J. Med. Chem. 2008, 51, 6627–6630
6627
Letters
Structure-Based Virtual Screening and
Biological Evaluation of Mycobacterium
tuberculosis Adenosine 5′-Phosphosulfate
Reductase Inhibitors
Sandro Cosconati,†,#,§ Jiyoung A. Hong,‡,§ Ettore Novellino,#
Kate S. Carroll,‡ David S. Goodsell,† and Arthur J. Olson*,†
Department of Molecular Biology, The Scripps Research Institute,
10550 North Torrey Pines Road, La Jolla, California 92037,
Department of Chemistry and The Life Sciences Institute, UniVersity
of Michigan, Ann Arbor, Michigan 48109, and Dipartimento di
Chimica Farmaceutica e Tossicologica, UniVersità di Napoli
“Federico II”, Via D. Montesano, 49-80131 Napoli, Italy
ReceiVed May 15, 2008
Abstract: Tuberculosis is among the world’s deadliest infectious
diseases. APS reductase catalyzes the first committed step in bacterial
sulfate reduction and is a validated drug target against latent tuberculosis
infection. We performed a virtual screening to identify APSR inhibitors.
These inhibitors represent the first non-phosphate-based molecules to
inhibit APSR. Common chemical features lay the foundation for the
development of agents that could shorten the duration of chemotherapy
by targeting the latent stage of TB infection.
Despite advances in chemotherapy and the Bacillus CalmetteGuérin (BCG) vaccine, tuberculosis (TB) remains a leading
infectious killer worldwide.1 Although drugs exist to treat TB,
they are not effective against bacilli that persist in a dormant
or latent state within host lesions.2 As a result, current treatments
for TB require a cocktail of three to five drugs for at least 6
months, a regime that many patients are unable or unwilling to
follow.3 The lengthy and complex therapy also contributes to
the development of drug-resistant TB, which is even more
difficult and expensive to treat. Of the 9 million known cases
of TB worldwide, as many as 2% could be extensively drugresistant.4 This statistic raises the specter of virtually untreatable
strains of TB and represents a severe public health problem.
For these reasons, there is an urgent need for drugs that target
the latent phase of TB infection.
To this end, microbial sulfate metabolism represents a
promising new area for TB therapy.5 Reduction of inorganic
sulfate is the means by which bacteria produce sulfide, the
oxidation state of sulfur required for the synthesis of essential
biomolecules including amino acids, proteins, and metabolites.5,6
APSa reductase (APSR, encoded by cysH) catalyzes the first
committed step in bacterial sulfate reduction.7 In this reaction
adenosine 5′-phosphosulfate (APS) is reduced to sulfite and
adenosine 5′-phosphate (AMP).7 Consistent with its important
* To whom correspondence should be addressed. Phone: (858) 784-9702.
Fax: (858) 784-2860. E-mail: olson@scripps.edu.
†
The Scripps Research Institute.
#
Università di Napoli “Federico II”.
§
These authors contributed equally to this work.
‡
University of Michigan.
a
Abbreviations: APS, adenosine 5′-phosphosulfate; APSR, adenosine
5′-phosphosulfate reductase; AD4, AutoDock4; VLS, virtual ligand screening; NCI, National Cancer Institute.
Figure 1. Experimental binding conformations of APS in APSR
structure. Substrate is displayed with carbon atoms in green, and key
binding site residues are labeled. Hydrogen bonds are represented with
dashed yellow lines.
metabolic role APSR was identified in a screen for essential
genes in M. boVis BCG and cysH is actively expressed during
the dormant phase of M. tuberculosis and in the environment
of the host macrophage.5 Most recently, Senaratne et al.
demonstrated that APSR is required for survival in the latent
phase of TB infection.8 APSR is not found in humans and thus
represents a unique target for antibacterial therapy. Recognizing
its value as novel antibiotic target, in 2006 Chartron et al.
reported the three-dimensional (3D) crystal structure of Pseudomonas aeruginosa APSR in complex with APS substrate.9 P.
aeruginosa and M. tuberculosis APSR are related by high
sequence homology (27.2% of sequence identity and 41.4% of
sequence similarity), particularly in residues that line the active
site (Supporting Information). In this structure, APS is situated
in a deep active site cavity with the phosphosulfate extending
toward the protein surface.
