Abstract: Increases in cancer diagnosis have tremendous negative impacts on patients and their families, and major societal and economic costs. The beneficial effect of chemotherapeutic agents on tumor suppression comes with major unwanted side effects such as weight and hair loss, nausea and vomiting, and neuropathic pain. Chemotherapy-induced peripheral neuropathy (CIPN), which can include both painful and non-painful symptoms, can persist 6 months or longer after the patient's last chemotherapeutic treatment. These peripheral sensory and motor deficits are poorly treated by our current analgesics with limited effectiveness. Therefore, the development of novel treatment strategies is an important preclinical research focus and an urgent need for patients. Approaches to prevent CIPN have yielded disappointing results since these compounds may interfere with the anti-tumor properties of chemotherapeutic agents. Nevertheless, the first (serotonin noradrenaline reuptake inhibitors [SNRIs], anticonvulsants, tricyclic antidepressants) and second (5% lidocaine patches, 8% capsaicin patches and weak opioids such as tramadol) lines of treatment for CIPN have shown some efficacy. The clinical challenge of CIPN management in cancer patients and the need to target novel therapies with long-term efficacy in alleviating CIPN are an ongoing focus of research. The endogenous cannabinoid system has shown great promise and efficacy in alleviating CIPN in preclinical and clinical studies. In this review, we will discuss the mechanisms through which the platinum, taxane, and vinca alkaloid classes of chemotherapeutics may produce CIPN and the potential therapeutic effect of drugs targeting the endocannabinoid system in preclinical and clinical studies, in addition to cannabinoid compounds diffuse mechanisms of action in alleviation of CIPN.

Abstract: Gastrointestinal side effects are among the most common classes of adverse reactions associated with orally absorbed drugs. These effects decrease patient compliance with the treatment and induce undesirable physiological effects. The prediction of drug action on the gut wall based on in vitro data solely can improve the safety of marketed drugs and first-in-human trials of new chemical entities. We used publicly available data of drug-induced gene expression changes to build drug-specific small intestine epithelial cell metabolic models. The combination of measured in vitro gene expression and in silico predicted metabolic rates in the gut wall was used as features for a multilabel support vector machine to predict the occurrence of side effects. We showed that combining local gut wall-specific metabolism with gene expression performs better than gene expression alone, which indicates the role of small intestine metabolism in the development of adverse reactions. Furthermore, we reclassified FDA-labeled drugs with respect to their genetic and metabolic profiles to show hidden similarities between seemingly different drugs. The linkage of xenobiotics to their transcriptomic and metabolic profiles could take pharmacology far beyond the usual indication-based classifications.

Abstract: The aim of the present study was to identify genes under the effect of transforming growth factor-beta (TGF-beta1), high glucose (HG) and glucosamine (GlcN) in MES-13 mesangial cells and elucidate the molecular mechanisms of diabetic nephropathy (DN). The gene expression datasets GSE2557 and GSE2558 were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were independently screened using the GEO2R online tool. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the Database for Annotation, Visualization, and Integrated Discovery. The protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes and Cytoscape software. The hub genes were identified by the NetworkAnalyzer plugin. Overlapping genes were subjected to molecular docking analysis using SystemsDock. A total of 202 upregulated and 158 downregulated DEGs from the HG-treated groups, 138 upregulated and 103 downregulated DEGs from the GlcN-treated groups, and 81 upregulated and 44 downregulated DEGs from the TGF-beta1-treated groups were identified. The majority of the DEGs were independently enriched in 'nucleosome assembly', 'chromatin silencing' and 'xenobiotic glucuronidation'. In addition, KEGG pathways were significantly enriched in 'systemic lupus erythematosus', 'protein processing in endoplasmic reticulum' and 'aldarate metabolism pathway', and 'TNF signaling pathway' intersected in the TGF-beta1-treated and HG-treated groups. In total, eight hub genes, Jun, prostaglandin-endoperoxide synthase 2 (Ptgs2), fibronectin 1 (Fn1), cyclin-dependent kinase (Cdk)2, Fos, heat shock protein family A (Hsp70) member 5 (Hspa5), Hsp90b1 and homo sapiens hypoxia upregulated 1 (Hyou1), and three overlapping genes, Ras homolog gene family, member B (RHOB), complement factor H (CFH) and Kruppel-like factor 15 (KLF15), were selected. Valsartan with RHOB, and fosinopril with CFH and KLF15 had preferential binding activity. In conclusion, Jun, Ptgs2, Fn1, Cdk2, Fos, Hspa5, Hsp90b1, Hyou1, RHOB, CFH and KLF15 may be potential therapeutic targets for mesangial cells associated with DN, which may provide insight into DN treatment strategies.

