Mark Andrew White1,2, Wei Lin3,4, Xiaodong Cheng3,4. 1. Sealy Center for Structural Biology and Molecular Biophysics, The University of Texas Medical Branch, Galveston, Texas 77555, United States. 2. Department of Biochemistry and Molecular Biology, The University of Texas Medical Branch, Galveston, Texas 77555, United States. 3. Department of Integrative Biology & Pharmacology, University of Texas Health Science Center at Houston, Houston, Texas 77030, United States. 4. Texas Therapeutics Institute, Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, Texas 77030, United States.
Abstract
The raging COVID-19 pandemic caused by SARS-CoV-2 has infected tens of millions of people and killed several hundred thousand patients worldwide. Currently, there are no effective drugs or vaccines available for treating coronavirus infections. In this study, we have focused on the SARS-CoV-2 helicase (Nsp13), which is critical for viral replication and the most conserved nonstructural protein within the coronavirus family. Using homology modeling that couples published electron-density with molecular dynamics (MD)-based structural refinements, we generated structural models of the SARS-CoV-2 helicase in its apo- and ATP/RNA-bound conformations. We performed virtual screening of ∼970 000 chemical compounds against the ATP-binding site to identify potential inhibitors. Herein, we report docking hits of approved human drugs targeting the ATP-binding site. Importantly, two of our top drug hits have significant activity in inhibiting purified recombinant SARS-CoV-2 helicase, providing hope that these drugs can be potentially repurposed for the treatment of COVID-19.
The raging COVID-19 pandemic caused by SARS-CoV-2 has infected tens of millions of people and killed several hundred thousand patients worldwide. Currently, there are no effective drugs or vaccines available for treating coronavirus infections. In this study, we have focused on the SARS-CoV-2helicase (Nsp13), which is critical for viral replication and the most conserved nonstructural protein within the coronavirus family. Using homology modeling that couples published electron-density with molecular dynamics (MD)-based structural refinements, we generated structural models of the SARS-CoV-2helicase in its apo- and ATP/RNA-bound conformations. We performed virtual screening of ∼970 000 chemical compounds against the ATP-binding site to identify potential inhibitors. Herein, we report docking hits of approved human drugs targeting the ATP-binding site. Importantly, two of our top drug hits have significant activity in inhibiting purified recombinant SARS-CoV-2helicase, providing hope that these drugs can be potentially repurposed for the treatment of COVID-19.
A novel strain of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)
is responsible for the COVID-19 pandemic.[1,2] Coronaviruses (CoVs) are
enveloped 5′-capped, polyadenylated, single-stranded nonsegmented,
positive sense RNA viruses that cause various diseases in animals.[3] In humans, manifestations of CoV infection range from
asymptomatic, common cold, to lethal viral respiratory illness.[4] There are no effective drugs or vaccines to treat or
prevent CoV infection. Therefore, developing novel therapeutics for CoV
represents an urgent medical need to combat the current COVID-19
devastation.Upon infecting host cells, CoVs assemble a multisubunit RNA-synthesis complex
of viral nonstructural proteins (Nsp) responsible for the replication and
transcription of the viral genome.[4] Among the 16 known
CoV Nsp proteins, the Nsp13helicase is a critical component for viral
replication and shares the highest sequence conservation across the CoV
family, highlighting their importance for viral viability. As such, this
vital enzyme represents a promising target for anti-CoV drug
development.[5−7]To date, there is no atomic structure of SARS-CoV-2Nsp13 available, and none
of the existing structural homologues (Table S1) published are suitable for molecular docking
analyses. The two available apo-Nsp13 crystal structures are from the
SARS-CoV (6JYT)[8] and MERS-CoV (5WWP).[9] Both 6JYT and 5WWP contain two
identical chains in their crystal lattice: S1A and S1B, or M1A and M1B,
respectively. The major difference between the two Nsp13 structures is
associated with the 333–353 loop of the Rec1A[10]
domain that interacts with domain 1B, which is absent in M1A due to it being
highly dynamic. The RMSD between M1B and S1A decreases from 1.57 to 0.64
Å when excluding this loop (Table S1). M1A and M1B have a larger difference in their
Rec1A–Rec2A orientations than that among S1A, S1B, and M1B. The CH
and Stalk domains are similar (RMSDs < 1 Å), while the orientations
of the nucleotide-binding domains (Rec1A and Rec2A) vary relative to them.
