In Silico Modeling of FDA-Approved Drugs for Discovery of Anticancer Agents: A Drug-Repurposing Approach

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17 In Silico Modeling of FDA-Approved Drugs for Discovery of Anticancer Agents: A Drug-Repurposing Approach Mengzhu Zheng*, Lixia Chen†, Li Hua*,† *

Hubei Key Laboratory of Natural Medicinal Chemistry and Resource Evaluation, School of Pharmacy, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China †Wuya College of Innovation, School of Traditional Chinese Materia Medica, Key Laboratory of Structure-Based Drug Design & Discovery, Ministry of Education, Shenyang Pharmaceutical University, Shenyang, China

1 INTRODUCTION Malignant tumors have become one of the leading causes of human death. Therefore cancer-associated research has always been at the forefront of medical science. Although significant progress has been made in the field of antitumor drug development, due to high costs and low success rates it has been difficult to bring new drugs from preclinical screening to clinical trials. The discovery of new drugs is a process of high input and low output. Usually the discovery of a novel drug takes 10–17 years from the establishment to the listing, and the total R&D expenditure is more than US $1 billion. In the past 10 years, fewer and fewer new chemical entities (NCEs) have been approved by the Food and Drug Administration (FDA); however, research funding has been gradually increasing. Despite continuing investment in drug development and biomedical research, the NCEs being developed by pharmaceutical companies and passed into clinical trials or the market have gradually declined. Some new drugs have had to be withdrawn from the market due to adverse reactions, causing huge economic losses (Hernandez et al., 2017; Ma, Chan, & Leung, 2013; Shim & Liu, 2014). For

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example, Pfizer’s Thelin, used to treat pulmonary arterial hypertension, was withdrawn because of its severe toxicity causing liver damage; Bayer Medical’s hypolipidemic drug, cerivastatin, was withdrawn from the market because of hundreds of deaths from rhabdomyolysis; and Astimizol by Janssen was withdrawn due to severe cardiotoxicity. At present, the FDA is increasingly scrutinizing the toxic side effects of new drugs and the review cycle has become longer and longer, making new drugs more difficult to the market. Due to the short development cycle, low risk, and high success rates, drug repositioning has received increasing attention in recent years. The advantages of drug repositioning are that these types of drugs may enter clinical trials faster and more cheaply due to the validation of their pharmacokinetics, toxicology, and safety data (Sukhai et al., 2011). Once the new drug is developed with new indications, it can rapidly enter phase II clinical, which will reduce research and development expenses by about 40% (Gupta, Sung, Prasad, Webb, & Aggarwal, 2013) and shorten the development cycle from 3 to 12 years (Pantziarka, Bouche, Meheus, Sukhatme, & Sukhatme, 2015). New molecular targets for known drugs can be used to develop new indications that are different from the initial one. Drug repositioning overcomes the potential clinical applicability risks of drug marketing, accelerates discovery of new drugs, and reduces the overall risk of drug development. In recent years, with the development of molecular biology, the deepening understanding of cancer biology, and the application of high-throughput screening, computational virtual ligand screening, and genetic engineering technology, the field of antitumor drug discovery has been greatly advanced, especially for the discovery of novel anticancer drugs through drug repositioning. Along with the advancement of IT technology and bioinformatics, in silico modeling of FDA-approved drugs for the discovery of anticancer agents has become more successful since a large amount of information on the structure of proteins and pharmacophores has been accumulated over the past few decades. Most of pharmaceutical companies have employed in silico models to discover lead compounds from different chemical spaces. Structure-based drug repositioning is a powerful technology that has some advantages over activity-based drug repositioning. According to the statistics, there are more than 60 kinds of molecular-docking tools, including free software and commercial software (Pagadala, Syed, & Tuszynski, 2017). Common commercial software tools include Schrodinger-Glide, ICM-Pro, Gold, MOE-Dock, etc.; free software are AutoDOCK Vina, LeDock, AutoDock, etc. The following are the most representative and comprehensive evaluations of Schrodinger-Glide, ICM-Pro, and Autodock Vina. The Autodock Vina scoring function is primarily evaluated by (i) spatial interactions, (ii) hydrophobic interactions, (iii) hydrogen-bond energy, and (iv) number of rotatable bonds in the ligand. ICM-Pro is a fast and accurate molecular-docking software that supports the docking of proteins with small molecules, ligands, or proteins (Abagyan, Totrov, & Kuznetsov, 1994). The protocol followed by the molecular docking is that the ligands are continuously and elastically docked with receptors that are represented by grid interaction-potential energy, and the scores are given according to internal coordinate mechanics (ICM). Glide is a docking tool in the Schrodinger software package that enables precise ligand and receptor molecular docking (Alogheli, Olanders, Schaal, Brandt, & Karlen, 2017). Glide’s scoring function can fully consider hydrophobicity, metal coordination, hydrogen bonding, steric hindrance, unfavorable bond rotation, etc., effectively increasing the enrichment rate of compounds and reducing the number of false positives. 3. EXAMPLES AND CASE STUDIES

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Structure-based virtual ligand screening as a new approach for the discovery of new drugs can quickly screen large numbers of compounds in a short period of time to find possible candidates with low cost and high success rates. There have been many successful examples in recent years. In this chapter, we focus on new therapeutic applications for known drugs in the field of cancer treatment and explain their possible mechanisms of action. Drug repositioning may help to find more effective anticancer drugs, including drugs that selectively target cancer stem cells.

2 EXAMPLES OF STRUCTURE-BASED VIRTUAL LIGAND SCREENING OF FDA-APPROVED DRUGS FOR DISCOVERY OF ANTICANCER AGENTS In 2000 Douglas Hanahan and Robert A. Weinberg wrote a review entitled “The Hallmarks of Cancer” in Cell, which explained the six basic characteristics of tumor cells, namely: selfsufficiency in growth signals, insensitivity to antigrowth signals, apoptosis evasion, limitless replicative potential, sustained angiogenesis, and tissue invasion and metastasis (Douglas Hanahan, 2000). On March 4, 2011, they republished an updated version of the review entitled “Hallmarks of Cancer: The Next Generation.” The entire review of 29 pages briefly described hotspots and advances in oncology over the last 10 years (e.g., autophagy, cancer stem cells, tumor microenvironment, etc.) and they increased the previous six features to ten. The four new characteristics are: avoiding immune destruction, tumor promotion inflammation, deregulating cellular energetics, and genome instability and mutation. In addition, evading apoptosis, from the previous list was updated to, resisting cell death (Hanahan & Weinberg, 2011) In this chapter, we will classify anticancer targets based on the characteristics of cancer cells, and enumerate examples of structure-based virtual ligand screening of FDA-approved drugs for the discovery of anticancer agents.

