Pathway-Centric Structure-Based Multi-Target Compound Screening for Anti-Virulence Drug Repurposing.

Int J Mol Sci. 2019 Jul 17;20(14):

Authors: Xie L, Xie L

Abstract
The emergence of superbugs that are resistant to last-resort antibiotics poses a serious threat to human health, and we are in a "race against time to develop new antibiotics." New approaches are urgently needed to control drug-resistant pathogens, and to reduce the emergence of new drug-resistant microbes. Targeting bacterial virulence has emerged as an important strategy for combating drug-resistant pathogens. It has been shown that pyocyanin, which is produced by the phenazine biosynthesis pathway, plays a key role in the virulence of Pseudomonas aeruginosa infection, making it an attractive target for anti-infective drug discovery. In order to discover efficient therapeutics that inhibit the phenazine biosynthesis in a timely fashion, we screen 2004 clinical and pre-clinical drugs to target multiple enzymes in the phenazine biosynthesis pathway, using a novel procedure of protein-ligand docking. Our detailed analysis suggests that kinase inhibitors, notably Lifirafenib, are promising lead compounds for inhibiting aroQ, phzG, and phzS enzymes that are involved in the phenazine biosynthesis, and merit further experimental validations. In principle, inhibiting multiple targets in a pathway will be more effective and have less chance of the emergence of drug resistance than targeting a single protein. Our multi-target structure-based drug design strategy can be applied to other pathways, as well as provide a systematic approach to polypharmacological drug repositioning.

PMID: 31319464 [PubMed - in process]

Limiting research on molecular targeted therapies in advanced solid cancers: beyond a cost-effectiveness ratio analysis.

Biomark Med. 2019 Jul 18;:

Authors: Nicolini A, Ferrari P, Carpi A

PMID: 31317773 [PubMed - as supplied by publisher]

Computational Drug Screening Identifies Compounds Targeting Renal Age-associated Molecular Profiles.

Comput Struct Biotechnol J. 2019;17:843-853

Authors: Koppelstaetter C, Leierer J, Rudnicki M, Kerschbaum J, Kronbichler A, Melk A, Mayer G, Perco P

Abstract
Aging is a major driver for chronic kidney disease (CKD) and the counterbalancing of aging processes holds promise to positively impact disease development and progression. In this study we generated a signature of renal age-associated genes (RAAGs) based on six different data sources including transcriptomics data as well as data extracted from scientific literature and dedicated databases. Protein abundance in renal tissue of the 634 identified RAAGs was studied next to the analysis of affected molecular pathways. RAAG expression profiles were furthermore analysed in a cohort of 63 CKD patients with available follow-up data to determine association with CKD progression. 23 RAAGs were identified showing concordant regulation in renal aging and CKD progression. This set was used as input to computationally screen for compounds with the potential of reversing the RAAG/CKD signature on the transcriptional level. Among the top-ranked drugs we identified atorvastatin, captopril, valsartan, and rosiglitazone, which are widely used in clinical practice for the treatment of patients with renal and cardiovascular diseases. Their positive impact on the RAAG/CKD signature could be validated in an in-vitro model of renal aging. In summary, we have (i) consolidated a set of RAAGs, (ii) determined a subset of RAAGs with concordant regulation in CKD progression, and (iii) identified a set of compounds capable of reversing the proposed RAAG/CKD signature.

PMID: 31316728 [PubMed]

A new screening method for ATP-independent kinase inhibitors identifies repurposed anti-cancer drugs.

EBioMedicine. 2018 Nov;37:21-22

Authors: Timaner M, Shaked Y

PMID: 30509398 [PubMed - indexed for MEDLINE]

Virtual screening of inhibitors against Envelope glycoprotein of Chikungunya Virus: a drug repositioning approach.