The domains 1B among S1A, S1B, and M1B are similar except for loops
202–208, which interact with the Rec2A domain. The Rec2A domains are
similar, except in the C-Terminus and several flexible loops. The Rec2A
domain seems to be intrinsically flexible with the crystallographic,
intraspecies, A/B domains having larger RMSDs than the interspecies Rec2A
domains (Table S1). These apparent structural dynamics of Nsp13
structures highlight the value of having templates of the highly flexible
helicase in multiple conformations, one of which may be a better target for
high-affinity inhibitors. Therefore, we generated a series of SARS-CoV-2Nsp13 homology models in its apo- or substrate-bound states and performed
in-silico docking, high-throughput virtual screening
(HTvS), using all these models to search for potential SARS-CoV-2
inhibitors. Considering the urgency of the COVID-19 pandemic, we focused on
targeting the Nsp13ATP-binding site with approved drugs for human use.The SARS-CoV-2Nsp13helicase shares a 99.8% sequence identity to SARS-CoV
(SARS) Nsp13helicase with only one single residue difference (Figure a). The SARSNsp13helicase
crystal structure was solved in its apo-state at a reported resolution of
2.8 Å.[8] The crystallographic asymmetric unit
contains two Nsp13 chains (S1A and S1B), offering a glimpse at the intrinsic
flexibility of this helicase (Table S1). This crystal structure would be an ideal
candidate for virtual screening, since as a homology model it differs from
the SARS-CoV-2Nsp13 in only one amino acid, I570 V, which is located away
from the ATP- and RNA-binding sites. However, a close examination of the
ATP-binding site in this structure found several problems.
Figure 1
SARS-CoV2 corona virus’s Nsp13 helicase structure. (a)
Sequence and domain structure of SARS-CoV2. The ATP-binding site
residues are highlighted in gray. The single residue V570 that
is different between SARS-CoV2 and SARS (I570) in the Rec2A
domain is colored red. The domain structure and coloring is
shown below the sequence. (b) (apo) SARS-CoV2 Nsp13 structural
model (S2A) based on the I570 V mutation of SARS Nsp13 (6JYT),
colored-by-domain. The V570 is shown as red sticks. The domain
structure and coloring scheme are the same as shown above.
SARS-CoV2corona virus’s Nsp13helicase structure. (a)
Sequence and domain structure of SARS-CoV2. The ATP-binding site
residues are highlighted in gray. The single residue V570 that
is different between SARS-CoV2 and SARS (I570) in the Rec2A
domain is colored red. The domain structure and coloring is
shown below the sequence. (b) (apo) SARS-CoV2Nsp13 structural
model (S2A) based on the I570 V mutation of SARSNsp13 (6JYT),
colored-by-domain. The V570 is shown as red sticks. The domain
structure and coloring scheme are the same as shown above.First, the published model and electron density are of significantly lower
quality than the MERS-CoVNsp13 structure.[9] The MERS
structure was used to fill-in gaps in the SARSNsp13 model, such as the
dynamic 1B domain, which they were not able to model in their SAD-phased
maps. In addition, the Walker-A loop[10] (residues
G282-G287, K288, S289), which is responsible for binding the ATP
substrate’s phosphates, has a poor fit to the density and was built
into the electron density with a highly improbable
cis-peptide. Most significantly, the SARS-CoV-2Nsp13
structure does not have the usual sulfate ions bound even though there was
