info:eu-repo/semantics/article
From Genome to Drugs: New Approaches in Antimicrobial Discovery
Fecha
2021-06Registro en:
Serral, Federico; Castello, Florencia Andrea; Sosa, Ezequiel; Pardo, Agustin Maria; Palumbo, Miranda Clara; et al.; From Genome to Drugs: New Approaches in Antimicrobial Discovery; Frontiers Media; Frontiers in Pharmacology; 12; 6-2021; 1-15
1663-9812
CONICET Digital
CONICET
Autor
Serral, Federico
Castello, Florencia Andrea
Sosa, Ezequiel
Pardo, Agustin Maria
Palumbo, Miranda Clara
Modenutti, Carlos Pablo
Palomino, Maria Mercedes
Lazarowski, Alberto Jorge
Auzmendi, Jerónimo Andrés
Ramos, Pablo Ivan P.
Nicolás, Marisa F.
Turjanski, Adrian
Marti, Marcelo Adrian
Fernández Do Porto, Darío Augusto
Resumen
Decades of successful use of antibiotics is currently challenged by the emergence of increasingly resistant bacterial strains. Novel drugs are urgently required but, in a scenario where private investment in the development of new antimicrobials is declining, efforts to combat drug-resistant infections become a worldwide public health problem. Reasons behind unsuccessful new antimicrobial development projects range from inadequate selection of the molecular targets to a lack of innovation. In this context, increasingly available omics data for multiple pathogens has created new drug discovery and development opportunities to fight infectious diseases. Identification of an appropriate molecular target is currently accepted as a critical step of the drug discovery process. Here, we review how diverse layers of multi-omics data in conjunction with structural/ functional analysis and systems biology can be used to prioritize the best candidate proteins. Once the target is selected, virtual screening can be used as a robust methodology to explore molecular scaffolds that could act as inhibitors, guiding the development of new drug lead compounds. This review focuses on how the advent of omics and the development and application of bioinformatics strategies conduct a “bigdata era” that improves target selection and lead compound identification in a costeffective and shortened timeline.