Conserved and semiconserved residues participate in four
main-chain hydrogen bonds with adenine and the ribose O2′
hydroxyl (Figure 1). Interaction between the phosphosulfate and
APSR occurs via strictly conserved residues K144, R242, and
R245 (Figure 1). The phosphosulfate is also positioned opposite
an [4Fe-4S] cofactor and C140. However, the substrate is not
in direct contact with the [4Fe-4S] cluster; the sulfate oxygens
are 7 Å from the closest iron atom and 6 Å from the closest
cysteine sulfur atom.
To date, only nucleotide-based inhibitors have been reported
for APSR, and these are expected to have limited bioavailability.10 Solution of the P. aeruginosa APSR structure in complex
with substrate affords a new opportunity for the discovery of
inhibitors, particularly in the application of high-throughput
docking of molecular databases to identify lead compounds. To
this end, we have taken an approach that combines computational docking methods with biochemical evaluation. The new
10.1021/jm800571m CCC: $40.75  2008 American Chemical Society
Published on Web 10/15/2008
6628 Journal of Medicinal Chemistry, 2008, Vol. 51, No. 21
Letters
Table 1. Structures, AutoDock Binding Energies, and Activities of
APSR First Generation Inhibitor Compounds
Figure 2. Results of the VS (using AD4) of the NCI Diversity Set
against APSR. (a, top) Bars represent numbers of Diversity Set
compounds with predicted free energies of binding in the indicated 1
kcal/mol bins. Red bars highlight the energies of those compounds
having a ∆GAD4 lower than -8 kcal/mol. (b, bottom) Bars represent
the population of the frequency of occurrence of the largest cluster for
each docked ligand. Red bars highlight a frequency of occurrence higher
than 20 out of 100.
version of AutoDock (AD4)11 was used to conduct virtual ligand
screening (VLS) of the National Cancer Institute (NCI) Diversity
Set12 against the P. aeruginosa APSR crystal structure (PDB
code 2GOY). Initial docking calculations were performed using
APS substrate to evaluate APSR as a structural model for VLS.
The docked conformation determined by AD4 with the lowest
predicted binding energy (-9.46 kcal/mol, ∆GAD4) was in
excellent agreement with the bound conformation observed for
APS in the crystal structure (rmsd 0.7 Å); the calculated
positions of the adenine ring, ribose sugar, and phosphosulfate
group were almost identical to those found in the crystal
structure. On the basis of these encouraging results, VLS
calculations were performed with the APSR crystal structure
using the database of compounds in the NCI Diversity Set. The
VLS results were sorted on the basis of their predicted binding
free energies (∆GAD4), which ranged from -3.16 to -13.76
kcal/mol, and according to the cluster size for each docking
conformation. Solutions with a predicted binding free energy
greater than -8.0 kcal/mol and a cluster size lower than 20 out
of 100 individuals were discarded.
Cluster size is included in these criteria as an empirical
measure of the configurational entropy, as shown in previous
work.10 On the basis of these criteria, 14.8% of the solutions
had energies lower than -8.0 kcal/mol, 43.3% had a cluster
population higher than 20 individuals, and 10.0% (192 compounds) met both these criteria (Figure 2). The predicted binding
conformations for these 192 solutions were visually inspected.
Compounds that were not predicted to interact with important
residues such as K234, R242, or R245 were removed from
consideration. After this final step, 42 compounds corresponding
to 2% of the original NCI Diversity Set were selected for further
analysis. When ordered from NCI (The NCI/DTP Open Chemical Repository), three of these compounds were not available,
so 39 compounds were obtained for biochemical testing.
Assessment of the 39 top-ranked compounds from the VLS as
potential inhibitors of APSR was performed using a standard
radioactive assay, measuring APSR reduction of 35S-labeled
APS substrate. The compounds that exhibited significant inhibitory activity (more than 50% inhibition) are listed in Table 1,
along with the AD4 binding energies and measured activities.
Three compounds from this set, tested at 100 µM, inhibited
APSR activity by more than 50%: 133896, 327704, and 348401
(Table 1). In particular, 348401 resulted in more than 90%
inhibition (Table 1).
Compounds listed in Table 1 were predicted to have the
similar affinities for APSR (see Table 1, ∆GAD4); however, the
experimental binding constants span a range of 6.81-48.11 µM.