clear difference density for the missing sulfate ions (Figure S1a), which are important in defining the
ATP-binding site. These errors in the published SARSNsp13 structure made it
unsuitable for use in molecular docking. Therefore, we decided to correct
these errors and crystallographically rerefine the structure. On the other
hand, the published apo crystal structure of MERS Nsp13, which retains 72%
identity to the SARS-CoV-2Nsp13helicase, has a better defined density
around the Walker-A loop and sulfate ions (Figure S1b).[9] Hence, we rebuilt the
Walker-A loops in both chains using crystallographic rerefinement guided by
the MERS-Nsp13 structure and added missing SO4 ions as supported
by the difference electron density. In addition, we fixed other
stereochemistry issues using the Crystallographic Object-Oriented Toolkit
(COOT)[11] and refined the structure in
Phenix,[12] following standard crystallographic
procedures. This SARSNsp13 template resulted in two models of
apo-SARS-CoV-2Nsp13, S2A and S2B (Table S2). All structural models were validated using
MolProbity web server[13] (Table S3).The published MERS Nsp13 crystal structure,[9] also consisting
of two molecules (M1A and M1B) in the asymmetric unit (Table S1), was first refined using Phenix and COOT. We
build the SARS-CoV-2 homology models using this refined MERS crystal
structure as a template, mutating the protein sequence. The resulting
SARS-CoV-2 models were then energy minimized by maintaining the
crystallographic orientation for common atoms using Phenix, while
stereochemical issues caused by mutation were corrected using COOT. The two
homologous structural models based on either 6JYT (S2A and S2B) or 5WWP (M2A and M2B) are
highly similar as expected with the Rec1A and Rec2A domains having a
Cα-RMSD of only 1.4 Å (Figure S2, Table S2). The major changes being in the
dynamic 1B domain, a slight rotation of the CH, Zn-binding, and the
ATP-clamping Rec2A domains, plus a few flexible loops. The M2B model is the
only complete apo-Nsp13 structure without gaps in the model.The yeastUpf1 helicase complex[14] with both
ADP-AlF4 and ssRNA bound was previously identified as a
structural homologue of apo MERS-CoVNsp13 (5WWP) structure.[9] While the
yeastUpf1 helicase shares low sequence homology with CoV helicases (24%
identity, 37% similarity), it has high structural homology to the SARS and
MERS Nsp13 helicases, permitting the domains to be aligned by their
secondary structure elements. Therefore, it represents a suitable template
of the ATP and RNA-bound conformation of the CoV family helicases. We used
the Upf1 complex structure to guide the modeling of the SARS-CoV-2Nsp13/ATP/ssRNA complex structure (S2C) prior to energy minimization. In
particular, modeling the domain motions upon complex formation (Figure , Table S2).
Figure 2
SARS-CoV2 Nsp13:ATP:ssRNA complex model (S2C). (a) Domain
organization in the S2C complex. Coloring is as in Figure . The ATP
carbons are yellow, and the ssRNA carbons are magenta; both are
shown as spheres. The missing CH, Zn-binding, domain is shown as
a pale-blue blob. (b) ATP-binding pocket showing specific
interactions with Nsp13. The view is from below the Rec2A (cyan)
toward the Rec1A (green) domain. The Walker-A loop is bright
green. (c) ssRNA binding between the Stalk, Rec1A, and Rec2A
domains. The view is from the Stalk (yellow) toward the Rec1A
(green)–1B (tan) domain interface.
