Synergistic drug combinations from electronic health records and gene expression.

J Am Med Inform Assoc. 2016 Dec 09;:

Authors: Low YS, Daugherty AC, Schroeder EA, Chen W, Seto T, Weber S, Lim M, Hastie T, Mathur M, Desai M, Farrington C, Radin AA, Sirota M, Kenkare P, Thompson CA, Yu PP, Gomez SL, Sledge GW, Kurian AW, Shah NH

Abstract
OBJECTIVE: Using electronic health records (EHRs) and biomolecular data, we sought to discover drug pairs with synergistic repurposing potential. EHRs provide real-world treatment and outcome patterns, while complementary biomolecular data, including disease-specific gene expression and drug-protein interactions, provide mechanistic understanding.
METHOD: We applied Group Lasso INTERaction NETwork (glinternet), an overlap group lasso penalty on a logistic regression model, with pairwise interactions to identify variables and interacting drug pairs associated with reduced 5-year mortality using EHRs of 9945 breast cancer patients. We identified differentially expressed genes from 14 case-control human breast cancer gene expression datasets and integrated them with drug-protein networks. Drugs in the network were scored according to their association with breast cancer individually or in pairs. Lastly, we determined whether synergistic drug pairs found in the EHRs were enriched among synergistic drug pairs from gene-expression data using a method similar to gene set enrichment analysis.
RESULTS: From EHRs, we discovered 3 drug-class pairs associated with lower mortality: anti-inflammatories and hormone antagonists, anti-inflammatories and lipid modifiers, and lipid modifiers and obstructive airway drugs. The first 2 pairs were also enriched among pairs discovered using gene expression data and are supported by molecular interactions in drug-protein networks and preclinical and epidemiologic evidence.
CONCLUSIONS: This is a proof-of-concept study demonstrating that a combination of complementary data sources, such as EHRs and gene expression, can corroborate discoveries and provide mechanistic insight into drug synergism for repurposing.

PMID: 27940607 [PubMed - as supplied by publisher]

Repurposing the anticancer drug mitomycin C for the treatment of persistent Acinetobacter baumannii infections.

Int J Antimicrob Agents. 2016 Oct 07;:

Authors: Cruz-Muñiz MY, López-Jacome LE, Hernández-Durán M, Franco-Cendejas R, Licona-Limón P, Ramos-Balderas JL, Martinéz-Vázquez M, Belmont-Díaz JA, Wood TK, García-Contreras R

Abstract
Acinetobacter baumannii is an emergent opportunistic bacterial pathogen responsible for recalcitrant infections owing to its high intrinsic tolerance to most antibiotics; therefore, suitable strategies to treat these infections are needed. One plausible approach is the repurposing of drugs that are already in use. Among them, anticancer drugs may be especially useful due their cytotoxic activities and ample similarities between bacterial infections and growing tumours. In this work, the effectiveness of four anticancer drugs on the growth of A. baumannii ATTC BAA-747 was evaluated, including the antimetabolite 5-fluorouracil and three DNA crosslinkers, namely cisplatin, mitomycin C (MMC) and merphalan. MMC was the most effective drug, having a minimum inhibitory concentration for 50% of growth in Luria-Bertani medium at ca. 7 µg/mL and completely inhibiting growth at 25 µg/mL. Hence, MMC was tested against a panel of 21 clinical isolates, including 18 multidrug-resistant (MDR) isolates, 3 of which were sensitive only to colistin. The minimum inhibitory concentrations and minimum bactericidal concentrations of MMC in all tested strains were found to be similar to those of A. baumannii ATCC BAA-747, and MMC also effectively killed stationary-phase, persister and biofilm cells. Moreover, MMC was able to increase survival of the insect larvae Galleria mellonella against an otherwise lethal A. baumannii infection from 0% to ≥53% for the antibiotic-sensitive A. baumannii ATCC BAA-747 strain and the MDR strains A560 and A578. Therefore, MMC is highly effective at killing the emergent opportunistic pathogen A. baumannii.

PMID: 27939675 [PubMed - as supplied by publisher]

Inhibition of mTOR/eIF4E by anti-viral drug ribavirin effectively enhances the effects of paclitaxel in oral tongue squamous cell carcinoma.

