Predicting Membrane-Active Peptide Dynamics in Fluidic Lipid Membranes

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

doi:10.1007/978-1-0716-1855-4_6

Predicting Membrane-Active Peptide Dynamics in Fluidic Lipid Membranes

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

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

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.

Original language	English
Title of host publication	Methods in Molecular Biology
Publisher	Humana Press Inc
Pages	115-136
Number of pages	22
DOIs	https://doi.org/10.1007/978-1-0716-1855-4_6
Publication status	Published - 2022

Publication series

Name	Methods in Molecular Biology
Volume	2405
ISSN (Print)	1064-3745
ISSN (Electronic)	1940-6029

Keywords

Membrane-active peptides
Molecular dynamics simulations
Pore formation
Protein design
Protein folding

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/978-1-0716-1855-4_6

Cite this

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title = "Predicting Membrane-Active Peptide Dynamics in Fluidic Lipid Membranes",

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.",

keywords = "Membrane-active peptides, Molecular dynamics simulations, Pore formation, Protein design, Protein folding",

author = "Chen, {Charles H.} and Karen Pepper and Ulmschneider, {Jakob P.} and Ulmschneider, {Martin B.} and Lu, {Timothy K.}",

note = "Funding Information: This work was supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health (NIH) under Award Number U19AI142780. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. The authors thank Kalina Hristova at Johns Hopkins University, William Wimley at Tulane University, Alexey Ladokhin at University of Kansas Medical Center, Jochen B{\"u}rck at Karlsruhe Institute of Technology, Nykola Jones at Aarhus University, Katherine Tripp at Johns Hopkins University, Gregory Wiedman at Seton Hall University, Sarah Kim at Duke University, Evan Troendle at King{\textquoteright}s College London, and Yukun Wang at Yale University for valuable discussions about the experimental setups and simulations. Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.",

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AU - Lu, Timothy K.

N1 - Funding Information: This work was supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health (NIH) under Award Number U19AI142780. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. The authors thank Kalina Hristova at Johns Hopkins University, William Wimley at Tulane University, Alexey Ladokhin at University of Kansas Medical Center, Jochen Bürck at Karlsruhe Institute of Technology, Nykola Jones at Aarhus University, Katherine Tripp at Johns Hopkins University, Gregory Wiedman at Seton Hall University, Sarah Kim at Duke University, Evan Troendle at King’s College London, and Yukun Wang at Yale University for valuable discussions about the experimental setups and simulations. Publisher Copyright: © 2022, The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

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N2 - 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.

AB - 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.

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ER -

Predicting Membrane-Active Peptide Dynamics in Fluidic Lipid Membranes

Abstract

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Keywords

UN SDGs

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