Abstract: MOTIVATION: The existing connections between large databases of chemicals, proteins, metabolites and assays offer valuable resources for research in fields ranging from drug design to metabolomics. Transparent search across multiple databases provides a way to efficiently utilize these resources. To simplify such searches, many databases have adopted semantic technologies that allow interoperable querying of the datasets using SPARQL query language. However, the interoperable interfaces of the chemical databases still lack the functionality of structure-driven chemical search, which is a fundamental method of data discovery in the chemical search space. RESULTS: We present a SPARQL service that augments existing semantic services by making interoperable substructure and similarity searches in small-molecule databases possible. The service thus offers new possibilities for querying interoperable databases, and simplifies writing of heterogeneous queries that include chemical-structure search terms. AVAILABILITY: The service is freely available and accessible using a standard SPARQL endpoint interface. The service documentation and user-oriented demonstration interfaces that allow quick explorative querying of datasets are available at https://idsm.elixir-czech.cz .

Abstract: INTRODUCTION: Soil-transmitted helminths infect billions of people, livestock and companion animals worldwide, and chronic infections with these nematodes represent a major health burden in many developing countries. On the other hand, complete elimination of parasitic helminths and other infectious pathogens has been implicated with rising rates of autoimmune and allergic disorders in developed countries. Given the enormous health impact of these parasites, it is surprising how little is known about the non-protein small metabolites of the excretory-secretory products (ESP), including their composition and pharmacological properties. OBJECTIVES: We sought proof-of-concept that Nippostrongylus brasiliensis and Trichuris muris, rodent models of two of the most important human soil-transmitted helminths, secrete small metabolites and that some of these metabolites may have specific pharmacological functions. METHODS: N. brasiliensis and T. muris ESP were collected from adult worms and filtered using a 10 kDa cut-off membrane to produce excretory-secretory metabolites (ESM). The ESM were analysed using targeted gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry for polar and non-polar small metabolites. RESULTS: ESM from both N. brasiliensis and T. muris contained small molecules. A total of 54 small molecules (38 polar metabolites and 16 fatty acids) were identified, 36 known polar metabolites from N. brasiliensis and 35 from T. muris. A literature review of the identified compounds revealed that 17 of them have various demonstrated pharmacological activities. CONCLUSION: N. brasiliensis and T. muris secrete polar and non-polar small molecules with as many as 17 metabolites known to exhibit various pharmacological activities.

Abstract: Several machine learning approaches have been proposed for predicting new benefits of the existing drugs. Although these methods have introduced new usage(s) of some medications, efficient methods can lead to more accurate predictions. To this end, we proposed a novel machine learning method which is based on a new optimization algorithm, named Trader. To show the capabilities of the proposed algorithm which can be applied to the different scope of science, it was compared with ten other state-of-the-art optimization algorithms based on the standard and advanced benchmark functions. Next, a multi-layer artificial neural network was designed and trained by Trader to predict drug-target interactions (DTIs). Finally, the functionality of the proposed method was investigated on some DTIs datasets and compared with other methods. The data obtained by Trader showed that it eliminates the disadvantages of different optimization algorithms, resulting in a better outcome. Further, the proposed machine learning method was found to achieve a significant level of performance compared to the other popular and efficient approaches in predicting unknown DTIs. All the implemented source codes are freely available at https://github.com/LBBSoft/Trader .

Abstract: Multitarget pharmacology of small-molecule cancer drugs significantly contributes to their mechanism of action, side effects, and emergence of drug resistance and opens ways to repurpose, combine, or customize drug therapy. In most cases, the set of targets affected at therapeutic concentrations is not fully characterized and/or the interaction efficacy values are not accurately quantified. We collected information about multiple targets for each cancer drug along with their experimental effective concentrations or binding activities from multiple sources. All multitarget activity values for each drug then were used to build two proximity network pharmacology maps of anticancer drugs and targets of those drugs, respectively. Together with the network map, we showed that the majority of the cancer drugs had substantial multitarget pharmacology based on our current knowledge. In addition, most of the cancer drugs simultaneously affect macromolecular targets from different classes and types. The target subset can further be accentuated and personalized by patient sample-specific expression data. The network maps of cancer drugs and targets as well as all quantified activity data were integrated into a freely available database, CancerDrugMap (http://ruben.ucsd.edu/dnet/maps/drugnet.html). The identified multitarget pharmacology of cancer drugs is essential for improving the efficacy of individually prescribed drugs and drug combinations and minimization of adverse effects.