Biochem Biophys Res Commun. 2016 Dec 05;:

Authors: Dai D, Chen H, Tang J, Tang Y

Abstract
Upregulation of eIF4E is associated with poor clinical outcome in many human cancers and represents a potential therapeutic target. However, the function of eIF4E remains unknown in oral tongue squamous cell carcinoma (OTSCC). In this work, we show that ribavirin, an anti-viral drug, effectively augments sensitivity of OTSCC cells to paclitaxel via inhibiting mTOR/eIF4E signaling pathway. Ribavirin dose-dependently inhibits proliferation and induces apoptosis in SCC-9 and CAL27 cells. Combination of ribavirin and paclitaxel are more effective in inhibiting proliferation and inducing apoptosis in OTSCC cells. Importantly, the in vivo efficacy of ribavirin and its synergism with paclitaxel is confirmed by two independent OTSCC xenograft mouse models. Mechanistically, ribavirin significantly decreases mTOR/eIF4E signaling pathway in OTSCC cells via suppressing phosphorylation of Akt, mTOR, 4EBP1 and eIF4E. Overexpression of the phosphor-mimetic form of eIF4E (eIF4E S209D) but not the nonphosphorylatable form (eIF4E S209A) reverses the effects of ribavirin, confirming that eIF4E inhibition is the mechanism of action of ribavirin in OTSCC cells. In addition, eIF4E depletion significantly enhances the anti-proliferative and pro-apoptotic effects of paclitaxel, demonstrating the critical role of eIF4E in OTSCC cell response to paclitaxel. Our work is the first to demonstrate the efficacy of ribavirin as a single agent and synergism as combination with paclitaxel in OTSCC in vitro and in vivo. Our findings also demonstrate the therapeutic value of inhibiting eIF4E in OTSCC treatment.

PMID: 27932243 [PubMed - as supplied by publisher]

Metformin and propranolol combination prevents cancer progression and metastasis in different breast cancer models.

Oncotarget. 2016 Dec 01;:

Authors: Rico M, Baglioni M, Bondarenko M, Laluce NC, Rozados V, André N, Carré M, Scharovsky OG, Márquez MM

Abstract
Discovery of new drugs for cancer treatment is an expensive and time-consuming process and the percentage of drugs reaching the clinic remains quite low.Drug repositioning refers to the identification and development of new uses for existing drugs and represents an alternative drug development strategy.In this work, we evaluated the antitumor effect of metronomic treatment with a combination of two repositioned drugs, metformin and propranolol, in triple negative breast cancer models.By in vitro studies with five different breast cancer derived cells, we observed that combined treatment decreased proliferation (P < 0.001), mitochondrial activity (P < 0.001), migration (P < 0.001) and invasion (P < 0.001). In vivo studies in immunocompetent mice confirmed the potential of this combination in reducing tumor growth (P < 0.001) and preventing metastasis (P < 0.05).Taken together our results suggest that metformin plus propranolol combined treatment might be beneficial for triple negative breast cancer control, with no symptoms of toxicity.

PMID: 27926515 [PubMed - as supplied by publisher]

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DPDR-CPI, a server that predicts Drug Positioning and Drug Repositioning via Chemical-Protein Interactome.

Sci Rep. 2016 Nov 02;6:35996

Authors: Luo H, Zhang P, Cao XH, Du D, Ye H, Huang H, Li C, Qin S, Wan C, Shi L, He L, Yang L

Abstract
The cost of developing a new drug has increased sharply over the past years. To ensure a reasonable return-on-investment, it is useful for drug discovery researchers in both industry and academia to identify all the possible indications for early pipeline molecules. For the first time, we propose the term computational "drug candidate positioning" or "drug positioning", to describe the above process. It is distinct from drug repositioning, which identifies new uses for existing drugs and maximizes their value. Since many therapeutic effects are mediated by unexpected drug-protein interactions, it is reasonable to analyze the chemical-protein interactome (CPI) profiles to predict indications. Here we introduce the server DPDR-CPI, which can make real-time predictions based only on the structure of the small molecule. When a user submits a molecule, the server will dock it across 611 human proteins, generating a CPI profile of features that can be used for predictions. It can suggest the likelihood of relevance of the input molecule towards ~1,000 human diseases with top predictions listed. DPDR-CPI achieved an overall AUROC of 0.78 during 10-fold cross-validations and AUROC of 0.76 for the independent validation. The server is freely accessible via http://cpi.bio-x.cn/dpdr/.

