Prediction of Drug-Target Interactions and Drug Repositioning via Network-Based Inference

Drug-target interaction (DTI) is the basis of drug discovery and design. It is time consuming and costly to determine DTI experimentally. Hence, it is necessary to develop computational methods for the prediction of potential DTI. Based on complex network theory, three supervised inference methods were developed here to predict DTI and used for drug repositioning, namely drug-based similarity inference (DBSI), target-based similarity inference (TBSI) and network-based inference (NBI). Among them, NBI performed best on four benchmark data sets. Then a drug-target network was created with NBI based on 12,483 FDA-approved and experimental drug-target binary links, and some new DTIs were further predicted. In vitro assays confirmed that five old drugs, namely montelukast, diclofenac, simvastatin, ketoconazole, and itraconazole, showed polypharmacological features on estrogen receptors or dipeptidyl peptidase-IV with half maximal inhibitory or effective concentration ranged from 0.2 to 10 µM. Moreover, simvastatin and ketoconazole showed potent antiproliferative activities on human MDA-MB-231 breast cancer cell line in MTT assays. The results indicated that these methods could be powerful tools in prediction of DTIs and drug repositioning

Lactic acid bacteria diversity in corn silage produced in Minas Gerais (Brazil)

Purpose The diversity of lactic acid bacteria (LAB) in silages produced in warm climate countries is not well known. This study aimed to identify and characterise the metabolic and genotypic aspects of autochthonous LAB isolated from corn silage produced in the state of Minas Gerais, Brazil. Methods Eighty-eight LAB were isolated. To evaluate their performance at the strain level, all isolates were distinguished among strains using random amplified polymorphic DNA polymerase chain reaction (RAPD-PCR) and repetitive extragenic palindromic PCR (REP-PCR) techniques. The organic acid and ethanol production were determined by high-performance liquid chromatography (HPLC). Result The fingerprints obtained by RAPD-PCR with a M13 primer were more discriminatory than those obtained with the REP-PCR technique using a (GACA)4 primer. Moreover, 28 representative isolates were identified as Lactobacillus acidophilus, L. buchneri, L. casei, L. diolivorans, L. hilgardii, L. paracasei, L. parafarraginis, L. plantarum, L. rhamnosus, L. zeae and Pediococcus acidilactici. Different fingerprinting profiles between isolates within the same species were observed. However, some strains isolated from different silages showed the same band profile, thus suggesting the presence of clusters with high similar fingerprints in silages from various regions. Conclusion A variation in LAB diversity was observed in the silages of the evaluated regions, with L. rhamnosus and L. buchneri showing the highest distribution. Differences in organic acid production were observed among the strains belonging to the same species. This research contributes to a better understanding of the LAB community present in corn silage produced in warm climates. These strains will be studied as potential silage starters.The study was financially supported by the Brazilian agencies CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico), FAPEMIG (Fundação de Amparo a Pesquisa do Estado de Minas Gerais) and CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior). At the University of Minho the study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of the UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER-006684), and the BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte 2020—Programa Operacional Regional do Norte.info:eu-repo/semantics/publishedVersio