2.1 Reprogramming Energy Metabolism Under aerobic conditions, normal cells process glucose, first to pyruvate via glycolysis in the cytosol and thereafter to carbon dioxide in the mitochondria; under anaerobic conditions, glycolysis is favored and relatively little pyruvate is dispatched to the oxygen-consuming mitochondria. Otto Warburg first observed an anomalous characteristic of cancer cell energy metabolism (Warburg, 1956): even in the presence of oxygen, cancer cells can reprogram their glucose metabolism and thus their energy production, by limiting their energy metabolism largely to glycolysis, leading to a state that has been termed “aerobic glycolysis.” Since Otto Warburg’s pioneering work on aerobic glycolysis (Warburg, 1956) was published, glucose has become a focus for cancer metabolic research. We have collected a number of targets related to tumor metabolism and elaborated them separately.

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EXAMPLE 1 BENSERAZIDE, A DOPADECARBOXYLASE INHIBITOR, SUPPRESSES TUMOR GROWTH BY TARGETING HEXOKINASE 2 The Warburg effect is the most fundamental metabolic alteration in tumor development and progression, especially in a solid tumor like colorectal cancer, breast cancer, liver cancer, etc. (Hanahan & Weinberg, 2011; Krasnov, Dmitriev, Lakunina, Kirpiy, & Kudryavtseva, 2013; Mathupala, Ko, & Pedersen, 2009). HK2 is the rate-limiting enzyme in the first reaction of glycolysis in cancer cells, and it plays a crucial role in the glycolytic pathway. Moreover, the expression level of HK2 is significantly elevated in various solid tumors and thus distinguishes cancer cells from normal cells; this makes HK2 a promising therapeutic target for cancer treatment (Patra et al., 2013; Ros & Schulze, 2013; Tan & Miyamoto, 2015). To search potential HK2 inhibitors, structure-based virtual ligand screening was performed by ICM 3.8.2 modeling software (MolSoft LLC, San Diego, CA) with the crystal structure of human HK2 (PDB code: 2NZT) as the model from ZINC Drug Database (Totrov & Abagyan, 1997). Benserazide (Benz) was identified as a possible HK2 inhibitor, which was further confirmed by enzymatic inhibition and microscale thermophoresis (MST) assay. Benserazide could specifically bind to HK2 with a certain binding affinity (Kd ¼ 149  4.95 μM) and significantly inhibit HK2 enzymatic activity in vitro with a combined mechanism that was both competitive and noncompetitive. Molecular docking results revealed that benserazide occupied the binding site of the substrate glucose and its pyrogallol part adopted a similar conformation as the glucose. Six hydrogen bonds were predicted between benserazide and HK2, they were 2-carbonyl and Gly681, 3-amino and Thr680, 200 -hydroxyl and Asn656, 300 -hydroxyl and Asn656, 400 -hydroxyl and Thr620, 400 -hydroxyl, and Glu708 (Fig. 1). Benserazide showed cytotoxicity to SW480 cells and without notable cytotoxicity

FIG. 1 H-bond interactions between benserazide and HK2 residues. Benserazide is depicted as ball-andstick model.

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to normal cells. In addition, benserazide reduced glucose uptake, lactate production, and intracellular ATP levels, and could cause cell apoptosis and an increased loss of MMP as well. In vivo study indicated that intraperitoneal (ip) injection of benserazide at 300 and 600 mg/kg suppressed cancer growth in tumor-bearing mice and no toxicity was shown. This study provides a new insight for the development of benserazide and its derivatives as novel antitumor agents (Li et al., 2017).

EXAMPLE 2 STRUCTURE BASED DISCOVERY OF CLOMIFENE AS A POTENT INHIBITOR OF MUTANT IDH1 Isocitrate dehydrogenase (IDH) mutations are present in nearly 75% of glioma and 20% of acute myeloid leukemia (Dang et al., 2009; Hartmann et al., 2009; Parsons et al., 2008; Wang et al., 2013; Xu et al., 2011). All of mutant IDH proteins, including IDH1R132H and IDH1R132C, demonstrate the concomitant gain of a neomorphic function that reduces α-KG to D-2-hydroxyglutaricacid (D-2HG) using NADPH as the cofactor (Popovici-Muller et al., 2012). As a result of mutations in IDH, high cellular concentration of D-2HG may cause global methylation of histone and DNA, which may lead to tumorigenesis (Zheng et al., 2013). A structure-based virtual ligand screening was conducted to identify small-molecule inhibitors of mutant IDH1 by using the X-ray structure of the IDH1R132H homodimer (PDB: 4UMX) (Yang, Tang, Habermehl, & Iczkowski, 2010; Yang, Zhong, Peng, Lai, & Ding, 2010; Zeng et al., 2016) as the molecular model. Clomifene was found to be an IDH1R132H inhibitor that can selectively suppress mutant enzyme activities in vitro and in vivo in a dose-dependent manner. The molecular docking indicated that clomifene occupied the allosteric site of the mutant IDH1 (Fig. 2). In contrast, for the known inhibitor AGI-5198, enzyme kinetics demonstrated that clomifene inhibited mutant enzymes in a noncompetitive manner. Knockdown

FIG. 2 Binding mode of clomifene with mutant IDH1. Molecular docking predicted that clomifene fitted the allosteric site of mutant IDH1 well with an extended conformation and the binding site of AGI-5198 with mutant IDH1 is close to the pocket of active center.

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of mutant IDH1 in HT1080 cells decreased sensitivity to clomifene. In vivo studies indicated that clomifene significantly suppressed the tumor growth of HT1080-bearing CB-17/Icr-scid mice with oral administration of 100 mg/kg and 50 mg/kg per day. These findings indicated clomifene may have clinical potential in tumor therapies as a mutant IDH1 inhibitor (Zheng, Luan, et al., 2017; Zheng, Sun, et al., 2017).