PMID: 27805045 [PubMed - in process]

Drug Repurposing: Tolfenamic Acid Inactivates PrbP, a Transcriptional Accessory Protein in Liberibacter asiaticus.

Front Microbiol. 2016;7:1630

Authors: Gardner CL, Pagliai FA, Pan L, Bojilova L, Torino MI, Lorca GL, Gonzalez CF

Abstract
CLIBASIA_01510, PrbP, is a predicted RNA polymerase binding protein in Liberibacter asiaticus. PrbP was found to regulate expression of a small subset of ribosomal genes through interactions with the β-subunit of the RNA polymerase and a short, specific sequence on the promoter region. Molecular screening assays were performed to identify small molecules that interact with PrbP in vitro. Chemical hits were analyzed for therapeutic efficacy against L. asiaticus via an infected leaf assay, where the transcriptional activity of L. asiaticus was found to decrease significantly after exposure to tolfenamic acid. Similarly, tolfenamic acid was found to inhibit L. asiaticus infection in highly symptomatic citrus seedlings. Our results indicate that PrbP is an important transcriptional regulator for survival of L. asiaticus in planta, and the chemicals identified by molecular screening assays could be used as a therapeutic treatment for huanglongbing disease.

PMID: 27803694 [PubMed - in process]

Antiviral Screening of Multiple Compounds against Ebola Virus.

Viruses. 2016 Oct 27;8(11):

Authors: Dowall SD, Bewley K, Watson RJ, Vasan SS, Ghosh C, Konai MM, Gausdal G, Lorens JB, Long J, Barclay W, Garcia-Dorival I, Hiscox J, Bosworth A, Taylor I, Easterbrook L, Pitman J, Summers S, Chan-Pensley J, Funnell S, Vipond J, Charlton S, Haldar J, Hewson R, Carroll MW

Abstract
In light of the recent outbreak of Ebola virus (EBOV) disease in West Africa, there have been renewed efforts to search for effective antiviral countermeasures. A range of compounds currently available with broad antimicrobial activity have been tested for activity against EBOV. Using live EBOV, eighteen candidate compounds were screened for antiviral activity in vitro. The compounds were selected on a rational basis because their mechanisms of action suggested that they had the potential to disrupt EBOV entry, replication or exit from cells or because they had displayed some antiviral activity against EBOV in previous tests. Nine compounds caused no reduction in viral replication despite cells remaining healthy, so they were excluded from further analysis (zidovudine; didanosine; stavudine; abacavir sulphate; entecavir; JB1a; Aimspro; celgosivir; and castanospermine). A second screen of the remaining compounds and the feasibility of appropriateness for in vivo testing removed six further compounds (ouabain; omeprazole; esomeprazole; Gleevec; D-LANA-14; and Tasigna). The three most promising compounds (17-DMAG; BGB324; and NCK-8) were further screened for in vivo activity in the guinea pig model of EBOV disease. Two of the compounds, BGB324 and NCK-8, showed some effect against lethal infection in vivo at the concentrations tested, which warrants further investigation. Further, these data add to the body of knowledge on the antiviral activities of multiple compounds against EBOV and indicate that the scientific community should invest more effort into the development of novel and specific antiviral compounds to treat Ebola virus disease.

PMID: 27801778 [PubMed - in process]

Aripiprazole, an Antipsychotic and Partial Dopamine Agonist, Inhibits Cancer Stem Cells and Reverses Chemoresistance.

Anticancer Res. 2016 Oct;36(10):5153-5161

Authors: Suzuki S, Okada M, Kuramoto K, Takeda H, Sakaki H, Watarai H, Sanomachi T, Seino S, Yoshioka T, Kitanaka C

Abstract
BACKGROUND: There is a growing interest in repurposing antipsychotic dopamine antagonists for cancer treatment; however, antipsychotics are often associated with an increased risk of fatal events. The anticancer activities of aripiprazole, an antipsychotic drug with partial dopamine agonist activity and an excellent safety profile, remain unknown.
MATERIALS AND METHODS: The effects of aripiprazole alone or in combination with chemotherapeutic agents on the growth, sphere-forming ability and stem cell/differentiation/chemoresistance marker expression of cancer stem cells, serum-cultured cancer cells from which they were derived, and normal cells were examined.
RESULTS: At concentrations non-toxic to normal cells, aripiprazole inhibited the growth of serum-cultured cancer cells and cancer stem cells. Furthermore, aripiprazole induced differentiation and inhibited sphere formation, as well as stem cell marker expression of cancer stem cells while inhibiting their survivin expression and sensitizing them to chemotherapeutic agents.
CONCLUSION: Repurposing aripiprazole as an anticancer stem cell drug may merit further consideration.

