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Cryptotanshinone deregulates unfolded protein response and eukaryotic initiation factor signaling in acute lymphoblastic leukemia cells.

ABSTRACT

Background: Unfolded protein responses (UPR) determine cell fate and are recognized as anticancer targets. In a previous research, we reported that cryptotanshinone (CPT) exerted cytotoxic effects toward acute lymphoblastic leukemia cells through mitochondria-mediated apoptosis.

Purpose: In the present study, we further investigated the role of UPR in CPT-induced cytotoxicity on acute lymphoblastic leukemia cells by applying tools of pharmacogenomics and bioinformatics.

Methods: Gene expression profiling was performed by mRNA microarray hybridization. Potential transcription factor binding motifs were identified in the promoter regions of the deregulated genes by Cistrome software. Molecular docking on eIF-4A and PI3K was performed to investigate the inhibitory activity of CPT on translation initiation.

Results: CPT regulated genes related to UPR and eIF2 signaling pathways. The DNA-Damage-Inducible Transcript 3 (DDIT3) gene, which is activated as consequence of UPR malfunction during apoptosis, was induced and validated by in vitro experiments. Transcription factor binding motif analysis of the microarrary-retrieved deregulated genes in the promoter region emphasized the relevance of transcription factors, such as ATF2, ATF4 and XBPI, regulating UPR and cell apoptosis. Molecular docking suggested inhibitory effects of CPT by binding to eIF-4A and PI3K providing evidence for a role of CPT's in the disruption of protein synthesis.

Conclusion: CPT triggered UPR and inhibited protein synthesis via elF-mediated translation initiation, potentially supporting CPT-induced cytotoxic effects toward acute leukemia cells.

Keywords:

Salvia miltiorrhiza Bunge (Lamiaceae)

Cryptotanshinone

Pharmacogenetics

DDIT3

Unfolded protein response (UPR)

Eukaryotic initiation factor (elF)

Introduction

Proteins have to be folded into specific conformations to properly execute their cellular functions. Besides being a major site for calcium storage and lipid biosynthesis, the endoplasmic reticulum (ER) is an essential organelle for post-translational modifications, structure maturation and correct folding of transmembrane and secretory proteins. These processes require molecular chaperones and enzymes residing in the ER such as oxidoreductases (Braakman and Hebert 2013). Acting as quality control system, the ER exports correctly-folded proteins to the sites of actions and eliminates misfolded proteins through the ER-associated degradation (ERAD) pathway, which disposes misfolded proteins from the ER to the cytosol for ubiquitin-mediated proteolytic degradation (Ruggiano et al. 2014).

Accumulation of misfolded proteins, which is considered to be harmful to cells threatening their survival, results from numerous physiological or pathophysiological factors, such as hypoxia, nutrient deprivation, loss of calcium homeostasis, and elevated uncompleted folding forms of proteins due to mutations and a failure in degradation (Braakman and Hebert 2013). In response to such a cellular condition referred to as ER stress, cells have evolved an adaptive mechanism, termed unfolded protein response (UPR) to maintain cellular homeostasis. UPR is triggered by three major ER-resident transducers: inositol-requiring enzyme-1 (IRE1), protein kinase RNA-like endoplasmic reticulum kinase (PERK), and activating transcription factor-6 (ATF6). IRE1 represents a strong homeostatic transcription factor. Upon stimulation, it multimerizes and trans-autophosphorylates, leading to cleavage of X-box protein 1 (XBP1) mRNA into a spliced mature form (XBP1s). XBPls translocates to the nucleus and induces the transcription of ERAD component genes and genes related to ER chaperones and biogenesis (Plongthongkum et al. 2007). Activated PERK phosphorylates eukaryotic initiation factor 2 (eIF2[alpha]) on Ser51 thereby blocking global protein synthesis by decreasing cap-dependent translation from most mRNAs. This in turn alleviates the heavy load of new peptides that require modification and folding in the ER compartment (Yan et al. 2002). Nevertheless, the downstream molecule of PERK, mRNAs encoding ATF4, paradoxically sustain translational efficiency, which induces transcription of target genes encoding enzymes involved in amino acid metabolism, enzymes required for protein folding and degradation, GADD34 phosphatase, and the transcription factor C/EBP homologous protein (CHOP/DDIT) (Han et al. 2013). ATF6 translocates to the Golgi apparatus for cleavage by site-1 and site-2 proteases. Together with XBP1, activated ATF6 subsequently translocates into the nucleus and regulates transcription of target genes to restore ER function (Li et al. 2000). Taken together, UPR activation serves as adaptive system against ER stress and promotes cell survival. Nevertheless, if prolonged ER stress occurs and UPR fails to restore protein folding homeostasis, PERK and IRE1 stimulate pro-apoptotic signaling and increase CHOP expression. CHOP, a key molecule involved in ER-stress-driven apoptosis, is associated with repression of BCL-2, which in turn translocates BCL-2-associated protein X (BAX) to mitochondria, ultimately leading to release of cytochrome c. This suggests that ER stress modulates intrinsic apoptosis via disruption of mitochondrial membrane potential and a series of caspase activation (Gorman et al. 2012; Weston and Puthalakath 2010). CHOP strongly correlates with ER stress-driven apoptosis and CHOP-deficient cell lines are resistant to ER stress-induced apoptosis (Oyadomari and Mori 2004). In light of the previous facts, sustained UPR activation, which leads to programmed cell death, might be a potential strategy in cancer therapy.