This is not unexpected, since the computed binding energies in
calibration experiments typically have errors in the range of 2
kcal/mol, which corresponds roughly to a 30-fold difference in
predicted binding constants. The above-mentioned compounds,
representing the most potent inhibitors from our screen, were
investigated further and were found to produce concentrationdependent inhibition of APSR activity without promiscuous
inhibition. Data were fit to a competitive inhibition model (R2
g 0.98), and the inhibition constant (Ki) was determined for
each compound in Table 1. Under the conditions employed for
these assays the Ki was equal to the dissociation constant (Kd)
of each compound (Supporting Information). Dissociation
constants for the most potent inhibitors in Table 1 ranged from
15 to 50 µM.
Second-generation lead compounds were identified by docking and assaying compounds from similarity searches, based
on chemical structures and substructures of the Diversity Set
leads. This search was performed using the Enhanced NCI
Letters
Journal of Medicinal Chemistry, 2008, Vol. 51, No. 21 6629
Table 2. Structures, AutoDock Binding Energies, and Activities of
APSR Second Generation Inhibitor Compounds
Database Browser, a Web-based graphical user interface with
a large number of possible query types and output formats. The
890 out of 250 000 compounds were identified in the Open NCI
database with at least 80% Tanimoto similarity and docked. The
40 highest-scoring solutions, ranked according to the criteria
outlined above, were experimentally evaluated using our
biochemical assay. Five compounds were identified with dissociation constants less than 50 µM, with four similar to primary
lead 133896 (60826, 55545, 57476, and 23180) and one similar
to primary lead 348401 (228155).
The similarity search based on the parent compound 133896
identified three new leads (60826, 55545, and 57476) with a
9-fluorenone core structure and activity against APSR and the
9-fluorenone core structure (Table 2). The dihydrophenanthrendione 23180 was the most potent inhibitor identified in this
study, with a dissociation constant of less than 10 µM. Visual
inspection of the predicted binding pose for 23180 (Figure 3a)
reveals that the aromatic polycyclic scaffold inserts into a
profound gorge (referred to as L1) and makes favorable
hydrophobic contacts with the side chains of residues L90 and
I98. Additional interactions include the nitro functional group
in proximity to positively charged active site residues K144 and
R245 (referred to as P1) as well as hydrogen bonding from the
carbonyl oxygens in the aromatic moiety to the backbone amide
of L85 and side chain of S62.
Similar binding poses and interactions are predicted for
compounds 133896, 60826, 55545, and 57476. However, these
Figure 3. Docked conformations of NSC23180 (a) and NSC348401
(b) in APSR structure. Ligands are displayed as in Figure 1. Hydrogen
bonds are represented with dashed yellow lines.
molecules have one less carbonyl oxygen in the aromatic moiety
relative to the dihydrophenanthrendione chemical scaffold.
As a result, the 9-fluorenone-derived compounds are not
predicted to form a hydrogen bond with S62 and could account
for the difference in potency between the two structural cores.
We also note that neither 9-fluorenone nor 2-nitro-9-fluorenone,
which are closely related to 133896, exhibited significant activity
against APSR. Rather, our data indicate that a H-bond acceptor
group is required at position 3 or 4 of the 9-fluoronone scaffold
to acquire inhibitor potency (Table 2 and Figure 3).
Previous studies show that compound 23180 can inactivate
the tyrosine phosphatase CD45 via a catalytic and oxygendependent reaction (Kinactivation 4300 M-1 s-1).13 Although the
precise mechanism remains unknown, inactivation of CD45 by
23180 is correlated with oxidation of a catalytic cysteine residue
6630 Journal of Medicinal Chemistry, 2008, Vol. 51, No. 21
Letters
latent TB infection. The molecules described here are the first
non-phosphate-based inhibitors of this enzyme and may form
the basis for development of an APSR inhibitor pharmacophore.
Further studies on the inhibitors identified here should also shed
light into the mechanism, targeting, and therapeutic potential
of this enzyme.
Acknowledgment. We thank Garrett M. Morris, Ruth Huey,
and Louis Noodleman for valuable discussions. This work was
funded in part by Grant R01GM069832 from the National
Institutes of Health. This is manuscript no. 19523 from the
Scripps Research Institute.