PMID: 27798875 [PubMed - in process]

Current Progress in Bioinformatics 2016.

Brief Bioinform. 2016 Jan;17(1):1

Authors: Altman R

PMID: 26628559 [PubMed - indexed for MEDLINE]

Recent Advances and Emerging Applications in Text and Data Mining for Biomedical Discovery.

Brief Bioinform. 2016 Jan;17(1):33-42

Authors: Gonzalez GH, Tahsin T, Goodale BC, Greene AC, Greene CS

Abstract
Precision medicine will revolutionize the way we treat and prevent disease. A major barrier to the implementation of precision medicine that clinicians and translational scientists face is understanding the underlying mechanisms of disease. We are starting to address this challenge through automatic approaches for information extraction, representation and analysis. Recent advances in text and data mining have been applied to a broad spectrum of key biomedical questions in genomics, pharmacogenomics and other fields. We present an overview of the fundamental methods for text and data mining, as well as recent advances and emerging applications toward precision medicine.

PMID: 26420781 [PubMed - indexed for MEDLINE]

Repurposing some older drugs that cross the blood-brain barrier and have potential anticancer activity to provide new treatment options for glioblastoma.

Br J Clin Pharmacol. 2016 Feb;81(2):199-209

Authors: Rundle-Thiele D, Head R, Cosgrove L, Martin JH

Abstract
Glioblastoma is a brain neoplasm with limited 5-year survival rates. Developments of new treatment regimens that improve patient survival in patients with glioblastoma are needed. It is likely that a number of existing drugs used in other conditions have potential anticancer effects that offer significant survival benefit to glioblastoma patients. Identification of such drugs could provide a novel treatment paradigm.

PMID: 26374633 [PubMed - indexed for MEDLINE]

Metformin for Prevention and Treatment of Colon Cancer: A Reappraisal of Experimental and Clinical Data.

Curr Drug Targets. 2016;17(4):439-46

Authors: Anisimov VN

Abstract
In the 70-80th of last century, it has been shown that the antidiabetic biguanide drugs phenformin (PF) and buformin (BF) can exert an inhibitory action on carcinogenesis in animal models and increase from 5 to 10-years survival of cancer patients. Since 2005, after first evidence publication of the capacity of metformin (MF), another biguanide, to prevent development of malignant tumors in individuals with type 2 diabetes (T2D) and suppress tumorigenesis in mice, the burst of studies started in this field focused on breast, pancreas, prostatic, endometrial and some other cancers. Colorectal cancer (CRC) is the most prevalent among digestive system cancers. In this mini-review are presented the available data on the capacity of antidiabetic biguanide drugs to prevent colorectal carcinogenesis and growth in vitro and in vivo in experimental models and clinical observations.

PMID: 25738299 [PubMed - indexed for MEDLINE]

Identification of Iguratimod as an Inhibitor of Macrophage Migration Inhibitory Factor (MIF) with Steroid-Sparing Potential.

J Biol Chem. 2016 Oct 28;:

Authors: Bloom J, Metz C, Nalawade S, Casabar J, Cheng KF, He M, Sherry B, Coleman T, Forsthuber T, Al-Abed Y

Abstract
Macrophage migration inhibitory factor (MIF) is a pleiotropic cytokine that has been implicated in a broad range of inflammatory and oncologic diseases. MIF is unique among cytokines in terms of its release profile and inflammatory role, notably as an endogenous counter- regulator of the anti-inflammatory effects of glucocorticoids. In addition, it exhibits a catalytic tautomerase activity amenable to the design of high-affinity small molecule inhibitors. Although several classes of these compounds have been identified, biological characterization of these molecules remains a topic of active investigation. In this study, we used in vitro LPS-driven assays to characterize representative molecules from several classes of MIF inhibitors. We determined that MIF inhibitors exhibit distinct profiles of anti- inflammatory activity, especially with regard to TNFα. We further investigated a molecule with relatively low anti- inflammatory activity, compound T-614 (also known as the anti-rheumatic drug iguratimod), and found that in addition to exhibiting selective MIF inhibition in vitro and in vivo, iguratimod also has additive effects with glucocorticoids. Furthermore, we found that iguratimod synergizes with glucocorticoids in attenuating experimental autoimmune encephalitis (EAE), a model of multiple sclerosis. Our work identifies iguratimod as a valuable new candidate for drug repurposing to MIF-relevant diseases, including multiple sclerosis.