EXAMPLE 3 REPOSITIONING PROTON PUMP INHIBITORS AS ANTICANCER DRUGS BY TARGETING FATTY ACID SYNTHASE Fatty acid synthase (FASN) is an enzyme responsible for the de-novo synthesis of free fatty acids. FASN expression is associated with the formation, maintenance, and progression of many types of cancer (Liu, Liu, Wu, & Zhang, 2010). FASN is essential for the survival of cancer cells and contributes to drug resistance and poor prognosis (Liu, Liu, & Zhang, 2008). However, it is not expressed in most nonfat normal tissues. Therefore FASN is an ideal target for drug discovery for many types of human cancers with high FASN expression. Although different FASN inhibitors have been identified, none have been successfully transferred to clinical use. Zhang et al. performed virtual ligand screening of FDA-approved drugs to search FASN inhibitors by using the crystal structure of FASN thioesterase (TE) domain (PDB code: 3TJM) as the model (Zhang et al., 2011). They found that proton pump inhibitors (PPIs) agents for the treatment of various acid-related diseases of digestive system, effectively inhibit FASN TE activity. In order to further elucidate the binding mode of each PPI within FASN TE, the AMBER 12 suite of programs were used to perform molecular dynamics (MD) simulations for each PPI docked in the active site of FASN TE. Omeprazole shows potential for the formation of a strong hydrogen bond between the active site serine residue (Ser 2308) of the catalytic triad of TE and the sulfoxide moiety of omeprazole, which may prevent Ser 2308 from nucleophilically attacking a substrate. Further examination showed that PPIs inhibit lipid synthesis and disturb the binding between serine hydrolase probes and FASN. It also inhibits cancer cell proliferation by inducing apoptosis. Thus PPIs may exert anticancer activity in part by targeting and inhibiting TE activity of human FASN (Fako, Wu, Pflug, Liu, & Zhang, 2015).

2.2 Inducing Angiogenesis Like normal tissues, tumors require sustenance in the form of nutrients and oxygen as well as an ability to evacuate metabolic wastes and carbon dioxide. During tumor progression, an “angiogenic switch” is almost always activated and remains on, causing normally quiescent vasculature to continually sprout new vessels that help sustain expanding neoplastic growths (Hanahan & Folkman, 1996). Vascular endothelial growth factor (VEGF) gene expression can be upregulated both by hypoxia and by oncogene signaling (Mac & Popel, 2008). Abnormal angiogenesis, a process by which new blood vessels sprout from preexisting vessels, is well recognized as a common characteristic of various cancer types (Marme, 2018). By increasing

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the number of capillaries into the expanding tumor tissues, tumor-associated neo-vasculature is induced to accelerate tumorigenesis through aiding the nutrient supply and metastasis of tumor cells (Ocana, Martinez-Poveda, Quesada, & Medina, 2018). VEGF/vascular endothelial growth factor receptor-2 (VEGFR2) signaling has been widely accepted for its proangiogenic role by dominating all steps of angiogenesis including survival, proliferation, migration, and capillary-like tube formation of endothelial cells (Chung, Lee, & Ferrara, 2010). Therefore inhibition of VEGFR2 activity emerges as a potential therapy strategy against tumor-induced angiogenesis (Granci, Dupertuis, & Pichard, 2010).

EXAMPLE 1 DISCOVERY OF VEGFR2 INHIBITORS BY INTEGRATING NAIVE BAYESIAN CLASSIFICATION, MOLECULAR DOCKING AND DRUG-SCREENING APPROACHES VEGFR2 acts as a central modulator of angiogenesis and is therefore an important pharmaceutical target for developing antiangiogenic agents. Ligand-based naive Bayesian (NB) (Bender, 2011) models and structure-based molecular docking were combined to develop a virtual screening (VS) for identifying potential VEGFR2 inhibitors from 1841 FDA-approved drugs. By identifying eight FDA-approved antiangiogenic agents, the integrated VS pipeline was validated for its excellent predictive accuracy. The crystal structure of VEGFR2, complexed with axitinib, was retrieved from the Protein Data Bank (PDB ID: 4AGC) as the docking model (McTigue et al., 2012). The molecular docking studies were performed in Discovery Studio 2016. Using the optimal model NB-c and molecular-docking module LibDock, 1841 FDA-approved drugs were sequentially screened. To analyze the results of VS, biological validation was performed on nine top-ranked drugs. VEGFR2 kinase assay results demonstrated that flubendazole, rilpivirine, and papaverine were found to inhibit the enzymatic activities of VEGFR2. Flubendazole was identified as the most potent inhibitor in this study, with a IC50 value of 0.47 μM against VEGFR2. The reference compound axitinib and the selected compounds were docked into the binding site by utilizing the LibDock and CDOCKER modules. It is speculated that flubendazole, rilpivirine, and papaverine formed Pi-cation interaction with Lys868. Flubendazole formed three hydrogen bonds with Asp1046, Gly922, and Cys919, and one carbon hydrogen bond with Lys920. Rilpivirine formed one hydrogen bond with Cys919 and one carbon hydrogen bond with Glu917. Papaverine was found to interact with Asp1046 via one hydrogen bond, as well as Cys919, Glu917 and Glu885 via carbon hydrogen bonds. In summary, three FDA-approved drugs were identified as novel VEGFR2 inhibitors that could be used as leads to design and develop new antiangiogenic agents (Kang et al., 2018).

EXAMPLE 2 PREDICTING NEW INDICATIONS FOR APPROVED DRUGS USING A PROTEOCHEMOMETRIC METHOD Using the “train, match, fit, streamline” (TMFS) method, Byers et al. performed extensive molecular-fit computations on 3671 FDA-approved drugs across 2335 human-protein crystal structures. They predicted that anti-hookworm medication mebendazole could inhibit VEGFR2 activity and angiogenesis. It was confirmed that mebendazole binds directly to VEGFR2 and affects VEGFR2

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kinase activity with an IC50 of 3.6 μM. Besides this, mebendazole inhibits angiogenesis in a HUVEC cell-based assay. Mebendazole significantly inhibited network formation with an IC50 of 8.8 μM, which was implicated by the lack of cellular migration, alignment, and branching. Overall, it was predicted and experimentally validated that the anti-hookworm medication mebendazole can inhibit VEGFR2 activity and angiogenesis (Dakshanamurthy et al., 2012).