Bioinformation. 2019;15(6):439-447

Authors: Agarwal G, Gupta S, Gabrani R, Gupta A, Chaudhary VK, Gupta V

Abstract
Chikungunya virus (CHIKV) a re-emerging mosquito-borne alpha virus causes significant distress which is further accentuated in the lack of specific therapeutics or a preventive vaccine, mandating accelerated research for anti-CHIKV therapeutics. In recent years, drug repositioning has gained recognition for the curative interventions for its cost and time efficacy. CHIKV envelope proteins are considered to be the promising targets for drug discovery because of their essential role in viral attachment and entry in the host cells. In the current study, we propose structure-based virtual screening of drug molecule on the crystal structure of mature Chikungunya envelope protein (PDB 3N41) using a library of FDA approved drug molecules. Several cephalosporin drugs docked successfully within two binding sites prepared at E1-E2 interface of CHIKV envelop protein complex with significantly low binding energies. Cefmenoxime, ceforanide, cefotetan, cefonicid sodium and cefpiramide were identified as top leads with a cumulative score of -67.67, -64.90, -63.78, -61.99, and - 61.77, forming electrostatic, hydrogen and hydrophobic bonds within both the binding sites. These shortlisted leads could be potential inhibitors of E1-E2 hetero dimer in CHIKV, hence might disrupt the integrity of envelope glycoprotein leading to loss of its ability to form mature viral particles and gain entry into the host.

PMID: 31312082 [PubMed]

Mitochondrial and ribosomal biogenesis are new hallmarks of stemness, oncometabolism and biomass accumulation in cancer: Mito-stemness and ribo-stemness features.

Aging (Albany NY). 2019 07 16;:

Authors: Peiris-Pagès M, Ozsvári B, Sotgia F, Lisanti MP

Abstract
Using proteomics analysis, we previously compared MCF7 breast cancer cells grown as 3D tumor spheres, with the same cell line grown as monolayers. Our results indicated that during 3D anchorage‐independent growth, the cellular machinery associated with i) mitochondrial biogenesis and ii) ribosomal biogenesis, were both significantly increased. Here, for simplicity, we refer to these two new oncogenic hallmarks as “mito‐stemness” and “ribo‐stemness” features. We have now applied this same type of strategy to begin to understand how fibroblasts and MCF7 breast cancer cells change their molecular phenotype, when they are co‐cultured together. We have previously shown that MCF7‐fibroblast co‐cultures are a valuable model of resistance to apoptosis induced by hormonal therapies, such as Tamoxifen and Fulvestrant. Here, we directly show that these mixed co‐cultures demonstrate the induction of mito‐stemness and ribo‐stemness features, likely reflecting a mechanism for cancer cells to increase their capacity for accumulating biomass. In accordance with the onset of a stem‐like phenotype, KRT19 (keratin 19) was induced by ~6‐fold during co‐culture. KRT19 is a well‐established epithelial CSC marker that is used clinically to identify metastatic breast cancer cells in sentinel lymph node biopsies. The potential molecular therapeutic targets that we identified by label‐free proteomics of MCF7‐fibroblast co‐cultures were then independently validated using a bioinformatics approach. More specifically, we employed publically‐available transcriptional profiling data derived from primary tumor samples from breast cancer patients, which were previously subjected to laser‐capture micro‐dissection, to physically separate breast cancer cells from adjacent tumor stroma. This allowed us to directly validate that the proteins up‐regulated in this co‐culture model were also transcriptionally elevated in patient‐derived breast cancer cells in vivo. This powerful approach for target identification and translational validation, including the use of patient outcome data, can now be applied to other tumor types as well, to validate new therapeutic targets that are more clinically relevant, for patient benefit. Moreover, we discuss the therapeutic implications of these findings for new drug development, drug repurposing and Tamoxifen‐resistance, to effectively target mito‐stemness and ribo‐stemness features in breast cancer patients. We also discuss the broad implications of this “organelle biogenesis” approach to cancer therapy.

PMID: 31311889 [PubMed - as supplied by publisher]

In Silico Repositioning of Cannabigerol as a Novel Inhibitor of the Enoyl Acyl Carrier Protein (ACP) Reductase (InhA).