PMID: 27793992 [PubMed - as supplied by publisher]

Targeting CYP2J to reduce paclitaxel-induced peripheral neuropathic pain.

Proc Natl Acad Sci U S A. 2016 Oct 17;:

Authors: Sisignano M, Angioni C, Park CK, Meyer Dos Santos S, Jordan H, Kuzikov M, Liu D, Zinn S, Hohman SW, Schreiber Y, Zimmer B, Schmidt M, Lu R, Suo J, Zhang DD, Schäfer SM, Hofmann M, Yekkirala AS, de Bruin N, Parnham MJ, Woolf CJ, Ji RR, Scholich K, Geisslinger G

Abstract
Chemotherapy-induced peripheral neuropathic pain (CIPNP) is a severe dose- and therapy-limiting side effect of widely used cytostatics that is particularly difficult to treat. Here, we report increased expression of the cytochrome-P450-epoxygenase CYP2J6 and increased concentrations of its linoleic acid metabolite 9,10-EpOME (9,10-epoxy-12Z-octadecenoic acid) in dorsal root ganglia (DRGs) of paclitaxel-treated mice as a model of CIPNP. The lipid sensitizes TRPV1 ion channels in primary sensory neurons and causes increased frequency of spontaneous excitatory postsynaptic currents in spinal cord nociceptive neurons, increased CGRP release from sciatic nerves and DRGs, and a reduction in mechanical and thermal pain hypersensitivity. In a drug repurposing screen targeting CYP2J2, the human ortholog of murine CYP2J6, we identified telmisartan, a widely used angiotensin II receptor antagonist, as a potent inhibitor. In a translational approach, administration of telmisartan reduces EpOME concentrations in DRGs and in plasma and reverses mechanical hypersensitivity in paclitaxel-treated mice. We therefore suggest inhibition of CYP2J isoforms with telmisartan as a treatment option for paclitaxel-induced neuropathic pain.

PMID: 27791151 [PubMed - as supplied by publisher]

Targeting Phosphatidylinositol 4-Kinase IIIα for Radiosensitization: A Potential Model of Drug Repositioning Using an Anti-Hepatitis C Viral Agent.

Int J Radiat Oncol Biol Phys. 2016 Nov 15;96(4):867-876

Authors: Kwon J, Kim DH, Park JM, Park YH, Hwang YH, Wu HG, Shin KH, Kim IA

Abstract
PURPOSE: To investigate which isotype of phosphatidylinositol 4-kinase (PI4K) may affect radiosensitivity and examine whether anti-hepatitis C viral (HCV) agents, some of which have been shown to inhibit PI4K IIIα activity, could be repositioned as a radiosensitizer in human cancer cells.
METHODS AND MATERIALS: U251, BT474, and HepG2 cell lines and normal human astrocyte were used. Ribonucleic acid interference, clonogenic assays, Western blotting, immunofluorescence, annexin V assay, lysotracker staining, and β-galactosidase assay were performed.
RESULTS: Of the 4 PI4K isotypes, specific inhibition of IIIα increased radiosensitivity. For pharmacologic inhibition of PI4K IIIα, we screened 9 anti-HCV agents by half-maximal inhibitory concentration assay. Simeprevir was selected, and its inhibition of PI4K IIIα activity was confirmed. Combination of simeprevir treatment and radiation significantly attenuated expression of phospho-phospho-PKC and phospho-Akt and increased radiation-induced cell death in tested cell lines. Pretreatment with simeprevir prolonged γH2AX foci formation and down-regulation of phospho-DNA-PKcs, indicating impairment of nonhomologous end-joining repair. Cells pretreated with simeprevir exhibited mixed modes of cell death, including apoptosis and autophagy.
CONCLUSION: These data demonstrate that targeting PI4K IIIα using an anti-HCV agent is a viable approach to enhance the therapeutic efficacy of radiation therapy in various human cancers, such as glioma, breast, and hepatocellular carcinoma.