2.3 Evading Growth Suppressors In addition to the hallmark capability of inducing and sustaining positively acting growthstimulatory signals, cancer cells must also circumvent powerful programs that negatively regulate cell proliferation. The cyclin-dependent kinase (CDK) pathway is an important and established target for cancer treatment (Mariaule & Belmont, 2014; Morgan, 1997; Murray, 2004; Sherr & Roberts, 1999). It has been reported that cyclin-dependent kinase 2 (CDK2), one of the serine/threonine protein kinases, is overexpressed in numerous types of human neoplasia, including colorectal, ovarian, breast, and prostate cancers (Robb et al., 2018; Webster, 1998); it is responsible for the transition from the G1 to S phase of the cell cycle, and its deregulation is a hallmark of cancer.

EXAMPLE 1 IN SILICO IDENTIFICATION AND IN VITRO AND IN VIVO VALIDATION OF THE ANTIPSYCHOTIC DRUG FLUSPIRILENE AS A POTENTIAL CDK2 INHIBITOR AND A CANDIDATE ANTICANCER DRUG In this study, the free and open-source protein ligand-docking software idock was used to screen 4311 FDA-approved small-molecule drugs against CDK2. Nine compounds were identified using the idock score and selected for further study. Among them, the antipsychotic drug fluspirilene showed the highest antiproliferative effect in human hepatoma HepG2 and Huh7 cells. Structural analysis predicted that fluspirilene bound inside the ATP-binding pocket of CDK2 (PDB ID: 1GZ8) (Li, Leung, Ballester, & Wong, 2014; Li, Leung, Nakane, & Wong, 2014) and interacted with CDK2 mainly through hydrogen bonds, hydrophobic contacts, and cation-π interactions. All these bindings were spread over the head, middle, and tail fragments of fluspirilene, thereby firmly holding fluspirilene at its predicted position and orientation. It also revealed that fluspirilene treatment increased the percentage of cells in the G1 phase and decreased the expression of CDK2, cyclin E, and Rb, as well as the phosphorylation of CDK2. In vivo results show that oral fluspirilene treatment significantly inhibits tumor growth in nude mice xenografted with Huh 7 cells. Fluspirilene (15 mg/kg) showed strong antitumor activity, which was comparable to the leading cancer drug 5-fluorouracil (10 mg/kg). Combined therapy with fluspirilene and 5-fluorouracil showed the highest therapeutic effect. These results demonstrate that fluspirilene is a potential CDK2 inhibitor and could be a candidate for the treatment of human hepatocellular carcinoma (Shi et al., 2015a, 2015b).

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EXAMPLE 2 ADAPALENE INHIBITS THE ACTIVITY OF CYCLINDEPENDENT KINASE 2 IN COLORECTAL CARCINOMA Among the nine top compounds identified by the idock score, adapalene exhibited the highest antiproliferative effects in LOVO and DLD1 human colon cancer cell lines. Adapalene (ADA) was predicted to reside in the adenosine triphosphate-binding site of CDK2 and interact with CDK2 mainly through hydrophobic contacts with Phe82, Ile10, Leu134, Lys33, and His84. The study assessed the effects of ADA on the viability and cell cycle of colorectal cancer cells, as well as the expression of CDK2, cyclin E, and retinoblastoma protein (Rb), and the phosphorylation of CDK2 (on Thr-160) and Rb (on Ser-795). Furthermore, ADA was evaluated in vivo in a BALB/C nude mouse xenograft model using a DLD1 human colorectal cancer cells alone or in combination with oxaliplatin. ADA (20 mg/kg orally) exhibited marked antitumor activity, comparable to that of oxaliplatin (40 mg/kg), and dosedependently inhibited tumor growth, while combined administration of ADA and oxaliplatin produced the highest therapeutic effect. As ADA is an FDA-approved drug, its clinical use is facilitated compared with that of novel drugs; therefore, its potential use as a drug for the treatment of human colorectal cancer, particularly in combination with oxaliplatin, should be further investigated.

Overall, the powerful synergy of drug repositioning combined with in-silico structurebased VS (Bernard, 1993), where, by targeting CDK2, two FDA-approved drugs fluspirilene and adapalene have been rediscovered as anticancer agents in vitro and in vivo for the treatment of hepatocellular and colorectal carcinomas, respectively (Shi et al., 2015a, 2015b).

2.4 Sustaining Proliferative Signaling Cancer cells, by deregulating the production and release of growth-promoting signals, become masters of their own destinies. The enabling signals are conveyed in large part by growth factors that bind cell-surface receptors, typically containing intracellular tyrosine kinase domains. Mutations in the catalytic subunit of phosphoinositide 3-kinase (PI3-kinase) isoforms are being detected in an array of tumor types, which serve to hyperactivate the PI3-kinase signaling circuitry, including its key Akt/PKB signal transducer (Yuan & Cantley, 2008). mTOR activation results, via negative feedback, in the inhibition of PI3K signaling. Thus when mTOR is pharmacologically inhibited in such cancer cells (such as by the drug rapamycin), the associated loss of negative feedback results in increased activity of PI3K and its effector Akt/PKB, thereby blunting the antiproliferative effects of mTOR inhibition (Sudarsanam & Johnson, 2010). The phosphatidylinositol-3-kinase (PI3K)/AKT signaling pathway plays a key role in many cellular processes, including proliferation, survival, and differentiation of lung cancer cells. Therefore PI3K is a promising therapeutic target for the treatment of lung cancer.