Regulation of gene expression at the level of protein synthesis is a unique mechanism, by which cells rapidly respond to extra- and intracellular stresses. In the case of cancer progression, synthesis of specific proteins required to initiate and maintain the transformed phenotype is hyperactivated by post-transcription via translation initiation. This process utilizes existing mRNA species to produce target proteins and skips transcription steps, favoring cancer cell development (Grzmil and Hemmings 2012). Therefore, the susceptibility of translation initiation to protein synthesis may be a determinant factor in cancer development.

Cryptotanshinone (CPT) is a main lipophilic diterpene quinone isolated from a valuable traditional Chinese herb called danshen (Salvia miltiorrhiza). Its mechanisms of inhibition of cancer cell growth have been widely investigated (Chen et al. 2013). A previous study revealed that CPT induced UPR-mediated apoptosis in cancer cell lines (Park et al. 2012). We recently observed that CPT stimulated the reactive oxygen species (ROS)-mediated, caspases-dependent pathway resulting in apoptosis in acute lymphoblastic leukemia (ALL) cells (Wu et al., 2015). In the present study, we use pharmacogenomics and bioinformatics to explore, whether UPR is involved in ALL cell death upon CPT treatment.

Materials and methods

Chemicals

CPT (Fig. 1) was purchased from Sigma-Aldrich (Munich, Germany).

Culture of cell lines

CCRF-CEM leukemia cells were kept in an incubator containing 5% C[O.sub.2] at 37[degrees]C and were cultured in RPMI medium (Invitrogen, Darmstadt, Germany) containing 10% fetal bovine serum (Invitrogen) and 1% penicillin and streptomycin (Invitrogen).

mRNA microarray

Total RNA was isolated using InviTrap Spin Universal RNA Mini kit (Stratec Molecular, Berlin). The procedure of microarray expression profiling including quality check of total RNA, probe labeling, hybridization, scanning and data analysis was performed by the Genomics and Proteomics Core Facility at the German Cancer Research Center (DKFZ) in Heidelberg, Germany (Eberwine et al. 1992).

Quantitative real-time polymerase chain reaction (qPCR)

Total RNA was isolated by InviTrap Spin Universal RNA Mini kit (Stratec Molecular) according to the manufacturer's instruction. One microgram RNA was converted to cDNA using RevertAid H Minus First Strand cDNA Synthesis Kit (Thermo Scientific, MS, USA). The mRNA levels were analyzed with the use of 5x Hot Start Tag EvaGreen qPCR Mix (no ROX) (Axon Labortechnik, Kaiserslautern, Germany) by CFX384[TM] Real-Time PCR Detection System (Bio-Rad, Munich, Germany). The running protocol of qPCR was set as follows: 50[degrees]C for 2 min, 95[degrees]C for 10 min, 40 cycles including denaturation at 95[degrees]C for 15 s, annealing at 58.1[degrees]C (DDIT3, RPS13) for 1 min and extension at 72[degrees]C for 1 min following 95[degrees]C for 1 min. RPS13 gene expression was used for normalization.