SARS-CoV2Nsp13:ATP:ssRNA complex model (S2C). (a) Domain
organization in the S2C complex. Coloring is as in Figure . The ATPcarbons are yellow, and the ssRNAcarbons are magenta; both are
shown as spheres. The missing CH, Zn-binding, domain is shown as
a pale-blue blob. (b) ATP-binding pocket showing specific
interactions with Nsp13. The view is from below the Rec2A (cyan)
toward the Rec1A (green) domain. The Walker-A loop is bright
green. (c) ssRNA binding between the Stalk, Rec1A, and Rec2A
domains. The view is from the Stalk (yellow) toward the Rec1A
(green)–1B (tan) domain interface.Since the structural similarity of the CH Zn-binding domains of Upf1 and
SARS-CoV-2 is very low and the CH is not directly involved in substrate
binding, we excluded it from the homology model of the Nsp13 complex. The
alignment of the Nsp13 homology model, based on MERS Nsp13 chain B (M2B), to
Upf1 started with the Rec1A domain, which includes the Walker-A loop. In
this orientation the Stalk was also in good alignment. The two other
domains, 1B and Rec2A, both rotate into their substrate-binding
conformations, which moves them toward their substrates. The 1B domain has
the largest motion to clamp against the 3′ end of the ssRNA in
contact with the Stalk (Figure b,c). The Rec1A’s 333–350 loop, which was mostly
disordered in the SARS crystal structures, shows motion upon ssRNA binding.
The Rec1A Pro335-Arg337-Arg339 loop interacts with the RNA and forms a
bridge with the Asn179-Tyr180 loop in domain 1B, which along with the Stalk
domain’s terminal helix residues, Glu143 and Lys146, is also in
contact with the RNA. The Rec1A domain forms the floor of the RNA-binding
tunnel, which has a mixture of backbone amides, plus the Asn361 and His311amines coordinating the backbone phosphates, as well as several carboxyl and
hydroxyl groups hydrogen bonding with the riboses and bases. The
478–490 loop of the Rec2A domain moves out and away from the Stalk,
increasing the space to accommodate the binding of the 5′ end of the
ssRNA (Figure c).For the ATP-binding pocket, the Walker-A loop closes around the bound ATP,
relative to the apo structures. The conventional A-loop adenine ring-distal
tyrosine π-stacking motif[15] is replaced by a H290
in the helix immediately following the Walker-A, adjacent to the S289, which
coordinates the Mg2+ ion (Figure b). The Rec2A domain rotates around the G439
link to Rec1A, bringing the Rec2A domain 5 Å closer to cover the ATP
and also bringing Q537 into coordination with both the Mg2+ and
the ATP-γP. The Rec2A’s arginine finger, R567, moves into the
pocket to coordinate the ATP-γP, along with R443, which coordinates
both the ATP-O3α and O3β (Figure b). At the exit of the ATP-binding site, N265
and S264 are both poised to interact with the adenine ring’s
NH2, while the adenine ring has hydrophobic stacking
interactions with H290 and the alkane side chain of R442. Together these
features distinguish the ternary complex from the apo-Nsp13 models as a
template for the active helicase.HTvS was performed using the five homology models that we have generated. The
ATP-binding site for all four apo-models was identified by homology to the
complex model (S2C). A suitable 30 × 26 × 26 Å3
box, centered on the ADP and encompassing the Rec1A Walker-A loop plus the
opposing arginine finger in Rec2A,[10] was defined and used
for HTvS (Figure S3). The Enamine Libraries (AC and PC) and
ZINC-in-Trials Library totaling roughly 970 000 compounds were used
for virtual screening of the ATP-binding sites in the five models. For this
study we focus on screening results based on the ZINC-in-Trials Library
(9270 compounds), which resulted in 369 drug hits approved for human use
(Figure S4a). The detailed HTvS information for all 369 of
these drugs from the ZINC Library is provided in the Excel spreadsheet (Table S4), part of the Supporting
Information. Chemical affinity propagation clustering of the
369 HTvS selected drugs found 93 exemplar compounds highlighting the
chemical diversity of the drugs selected by HTvS. These 369 drug hits can be
filtered to a smaller number using a lower limit cutoff. For example, a
Total-Score cutoff of 80 will yield a list of 31 potential Nsp13 inhibitors
for in vitro or in vivo screening assays
(Figure S4a). The multiple targets produced groups of
overlapping and nonoverlapping hits (Figure S4b), which is to be expected since they include
the ATP-bound and four apo-ATP sites, which were unrestrained by bound
ligands.The four models of the apo-Nsp13helicase provided possible targets of the
dynamic helicase. As expected, the Vina docking scores for ATP in the
apo-models were significantly worse (−7.1, −7.8, −8.1,
−7.1) than the score for that of the complex-based target
(−9.3), indicating that the apo-models were not an ATP-binding
competent. The top-scoring hits in these apo-Nsp13ATP-binding sites (Figure , Table S5) include Cepharanthine,[16]
Cefoperazone,[17] Dihydroergotamine,[18] Cefpiramide,[19] Ergoloid
(Dihydroergocristine (DHEC)),[20] Ergotamine,[21] Netupitant,[22] Dpnh (NADH),
Lifitegrast,[23] Nilotinib,[24] and
Tubocurarin.[25] The top-scoring hit Cepharanthine
(CEP) is an anti-inflammatory drug used in Japan since the 1950s to treat a
number of acute and chronic diseases, including the treatment of leukopenia
and alopecia. A list of common ligand-protein interactions are summarized in
Table S6.