EXAMPLE 1 ECONAZOLE NITRATE INHIBITS PI3K ACTIVITY AND PROMOTES APOPTOSIS IN LUNG CANCER CELLS A free and open-source protein-ligand docking software was applied to screen 3167 FDA-approved small molecules in order to identify putative PI3Kα inhibitors. The antifungal agent econazole nitrate was found to show the highest activity of reducing cell viability in pathological

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types of nonsmall-cell lung cancer (NSCLC) cell lines including H661 and A549. Econazole was predicted to bind to PI3Kα (PDB ID: 4JPS) (Vansteenkiste et al., 2015) by forming a hydrogen bond with Ser854, a halogen bond with Asp810, and hydrophobic contacts with Ile848 and Ile932. Econazole specifically inhibited AKT phosphorylation and Bcl-2 gene expression but had no effects on the phosphorylation level of ERK. It inhibited cell growth and promoted apoptosis in lung cancer cells in a dose-dependent manner. In addition, the combination of econazole and cisplatin produced additive effects in H661 and A549 lung cancer cell lines, respectively. Finally, econazole significantly inhibited A549 tumor growth in nude mice. These results suggested that econazole was a new PI3K inhibitor and a candidate for the treatment of lung cancer (Dong et al., 2017).

EXAMPLE 2 IN SILICO PREDICTION AND IN VITRO AND IN VIVO VALIDATION OF ACARICIDE FLUAZURON AS A POTENTIAL INHIBITOR OF FGFR3 AND A CANDIDATE DRUG FOR BLADDER CARCINOMA Bladder cancer (BC) is the ninth most common cause of cancer worldwide, so there is an urgent need to develop new therapeutic methods. Due to tumor recurrence and resistance, surgical resection, conventional chemotherapy, and radiotherapy eventually fail. The fibroblast growth factor receptor (FGFR) family represents an attractive therapeutic target in oncology that is attracting more and more attention. Fibroblast growth factor receptor 3 (FGFR3) is an important target for BC therapy. A free and open-source protein ligand-docking software idock (Li, Leung, Ballester, et al., 2014; Li, Leung, Nakane, et al., 2014) together with the binding affinity prediction software RF-Scire-v3 (Li, Leung, Wong, & Ballester, 2015) was used to prospectively identify potential inhibitors of FGFR3 from 3167 globally recognized small-molecule drugs. The molecular visualization tool iview (Li, Leung, Ballester, et al., 2014; Li, Leung, Nakane, et al., 2014) was used to inspect and analyze putative interactions. The X-ray structure of FGFR3 bearing the ATP-binding site (PDB code: 4K33) (Mir et al., 2018) was chosen to generate a molecular model. Six high-score compounds were tested in vitro. Among them, the acaricide drug fluazuron showed the highest antiproliferative effects in human BC cell lines. Structural analysis revealed that fluazuron formed three hydrogen bonds with Lys508, a hydrogen bond with Gly484, and a hydrophobic contact with Phe483. Further studies showed that fluoxetine treatment significantly increased the percentage of apoptotic cells and decreased the phosphorylation of FGFR3. The in vivo antitumor results showed that fluazuron given orally (80 mg/kg) significantly inhibited tumor growth in BALB/C nude mice transplanted with RT112 cells. These results demonstrate that fluazuron is a potential inhibitor of FGFR3 and is a candidate drug for the treatment of BC (Ke et al., 2017).

EXAMPLE 3 IN SILICO IDENTIFICATION OF NOVEL KINASE INHIBITORS TARGETING WILD-TYPE AND T315I MUTANT ABL1 FROM FDA-APPROVED DRUGS The proto-oncoprotein ABL1, a member of the nonreceptor tyrosine kinase (TK) family, is ubiquitously expressed in various mammalian cells (Laneuville, 1995). It participates in the cell cycle and apoptosis through integrating extracellular and intracellular signals. The constitutively active fusion 3. EXAMPLES AND CASE STUDIES

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protein BCR-ABL1 is the major cause of chronic myelogenous leukemia (CML), and the selective inhibition of ABL1 is a promising method for the treatment of CML. The fusion protein kinase can then stimulate numerous signal pathways including JAK-STAT, PI3K/AKT, Ras/MAPK (An et al., 2010; Kantarjian, Giles, Quintas-Cardama, & Cortes, 2007), and NF-kB (Cortes et al., 2007; Quintas-Cardama & Cortes, 2009), leading to uncontrolled cell proliferation and suppression of apoptosis. The reported drugs, such as imatinib, dasatinib, nilotinib, and bosutinib work well in clinical practice. However, resistance has manifested due to mutations within the kinase domain undermining the interaction between imatinib and ABL1, particularly T315I-gated mutations. Therefore there is an urgent need for broad-spectrum drugs that target ABL1. Two X-ray crystal structures of ABL1 were obtained from the RCSB protein databank (Berman et al., 2000): the wild-type (PDB code 2HYY, in complex with imatinib) (Cowan-Jacob et al., 2007) and the T315I mutant (PDB code 3QRJ, in complex with DCC2036) (Cortes et al., 2007). Molecular docking was performed by UCSF DOCK (version 6.5) (Lang et al., 2009). To screen for potential drugs targeting the wild-type ABL1 and T315I mutant ABL1, 1408 FDA-approved small-molecule drugs were screened by molecular docking. Following MD simulations and MM/GBSA combined with free energy calculations and energy decomposition, chlorhexidine and sorafenib were identified as potential “new use” drugs targeting wild-type ABL1, while nicergoline and plerixafor were identified to target T315I ABL1. At the same time, residues located at the ATP binding site and the A ring motif were found to play key roles in the interaction with ABL1. These findings could not only serve as an example for the repositioning of existing approved drugs, but also inject new vitality into ABL1-targeted antiCML therapeutics (Xu et al., 2014).

2.5 Resisting Cell Death The apoptotic regulators are divided into two major circuits, one receiving and processing extracellular death-inducing signals (the extrinsic apoptotic program, involving, for example, the Fas ligand/Fas receptor), and the other sensing and integrating a variety of signals of intracellular origin (the intrinsic program). Each culminates in activation of a normally latent protease (caspases 8 and 9, respectively). The archetype, Bcl-2, along with its closest relatives (Bcl-xL, Bcl-w, Mcl-1, A1) are inhibitors of apoptosis, acting in a large part by binding to and thereby suppressing two proapoptotic triggering proteins (Bax and Bak); the latter are embedded in the mitochondrial outer membrane.