Primer sequences were as follows: RPS13, forward: GGTTGAAGTTGACATCTGACGA, reverse: CTTGTGCAACACATGT GAAT. DDIT3, forward: GGAAACGGAAACAGAGTGGT, reverse: TGTTCTTTCTCCTTCATGCG.

Motif analysis

Transcription factor binding site analysis was performed by the Cistrome analysis software (Liu et al. 2011). Briefly, regulated genes were input and BED formats, a tab-delimited text file which defines data lines displayed in an annotation track, were retrieved with an upstream setting (promoter region) at 2 or 3 kb through the following link: http://genome.ucsc.edu/cgi-bin/hgTables. SeqPos motif analysis was used to screen for enriched motifs in given regions (http://cistrome.org). SeqPos scans all the motifs not only in Transfac, JASPAR, UniPROBE (pbm), hPDI database, but also tries to find de novo motifs using MDscan algorithm. The output of genes was ranked by -log10 (p-value).

Molecular docking

Preparation of docking files was carried out with

AutodockTools-1.5.6rc3 and molecular docking was performed by Autodock4 using lamarckian algorithm (Morris et al. 2009). The three-dimensional CPT structure was prepared in protein data bank (PDB) format from PubChem website. The X-ray crystallography-based structure of eIF-4A and phosphoinositide-3-kinase (PI3K) were obtained from the PDB (http://www.rcsb.org/pdb/home/home.do). We defined the docking space within a grid box placed at the pharmacophore of each protein. Docking parameters were set to 250 runs and 2,500,000 for energy evaluations. Docking sites and residues were visualized by using AutodockTools-1.5.6rc3 and Visual Molecular Dynamics (VMD) software. Docking log (dig) files provided information regarding the lowest binding energy, the number of clusters and predicted inhibition constant (pKi).

Statistical analysis

Data were presented as mean [+ or -] standard deviation of three independent experiments, and statistical analysis was performed using Student's t-test. A p-value lower than 0.05 was considered as statistically significant.

Results and discussion

Microarray gene profile of CPT on CCRF-CEM cells

CCRF-CEM cells were treated with 10 [micro]M CPT or DMSO for 24 h. Microarray-based mRNA hybridizations were performed to determine deregulated gene expression in response to CPT treatment. A total of 660 genes were significantly deregulated and were filtered by Chipster software with three times standard deviation. Significance was assessed using empirical Bayes t-test (P < 0.05) with Benjamini-Hochberg correction. Genes with a threshold of 1 (fold change) were subsequently analyzed by Ingenuity Pathway Analysis (1PA) software to investigate signaling pathways potentially involved in the response to CPT treatment. The gene expression of microarray results was validated by qPCR (Wu et al., 2015).

As shown in Fig. 2, the most pronounced canonical pathways correlating with the deregulated genes included unfolded protein response (UPR), EIF2 signaling, antioxidant action, TNFR2 signaling, and JAK/STAT signaling. Considering the top deregulated pathways, it can be implied that a 24 h treatment with 10 [micro]M CPT affected UPR signaling, which in turn regulated general protein translation via eIF2 signaling. Thus, we further explored these mechanisms in more detail.

Gene expression and analysis of transcription factor binding motifs which account for initiation of UPR upon CPT treatment on CCRF-CEM cells

According to our microarray and computational results, it is implied that 24 h of CPT treatment induced ER stress towards ALL cells mainly through deregulation of IRE1-XBP1 and ATF4-CHOP pathways. The detailed gene expression regarding UPR signaling is listed in Table 1. Upregulation of CEBPB, CEBPG, SREBP1 and INSIG1 genes implied that ER stress-mediated lipid synthesis was activated. Expression of XBP1 and EDEM1 suggested induction of ERAD pathway, which in turn stimulates ER chaperones. Interestingly, expression of FISPA4 and HSPA14, which encodes ER chaperone FISP70, was down-regulated, though a co-chaperone of HSP70 encoded by DNAJB9, was upregulated.