Abstract: Targeting chokepoint enzymes in metabolic pathways has led to new drugs for cancers, autoimmune disorders and infectious diseases. This is also a cornerstone approach for discovery and development of anthelmintics against nematode and flatworm parasites. Here, we performed omics-driven knowledge-based identification of chokepoint enzymes as anthelmintic targets. We prioritized 10 of 186 phylogenetically conserved chokepoint enzymes and undertook a target class repurposing approach to test and identify new small molecules with broad spectrum anthelmintic activity. First, we identified and tested 94 commercially available compounds using an in vitro phenotypic assay, and discovered 11 hits that inhibited nematode motility. Based on these findings, we performed chemogenomic screening and tested 32 additional compounds, identifying 6 more active hits. Overall, 6 intestinal (single-species), 5 potential pan-intestinal (whipworm and hookworm) and 6 pan-Phylum Nematoda (intestinal and filarial species) small molecule inhibitors were identified, including multiple azoles, Tadalafil and Torin-1. The active hit compounds targeted three different target classes in humans, which are involved in various pathways, including carbohydrate, amino acid and nucleotide metabolism. Last, using representative inhibitors from each target class, we demonstrated in vivo efficacy characterized by negative effects on parasite fecundity in hamsters infected with hookworms.

Abstract: Buruli ulcer is a neglected tropical disease caused by the bacterium Mycobacterium ulcerans. Its virulence is attributed to the dermo-necrotic polyketide toxin mycolactone, whose synthesis is regressed when its iron acquisition system regulated by the iron-dependent regulator (ideR) is deactivated. Interfering with the activation mechanism of ideR to inhibit the toxin's synthesis could serve as a possible cure for Buruli ulcer. The three-dimensional structure of the ideR for Mycobacterium ulcerans was generated using homology modeling. A library of 832 African natural products (AfroDB), as well as five known anti-mycobacterial compounds were docked against the metal binding site of the ideR. The area under the curve (AUC) values greater than 0.7 were obtained for the computed Receiver Operating Characteristics (ROC) curves, validating the docking protocol. The identified top hits were pharmacologically profiled using Absorption, Distribution, Metabolism, Elimination and Toxicity (ADMET) predictions and their binding mechanisms were characterized. Four compounds with ZINC IDs ZINC000018185774, ZINC000095485921, ZINC000014417338 and ZINC000005357841 emerged as leads with binding energies of -7.7 kcal/mol, -7.6 kcal/mol, -8.0 kcal/mol and -7.4 kcal/mol, respectively. Induced Fit Docking (IFD) was also performed to account for the protein's flexibility upon ligand binding and to estimate the best plausible conformation of the complexes. Results obtained from the IFD were consistent with that of the molecular docking with the lead compounds forming interactions with known essential residues and some novel critical residues Thr14, Arg33 and Asp17. A hundred nanoseconds molecular dynamic simulations of the unbound ideR and its complexes with the respective lead compounds revealed changes in the ideR's conformations induced by ZINC000018185774. Comparison of the lead compounds to reported potent inhibitors by docking them against the DNA-binding domain of the protein also showed the lead compounds to have very close binding affinities to those of the potent inhibitors. Interestingly, structurally similar compounds to ZINC000018185774 and ZINC000014417338, as well as analogues of ZINC000095485921, including quercetin are reported to possess anti-mycobacterial activity. Also, ZINC000005357841 was predicted to possess anti-inflammatory and anti-oxidative activities, which are relevant in Buruli ulcer and iron acquisition mechanisms, respectively. The leads are molecular templates which may serve as essential scaffolds for the design of future anti-mycobacterium ulcerans agents.

Abstract: BACKGROUND: Drug repurposing is a swift, safe, and cheap drug discovery method. Melanoma disorders present low survival and high mortality rates and are challenging to diagnose and treat. Moreover, there is a high volume of worldwide investigations that are attempting to find melanoma-related genes of influence, which can be identified as responsive targets for reliable treatment. METHOD: In this study, we used a wide range of data analyses to analyze over 1100 genes and proteins of influence with respect to cutaneous malignant melanoma. Our analysis included various investigational results from genome- and phenome-wide association studies (GWAS and PheWAS, respectively), biomedical, transcriptomic, and metabolomic datasets. We then researched the DrugBank for potential melanoma targets from the selected list. We excluded known melanoma targets to obtain a list of druggable proteins. We performed a precise analysis of the drugs' pathogenesis and checked the expression profiles of the selected drugs having high associations with known anti-melanoma drugs. RESULT: We found 35 drugs that interacted with 20 unique targets. These drugs appear to have high melanoma treatment potentials. We confirmed our results with previous studies and found supporting references for 30 of these drugs. In conclusion, this investigation can be applied to various diseases for the efficient and economical repurposing of various drug compounds. For further validation, the results may be applicable for in vivo tests and clinical trials.