EXAMPLE 1 REPOSITIONING OF AMPRENAVIR AS A NOVEL EXTRACELLULAR SIGNAL-REGULATED KINASE-2 INHIBITOR AND APOPTOSIS INDUCER IN MCF-7 HUMAN BREAST CANCER Studies have shown that ERK 1/2 acts as an extracellular signal-regulated kinase that mediates the phosphorylation of the Ser69 site of BimEL, thereby enhancing proteasomal degradation of BimEL (Luciano et al., 2003) or reducing its association with pro-survival molecules such as Mcl-1, Bcl-xL Bcl-2 (Ewings et al., 2007); so it promotes the survival of cancer cells. Therefore the identification of compounds that can inhibit ERK1/2 kinase activity is of considerable therapeutic importance for breast cancer. 3. EXAMPLES AND CASE STUDIES

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Since ERK1 has only one X-ray structure reported, but several high-resolution crystal structures of ERK2 complexed with selective inhibitors were available, a library of 1447 FDA-approved smallmolecule drugs was screened in silico to search for inhibitors of extracellular signal-regulated kinase 2 (ERK2) with the PDB code 2OJJ as the model (Aronov et al., 2007). A HIV-1 protease inhibitor, amprenavir was predicted to bind in the ATP-binding site via hydrophobic interactions with Ile18, Ala22, Val26, Ala39, Ile43, Ile71, and Leu143. In vivo kinase assays showed that amprenavir inhibited ERK2-mediated phosphorylation of BimEL at the Ser69 site. Amprenavir can inhibit this phosphorylation in MCF-7 cells, which may further promote the binding of BimEL to several prosurvival molecules. In addition, amprenavir inhibits the ERK2-BimEL signaling pathway, which may contribute to its antiproliferation and apoptosis-inducing activity in MCF-7 cells. Finally, in vivo tumor growth and immune-histochemical studies confirmed that amprenavir significantly inhibited tumor proliferation and induced apoptosis in MCF-7 xenograft models. In conclusion, amprenavir can effectively inhibit the kinase activity of ERK2, thereby inducing apoptosis in vitro and in vivo, and inhibiting tumor growth of human MCF-7 cancer cells; therefore it would be a promising candidate for future anticancer therapies ( Jiang, Li, et al., 2017; Jiang, Xing, et al., 2017).

EXAMPLE 2 IN SILICO SCREENING FOR DNA-DEPENDENT PROTEIN KINASE (DNA-PK) INHIBITORS: COMBINED HOMOLOGY MODELING, DOCKING, MOLECULAR DYNAMIC STUDY FOLLOWED BY BIOLOGICAL INVESTIGATION DNA-dependent protein kinase (DNA-PK), a serine/threonine nuclear kinase, belonging to the phosphatidylinositol-3 (PI-3) kinase-like kinase (PIKK) family (Abramenkovs & Stenerlow, 2017; Davis, Chen, & Chen, 2014) plays an essential role in protecting genome stability and is considered as the key enzyme in the nonhomologous DNA end-joining (NHEJ) repair pathway. Targeted inhibition of DNA-PK will provide a valuable option for cancer treatment. An enzyme homology model was validated and subsequently used as the model for dockingbased VS of FDA-approved drug databases. The results identified co-crystal structures of truncated mTOR with mLST8 subunit (4JSP) (Yang et al., 2013) as the best template candidate, which has 31% of sequence identities to DNA-PK. The nominated highest-ranking compounds, praziquantel and dutasteride, were investigated biologically. Praziquantel displayed the ability to interact with Ala-3730, Lys-3753, Thr-3809, and Asn-3926 by direct hydrogen bonding, while the amino acid Phe-3928 was shown to be able to form a water-bridge with praziquantel. Furthermore, praziquantel interacts with the key amino acids Leu-3751 (16% hydrophobic) and Lys-3753 (4% ionic). In addition, MD studies were conducted to explore the binding modes. The results of the biological evaluation showed that the two compounds inhibited DNA-PK enzyme activity at relatively high levels of concentration, the IC50 of praziquantel was 17.3 μM, and the IC50 of dutasteride was more than 20 μM. In addition, these two drugs enhanced the antiproliferative effects of doxorubicin and cisplatin on breast cancer (MCF7) and lung cancer (A549) cell lines. These results indicated that these two hits were good candidates as DNA-PK inhibitors and deserve further structural modifications to enhance their activities (Tarazi, Saleh, & El-Awady, 2016).

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EXAMPLE 3 DISCOVERY OF NOVEL BRD4 INHIBITORS BY DRUG REPURPOSING OF NITROXOLINE AND ITS ANALOGUES The bromodomain and extra-terminal (BET) family of brominated domain (BRDs)-containing proteins is thought to be a promising drug target for therapeutic intervention in many diseases, including cancer, inflammation, and cardiovascular disease. BRD4 is the most widely studied in hematology and solid tumors in the BRD family ( Jung, Gelato, Fernandez-Montalvan, Siegel, & Haendler, 2015; Zuber et al., 2011). BRD4 can recruit positive transcription elongation factor b to the promoter, stimulate RNA phosphorylation of RNA polymerase II, and regulate transcription of the famous carcinogenic driver c-Myc (Itzen, Greifenberg, Bosken, & Geyer, 2014; Jang et al., 2005; Yang et al., 2005). The localization of BRD4 on chromatin greatly attenuates the expression of c-Myc, cyclindependent kinase 6, and BCL-2, and leads to cell-cycle arrest on G1 phase and apoptosis (Delmore et al., 2011). These findings conformed that BRD4 is a promising drug target for therapeutic intervention. Therefore there is a great demand for new chemical forms of BRD4 inhibitors. Using a drugrepositioning strategy, a VS based on BRD4 specificity scores was performed in the internal drug library, followed by an ALPHA screening assay test. The protein structure of BRD4_BD1 (PDB Code: 4GPJ) was prepared by Protein Preparation Wizard in Maestro 9.1 (Schr€ odinger, LLC, New York, NY, 2010). The FDA-approved antioxidant nitroxoline exhibited potent inhibition and could significantly disrupt the binding between BRD4_BD1 and the acetylated H4 peptide on the ALPHA screen with an IC50 of 0.98 μM. Nitroxide inhibited all BET proteins’ selectivity. The crystal structure of nitroxoline-BRD4_BD1 complex provided that nitroxoline formed a crucial hydrogen-bonding interaction with N140 and occupied the substrate pocket in a stable manner through multiple hydrogen-bond interactions. Effective hydrophobic interactions with residues, including P82, L92, V87, L94, Y97, Y139, C136, and I146, also contributed to the binding affinity of nitroxoline. Nitroxoline could effectively inhibit the proliferation of mixed-lineage leukemia (MLL) cells by inducing cell-cycle arrest and apoptosis. This is due to the inhibition of BET and the downregulation of target-gene transcription. Overall, nitroxoline was found as a BRD4 inhibitor and can be used for the clinical translation of BET family-related diseases ( Jiang, Li, et al., 2017; Jiang, Xing, et al., 2017).