The computational technique of Cistrome analysis aims to identify binding sites for transcription factors in the DNA promoter regions. We applied this method to investigate the DNA promoter sequences of genes found to be deregulated in microarray experiments. In total, 166 genes with a fold-change threshold over 1 sorted from top CPT-deregulated cellular functions were subjected to Cistrome analysis for SeqPos motif search. These included genes involved in cell death and survival, cell cycle and cellular growth and proliferation. The most pronounced motifs for each deregulated gene list are depicted in Table 2. ATF4, a crucial transcription factor, which is induced by PERK-mediation of phosphorylation of eIF2[alpha]; and activates pro-apoptotic factor CFIOP and GADD34 (Fian et al. 2013), was found among the list of transcription factors that potentially bind to these gene promoters. ATF2 was also shown to regulate expression of CFIOP (Averous et al. 2004). XBP1 and SREBP1 motifs emphasized the participation of the activation of XBP1-ERAD pathway and lipid biogenesis potentially in CPT-induced ER stress. Taken together, occurrence of these motifs further supports a role of UPR in response to CPT treatment.

The CHOP/DDIT3 gene was upregulated upon CPT treatment. This result was validated by qPCR and the mRNA expression (Fig. 3, Table 1). This and the upregulation of PPP1R15A/GADD34, a growth arrest and DNA-damage inducible factor (Hollander et al. 1997) suggested that the PERK-eIF2[alpha]-ATF4 pathway was activated, which is stimulated by protein misfolding, and that ER stress-mediated apoptosis was triggered. This global view of gene expression elucidated the possible mechanism, by which CPT may regulate the cellular response to ER stress.

Transcription of the CFIOP gene has been reported to be activated by XBP1, ATF4 and ATF6 (Oyadomari and Mori 2004). It is worth mentioning that CHOP induced GADD34 expression, which regulates restoration of protein synthesis via a negative feedback loop by dephosphorylation of eIF-2[alpha]. The recovery of protein translation might be in favor of synthesis of pro-apoptotic molecules (Marciniak et al. 2004; Han et al. 2013). Expression of GADD34 is associated with increased sensitivity to apoptosis (Gorman et al. 2012). Previous reports showed that CPT induced ROS and CHOP expression, and contributed to apoptosis of human hematoma, melanoma and breast cancer cells (Tse et al. 2013; Park et al. 2012). Combined with our previous data (Wu et al., 2015), which unraveled the ROS-dependent intrinsic apoptotic pathway upon CPT treatment, the present investigation suggested that ER stress is potentially involved in CPT-induced apoptosis in ALL cells.

Expression of genes involved in eIF2 signaling upon CPT treatment

The eIF2 pathway was the second significant pathway deregulated after CPT treatment. Therefore, we further analyzed this pathway, which responds to UPR and regulates protein synthesis via initiation of PERK-eIF2[alpha] phosphorylation. A global inhibition of genes regulating eukaryotic initiation factors and ribosomal proteins has been observed (Table 3), implying that the overall protein synthesis was reduced due to sustained CPT-triggered UPR.

CPT interfered protein translation

During ER stress, protein synthesis is regulated not only by UPR through the control of eIF2[alpha] phosphorylation, but also by the PI3K/mTOR pathway. The latter represents a major hyperactivated signaling pathway in cancer development and hence, an important target in cancer therapy (Grzmil and Hemmings 2012). In our study, we observed a global reduction of genes related to protein synthesis (Table 3). Therefore, using a computational approach, we attempted to investigate, whether CPT potentially targets the PI3K/mTOR signaling pathway. Due to the high homology between mTOR and PI3K[gamma] within the ATP binding site, the binding of the kinase domain of PI3K[gamma] could provide insights into how drugs bind to the mTOR active site (Peterson et al. 2011). The region known as the affinity pocket within the ATP binding site contains hydrophobic interactions with Asp841 and Tyr867, and a hydrogen bond with Val882 (known as hinge residue) (Knight et al. 2006). Other interacting residues include Met804, Trp812, Lys833, Asp836, Asp964 and Phe965. These interacting residues are conserved between mTOR and PI3K[gamma] (Peterson et al. 2011). PI-103 (Knight et al. 2010) and GSK2126458 (Park et al. 2008) were selected as positive control in our study. CPT bound to the same binding site as the two control drugs. CPT formed a hydrogen bond with Val882 and hydrophobic interaction with Tyr867 implying that it bound to the affinity pocket (Fig. 4).