Figure 4. Binding pose of both NSC23180 and NSC348401 in the
APSR binding site. Ligands and residues belonging to the P1 site and
are depicted in capped sticks colored by atom types. Residues belonging
to the L1 and L2 sites are depicted as MSMS surface colored by atom
type with charged atoms in bright colors and uncharged atom in pale
colors. The protein secondary structure (white ribbon) is also depicted.
to sulfinic and sulfonic acid. To test whether 23180 inhibited
APSR in a similar fashion, control experiments were performed.
Unlike CD45, preincubation of APSR with 23180 did not result
in enzyme inactivation and C256 was not covalently modified
(Supporting Information).
Compound 327704 is structurally unrelated to other inhibitor
cores identified by these studies. Nonetheless, this compound
is also predicted to interact with the L1 pocket via its polycyclic
aromatic ring and the P1 region through the polar carboxylate
group.
Compounds 348401 and 228155 contain a benzoxadiazole
moiety. This functional group adopts the same binding pose in
both compounds and is oriented in a way that maximizes
electrostatic interactions with R242 and K144 (Figure 3b). Each
benzoxadiazole is distinguished by a pendent thioaryl group,
which is embedded in a hydrophilic cleft (referred as L2) and
forms two hydrogen bonds to the side chains of D66 and E65.
The low micromolar activity of 348401 and 228155, combined
with the ability to chemically derivatize the purine scaffold,
suggests that this compound class may be a promising lead.
Interestingly, though compounds 23180 and 348401 contain
a polycyclic aromatic ring, they are not predicted to adopt the
same binding position and interact with similar residues (Figure
4). Rather, 23180 is positioned deep inside the L1 cavity, flanked
by the [4Fe-4S] cluster while 34801 occupies the shallower
and more polar L2 region of the active site, which is consistent
with the more polar nature of the ring in this compound.
Nevertheless, both classes of inhibitors are predicted to interact
with the conserved positively charged residues that border both
clefts in the P1 site. These observations suggest that a ligand,
which can occupy both L1/L2 clefts and bears polar hydrogen
bond accepting groups to interact with the P1 site, may exhibit
higher activity against APSR. We are currently testing this
model, and the results of these studies will be reported in due
course.
In conclusion, we have applied virtual ligand screening of
compounds from the NCI database to identify low micromolar
inhibitors of M. tuberculosis APSR, a validated target against
Supporting Information Available: Molecular modeling methods and experimental procedure for enzymatic inhibition assays.
This material is available free of charge via the Internet at http://
pubs.acs.org.
References
(1) (a) Corbett, E. L.; Watt, C. J.; Walker, N.; Maher, D.; Williams, B. G.;
Raviglione, M. C.; Dye, C. The growing burden of tuberculosis: global
trends and interactions with the HIV epidemic. Arch. Intern. Med.
2003, 163, 1009–1021. (b) Dye, C.; Scheele, S.; Dolin, P.; Pathania,
V.; Raviglione, M. C. Consensus statement. Global burden of
tuberculosis: estimated incidence, prevalence, and mortality by country.
WHO Global Surveillance and Monitoring Project. JAMA, J. Am. Med.
Assoc. 1999, 282, 677–686. (c) Kochi, A. The global tuberculosis
situation and the new control strategy of the World Health Organization. 1991. Bull. W. H. O. 2001, 79, 71–75.
(2) (a) Flynn, J. L.; Chan, J. Tuberculosis: latency and reactivation. Infect.
Immun. 2001, 69, 4195. (b) Zhang, Y. Persistent and dormant tubercle
bacilli and latent tuberculosis. Front. Biosci. 2004, 9, 1136–1156.
(3) Espinal, M. A. The global situation of MDR-TB. Tuberculosis
(Edinburgh), 2003, 83, 44–51.
(4) World Health Organization. http://www.who.int/gtb/, 2003.
(5) Bhave, D. P.; Muse, W. B., III; Carroll, K. S. Drug targets in
mycobacterial sulfur metabolism. Infect. Disord. Drug Targets. 2007,
7, 140–158, and references within.
(6) (a) Mougous, J. D.; Green, R. E.; Williams, S. J.; Brenner, S. E.;
Bertozzi, C. R. Sulfotransferases and sulfatases in mycobacteria. Chem.