EXAMPLE 4 PANTOPRAZOLE, AN FDA-APPROVED PROTONPUMP INHIBITOR, SUPPRESSES COLORECTAL CANCER GROWTH BY TARGETING T-CELL-ORIGINATED PROTEIN KINASE T-LAK cell-originated protein kinase (TOPK, also known as PBK or PDZ-binding kinase) is a serine-threonine kinase belonging to the MAPKK family (Abe, Matsumoto, Kito, & Ueda, 2000; Gaudet, Branton, & Lue, 2000), which is highly expressed in various cancer cells. TOPK plays a critical role in the early stages of mitosis, it could phosphorylate histone H3 at Ser10 in vitro and in vivo and mediate its growth promoting effect by histone H3 modification (Li et al., 2016). Previous studies show that TOPK could link PDZ-containing proteins to signal-transduction pathways that regulate the cell cycle or cellular proliferation (Kim et al., 2012). TOPK promotes the resistance of cancer cells to epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor gefitinib by

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phosphorylating c-Jun, while inhibiting the expression of TOPK can restore the sensitivity of cancer cells to gefitinib. TOPK inhibitors HI-TOPK-032 (Kim et al., 2012) and OTS964 (Matsuo Y, 2014), were reported on in 2012 and 2014, respectively. However, neither of them has been put into clinical trials because of their toxicities or poor pharmacokinetic properties. The structure-based virtual ligand screening method was employed to screen the FDA-approved drug databases. A homology model of human TOPK was constructed using the X-ray structure of IRAK-4 kinase (PDB code: 2NRU) as the template and the docking was performed using ICM 3.8.1 modeling software (MolSoft LLC, San Diego, CA). With the best docking score, pantoprazole (PPZ) was identified to be a potential TOPK inhibitor from the FDA-approved drug databases. From the generated docking model two hydrogen bonds were predicted between pantoprazole with K213 and Y264, and a π-π stacking interaction was predicted between the compound and the benzene ring of F197 (Fig. 3). Further studies indicated that pantoprazole inhibited TOPK activities by directly binding with TOPK in vitro and in vivo. Pantoprazole inhibited TOPK activities in HCT 116 colorectal cancer cells, and the knockdown of TOPK in HCT 116 cells decreased their sensitivities to pantoprazole. In vivo study also demonstrated that pantoprazole effectively suppressed cancer growth in the xenograft model of HCT116 colorectal cancer. In short, pantoprazole can suppress the growth of colorectal cancer cells as a TOPK inhibitor both in vitro and in vivo (Zeng et al., 2016).

FIG. 3 Low-energy binding conformations of pantoprazole bound to TOPK generated by virtual ligand docking. Pantoprazoleis depicted as the ball-and-stick model. Hydrogen bonds are represented in dotted lines.

EXAMPLE 5 PROTON PUMP INHIBITOR ILAPRAZOLE SUPPRESSES CANCER GROWTH BY TARGETING T-CELLORIGINATED PROTEIN KINASE Inspired by the results of pantoprazole, other PPIs were speculated to be developed as potential TOPK inhibitors. Another six PPIs in clinical use were screened against TOPK using the virtual

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ligand-screening method, the homology model of human TOPK was constructed using the X-ray structure of the mixed-lineage kinase MLK1 (PDB code: 3DTC) as the template, which has 29% of sequence homology identities to the human TOPK. Among these PPIs, liaprazole was identified to be a potent TOPK inhibitor. From the generated docking model of ilaprazole, two hydrogen bonds were predicted between the methoxyl oxygen of ilaprazole and Gly223 and pyridine nitrogen and Arg155, respectively. π-π stacking interactions also were predicted to form between the pyridine ring of ilaprazole and the pyrrole ring of Pro169, and the pyrrole ring of ilaprazole and the pyrrole ring of Pro154. In vitro studies confirmed that ilaprazole inhibited TOPK activities in HCT116, ES-2, A549, and SW1990 cancer cells. At the same time, knockdown of TOPK in these cells decreased their sensitivities to ilaprazole. In vivo study also demonstrated that gavage of ilaprazole effectively suppressed cancer growth in the xenograft model of HCT116 colorectal cancer. The TOPK downstream signaling molecule phospho-histone H3 in tumor tissues was also decreased after ilaprazole treatment (Zheng, Luan, et al., 2017; Zheng, Sun, et al., 2017).

EXAMPLE 6 IN SILICO PREDICTION OF NEW INHIBITORS FOR THE NUCLEOTIDE POOL SANITIZING ENZYME, MTH1, USING DRUG REPURPOSING MTH1, a homologue of bacterial mutT, is a nucleotide pool sanitizing enzyme that converts oxidative nucleotides such as 8-oxo-dGTP or 2-OH-dATP into their corresponding monophosphates 8-oxod-GMP or 2-OH-dAMP, respectively (Burton & Rai, 2015; Fujikawa et al., 1999; Gad et al., 2014). Recent studies reported that MTH1 play an important role in maintaining tumor-cell survival. FDA-approved drug datasets were docked with MTH1 and then used consensus scores to screen for more effective compounds. The selected hit compounds, such as rolapitant and nilotinib, exhibited higher binding free energies than the co-crystalized inhibitor. From the docking results, Phe27 and Trp117 were found to be important in π-π stacking and hydrophobic interactions, while Asp119, Asp120, Glu77, Lys23, and Tyr7 could form hydrogen bonds with the hit compounds. These residues of MTH1 played major roles in the binding of hit compounds with the enzyme (Sohraby, Bagheri, Javaheri, & Aryapour, 2017).

