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EML webinar overview: Simulation-assisted discovery of membrane targeting nanomedicine
The COVID-19 pandemic has brought infectious diseases again to the forefront of global public health concerns. In this EML webinar (Gao, 2020), we discuss some recent work on simulation-assisted discovery of membrane targeting nanomedicine to counter increasing antimicrobial resistance and potential...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7278653/ https://www.ncbi.nlm.nih.gov/pubmed/32537481 http://dx.doi.org/10.1016/j.eml.2020.100817 |
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author | Zou, Guijin Liu, Yue Gao, Huajian |
author_facet | Zou, Guijin Liu, Yue Gao, Huajian |
author_sort | Zou, Guijin |
collection | PubMed |
description | The COVID-19 pandemic has brought infectious diseases again to the forefront of global public health concerns. In this EML webinar (Gao, 2020), we discuss some recent work on simulation-assisted discovery of membrane targeting nanomedicine to counter increasing antimicrobial resistance and potential application of similar ideas to the current pandemic. A recent report led by the world health organization (WHO) warned that 10 million people worldwide could die of bacterial infections each year by 2050. To avert the crisis, membrane targeting antibiotics are drawing increasing attention due to their intrinsic advantage of low resistance development. In collaboration with a number of experimental groups, we show examples of simulation-assisted discovery of molecular agents capable of selectively penetrating and aggregating in bacterial lipid membranes, causing membrane permeability/rupture. Through systematic all-atom molecular dynamics simulations and free energy analysis, we demonstrate that the membrane activity of the molecular agents correlates with their ability to enter, perturb and permeabilize the lipid bilayers. Further study on different cell membranes demonstrates that the selectivity results from the presence of cholesterol in mammalian but not in bacterial membranes, as the cholesterol can condense the hydrophobic region of membrane, preventing the penetration of the molecular agents. Following the molecular penetration, we establish a continuum theory and derive the energetic driving force for the domain aggregation and pore growth on lipid membrane. We show that the energy barrier to membrane pore formation can be significantly lowered through molecular aggregation on a large domain with intrinsic curvature and a sharp interface. The theory is consistent with experimental observations and validated with coarse-grained molecular dynamics simulations of molecular domain aggregation leading to pore formation in a lipid membrane. The mechanistic modelling and simulation provide some fundamental principles on how molecular antimicrobials interact with bacterial membranes and damage them through domain aggregation and pore formation. For treating viral infections and cancer therapy, we discuss potential size- and lipid-type-based selectivity principles for developing membrane active nanomedicine. These studies suggest a general simulation-assisted platform to accelerate discovery and innovation in nanomedicine against infectious diseases. EML Webinar speakers are updated at https://imechanica.org/node/24132 |
format | Online Article Text |
id | pubmed-7278653 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-72786532020-06-09 EML webinar overview: Simulation-assisted discovery of membrane targeting nanomedicine Zou, Guijin Liu, Yue Gao, Huajian Extreme Mech Lett Article The COVID-19 pandemic has brought infectious diseases again to the forefront of global public health concerns. In this EML webinar (Gao, 2020), we discuss some recent work on simulation-assisted discovery of membrane targeting nanomedicine to counter increasing antimicrobial resistance and potential application of similar ideas to the current pandemic. A recent report led by the world health organization (WHO) warned that 10 million people worldwide could die of bacterial infections each year by 2050. To avert the crisis, membrane targeting antibiotics are drawing increasing attention due to their intrinsic advantage of low resistance development. In collaboration with a number of experimental groups, we show examples of simulation-assisted discovery of molecular agents capable of selectively penetrating and aggregating in bacterial lipid membranes, causing membrane permeability/rupture. Through systematic all-atom molecular dynamics simulations and free energy analysis, we demonstrate that the membrane activity of the molecular agents correlates with their ability to enter, perturb and permeabilize the lipid bilayers. Further study on different cell membranes demonstrates that the selectivity results from the presence of cholesterol in mammalian but not in bacterial membranes, as the cholesterol can condense the hydrophobic region of membrane, preventing the penetration of the molecular agents. Following the molecular penetration, we establish a continuum theory and derive the energetic driving force for the domain aggregation and pore growth on lipid membrane. We show that the energy barrier to membrane pore formation can be significantly lowered through molecular aggregation on a large domain with intrinsic curvature and a sharp interface. The theory is consistent with experimental observations and validated with coarse-grained molecular dynamics simulations of molecular domain aggregation leading to pore formation in a lipid membrane. The mechanistic modelling and simulation provide some fundamental principles on how molecular antimicrobials interact with bacterial membranes and damage them through domain aggregation and pore formation. For treating viral infections and cancer therapy, we discuss potential size- and lipid-type-based selectivity principles for developing membrane active nanomedicine. These studies suggest a general simulation-assisted platform to accelerate discovery and innovation in nanomedicine against infectious diseases. EML Webinar speakers are updated at https://imechanica.org/node/24132 Elsevier Ltd. 2020-09 2020-06-08 /pmc/articles/PMC7278653/ /pubmed/32537481 http://dx.doi.org/10.1016/j.eml.2020.100817 Text en © 2020 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Zou, Guijin Liu, Yue Gao, Huajian EML webinar overview: Simulation-assisted discovery of membrane targeting nanomedicine |
title | EML webinar overview: Simulation-assisted discovery of membrane targeting nanomedicine |
title_full | EML webinar overview: Simulation-assisted discovery of membrane targeting nanomedicine |
title_fullStr | EML webinar overview: Simulation-assisted discovery of membrane targeting nanomedicine |
title_full_unstemmed | EML webinar overview: Simulation-assisted discovery of membrane targeting nanomedicine |
title_short | EML webinar overview: Simulation-assisted discovery of membrane targeting nanomedicine |
title_sort | eml webinar overview: simulation-assisted discovery of membrane targeting nanomedicine |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7278653/ https://www.ncbi.nlm.nih.gov/pubmed/32537481 http://dx.doi.org/10.1016/j.eml.2020.100817 |
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