Biol. 2002, 9, 767–776. (b) Schelle, M. W.; Bertozzi, C. R. Sulfate
metabolism in mycobacteria. ChemBioChem 2006, 7, 1516–1524. (c)
Williams, S. J.; Senaratne, R. H.; Mougous, J. D.; Riley, L. W.;
Bertozzi, C. R. 5′-Adenosinephosphosulfate lies at a metabolic branch
point in mycobacteria. J. Biol. Chem. 2002, 277, 32606–32615.
(7) Carroll, K. S.; Gao, H.; Chen, H.; Leary, J. A.; Bertozzi, C. R.
Investigation of the iron-sulfur cluster in Mycobacterium tuberculosis
APS reductase: implications for substrate binding and catalysis.
Biochemistry 2005, 44, 14647–14657.
(8) Senaratne, R. H.; De Silva, A. D.; Williams, S. J.; Mougous, J. D.;
Reader, J. R.; Zhang, T.; Chan, S.; Sidders, B.; Lee, D. H.; Chan, J.;
Bertozzi, C. R.; Riley, L. W. 5′-Adenosinephosphosulphate reductase
(CysH) protects Mycobacterium tuberculosis against free radicals
during chronic infection phase in mice. Mol. Microbiol. 2006, 59,
1744–1753.
(9) Chartron, J.; Carroll, K. S.; Shiau, C.; Gao, H.; Leary, J. A.; Bertozzi,
C. R.; Stout, C. D. Substrate recognition, protein dynamics, and ironsulfur cluster in Pseudomonas aeruginosa adenosine 5′-phosphosulfate
reductase. J. Mol. Biol. 2006, 364, 152–169.
(10) Chang, M. W.; Belew, R. K.; Carroll, K. S.; Olson, A. J.; Goodsell,
D. S. Empirical entropic contributions in computational docking:
evaluation in APS reductase complexes. J. Comput. Chem., in press.
(11) Huey, R.; Morris, G. M.; Olson, A. J.; Goodsell, D. S. A semiempirical
free energy force field with charge-based desolvation. J. Comput.
Chem. 2007, 28, 1145–1152.
(12) http://dtp.nci.nih.gov/branches/dscb/diversity_explanation.html.
(13) Wang, Q.; Dubé, D.; Friesen, R. W.; LeRiche, T. G.; Bateman, K. P.;
Trimble, L.; Sanghara, J.; Pollex, R.; Ramachandran, C.; Gresser, M. J.;
Huang, Z. Catalytic inactivation of protein tyrosine phosphatase CD45
and protein tyrosine phosphatase 1B by polyaromatic quinones.
Biochemistry 2004, 43, 4294–4303.
JM800571M
Supporting Information
Structure-Based Virtual Screening and Biological
Evaluation of Mycobacterium tuberculosis APS
Reductase Inhibitors
Sandro Cosconati,†,
,§
Jiyoung A. Hong‡,§, Ettore Novellino , Kate S Carroll,‡ David S. Goodsell,† and
Arthur J Olson† ,*
Department of Molecular Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, La
Jolla, California 92037, Department of Chemistry and The Life Sciences Institute, University of Michigan,
Ann Arbor, Michigan 48109, and Dipartimento di Chimica Farmaceutica e Tossicologica, Università di
Napoli “Federico II”, Via D. Montesano, 49-80131 Napoli, Italy
§
These authors contributed equally to this work.
*
To whom correspondence should be addressed. Phone: (858) 784-9702. Fax: (858) 784-2860. E-mail:
olson@scripps.edu
†
Dept. of Molecular Biology, The Scripps Research Institute
‡
Dept. of Chemistry and The Life Sciences Institute, University of Michigan
Dip. di Chimica Farmaceutica e Tossicologica, Università di Napoli “Federico II”
Contents of Supporting Information:
Supplementary Figure 1. Structure based sequence alignment of 17 APS reductases from prokaryotes.
The ClustalW Multiple Sequence Alignment program was used. Strictly conserved residues are outlined in
red, red letters indicate conserved residues and conserved regions are boxed in blue. Alignment pictures
were rendered with the server ESPript 2.2 (http://espript.ibcp.fr)
Supplementary Figure 2. Structure based sequence alignment of Pseudomonas Aeruginosa and
Micobacterium tuberculosis APS reductases. The ClustalW Multiple Sequence Alignment program was
used. Strictly conserved residues are outlined in red, red letters indicate conserved residues and conserved
regions are boxed in blue. Residues flanking the active site are outlined in green.