Figure 3
Selection of apo-Nsp13 ATP-binding site hits from virtual
screening. (a) Cepharanthine shown fit in the (S2A) SARS Nsp13
structure’s ATP-binding site. (b) Idarubicin in M2B. (c)
Nilotinib in M2B. Insets: (left) overview of the inhibitor bound
to the Nsp13; (right) electrostatic surface in the active site.
Color gradient: blue-to-red ±5 V.
Selection of apo-Nsp13ATP-binding site hits from virtual
screening. (a) Cepharanthine shown fit in the (S2A) SARSNsp13
structure’s ATP-binding site. (b) Idarubicin in M2B. (c)
Nilotinib in M2B. Insets: (left) overview of the inhibitor bound
to the Nsp13; (right) electrostatic surface in the active site.
Color gradient: blue-to-red ±5 V.In the complex the top scoring drugs were Lumacaftor,[26]
Emend (Aprepitant),[27] Nilotinib,[24]
Irinotecan,[28] Enjuvia,[29]
Zelboraf,[30] Cromolyn,[31]
Diosmin,[32] Risperdal,[33] and
Differin (Adapalene).[34] Again, interactions important for
ligand docking are summarized in Table S6. Surprisingly, although the ATP-binding pocket
undergoes significant conformational changes upon ATP binding there is a
significant overlap in hits even in this small group, with Lumacaftor,
Nilotinib, Liftegrast, Idarubicin (Duanorubicin, Valrubicin), and Irinotecan
scoring in the top-20 for both the apo- and ATP-bound models (Figure , Table S5).
Figure 4
Top scoring hits for the Nsp13 complex ATP-site using virtual
screening. (a) Nsp13:ATP:RNA complex. (b) ATP. (c) Lumacaftor.
(d) Emend (Aprepitant). (e) Nilotinib. (f) Zelboraf. (g)
Cromolyn. (h) Risperdal.
Top scoring hits for the Nsp13 complex ATP-site using virtual
screening. (a) Nsp13:ATP:RNA complex. (b) ATP. (c) Lumacaftor.
(d) Emend (Aprepitant). (e) Nilotinib. (f) Zelboraf. (g)
Cromolyn. (h) Risperdal.The two drugs Nilotinib[24] and Lumacaftor,[26] were common top-scoring hits to the ATP site in both the apo- and
ATP-bound models. Lumacaftor acts as a chaperone of protein folding and
improves the processing of the most common cystic fibrosis transmembrane
conductance regulator (CFTR) mutant, F508del, and its transport to the cell
surface. Lumacaftor, in combination with Ivacaftor, is approved for the
treatment of F508delCFTR.[35] On the other hand, Nilotinib
is a second generation Bcr-Abltyrosine kinase inhibitor for the treatment
of chronic myelogenous leukemia (CML). Nilotinib was designed on the basis
of the crystal structure of the Imatinib-Abl complex[36] to
fit into the ATP-binding site of the BCR-ABL protein with higher
affinity.[37] Nilotinib has also been identified as a
potential inhibitor of the SARS-CoV-2 Nsp12-Nsp7-Nsp8 complex, which is
responsible for the RNA-dependent RNA polymerase activity, another key
component of the multisubunit RNA-synthesis complex.[38]To validate our HTvS results, we ordered pure compound powder for several top
hits and tested their ability to inhibit the ATPase activity of purified
recombinant SARS-CoV-2Nsp13 protein. Among the 10 drug candidates tested,
two of our top HTvS hits Lumacaftor and Cepharanthine displayed activity in
inhibiting Nsp13ATPase activity with estimated IC50 values of
0.3 and 0.4 mM, respectively (Figure ).
