methanol. A 30μL sample of the methanol extract of media (see above) was injected into the in-line C18 column using an auto-sampler 1100 (Agilent). The flow rate was maintained at 300 μL/min using 50% aqueous methanol as mobile phase. The melatonin value was calculated from the area of the intensity peak (expressed as cycles per second) using the Analyst 1.4 software and a standard curve.
To detect the expression of AANAT, rat pinealocytes (that were previously treated with 2B) were homogenized in 0.1 mM Tris-HCl pH 7.5 containing protease inhibitor cocktail. The homogenate was subjected to a brief sonication (3 × 1 s pulses; Bronwill Scientific) and clarified by centrifugation (6,000 × g, 5 min). The supernatant was boiled in Laemmli sample buffer under reducing conditions and proteins were separated by SDS-PAGE. The proteins were then transferred onto an Immobilon-P membrane (Millipore) and AANAT was detected with a rabbit polyclonal anti-sera (1:10,000 dilution) raised against rat AANAT25-205 sequence.
The radioactive PCAF HAT assay was adapted from Lau et al.24a The reaction buffer contained 50 mM Tris-HCl (pH 8.0), 1 mM DTT, 0.1 mM EDTA, and 50 μg/mL BSA. Reactions used purified PCAF HAT enzyme at concentration of 10 nM in presence/absence of compound 2B (0-50 μM) in DMSO (3.3% final v/v) along with 10 μM substrate (histone H3 residues 1-20, H3-20). Assays were carried out at 30 °C with reaction volumes of 30 μL. Reactions were initiated with 20 μM [14C]-AcCoA after the other components were equilibrated at 30 °C and quenched after 5 min with 6× Tris-tricine gel loading buffer. Mixtures were separated on 16% SDS Tris-tricine polyacrylamide gels and dried, and radioactivity was quantified by PhosphorImage analysis (Molecular Dynamics) by comparison to known quantities of [14C]-BSA standard. In all cases, background acetylation (in the absence of enzyme) was subtracted from the total signal. All assays were performed in duplicate, and data agreed within 20%.
This work was supported by the NIH. R.A. is a co-founder of Molsoft and has a significant financial interest in this company. M.J. appreciates support from the MARC program, and M.H. has been supported by the W.M. Keck Foundation.
aAbbreviations: serotonin N-acetyltransferase, AANAT; GCN5 N-acetyltransferase, GNAT; coenzyme A, CoA; acetyl-coenzyme A, AcCoA; virtual screening, VS; 5-hydroxytryptamine, serotonin; 5-hydroxyindole O-methyltransferase, HIOMT; 5-hydroxy-N-acetyltryptamine, N-acetylserotonin; 5-methoxy-N-acetyltryptamine, melatonin; ovine AANAT, oAANAT; α-ketoglutarate dehydrogenase, αKD; tryptamine, TrpNH2; P300/CBP associated factor histone acetyltransferase, PCAF HAT; thiamine pyrophosphate, TPP; expressed protein ligation, EPL; ethyl acetate, EtOAc; norepinephrine, NE; histone H3 residues 1-20, H3-20; ICM (Internal Coordinate Mechanics).