TY - GEN
T1 - Designing novel antimicrobial peptides against multi-drug resistant bacteria
AU - Bobde, Shravani
AU - Alsaab, Fahad
AU - Wang, Guangshun
AU - Van Hoek, Monique L.
N1 - Publisher Copyright:
© 2021 Owner/Author.
PY - 2021/1/18
Y1 - 2021/1/18
N2 - Antimicrobial peptides (AMPs) are ubiquitous amongst living organisms and are part of the innate immune system with the ability to kill pathogens directly or indirectly by modulating the immune system. AMPs have potential as a novel therapeutic against bacteria due to their quick-acting mechanism of action that prevents bacteria from developing resistance. Additionally, there is a dire need for therapeutics with activity specifically against gram-negative bacterial infections that are dangerous and difficult to treat. Development of new antibiotics has slowed in recent years and novel therapeutics like AMPs with a focus against gram-negative bacteria are needed. We designed 8 novel AMPs, termed PHNX peptides, using ab initio computational design (database filtering technology on APD3 dataset of natural AMPs against gram negative bacteria as described by Wang et al.) and assessed their theoretical function using published machine learning algorithms as well as measured their activity in our laboratory. These AMPs were tested and demonstrated greater activity against gramnegative MDR Escherichia coli than MRSA (Methicillin Resistant Staphylococcus aureus) bacteria and showed low hemolytic activity against human red-blood cells.
AB - Antimicrobial peptides (AMPs) are ubiquitous amongst living organisms and are part of the innate immune system with the ability to kill pathogens directly or indirectly by modulating the immune system. AMPs have potential as a novel therapeutic against bacteria due to their quick-acting mechanism of action that prevents bacteria from developing resistance. Additionally, there is a dire need for therapeutics with activity specifically against gram-negative bacterial infections that are dangerous and difficult to treat. Development of new antibiotics has slowed in recent years and novel therapeutics like AMPs with a focus against gram-negative bacteria are needed. We designed 8 novel AMPs, termed PHNX peptides, using ab initio computational design (database filtering technology on APD3 dataset of natural AMPs against gram negative bacteria as described by Wang et al.) and assessed their theoretical function using published machine learning algorithms as well as measured their activity in our laboratory. These AMPs were tested and demonstrated greater activity against gramnegative MDR Escherichia coli than MRSA (Methicillin Resistant Staphylococcus aureus) bacteria and showed low hemolytic activity against human red-blood cells.
KW - antimicrobial peptide
KW - database filtering technology
KW - gram-negative bacterium
KW - nucleic acid
UR - http://www.scopus.com/inward/record.url?scp=85112375703&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85112375703&partnerID=8YFLogxK
U2 - 10.1145/3459930.3469507
DO - 10.1145/3459930.3469507
M3 - Conference contribution
AN - SCOPUS:85112375703
T3 - Proceedings of the 12th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, BCB 2021
BT - Proceedings of the 12th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, BCB 2021
PB - Association for Computing Machinery, Inc
T2 - 12th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, BCB 2021
Y2 - 1 August 2021 through 4 August 2021
ER -