Molecules. 2019 Jul 15;24(14):

Authors: Pinzi L, Lherbet C, Baltas M, Pellati F, Rastelli G

Abstract
Cannabigerol (CBG) and cannabichromene (CBC) are non-psychoactive cannabinoids that have raised increasing interest in recent years. These compounds exhibit good tolerability and low toxicity, representing promising candidates for drug repositioning. To identify novel potential therapeutic targets for CBG and CBC, an integrated ligand-based and structure-based study was performed. The results of the analysis led to the identification of CBG as a low micromolar inhibitor of the Enoyl acyl carrier protein (ACP) reductase (InhA) enzyme.

PMID: 31311157 [PubMed - in process]

YM155 enhances the cytotoxic activity of etoposide against canine osteosarcoma cells.

J Vet Med Sci. 2019 Jul 15;:

Authors: Ong SM, Saeki K, Kok MK, Nakagawa T, Nishimura R

Abstract
Canine osteosarcoma (OSA) is an aggressive and highly malignant primary bone tumor. Its poor survival outcome remains problematic despite recent advances in anti-cancer therapy, therefore highlighting the need for alternative treatment options or drug repositioning. The aim of this study was to determine if YM155, a small-molecule survivin inhibitor, potentiates the chemotherapeutic efficacy of etoposide against canine OSA in vitro and in vivo. In cell culture, YM155 enhanced the cytotoxic effect of etoposide against canine OSA cell lines; however, the molecular mechanism behind this effect was heterogeneous, as only one cell line had an elevated apoptotic level. In addition, this effect was not associated with survivin suppression in two of the cell lines. These results suggest that the molecular target of YM155 is not restricted to survivin alone. When tested on a murine xenograft model, the average tumor volume of the combination treatment group (YM155, 5 mg/kg, intraperitoneally, 5 consecutive days/week; and etoposide, 20 mg/kg, intraperitoneally, every 5 days) was 66% smaller than the control group, although this difference was not statistically significant (P=0.17). Further studies to improve the treatment protocol are necessary to confirm the findings of this study.

PMID: 31308291 [PubMed - as supplied by publisher]

NGSEA: Network-Based Gene Set Enrichment Analysis for Interpreting Gene Expression Phenotypes with Functional Gene Sets.

Mol Cells. 2019 Jul 16;:

Authors: Han H, Lee S, Lee I

Abstract
Gene set enrichment analysis (GSEA) is a popular tool to identify underlying biological processes in clinical samples using their gene expression phenotypes. GSEA measures the enrichment of annotated gene sets that represent biological processes for differentially expressed genes (DEGs) in clinical samples. GSEA may be suboptimal for functional gene sets; however, because DEGs from the expression dataset may not be functional genes per se but dysregulated genes perturbed by bona fide functional genes. To overcome this shortcoming, we developed network-based GSEA (NGSEA), which measures the enrichment score of functional gene sets using the expression difference of not only individual genes but also their neighbors in the functional network. We found that NGSEA outperformed GSEA in identifying pathway gene sets for matched gene expression phenotypes. We also observed that NGSEA substantially improved the ability to retrieve known anti-cancer drugs from patient-derived gene expression data using drug-target gene sets compared with another method, Connectivity Map. We also repurposed FDA-approved drugs using NGSEA and experimentally validated budesonide as a chemical with anti-cancer effects for colorectal cancer. We, therefore, expect that NGSEA will facilitate both pathway interpretation of gene expression phenotypes and anti-cancer drug repositioning. NGSEA is freely available at www.inetbio.org/ngsea.

PMID: 31307154 [PubMed - as supplied by publisher]

Fluoxetine and thioridazine inhibit efflux and attenuate crystalline biofilm formation by Proteus mirabilis.

