Author | Serral, Federico | |
Author | Castello, Florencia A. | |
Author | Sosa, Ezequiel J. | |
Author | Pardo, Agustín M. | |
Author | Palumbo, Miranda Clara | |
Author | Modenutti, Carlos | |
Author | Palomino, María Mercedes | |
Author | Lazarowski, Alberto | |
Author | Auzmendi, Jerónimo | |
Author | Ramos, Pablo Ivan P. | |
Author | Nicolás, Marisa F. | |
Author | Turjanski, Adrián G. | |
Author | Martí, Marcelo A. | |
Author | Porto, Darío Fernández do | |
Access date | 2021-08-17T11:03:26Z | |
Available date | 2021-08-17T11:03:26Z | |
Document date | 2021 | |
Citation | SERRAL, Federico et al. From Genome to Drugs: New Approaches in Antimicrobial Discovery. Frontiers in Pharmacology, 2021. | pt_BR |
ISSN | 1663-9812 | pt_BR |
URI | https://www.arca.fiocruz.br/handle/icict/48638 | |
Sponsorship | CNPq (process no. 306894/
2019-0) and granted by CAPES (process no. 88887.368759/ | pt_BR |
Language | eng | pt_BR |
Publisher | Frontiers Media | pt_BR |
Rights | open access | pt_BR |
Subject in Portuguese | Descoberta de drogas | pt_BR |
Subject in Portuguese | Antibacterianos | pt_BR |
Subject in Portuguese | Doenças transmissíveis | pt_BR |
Subject in Portuguese | Investimentos em Saúde | pt_BR |
Subject in Portuguese | Biologia computacional | pt_BR |
Title | From Genome to Drugs: New Approaches in Antimicrobial Discovery | pt_BR |
Type | Article | pt_BR |
Abstract | 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. | pt_BR |
Affilliation | Universidad de Buenos Aires. Instituto de Cálculo. Facultad de Ciencias Exactas y Naturales. Buenos Aires, Argentina. | pt_BR |
Affilliation | Universidad de Buenos Aires. Instituto de Cálculo. Facultad de Ciencias Exactas y Naturales. Buenos Aires, Argentina. | pt_BR |
Affilliation | Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica. Buenos Aires, Argentina / Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica. Buenos Aires, Argentina. | pt_BR |
Affilliation | Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica. Buenos Aires, Argentina. | pt_BR |
Affilliation | Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica. Buenos Aires, Argentina. | pt_BR |
Affilliation | Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica. Buenos Aires, Argentina / Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica. Buenos Aires, Argentina. | pt_BR |
Affilliation | Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica. Buenos Aires, Argentina / Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica. Buenos Aires, Argentina. | pt_BR |
Affilliation | Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Investigaciones en Fisiopatología y Bioquímica Clínica. Departamento de Bioquímica Clínica. Buenos Aires, Argentina. | pt_BR |
Affilliation | Consejo Nacional de Investigaciones Científicas y Técnicas. Buenos Aires, Argentina / Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Investigaciones en Fisiopatología y Bioquímica Clínica. Departamento de Bioquímica Clínica. Buenos Aires, Argentina. | pt_BR |
Affilliation | Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimento para Saúde. Salvador, BA, Brasil. | pt_BR |
Affilliation | Laboratório Nacional de Computação Científica. Petrópolis, Brasil. | pt_BR |
Affilliation | Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica. Buenos Aires, Argentina / Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica. Buenos Aires, Argentina. | pt_BR |
Affilliation | Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica. Buenos Aires, Argentina / Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica. Buenos Aires, Argentina. | pt_BR |
Affilliation | Universidad de Buenos Aires. Instituto de Cálculo. Facultad de Ciencias Exactas y Naturales. Buenos Aires, Argentina / Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica. Buenos Aires, Argentina. | pt_BR |
Subject | drug discovery, | pt_BR |
Subject | Drug target | pt_BR |
Subject | Metabolic reconstruction | pt_BR |
Subject | Structural modeling | pt_BR |
Subject | Target prioritization | pt_BR |
Subject | Virtual screening | pt_BR |
e-ISSN | 10.3389/fphar.2021.647060 | |