Experimental Section.
Supplementary Figure 1.
Supplementary Figure 2.
Experimental Section.
Virtual Screening Calculations. The AutoDock 4.0 (AD4)1,2 software package, as implemented
through the graphical user interface called AutoDockTools (ADT),3 was used to dock small molecules to
APS reductase. The enzyme file was prepared using published coordinates (PDB 2GOY).4 The terminal
residues were modified to charged quaternary amine and carboxylate forms. The [4Fe-4S] cluster was
retained with the protein structure. Charges of this group were manually assigned. In our case, the cluster is
believed to have two ferric (+3) and two ferrous (+2) irons.5 Since the eight sulfur atoms (four belonging
to the cluster and four belonging to the four cysteines) have a net charge of -1, the total net charge of the
system should be of -2. Noodleman and co-workers calculated the ESP charges for models of the cluster
in this oxidation state.6 These charges were added to APS reductase iron-sulfur cluster atoms and to the
four sulfur of the coordinating cysteines (Table 1).
Table 1. Calculated Charges for [Fe4 S4 (SCH3 )4 ]2Atom ESP Charges
Feo x
+0.642 (_2)
Fered
+0.635 (_2)
S *o x
-0.584 (_2)
S *red
-0.580 (_2)
So x
-0.574 (_2)
Sred
-0.571 (_2)
All other atom values were generated automatically by ADT. The docking area was assigned visually
around the enzyme active site. A grid of 80 Å x 80 Å x 80 Å with 0.375 Å spacing was calculated around
the docking area for 13 ligand atom types using AutoGrid4. These atom types were sufficient to describe
all atoms in the NCI database. For VS, compound structures of the NCI Diversity Set and the ones derived
from
the
similarity
search
were
prepared
using
the
ZINC
database
server
(http://zinc.docking.org/upload.shtml)7 to take into account the different protomeric and tautomeric states
of each compound. All the ligands were then converted in the AutoDock format file (.pdbqt). For each
ligand, 100 separate docking calculations were performed. Each docking calculation consisted of 10 million
energy evaluations using the Lamarckian genetic algorithm local search (GALS) method. The GALS
method evaluates a population of possible docking solutions and propagates the most successful
individuals from each generation into the subsequent generation of possible solutions. A low-frequency
local search according to the method of Solis and Wets is applied to docking trials to ensure that the final
solution represents a local minimum. All dockings described in this paper were performed with a
population size of 150, and 300 rounds of Solis and Wets local search were applied with a probability of
0.06. A mutation rate of 0.02 and a crossover rate of 0.8 were used to generate new docking trials for
subsequent generations, and the best individual from each generation was propagated to the next
generation. The docking results from each of the eight calculations were clustered on the basis of rootmeansquare deviation (rmsd) between the Cartesian coordinates of the atoms and were ranked on the basis
of free energy of binding. The top-ranked compounds were visually inspected for good chemical geometry.
Pictures of the modelled ligand/enzyme complexes were rendered with PMV.3
Preparation of NCI Compounds. Compounds determined by AD4 to have low binding energies to
APS reductase were requested in groups of 40 and received from the Drug Synthesis and Chemistry
Branch, Developmental Therapeutics Program, Division of Cancer Treatment and Diagnosis, National
Cancer Insititute (http://dtp.nci.nih.gov/branches/dscb/repo_request.html). Chemical compounds were
dissolved in DMSO to 10 mM final concentration and stored at room temperature.
Enzyme purification. Purification of APS reductase was carried out as previously described.4
APS Reductase Activity Assay. APS reductase activity was assayed using a modification of an assay
for monitoring
35
SO4 2- release from ATP-sulfurylase as follows.5 Reactions were performed in a final
volume of 100 µL. At various time points, a 10 µL aliquot was removed from the reaction and added to 0.5
mL of a 2% (w/v) charcoal solution containing 20 mM Na2 SO3 . The suspension was vortexed, clarified by
centrifugation and a 400 µL aliquot of the supernatant solution, containing the radiolabeled sulfite product,
was counted in 10 mL of scintillation fluid. 3 5S-labeled APS was synthesized and purified as previously
described8 with the inclusion of an additional anion exchange purification step (5 ml Fast Flow Q column
(GE Healthcare) eluting with a linear gradient of ammonium bicarbonate, pH 8.0, from 0.005 to 0.7 M.