Sci Rep. 2017 09 22;7(1):12222

Authors: Nzakizwanayo J, Scavone P, Jamshidi S, Hawthorne JA, Pelling H, Dedi C, Salvage JP, Hind CK, Guppy FM, Barnes LM, Patel BA, Rahman KM, Sutton MJ, Jones BV

Abstract
Proteus mirabilis forms extensive crystalline biofilms on indwelling urethral catheters that block urine flow and lead to serious clinical complications. The Bcr/CflA efflux system has previously been identified as important for development of P. mirabilis crystalline biofilms, highlighting the potential for efflux pump inhibitors (EPIs) to control catheter blockage. Here we evaluate the potential for drugs already used in human medicine (fluoxetine and thioridazine) to act as EPIs in P. mirabilis, and control crystalline biofilm formation. Both fluoxetine and thioridazine inhibited efflux in P. mirabilis, and molecular modelling predicted both drugs interact strongly with the biofilm-associated Bcr/CflA efflux system. Both EPIs were also found to significantly reduce the rate of P. mirabilis crystalline biofilm formation on catheters, and increase the time taken for catheters to block. Swimming and swarming motilies in P. mirabilis were also significantly reduced by both EPIs. The impact of these drugs on catheter biofilm formation by other uropathogens (Escherichia coli, Pseudomonas aeruginosa) was also explored, and thioridazine was shown to also inhibit biofilm formation in these species. Therefore, repurposing of existing drugs with EPI activity could be a promising approach to control catheter blockage, or biofilm formation on other medical devices.

PMID: 28939900 [PubMed - indexed for MEDLINE]

Clarithromycin as a "repurposing drug" against MALT lymphoma.

Br J Haematol. 2018 09;182(6):913-915

Authors: Ferreri AJM, Cecchetti C, Kiesewetter B, Sassone M, Calimeri T, Perrone S, Ponzoni M, Raderer M

PMID: 28771670 [PubMed - indexed for MEDLINE]

8 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"drug repositioning" OR "drug repurposing"

These pubmed results were generated on 2019/07/16

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

6 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"drug repositioning" OR "drug repurposing"

These pubmed results were generated on 2019/07/16

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Dopamine receptor D2 activation suppresses the radiosensitizing effect of aripiprazole via activation of AMPK.

FEBS Open Bio. 2019 Jul 13;:

Authors: Lee H, Kang S, Sonn JK, Lim YB

Abstract
Drug repositioning has garnered attention as an alternative strategy to the discovery and development of novel anticancer drug candidates. In this study, we screened 321 FDA-approved drugs against non-irradiated and irradiated MCF-7 cells, revealing that aripiprazole, a dopamine receptor D2 (D2R) partial agonist, enhances the radiosensitivity of MCF-7 cells. Unexpectedly, D2R-selective antagonist treatment significantly enhanced the radiosensitizing effects of aripiprazole, and prevented aripiprazole-induced 5' adenosine monophosphate-activated protein kinase (AMPK) phosphorylation. Direct AMPK activation with A769662 treatment blunted the radiosensitizing effects of aripiprazole. These results indicate that aripiprazole has potential as a radiosensitizing drug. Furthermore, prevention of D2R/AMPK activation might enhance these anticancer effects of aripiprazole in breast cancer cells.

PMID: 31301124 [PubMed - as supplied by publisher]

Peptides as epigenetic modulators: therapeutic implications.

Clin Epigenetics. 2019 Jul 12;11(1):101

Authors: Janssens Y, Wynendaele E, Vanden Berghe W, De Spiegeleer B

Abstract
Peptides originating from different sources (endogenous, food derived, environmental, and synthetic) are able to influence different aspects of epigenetic regulation. Endogenous short peptides, resulting from proteolytic cleavage of proteins or upon translation of non-annotated out of frame transcripts, can block DNA methylation and hereby regulate gene expression. Peptides entering the body by digestion of food-related proteins can modulate DNA methylation and/or histone acetylation while environmental peptides, synthesized by bacteria, fungi, and marine sponges, mainly inhibit histone deacetylation. In addition, synthetic peptides that reverse or inhibit different epigenetic modifications of both histones and the DNA can be developed as well. Next to these DNA and histone modifications, peptides can also influence the expression of non-coding RNAs such as lncRNAs and the maturation of miRNAs.Seen the advantages over small molecules, the development of peptide therapeutics is an interesting approach to treat diseases with a strong epigenetic basis like cancer and Alzheimer's disease. To date, only a limited number of drugs with a proven epigenetic mechanism of action have been approved by the FDA of which two (romidepsin and nesiritide) are peptides. A large knowledge gap concerning epigenetic effects of peptides is present, and this class of molecules deserves more attention in the development as epigenetic modulators. In addition, none of the currently approved peptide drugs are under investigation for their potential effects on epigenetics, hampering drug repositioning of these peptides to other indications with an epigenetic etiology.