PMID: 27788957 [PubMed - in process]

Drug repurposing by integrated literature mining and drug-gene-disease triangulation.

Drug Discov Today. 2016 Oct 22;:

Authors: Sun P, Guo J, Winnenburg R, Baumbach J

Abstract
Drug design is expensive, time-consuming and becoming increasingly complicated. Computational approaches for inferring potentially new purposes of existing drugs, referred to as drug repositioning, play an increasingly important part in current pharmaceutical studies. Here, we first summarize recent developments in computational drug repositioning and introduce the utilized data sources. Afterwards, we introduce a new data fusion model based on n-cluster editing as a novel multi-source triangulation strategy, which was further combined with semantic literature mining. Our evaluation suggests that utilizing drug-gene-disease triangulation coupled to sophisticated text analysis is a robust approach for identifying new drug candidates for repurposing.

PMID: 27780789 [PubMed - as supplied by publisher]

Antibiotic drug levofloxacin inhibits proliferation and induces apoptosis of lung cancer cells through inducing mitochondrial dysfunction and oxidative damage.

Biomed Pharmacother. 2016 Oct 22;84:1137-1143

Authors: Song M, Wu H, Wu S, Ge T, Wang G, Zhou Y, Sheng S, Jiang J

Abstract
Lung cancer is the leading cause of cancer death worldwide and its clinical management remains challenge. Here, we repurposed antibiotic levofloxacin for lung cancer treatment. We show that levofloxacin is effectively against a panel of lung cancer cell lines via inhibiting proliferation and inducing apoptosis, regardless of cellular origin and genetic pattern, in in vitro cell culture system and in vivo xenograft lung tumor model. Mechanistically, levofloxacin inhibits activities of mitochondrial electron transport chain complex I and III, leading to inhibition of mitochondrial respiration and reduction of ATP production. In addition, levofloxacin significantly increases levels of ROS, mitochondrial superoxide and hydrogen peroxide in vitro and oxidative stress markers (HEL and 4-HNE) in vivo. Antioxidants, such as NAC and vitamin C, prevent the inhibitory effects of levofloxacin, confirming the induction of oxidative damage as the mechanism of its action in lung cancer cells. Our work demonstrates that levofloxacin is a useful addition to the treatment of lung cancer. Our work also suggests that targeting mitochondria may be an alternative therapeutic strategy for lung cancer treatment.

PMID: 27780143 [PubMed - as supplied by publisher]

A Computational Systems Biology Approach for Identifying Candidate Drugs for Repositioning for Cardiovascular Disease.

Interdiscip Sci. 2016 Oct 24;

Authors: Yu AZ, Ramsey SA

Abstract
We report an in silico method to screen for receptors or pathways that could be targeted to elicit beneficial transcriptional changes in a cellular model of a disease of interest. In our method, we integrate: (1) a dataset of transcriptome responses of a cell line to a panel of drugs; (2) two sets of genes for the disease; and (3) mappings between drugs and the receptors or pathways that they target. We carried out a gene set enrichment analysis (GSEA) test for each of the two gene sets against a list of genes ordered by fold-change in response to a drug in a relevant cell line (HL60), with the overall score for a drug being the difference of the two enrichment scores. Next, we applied GSEA for drug targets based on drugs that have been ranked by their differential enrichment scores. The method ranks drugs by the degree of anti-correlation of their gene-level transcriptional effects on the cell line with the genes in the disease gene sets. We applied the method to data from (1) CMap 2.0; (2) gene sets from two transcriptome profiling studies of atherosclerosis; and (3) a combined dataset of drug/target information. Our analysis recapitulated known targets related to CVD (e.g., PPARγ; HMG-CoA reductase, HDACs) and novel targets (e.g., amine oxidase A, δ-opioid receptor). We conclude that combining disease-associated gene sets, drug-transcriptome-responses datasets and drug-target annotations can potentially be useful as a screening tool for diseases that lack an accepted cellular model for in vitro screening.

PMID: 27778232 [PubMed - as supplied by publisher]

Editorial: Alternative Therapeutics against MDR Bacteria - "Fighting the Epidemic of Antibiotic Resistance".

Front Microbiol. 2016;7:1559

Authors: Martins M, McCusker MP

PMID: 27774086 [PubMed - in process]