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dc.contributor.authorTorres, Marcelo DT
dc.contributor.authorCao, Jicong
dc.contributor.authorFranco, Octavio L
dc.contributor.authorLu, Timothy K
dc.contributor.authorde la Fuente-Nunez, Cesar
dc.date.accessioned2022-07-15T14:47:47Z
dc.date.available2022-07-15T14:47:47Z
dc.date.issued2021
dc.identifier.urihttps://hdl.handle.net/1721.1/143764
dc.description.abstract© 2021 American Chemical Society. Antibiotic resistance is one of the greatest challenges of our time. This global health problem originated from a paucity of truly effective antibiotic classes and an increased incidence of multi-drug-resistant bacterial isolates in hospitals worldwide. Indeed, it has been recently estimated that 10 million people will die annually from drug-resistant infections by the year 2050. Therefore, the need to develop out-of-the-box strategies to combat antibiotic resistance is urgent. The biological world has provided natural templates, called antimicrobial peptides (AMPs), which exhibit multiple intrinsic medical properties including the targeting of bacteria. AMPs can be used as scaffolds and, via engineering, can be reconfigured for optimized potency and targetability toward drug-resistant pathogens. Here, we review the recent development of tools for the discovery, design, and production of AMPs and propose that the future of peptide drug discovery will involve the convergence of computational and synthetic biology principles.en_US
dc.language.isoen
dc.publisherAmerican Chemical Society (ACS)en_US
dc.relation.isversionof10.1021/ACSNANO.0C09509en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcePMCen_US
dc.titleSynthetic Biology and Computer-Based Frameworks for Antimicrobial Peptide Discoveryen_US
dc.typeArticleen_US
dc.identifier.citationTorres, Marcelo DT, Cao, Jicong, Franco, Octavio L, Lu, Timothy K and de la Fuente-Nunez, Cesar. 2021. "Synthetic Biology and Computer-Based Frameworks for Antimicrobial Peptide Discovery." ACS Nano, 15 (2).
dc.contributor.departmentMassachusetts Institute of Technology. Synthetic Biology Center
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biological Engineering
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.contributor.departmentMassachusetts Institute of Technology. Research Laboratory of Electronics
dc.relation.journalACS Nanoen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2022-07-15T14:34:56Z
dspace.orderedauthorsTorres, MDT; Cao, J; Franco, OL; Lu, TK; de la Fuente-Nunez, Cen_US
dspace.date.submission2022-07-15T14:34:58Z
mit.journal.volume15en_US
mit.journal.issue2en_US
mit.licenseOPEN_ACCESS_POLICY
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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