PMID: 31300053 [PubMed - in process]

The anthelmintic oxyclozanide restores the colistin activity in colistin-resistant Gram-negative bacilli.

Int J Antimicrob Agents. 2019 Jul 09;:

Authors: Ayerbe-Algaba R, Gil-Marqués ML, Miró-Canturri A, Parra-Millán R, Pachón-Ibáñez ME, Jiménez-Mejías ME, Pachón J, Smani Y

Abstract
Due to the significant increase in the antimicrobial resistance of Gram-negative bacilli (GNB), the development of non-antimicrobial therapeutic alternatives, which can be used together with the few and non-optimal available antimicrobial agents such as colistin, has become an urgent need. In this context, the desregulation of the bacterial cell wall could be a therapeutic alternative adjuvant to colistin. The aim of this study was to analyse the activity of oxyclozanide, an anthelmintic drug, in combination with colistin against colistin-susceptible (Col-S) and colistin-resistant (Col-R) GNB. Three reference Col-S strains and 13 Col-R clinical isolates of Acinetobacter baumannii, Pseudomonas aeruginosa and Klebsiella pneumoniae were studied. Microdilution assays and time-kill curves were performed to examine the activity of oxyclozanide in combination with colistin. Outer membrane proteins (OMPs) profile, membrane permeation and cell wall structure of Col-S and Col-R A. baumannii, P. aeruginosa and K. pneumoniae in presence of oxyclozanide were assessed by SDS-PAGE, fluorescence and transmission electron microscopy, respectively. Oxyclozanide in combination with colistin increases the activity of colistin against Col-S and Col-R A. baumannii, P. aeruginosa and K. pneumoniae. Time-killing curves have showed synergistic activity between oxyclozanide and colistin against these bacterial isolates. Moreover, Col-R A. baumannii, P. aeruginosa and K. pneumoniae in presence of oxyclozanide present higher permeation and disruption in their cell wall than Col-S strains, without modifying their OMPs profile. These data suggest that the combination of oxyclozanide and colistin may be a new alternative for the treatment of Col-R GNB infections.

PMID: 31299296 [PubMed - as supplied by publisher]

Artemisinin and its derivatives; ancient tradition inspiring the latest therapeutic approaches against malaria.

Future Med Chem. 2019 Jul 12;:

Authors: Martino E, Tarantino M, Bergamini M, Castelluccio V, Coricello A, Falcicchio M, Lorusso E, Collina S

Abstract
Artemisinin (ART) is an endoperoxide sesquiterpene lactone, commonly used in the treatment of malaria. Although it was isolated from Artemisia annua L., a plant widely applied in Chinese Traditional Medicine, its mechanism of action remains uncertain and its clinical use is still limited due to its low solubility, its poor bioavailability and short in vivo half-life. Over time, several studies have been aimed towards the discovery of potent ART derivatives that could overcome clinical drawbacks. In this review, we focus on the multifaced aspects of ART and on the efforts spent to improve its pharmacological profile that so far culminated in the discovery of more effective drugs. Lastly, we outline the new perspectives in the ART-derivatives scenario.

PMID: 31298579 [PubMed - as supplied by publisher]

A High-Content Screening of Anticancer Compounds Suggests the Multiple Tyrosine Kinase Inhibitor Ponatinib for Repurposing in Neuroblastoma Therapy.