Figure 5
Inhibition of SARS-CoV-2 Nsp13 ATPase activity. Lumacaftor
(○) and Cepharanthine (□). Data are presented as
Mean ± SEM (N = 3).
Inhibition of SARS-CoV-2Nsp13ATPase activity. Lumacaftor
(○) and Cepharanthine (□). Data are presented as
Mean ± SEM (N = 3).Cepharanthine was the top scoring hit for our apo-ATP site screens while
Lumacaftor was the top scoring hit for complex-ATP site screen (Figures and 4,
Table S5). Experimental confirmation of our top HTvS drug
hits validates our structural models and HTvS approach targeting multiple
conformational states. Cepharanthine is a strong candidate of potential
antivirals for the treatment of COVID-19.[39,40] Cepharanthine was
previously identified as an inhibitor of SARS.[41] It has
been found to effectively inhibit SARS-CoV-2 in high throughput drug
screening assay[42] and in a separate siRNA assay,[43] both using Vero cells. It has also been identified as a
potential inhibitor of the SARS-CoV-2 Nsp12-Nsp8-Nsp7 complex.[38] Results from this study suggest that Cepharanthine may
also synergistically target Nsp13 within the viral replication complex. On
the other hand, Lumacaftor has not been directly implicated to play a role
in inhibiting SARS-CoV-2. Our study provides strong evidence to support the
further testing of Lumacaftor in cell- and animal-based COVID-19 models.In conclusion, we have performed extensive integrated structural modeling to
build atomic structural models of SARS-CoV-2Nsp13 in its apo- and
substrate-bound conformations. Virtual molecular docking analyses targeting
the ATP-binding pocket using these structural models have led to the
identification of potential inhibitor compounds, many of them approved human
drugs. Of particular interest, two of our top HTvS hits show significant
activity in inhibiting purified recombinant SARS-CoV-2helicase, providing
hope that these drugs can be potentially repurposed for the treatment of
COVID-19.
Experimental Methods
Homology Modeling of SARS-CoV-2Nsp13: Homology models of the
SARS-CoV-2Nsp13helicase were generated using the two available SARS[8]/MERS[9] Nsp13 crystal structures. Issues
we found with the highly similar SARSNsp13 (6JYT) crystal structure prompted us to rebuild
it in COOT[11] and refine the new model in Phenix[12] using standard crystallographic techniques (see results
discussed above, Figure S1). Mutation of the MERS (5WWP) crystal structure
to the SARS-CoV-2 sequence was performed in COOT. Energy minimization was
performed in Phenix, followed by optimization of stereochemistry in COOT for
several rounds.Molecular Dynamics: After rough domain alignment of the
MERS-based apo SARS-CoV-2Nsp13 model to the Upf1 crystal structure, the
domain linkers were remodeled in Coot with full stereochemical energy
minimization, using the Upf1 electron density as a guide. Energy
minimization of this SARS2-CoV-2:ATP:ssRNA complex model was performed using
NAMD,[44] either through the VMD-NAMD[45] interface or command line scripts. A 10 ns MD run, with
implicit water, was then performed, which permitted further motion of the
domains. This model was then placed in an equilibrated TIP3water box, with
0.15 mM NaCl, for further rounds of equilibration, annealing, and energy