General Kinetic Methods. Unless otherwise specified, the reaction buffer was 100 mM Bis-Tris pH
7.5, 5 mM DTT, and the temperature was 30 °C. The auxillary protein reductant, thioredoxin was added at
10 µM. With the exception of slow reactions, the enzymatic reactions were monitored to completion (≥ 3
half lives) and rate constants were obtained by nonlinear least-squares fit to a single exponential
(Kaleidagraph). To ensure single-turnover reactions, the concentration of APS reductase was kept in excess
of the concentration of labeled APS (~1 nM). Two or three concentrations of APS reductase were chosen
that were at least 10-fold below the KM value. Under these conditions, the observed rate constant was
linearly dependent on enzyme concentration. Thus, reactions were first order in APS and APS reductase in
all cases. Under subsaturing conditions, with [APS] << KM, the Michaelis-Menton equation (eq 1)
simplifies to equation 2.9 The reaction progress curve was plotted as a function of time and the fractional
extent of reaction, and fit by a single-exponential function (eq 3) to yield kobs, which is the product of
enzyme concentration and the apparent second-order rate constant (eq 4). Kinetic data were measured in at
least two independent experiments and the standard error was typically less than 15%.
Vobs = [E][S]kcat/(Km + [S])
(1)
Vobs = (kcat/Km)[E][S]
(2)
fraction product = 1 – e-kobst
(3)
kobs = (kcat/Km)[E]
(4)
Inhibitor Screening. For initial screening, compounds were tested in kinetic assays at 100 µM final
concentration. Compounds that inhibited more than 50% at this concentration were analyzed further as
described below.
Analog Dissociation Constants. The standard assays and conditions described above were used to
monitor the Kcat/KM for reduction of APS in the presence and absence of inhibitor. Values of Ki were
determined from the dependence of the observed rate constant (kobs) on inhibitor concentration. With
subsaturing APS, the inhibition constant is equal to the dissociation constant (Ki = Kd ). Except in cases
where solubility was a limiting factor, a range of inhibitor concentrations was employed from at least 5-fold
below to 10-fold above the inhibition constant. Nonlinear least-squares fits of the equation for competitive
inhibition (eq 5) gave excellent fits in all cases, and the standard error was typically less than 15%.
(kcat/KM)obs = (kcat/KM)/(1 + [I]/Ki)
(5)
Catalytic inactivation of APS reductase by 2-nitro-9,10-phenanthrenedione. APS reductase (9
µM) was incubated with compound 23180 (0.9 µM) or DMSO and enzyme activity was measured at 1, 15
and 30 min. No statistical difference was observed in the activity of the enzyme in these experiments
indicating that compound 23180 did not catalytically inactivate APS reductase.
Thiol Quantitation. Labeling of APS reductase by the thiol-reactive probe NBDCl was carried out
using a modification of a following the published procedure.1 0 Briefly, APS reductase (10 µM) was
incubated, at room temperature, in a final volume of 1 mL of buffer containing 50 mM BisTris (pH=7.5), 1
mM EDTA, and 1 mM DTT with (a) DMSO or (b) 10 µM compound 23180. NBDCl (50 µM) was added
to each of the resulting solutions and incubated for 30 minutes at room temperature. Excess NBDCL was
removed from the labeled APS reductase by ultracentrifugation prior to the UV-vis scan. No loss in APS
reductase thiol labeling was observed in the presence of inhibitor.
Promiscuous Inhibition. At the suggestion of one reviewer, we tested members of each structural
class of inhibitor for promiscuous inhibition. Assays were carried out as described above in the presence of
0.01% Triton, and showed no significant difference in Kd with the assay without detergent. We also
performed a gel shift assay of trypsin activity acting on APS reductase in the presence of inhibitors. By
this gel assay, none of the inhibitors at concentrations of 50 uM changed the proteolysis pattern of trypsin
and qualitatively indicates that the compounds are not inhibiting trypsin.
References.
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