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1.
PLoS One ; 17(7): e0271002, 2022.
Article in English | MEDLINE | ID: mdl-35797386

ABSTRACT

Drug repurposing has been applied in the biomedical field to optimize the use of existing drugs, leading to a more efficient allocation of research resources. In oncology, this approach is particularly interesting, considering the high cost related to the discovery of new drugs with therapeutic potential. Computational methods have been applied to predict associations between drugs and their targets. However, drug repurposing has not always been promising and its efficiency has yet to be proven. Therefore, the present scoping review protocol was developed to screen the literature on how in silico strategies can be implemented in drug repurposing in oncology. The scoping review will be conducted according to the Arksey and O'Malley framework (2005) and the Joanna Briggs Institute recommendations. We will search the PubMed/MEDLINE, Embase, Scopus, and Web of Science databases, as well as the grey literature. We will include peer-reviewed research articles involving in silico strategies applied to drug repurposing in oncology, published between January 1, 2003, and December 31, 2021. Data will be charted and findings described according to review questions. We will report the scoping review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Review guidelines (PRISMA-ScR).


Subject(s)
Drug Repositioning , Peer Review , Delivery of Health Care , Research Design , Review Literature as Topic , Systematic Reviews as Topic
2.
Tuberculosis (Edinb) ; 97: 181-92, 2016 Mar.
Article in English | MEDLINE | ID: mdl-26791267

ABSTRACT

Current Tuberculosis treatment is long and expensive, faces the increasing burden of MDR/XDR strains and lack of effective treatment against latent form, resulting in an urgent need of new anti-TB drugs. Key to TB biology is its capacity to fight the host's RNOS mediated attack. RNOS are known to display a concentration dependent mycobactericidal activity, which leads to the following hypothesis "if we know which proteins are targeted by RNOS and kill TB, we we might be able to inhibit them with drugs resulting in a synergistic bactericidal effect". Based on this idea, we performed an Mtb metabolic network whole proteome analysis of potential RNOS sensitive and relevant targets which includes target druggability and essentiality criteria. Our results, available at http://tuberq.proteinq.com.ar yield new potential TB targets, like I3PS, while also providing and updated view of previous proposals becoming an important tool for researchers looking for new ways of killing TB.


Subject(s)
Antitubercular Agents/therapeutic use , Bacterial Proteins/genetics , Computational Biology , Drug Discovery/methods , Genome, Bacterial , Genome-Wide Association Study , Latent Tuberculosis/drug therapy , Mycobacterium tuberculosis/drug effects , Mycobacterium tuberculosis/genetics , Animals , Bacterial Proteins/metabolism , Databases, Genetic , Gene Expression Profiling , Host-Pathogen Interactions , Humans , Latent Tuberculosis/metabolism , Latent Tuberculosis/microbiology , Mice, Inbred C57BL , Microbial Viability , Molecular Targeted Therapy , Mycobacterium tuberculosis/metabolism , Mycobacterium tuberculosis/pathogenicity , Oligonucleotide Array Sequence Analysis , Protein Interaction Maps , Reactive Nitrogen Species/metabolism , Reactive Oxygen Species/metabolism , Signal Transduction
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