minimization, totaling 50 ns.HT Virtual Screening of the Models: Potential sites for
inhibitor binding were identified by homology to the ATP- or RNA-binding
sites in the structurally similar Upf1 helicase complex. We screened the
identified substrate-binding sites in each Nsp13 model using an
implementation of AutoDock Vina[46] on the Drug Discovery
Portal at TACC.[47] The ZINC[48,49] drugs in
Trials (9270 compounds) Library, the Enamine-PC (84,359 compounds), and
Enamine-AC (876 985 compounds) were used in high-throughput virtual
screening of the five targets. Only the ZINC library
“in-Trials” subset contains drugs currently approved for human
use. Chemical clustering of hits was performed using the Affinity
Propagation Clustering algorithm with Soergel (Tanimoto coefficient)
distances on the ChemBio[50] server (https://chembioserver.vi-seem.eu/). The Vina PDBQT files for
other ligands were generated using ProDrg[51] and OpenBabel
(https://openbabel.org/).Expression and Purification of Recombinant SARS-CoV-2Nsp13
Protein: The expression vector for SARS-CoV-2Nsp13 protein
was constructed by site-directed mutagenesis (I570 V) using the pET28a
vector for SARS-CoVNsp13 (kindly provided by Dr. Jian-dong Huang) as a
template.[52] SARS-CoV-2Nsp13 protein was expressed
in BL21(DE3) cells and purified using a Ni-affinity column and a FPLC
Superdex 200 Increase column as described previously.[8]Nsp13ATPase Activity Assay: A modified ATPase assay was
carried out by measuring phosphate release using a colorimetric method based
on complexation with malachite green and molybdate (AM/MG reagent) using
96-well plates.[53,54] Briefly, 20 μL reaction mixtures, containing
25 mM HEPES (pH 7.5), 50 mM NaCl, 5 mM MgCl2, 1 mM DTT, 0.25 mM
ATP, and 150 nM of Nsp13 in the presence or absence of various concentration
of inhibitor, were incubated at 37 °C for 20 min. 80 μL of AM/AG
dye solution was added into the reaction buffer and incubated at room
temperature for 5 min. The production of phosphate was measured by
monitoring the absorbance at 620 nm using a Molecular Devices FlexStation 3
Microplate Reader.
Authors: James C Phillips; Rosemary Braun; Wei Wang; James Gumbart; Emad Tajkhorshid; Elizabeth Villa; Christophe Chipot; Robert D Skeel; Laxmikant Kalé; Klaus Schulten Journal: J Comput Chem Date: 2005-12 Impact factor: 3.376
Authors: Ellen Weisberg; Paul W Manley; Werner Breitenstein; Josef Brüggen; Sandra W Cowan-Jacob; Arghya Ray; Brian Huntly; Doriano Fabbro; Gabriele Fendrich; Elizabeth Hall-Meyers; Andrew L Kung; Jürgen Mestan; George Q Daley; Linda Callahan; Laurie Catley; Cara Cavazza; Mohammad Azam; Azam Mohammed; Donna Neuberg; Renee D Wright; D Gary Gilliland; James D Griffin Journal: Cancer Cell Date: 2005-02 Impact factor: 31.743
Authors: John J Irwin; Teague Sterling; Michael M Mysinger; Erin S Bolstad; Ryan G Coleman Journal: J Chem Inf Model Date: 2012-06-15 Impact factor: 4.956
Authors: Julian A Tanner; Rory M Watt; Yu-Bo Chai; Lin-Yu Lu; Marie C Lin; J S Malik Peiris; Leo L M Poon; Hsiang-Fu Kung; Jian-Dong Huang Journal: J Biol Chem Date: 2003-08-13 Impact factor: 5.157
Authors: Christine Vazquez; Sydnie E Swanson; Seble G Negatu; Mark Dittmar; Jesse Miller; Holly R Ramage; Sara Cherry; Kellie A Jurado Journal: PLoS One Date: 2021-06-24 Impact factor: 3.752