In general, cellular stress caused for example by DNA-damaging agents suppressed cap-dependent translation, mostly by inhibition of eIF4F and eIF2 ternary complex (Spriggs et al. 2010). The PI3K/mTOR signaling pathway controls the assembly of eIF4F, which of eIF4A is a specific component with helicase activity in regulating protein translation (Chu and Pelletier 2015). eIF4A is considered as an oncogene, which is involved in T-cell ALL (T-ALL) development (Wolfe et al. 2014). Targeting elF4A is a novel anticancer strategy that has shown predinical efficacy (Chu and Pelletier 2015). Thus, we studied the binding of CPT to eIF4A using molecular docking. Our analysis showed that CPT bound to the same ATP binding region as pateamine A, a novel inhibitor for eIF4A, interacting with the same hydrophobic residues, including Phe200, Asn204, Phe227 and Arg229 (Fig. 5). Since, CPT showed lower binding affinity with higher binding energy and predicted Ki values (-8.03 kcal/mol; 1.31 [micro]M) than pateamine A (-11.27 kcal/mol; 0.004 [micro]M) (Table 4), the docking indeed suggests a possible interaction of CPT with eIF4A.

Inhibitors targeting PI3K/mTOR signaling are under evaluation in human clinical trials, including BEZ235 (phase II) and GSK2126458 (phase I) showing anticancer activity in a variety of cancers, such as metastatic breast cancer, lymphoma and advanced solid tumors (Polivka and Janku 2014). Previous investigations also revealed that CPT inhibited signaling pathways of PI3K and mTOR, and regulated expression of downstream molecules, which led to attenuation of cancer development (Ge et al. 2015; Chen et al. 2010). Our docking approach revealed that CPT may target PI3K/mTOR, which corroborates these findings. However, it is also reported that mTOR inhibitors or PI3K/mTOR dual inhibitors led to resistance by MYC-driven elevation of eIF4F complex (Ilic et al. 2011). Therefore, the combination of such inhibitors with those targeting the elF4F complex may be expected as improved anticancer strategy. Here we showed that CPT potentially bound to eIF4A, one of the components of eIF4F. Hence, CPT may be a suitable component for such combination treatments.

In conclusion, our results provide new insights into the molecular mechanisms of CPT. ER stress-induced UPR and inhibition of protein synthesis may play important roles in the multifactorial effects of CPT against cancer cells.

Conflict of interest

The authors declare that they have no conflict of interest.

http://dx.doi.org/10.1016/j.phymed.2015.12.011

ARTICLE INFO

Article history:

Received 7 October 2015

Accepted 20 December 2015

Abbreviations: ALL, acute lymphoblastic leukemia; ATF4, activating transcription factor-4; ATF6, activating transcription factor-6; CHOP, C/EBP homologous protein; CPT, cryptotanshinone; DDIT3, DNA damage-inducible transcript 3; elF, eukaryotic initiation factor; ER, endoplasmic reticulum; ERAD, ER-associated degradation pathway; IPA, Ingenuity Pathway Analysis; IRE1, inositol-requiring enzyme-1; mTOR, mammalian target of rapamycin; PERK, protein kinase RNA-like endoplasmic reticulum kinase; PI3K, phosphoinositide-3-kinase; ROS, reactive oxygen species; UPR, unfolded protein responses; XBPI, X-box protein 1.

Ching-Fen Wu (a,1), Ean-Jeong Seo (a,1), Sabine M. Klauck (b), Thomas Efferth (a,*)

(a) Department of Pharmaceutical Biology, Institute of Pharmacy and Biochemistry. Johannes Gutenberg University, Staudinger Weg 5, 55128 Maim, Germany

(b) Working Group Cancer Genome Research, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), National Center for Tumor Diseases (NCT), Im Neuenheimer Feld 460, 69120 Heidelberg, Germany

* Corresponding author. Tel.: +49 6131 3925751; fax; +49 6131 23752.

E-mail address: efferth@uni-mainz.de (T. Efferth).

(1) Both authors equally contributed.

Acknowledgment

We are thankful to the National Science Council (Taiwan) and German Academic Exchange Service for providing a scholarship to Ching-fen Wu. We thank the Genomics and Proteomics Core Facility of the German Cancer Research Center (DKFZ) for providing the Illumina Whole-Genome Expression Beadchips and related services, and technical support from the Cytometry Core Facility in IMB (Mainz, Germany). Thanks to Dr. M. Zeino for critical reading of the manuscript.