EXAMPLE 7 COULD THE FDA-APPROVED ANTI-HIV PR INHIBITORS BE PROMISING ANTICANCER AGENTS? AN ANSWER FROM ENHANCED DOCKING APPROACH AND MOLECULAR DYNAMICS ANALYSES The FDA-approved HIV-1 protease inhibitor (PI) nelfinavir (NFV) was reported to have anticancer activities. However, the mechanism of its anticancer effects have not yet been confirmed. It has been speculated that the anticancer activities of NFV are ascribed to its inhibitory effects on the heat shock protein 90 (Hsp90), a promising target for anticancer therapy. In order to investigate the potential anticancer activity of all other FDA-approved HIV-1 PIs against human Hsp90, the VS

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method was used to elucidate the mechanism of binding and the relative binding affinity for FDAapproved HIV-1 PIs against HSP90. Homology modeling was performed to create its subsequent simulated 3D structure. Hsp90 MD from Homo sapiens (PDB Code: 3PRY) and Hsp90 CTD from Leishmania major (PDB Code: 3HJC) were selected as structural templates. The results showed that NFV had better binding affinity than other PIs, with the reasonable experimental data (IC50 3.1 μM). Indinavir, saquinavir, and ritonavir had similar affinities with NFV. The dissociation analysis of the interaction energy per residue showed that hydrophobic interactions with the active site residues Trp598, Met602, Tyr596, Val522, Met620, and Leu533, and hydrogen bonding with active site residues Gln523 and Tyr596 seem to play major roles in ligand-enzyme binding. This finding prompts researchers from different scientific domains to further investigate the potential applications of current FDA-approved HIV-1 PIs as dual antiHIV-1 and anticancer drugs (Arodola & Soliman, 2015).

2.6 An Enabling Characteristic: Tumor-Promoting Inflammation Inflammation is in some cases evident at the earliest stages of neoplastic progression and is demonstrably capable of fostering the development of incipient neoplasias into full-blown cancers. Additionally, inflammatory cells can release chemicals, notably reactive oxygen species, that are actively mutagenic for nearby cancer cells, accelerating their genetic evolution toward states of heightened malignancy.

EXAMPLE 1 PREDICTING NEW INDICATIONS FOR APPROVED DRUGS USING A PROTEOCHEMOMETRIC METHOD Predicted by the TMFS method and confirmed by surface plasmon resonance, dimethyl celecoxib (DMC) and the antiinflammatory drug celecoxib can bind cadherin-11 (CDH11), an adhesion molecule present in rheumatoid arthritis and the source of a poor prognosis in malignancy, which has no current targeted therapies. The growth inhibition assay of the MDA-MB-231 invasive breastcancer cell line by celecoxib and DMC were performed. The results confirmed that celecoxib and DMC cause growth inhibition with an IC50 of 40 and 36 μM, respectively (Dakshanamurthy et al., 2012).

EXAMPLE 2 SUBSTRUCTURE-DRUG-TARGET NETWORKBASED INFERENCE: AN INTEGRATED NETWORK AND CHEMOINFORMATICS TOOL FOR SYSTEMATIC PREDICTION OF DRUG-TARGET INTERACTIONS AND DRUG REPOSITIONING Substructure-drug-target network-based inference (SDTNBI) was used to predict potential targets for old drugs, failed drugs, and NCEs. Previous studies have suggested that COX-2, a well-known primary target for nonsteroidal antiinflammatory drugs (NSAIDs), plays a crucial role in cancer (Subbaramaiah & Dannenberg, 2003). In addition, inhibition of COX-2 by NSAIDs has potential anticancer indications for colorectal cancer (Carothers, Davids, Damas, & Bertagnolli, 2010) and breast cancer (Harris, Alshafie, Abou-Issa, & Seibert, 2000).

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Several potential targets were chosen to explore new potential anticancer indications for NSAIDs via SDTNBI. For instance, AKR1C3 was predicted as a novel potential antitumor target for several NSAIDs. Several previous studies reported that AKR1C3 played a crucial role in prostate cancer (Yang, Tang, et al., 2010; Yang, Zhong, et al., 2010). Previous preclinical studies demonstrated that multiple NSAIDs (Inoue et al., 2013; John-Aryankalayil et al., 2009; Soriano-Hernandez et al., 2012; Wechter et al., 2000), had potential antiprostate-cancer indications. Thus the predicted interactions of diclofenac-AKR1C3 and ibuprofen-AKR1C3 via SDTNBI were consistent with pharmacological experiments and co-crystal structure data (Lovering et al., 2004). Carbonic anhydrases, which were associated with breast cancer, were found to be potential anticancer targets for several NSAIDs (Watson et al., 2003). Previous studies have reported that NSAIDs were potent carbonic anhydrase inhibitors and had potential antibreast-cancer effects (Innocenti, Vullo, Scozzafava, & Supuran, 2008). Collectively inhibiting AKR1C3 carbonic anhydrases with NSAIDs may provide a new strategy for cancer chemoprevention. Also, CDK2 was identified to be targeted by carprofen, etodolac, and rofecoxib via SDTNBI. Previous studies demonstrated that CDK2 plays a crucial role in several cancer types (Shapiro, 2006). Overall SDTNBI is a powerful approach to predict potential targets for NCEs on a large scale in drug repositioning (Wu et al., 2017).

3 CONCLUSION Compared to the ever-increasing failure rates, high cost, and limited efficacy of the traditional drug-screening approaches, drug repurposing via the analysis of FDA-approved drugs is an effective method to identify therapeutic opportunities in cancer and other human diseases. Structure-based virtual ligand screening is a computational method that docks small molecules into the structures of macromolecular targets and scores their potential complementarity to binding sites. Along with great advances in both computational algorithms and computer-processing power, this approach is widely used in hit identification and lead optimization. Thus, the combination of structure-based virtual ligand screening and drug repositioning represents an efficient approach to accelerate drug discovery. Because of the verified bioavailability and safety evaluation of approved drugs, the obtained hits have higher probability to enter clinical trials than a NCE.

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