Evidence map›Paper›PMID 32537481›Full record

ArticleExtreme Mechanics Letters2020

EML webinar overview: Simulation-assisted discovery of membrane targeting nanomedicine.

Guijin Zou, Yue Liu, Huajian Gao

Open access · hybridAbstract read
In one paragraph

Article in Extreme Mechanics Letters, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.8field-weighted citation impact, top 28% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 9 citations in OpenAlex.

  1. An Elastocaloric Polymer with Ultra-High Solid-State Cooling via Defect Engineering.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 2 countries.

Guijin ZouInstitute of High Performance Computing, ASTAR, Singapore 138632, Singapore.
Yue LiuSchool of Engineering, Brown University, Providence, RI 02912, USA.
Huajian GaoInstitute of High Performance Computing, ASTAR, Singapore 138632, Singapore.
Agency for Science, Technology and Research · SGBrown University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

AntibioticsAntiviral agentsBacterial persisterCholesterol-based selectivityCoronavirusDrug discoveryMembrane selectivityMembrane targetingModelling and simulationSize-based selectivity

Identifiers

PMID32537481
PMCPMC7278653
OpenAlexW3033132944

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.