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Table 1
Deregulated genes involved in unfolded protein response
(UPR) upon treatment with 10 [micro]M CPT.

                                                             Fold
Gene        Description                                     change

Unfolded    protein response (UPR)
CEBPB       CCAAT/Enhancer binding protein (C/EBP), beta     1.537
CEBPG       CCAAT/Enhancer binding protein (C/EBP), gamma    1.439
DDIT3       DNA-damage-inducible transcript 3                1.905
DNAJB9      DnaJ (Hsp40) homologue, subfamily B, member 9    1.385
EDEM1       ER degradation enhancer, mannosidase             1.510
              alpha-like 1
HSPA4       Heat shock 70kDa protein 4                      -1.542
HSPA14      Heat shock 70kDa protein 14                     -1.361
INSIG1      Insulin induced gene 1                           1.429
PPP1R15A    Protein phosphatase 1, regulatory subunit 15A    1.784
SREBP1      Sterol regulatory element binding                1.380
              transcription factor 1
XBP1        X-Box binding protein 1                          1.790

Gene expression and analysis of transcription factor
binding motifs which account for initiation of UPR
upon CPT treatment on CCRF-CEM cells

Table 2
Cistrome analysis of transcription factor binding motifs
in DNA promoter sequences of genes deregulated upon CPT
treatment (10 [micro]M).

Upstream 2 kb

      Motif              Z score   -log10
                                   (p-value)

1     CEBPA#             -7.082#   279.74#
2     Rhox11             -6.859    263.84
3     Arid5a             -6.771    257.76
4     PBX1               -6.636    248.5
5     SNAPC5             -6.487    238.54
6     LARP1              -6.25     223.05
7     RARA               -6.245    222.73
8     GATA-1             -6.036    209.62
9     Nhp6b              -5.868    199.31
10    FOX03              -5.757    193.22
11    DMRT3              -5.693    192.67
12    NKX2-5             -5.54     188.92
13    TGA1a              -5.539    180.04
14    POU2F3             -5.44     179.98
15    TBP                -5.436    174.39
16    C1                 -5.376    174.17
17    RGT1               -5.322    170.81
18    FOXD1              -5.258    167.85
19    HOXA13             -5.244    164.34
20    MAT[alpha]2        -5.114    163.59
21    NFKB1              -5.013    156.6
22    Pbx-lb             -4.988    151.31
23    TCF3               -4.98     150.04
24    ZAP1               -4.775    149.62
25    ATF4#              -4.762#   139.21#
26    HNF1B              -4.756    138.57
27    GZF3               -4.749    138.29
28    FOXP3              -4.749    137.95
29    TRAP4              -4.685    137.92
30    STAT5A             -4.626    134.77
31    ABF1               -4.624    131.92
32    AIRE               -4.593    131.83

Upstream 3kb

      Motif              Z score   -log10
                                   (p-value)

1     ZBTB33             -6.312    227.04
2     NR4A1              -5.466    175.89
3     CDP|CUX1           -5.351    169.44
4     ETS1               -5.258    164.34
5     TFEB               -5.17     159.58
6     XBP1#              -5.034#   152.44#
7     NR2E3              -5.009    151.13
8     SREBP1#            -4.999#   150.59#
9     PU.1|SPI1          -4.943    147.69
10    C-MAF              -4.897    145.34
11    ATF2#              -4.892#   145.12#
12    Zfpl87             -4.878    144.40
13    EFNA2              -4.849    142.94
14    ELK1               -4.8      140.46
15    POU6F1             -4.742    137.56
16    SPIB               -4.739    137.43
17    PEA3|ETV4          -4.695    135.26
18    E2F1               -4.502    126.03
19    FACB               -4.492    125.54
20    CREB1#             -4.475#   124.76#
21    SRY                -4.452    123.66
22    C/EBPalpha|CEBPA   -4.342    118.61
23    HOXC9              -4.319    117.57
24    aMEF-2             -4.294    116.45
25    PlTX2|Nr2f2        -4.294    116.43
26    NR3C1|PGR          -4.288    116.15
27    ERG                -4.252    114.55
28    TATA               -4.239    113.95
29    TBP                -4.239    113.95
30    HLF                -4.21     112.66
31    HSF1               -4.2      112.24
32    Elf5               -4.15     110.04

* Items marked in bold: possible transcriptional
motif related to UPR.

