Evidence map›Paper›PMID 35298811›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2022

Predicting Membrane-Active Peptide Dynamics in Fluidic Lipid Membranes.

Charles H Chen, Karen Pepper, Jakob P Ulmschneider, Martin B Ulmschneider, Timothy K Lu

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 94% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

5 authors at 3 institutions in 3 countries.

Charles H ChenSynthetic Biology Group, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA. chenchar@mit.edu.
Karen PepperSynthetic Biology Group, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA.
Jakob P UlmschneiderDepartment of Physics, Institute of Natural Sciences, Shanghai Jiao Tong University, Shanghai, China.
Martin B UlmschneiderDepartment of Chemistry, King's College London, London, UK.
Timothy K LuSynthetic Biology Group, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA.
Massachusetts Institute of Technology · USKing's College London · GBShanghai Jiao Tong University · CN

Funding

Innovative technologies to transform antibiotic discovery. Project 4 Infection site-specific amplification of antimicrobial conjugatesU19AI142780 · NIAID · BROAD INSTITUTE, INC. · PI HUNG, DEBORAH T · 2019 to 2023
$33.9M
NIAID NIH HHS U19 AI142780
6 · The paper itself

Abstract

Understanding the interactions between peptides and lipid membranes could not only accelerate the development of antimicrobial peptides as treatments for infections but also be applied to finding targeted therapies for cancer and other diseases. However, designing biophysical experiments to study molecular interactions between flexible peptides and fluidic lipid membranes has been an ongoing challenge. Recently, with hardware advances, algorithm improvements, and more accurate parameterizations (i.e., force fields), all-atom molecular dynamics (MD) simulations have been used as a "computational microscope" to investigate the molecular interactions and mechanisms of membrane-active peptides in cell membranes (Chen et al., Curr Opin Struct Biol 61:160-166, 2020; Ulmschneider and Ulmschneider, Acc Chem Res 51(5):1106-1116, 2018; Dror et al., Annu Rev Biophys 41:429-452, 2012). In this chapter, we describe how to utilize MD simulations to predict and study peptide dynamics and how to validate the simulations by circular dichroism, intrinsic fluorescent probe, membrane leakage assay, electrical impedance, and isothermal titration calorimetry. Experimentally validated MD simulations open a new route towards peptide design starting from sequence and structure and leading to desirable functions.

Indexed as

Molecular Dynamics SimulationPeptidesCell MembraneLipidsMembranesLipidsPeptidesMembrane-active peptidesMolecular dynamics simulationsPore formationProtein designProtein folding

Identifiers

PMID35298811
OpenAlexW4220687380

What OpenQuestion holds

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Registered trials

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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.