Mol Cancer Ther. 2018 07;17(7):1405-1415

Authors: Sidarovich V, De Mariano M, Aveic S, Pancher M, Adami V, Gatto P, Pizzini S, Pasini L, Croce M, Parodi F, Cimmino F, Avitabile M, Emionite L, Cilli M, Ferrini S, Pagano A, Capasso M, Quattrone A, Tonini GP, Longo L

Abstract
Novel druggable targets have been discovered in neuroblastoma (NB), paving the way for more effective treatments. However, children with high-risk NB still show high mortality rates prompting for a search of novel therapeutic options. Here, we aimed at repurposing FDA-approved drugs for NB treatment by performing a high-content screening of a 349 anticancer compounds library. In the primary screening, we employed three NB cell lines, grown as three-dimensional (3D) multicellular spheroids, which were treated with 10 μmol/L of the library compounds for 72 hours. The viability of 3D spheroids was evaluated using a high-content imaging approach, resulting in a primary hit list of 193 compounds. We selected 60 FDA-approved molecules and prioritized drugs with multi-target activity, discarding those already in use for NB treatment or enrolled in NB clinical trials. Hence, 20 drugs were further tested for their efficacy in inhibiting NB cell viability, both in two-dimensional and 3D models. Dose-response curves were then supplemented with the data on side effects, therapeutic index, and molecular targets, suggesting two multiple tyrosine kinase inhibitors, ponatinib and axitinib, as promising candidates for repositioning in NB. Indeed, both drugs showed induction of cell-cycle block and apoptosis, as well as inhibition of colony formation. However, only ponatinib consistently affected migration and inhibited invasion of NB cells. Finally, ponatinib also proved effective inhibition of tumor growth in orthotopic NB mice, providing the rationale for its repurposing in NB therapy. Mol Cancer Ther; 17(7); 1405-15. ©2018 AACR.

PMID: 29695637 [PubMed - indexed for MEDLINE]

Predicting drug activity against cancer cells by random forest models based on minimal genomic information and chemical properties.

PLoS One. 2019;14(7):e0219774

Authors: Lind AP, Anderson PC

Abstract
A key goal of precision medicine is predicting the best drug therapy for a specific patient from genomic information. In oncology, cancers that appear similar pathologically can vary greatly in how they respond to the same drug. Fortunately, data from high-throughput screening programs often reveal important relationships between genomic variability of cancer cells and their response to drugs. Nevertheless, many current computational methods to predict compound activity against cancer cells require large quantities of genomic, epigenomic, and additional cellular data to develop and to apply. Here we integrate recent screening data and machine learning to train classification models that predict the activity/inactivity of compounds against cancer cells based on the mutational status of only 145 oncogenes and a set of compound structural descriptors. Using IC50 values of 1 μM as activity cutoffs, our predictive models have sensitivities of 87%, specificities of 87%, and yield an area under the receiver operating characteristic curve equal to 0.94. We also develop regression models to predict log(IC50) values of compounds for cancer cells; the models achieve a Pearson correlation coefficient of 0.86 for cross-validation and up to 0.65-0.73 against blind test sets. Predictive performance remains strong when as few as 50 oncogenes are included. Finally, even when 40% of experimental IC50 values are missing from screening data, they can be imputed with sufficient reliability that classification accuracy is not diminished. The presented models are fast to generate and may serve as easily implemented screening tools for personalized oncology medicine, drug repurposing, and drug discovery.

PMID: 31295321 [PubMed - in process]

Concepts of Artificial Intelligence for Computer-Assisted Drug Discovery.

Chem Rev. 2019 Jul 11;:

Authors: Yang X, Wang Y, Byrne R, Schneider G, Yang S

Abstract
Artificial intelligence (AI), and, in particular, deep learning as a subcategory of AI, provides opportunities for the discovery and development of innovative drugs. Various machine learning approaches have recently (re)emerged, some of which may be considered instances of domain-specific AI which have been successfully employed for drug discovery and design. This review provides a comprehensive portrayal of these machine learning techniques and of their applications in medicinal chemistry. After introducing the basic principles, alongside some application notes, of the various machine learning algorithms, the current state-of-the art of AI-assisted pharmaceutical discovery is discussed, including applications in structure- and ligand-based virtual screening, de novo drug design, physicochemical and pharmacokinetic property prediction, drug repurposing, and related aspects. Finally, several challenges and limitations of the current methods are summarized, with a view to potential future directions for AI-assisted drug discovery and design.

PMID: 31294972 [PubMed - as supplied by publisher]