Note: bold indicated with #.

Table 3
Deregulated genes involved in eIF2 signaling upon
treatment with 10 [micro]M CPT.

                                                                Fold
Gene             Description                                    change

elF2 signaling
E1F1AX           Eukaryotic translation initiation factor 1A,   -1.343
                 X-Linked
EIF2B3           Eukaryotic translation initiation factor 2B,   -1.361
                 subunit 3 gamma, 58kDa
EIF3B            Eukaryotic translation initiation factor 3,    -1.385
                 subunit B
EIF4G1           Eukaryotic translation initiation factor 4     -1.306
                 gamma, 1
MAP2K1           Mitogen-activated protein kinase inase 1        1.306
PPP1R15A         Protein phosphatase 1, regulatory subunit 15A   1.784
RPL7L1           Ribosomal protein L7-like 1                    -1.283
RPL14            Ribosomal protein L14                          -1.297
RPL36            Ribosomal protein L36                          -1.424
RPL36A           Ribosomal protein L36a                         -1.400
RPS2             Ribosomal protein S2                           -1.376
RPS7             Ribosomal protein S7                           -1.619
RPS15            Ribosomal protein S15                          -1.641

Table 4

Molecular docking of CPT to P13K (PDB ID: 1E8Y) and eIF4A
(PDB ID:2G9N). Docking of control drugs (Pl-103 and
GSK2126458 for PI3K and pateamine A for eIF4A) was performed
for comparison.

Protein    Compound     Lowest energy of       Mean binding
                        docking                energy
                        (kcal/mol)             (kcal/mol)

PI3K       CPT          -8.20 [+ or -] <0.00   -8.20 [+ or -] <0.00

           PI-103       -8.77 [+ or -] 0.01    -8.57 [+ or -] 0.03

           GSK2126458   -11.20 [+ or -] 0.09   -10.78 [+ or -] 0.15

eIF-4A     CPT          -8.03 [+ or -] <0.00   -8.03 [+ or -] <0.00

           Pateamine    -11.51 [+ or -] 0.01   -11.27 [+ or -] <0.00
           A

Protein    Compound     Residues hydrogen   Residues involved in
                        bond interaction    hydrophobic interaction
                        with the ligand     with ligand

PI3K       CPT          Val882              Met804, Trp812,
                                            Tyr867, Ile879, Glu880,
                                            Lys890, Met953, Ile963
           PI-103       Val882, Lys890      Met804, Ser806,
                                            Trp812, Tyr867, Ile879,
                                            Glu880, Ile881, Ala885,
                                            Met953
           GSK2126458   Ser806, Lys833,     Met804, Ala805,
                        Val882, Asp964      Lys807, Lys808, Pro810,
                                            Ile831, Tyr867, Ile879,
                                            Glu880. Asp950,
                                            Met953, Ile963
eIF-4A     CPT                              Phe200, Leu203,
                                            Asn204, Thr207,
                                            Phe227, Arg229
           Pateamine                        Asp194, Tyr197,
           A                                Asp198, Phe200,
                                            Gln201, Asn204,
                                            Ser205, Phe227,
                                            Met228, Arg229

Protein    Compound     (a) pKi
                        ([micro] M)

PI3K       CPT          0.97 [+ or -] <0.00

           PI-103       0.37 [+ or -] <0.00

           GSK2126458   0.01 [+ or -] <0.00

eIF-4A     CPT          1.31 [+ or -] <0.00

           Pateamine    0.004 [+ or -] <0.00
           A

(a) pKi (predicted Ki): Ki is the inhibition constant for a
drug. The pKi value is used to evaluate affinity of drug to
a target structure.
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Author:Wu, Ching-Fen; Seo, Ean-Jeong; Klauck, Sabine M.; Efferth, Thomas
Publication:Phytomedicine: International Journal of Phytotherapy & Phytopharmacology
Article Type:Report
Geographic Code:4EUGE
Date:Feb 15, 2016
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