Antimicrobial resistance (AMR) represents a major threat to global public health in the 21st century, dramatically increasing the pandemic expectations in the coming years. The ongoing need to develop new antimicrobial treatments that are effective against multi-drug-resistant pathogens has led the research community to investigate innovative strategies to tackle AMR. The bacterial cell envelope has been identified as one of the key molecular players responsible for antibiotic resistance, attracting considerable interest as a potential target for novel antimicrobials effective against AMR, to be used alone or in combination with other drugs. However, the multicomponent complexity of bacterial membranes provides a heterogeneous morphology, which is typically difficult to study at the molecular level by experimental techniques, in spite of the significant development of fast and efficient experimental protocols. In recent years, computational modeling, in particular, molecular dynamics simulations, has proven to be an effective tool to reveal key aspects in the architecture and membrane organization of bacterial cell walls. Here, after a general overview about bacterial membranes, AMR mechanisms, and experimental approaches to study AMR, we review the state-of-the-art computational approaches to investigate bacterial AMR envelopes, including their limitations and challenges ahead. Representative examples illustrate how these techniques improve our understanding of bacterial membrane resistance mechanisms, hopefully leading to the development of novel antimicrobial drugs escaping from bacterial resistance strategies.

Understanding the Antibacterial Resistance: Computational Explorations in Bacterial Membranes / Matamoros-Recio, A.; Franco-Gonzalez, J. F.; Forgione, R. E.; Torres-Mozas, A.; Silipo, A.; Martin-Santamaria, S.. - In: ACS OMEGA. - ISSN 2470-1343. - 6:9(2021), pp. 6041-6054. [10.1021/acsomega.0c05590]

Understanding the Antibacterial Resistance: Computational Explorations in Bacterial Membranes

Forgione R. E.;Silipo A.;
2021

Abstract

Antimicrobial resistance (AMR) represents a major threat to global public health in the 21st century, dramatically increasing the pandemic expectations in the coming years. The ongoing need to develop new antimicrobial treatments that are effective against multi-drug-resistant pathogens has led the research community to investigate innovative strategies to tackle AMR. The bacterial cell envelope has been identified as one of the key molecular players responsible for antibiotic resistance, attracting considerable interest as a potential target for novel antimicrobials effective against AMR, to be used alone or in combination with other drugs. However, the multicomponent complexity of bacterial membranes provides a heterogeneous morphology, which is typically difficult to study at the molecular level by experimental techniques, in spite of the significant development of fast and efficient experimental protocols. In recent years, computational modeling, in particular, molecular dynamics simulations, has proven to be an effective tool to reveal key aspects in the architecture and membrane organization of bacterial cell walls. Here, after a general overview about bacterial membranes, AMR mechanisms, and experimental approaches to study AMR, we review the state-of-the-art computational approaches to investigate bacterial AMR envelopes, including their limitations and challenges ahead. Representative examples illustrate how these techniques improve our understanding of bacterial membrane resistance mechanisms, hopefully leading to the development of novel antimicrobial drugs escaping from bacterial resistance strategies.
2021
Understanding the Antibacterial Resistance: Computational Explorations in Bacterial Membranes / Matamoros-Recio, A.; Franco-Gonzalez, J. F.; Forgione, R. E.; Torres-Mozas, A.; Silipo, A.; Martin-Santamaria, S.. - In: ACS OMEGA. - ISSN 2470-1343. - 6:9(2021), pp. 6041-6054. [10.1021/acsomega.0c05590]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/880162
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