Coarse-Grained Simulations for the Characterization and Optimization of Hybrid Protein-DNA Nanostructures

Raghu Pradeep Narayanan; Jonah Procyk; Purbasha Nandi; Abhay Prasad; Yang Xu; Erik Poppleton; Dewight Williams; Fei Zhang; Hao Yan; Po Lin Chiu; Nicholas Stephanopoulos; Petr Šulc

doi:10.1021/acsnano.2c04013

Coarse-Grained Simulations for the Characterization and Optimization of Hybrid Protein-DNA Nanostructures

Raghu Pradeep Narayanan, Jonah Procyk, Purbasha Nandi, Abhay Prasad, Yang Xu, Erik Poppleton, Dewight Williams, Fei Zhang, Hao Yan, Po Lin Chiu, Nicholas Stephanopoulos, Petr Šulc

Molecular Sciences, School of (SMS)

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

We present here the combination of experimental and computational modeling tools for the design and characterization of protein-DNA hybrid nanostructures. Our work incorporates several features in the design of these nanostructures: (1) modeling of the protein-DNA linker identity and length; (2) optimizing the design of protein-DNA cages to account for mechanical stresses; (3) probing the incorporation efficiency of protein-DNA conjugates into DNA nanostructures. The modeling tools were experimentally validated using structural characterization methods like cryo-TEM and AFM. Our method can be used for fitting low-resolution electron density maps when structural insights cannot be deciphered from experiments, as well as enable in-silico validation of nanostructured systems before their experimental realization. These tools will facilitate the design of complex hybrid protein-DNA nanostructures that seamlessly integrate the two different biomolecules.

Original language	English (US)
Pages (from-to)	14086-14096
Number of pages	11
Journal	ACS nano
Volume	16
Issue number	9
DOIs	https://doi.org/10.1021/acsnano.2c04013
State	Published - Sep 27 2022

Keywords

DNA nanotechnology
coarse-grained models
cryo-EM fitting
molecular dynamics
protein-DNA

ASJC Scopus subject areas

Materials Science(all)
Engineering(all)
Physics and Astronomy(all)

Access to Document

10.1021/acsnano.2c04013

Cite this

@article{c050b69b2b2a4b32b949942c493b059f,

title = "Coarse-Grained Simulations for the Characterization and Optimization of Hybrid Protein-DNA Nanostructures",

abstract = "We present here the combination of experimental and computational modeling tools for the design and characterization of protein-DNA hybrid nanostructures. Our work incorporates several features in the design of these nanostructures: (1) modeling of the protein-DNA linker identity and length; (2) optimizing the design of protein-DNA cages to account for mechanical stresses; (3) probing the incorporation efficiency of protein-DNA conjugates into DNA nanostructures. The modeling tools were experimentally validated using structural characterization methods like cryo-TEM and AFM. Our method can be used for fitting low-resolution electron density maps when structural insights cannot be deciphered from experiments, as well as enable in-silico validation of nanostructured systems before their experimental realization. These tools will facilitate the design of complex hybrid protein-DNA nanostructures that seamlessly integrate the two different biomolecules.",

keywords = "DNA nanotechnology, coarse-grained models, cryo-EM fitting, molecular dynamics, protein-DNA",

author = "Narayanan, {Raghu Pradeep} and Jonah Procyk and Purbasha Nandi and Abhay Prasad and Yang Xu and Erik Poppleton and Dewight Williams and Fei Zhang and Hao Yan and Chiu, {Po Lin} and Nicholas Stephanopoulos and Petr {\v S}ulc",

note = "Funding Information: NSF Grant no 1931487. NSF Grant no 1753387. NIH Grant DP2GM132931. DOE grant DE-SC0002423. ONR Grant N000142012094. NSF MRI Grant 1531991. Funding Information: This work was supported by NSF Grant no 1931487 and ONR Grant N000142012094. Nicholas Stephanopoulos acknowledges support from the National Science Foundation (DMR-BMAT CAREER award 1753387). Research reported in this publication was supported by The National Institute of General Medical Sciences of the National Institutes of Health under grant number DP2GM132931. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Po-Lin Chiu acknowledges the support from the US Department of Energy (DE-SC0002423). Publisher Copyright: {\textcopyright} 2022 American Chemical Society. All rights reserved.",

year = "2022",

month = sep,

day = "27",

doi = "10.1021/acsnano.2c04013",

language = "English (US)",

volume = "16",

pages = "14086--14096",

journal = "ACS nano",

issn = "1936-0851",

publisher = "American Chemical Society",

number = "9",

}

TY - JOUR

T1 - Coarse-Grained Simulations for the Characterization and Optimization of Hybrid Protein-DNA Nanostructures

AU - Narayanan, Raghu Pradeep

AU - Procyk, Jonah

AU - Nandi, Purbasha

AU - Prasad, Abhay

AU - Xu, Yang

AU - Poppleton, Erik

AU - Williams, Dewight

AU - Zhang, Fei

AU - Yan, Hao

AU - Chiu, Po Lin

AU - Stephanopoulos, Nicholas

AU - Šulc, Petr

N1 - Funding Information: NSF Grant no 1931487. NSF Grant no 1753387. NIH Grant DP2GM132931. DOE grant DE-SC0002423. ONR Grant N000142012094. NSF MRI Grant 1531991. Funding Information: This work was supported by NSF Grant no 1931487 and ONR Grant N000142012094. Nicholas Stephanopoulos acknowledges support from the National Science Foundation (DMR-BMAT CAREER award 1753387). Research reported in this publication was supported by The National Institute of General Medical Sciences of the National Institutes of Health under grant number DP2GM132931. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Po-Lin Chiu acknowledges the support from the US Department of Energy (DE-SC0002423). Publisher Copyright: © 2022 American Chemical Society. All rights reserved.

PY - 2022/9/27

Y1 - 2022/9/27

N2 - We present here the combination of experimental and computational modeling tools for the design and characterization of protein-DNA hybrid nanostructures. Our work incorporates several features in the design of these nanostructures: (1) modeling of the protein-DNA linker identity and length; (2) optimizing the design of protein-DNA cages to account for mechanical stresses; (3) probing the incorporation efficiency of protein-DNA conjugates into DNA nanostructures. The modeling tools were experimentally validated using structural characterization methods like cryo-TEM and AFM. Our method can be used for fitting low-resolution electron density maps when structural insights cannot be deciphered from experiments, as well as enable in-silico validation of nanostructured systems before their experimental realization. These tools will facilitate the design of complex hybrid protein-DNA nanostructures that seamlessly integrate the two different biomolecules.

AB - We present here the combination of experimental and computational modeling tools for the design and characterization of protein-DNA hybrid nanostructures. Our work incorporates several features in the design of these nanostructures: (1) modeling of the protein-DNA linker identity and length; (2) optimizing the design of protein-DNA cages to account for mechanical stresses; (3) probing the incorporation efficiency of protein-DNA conjugates into DNA nanostructures. The modeling tools were experimentally validated using structural characterization methods like cryo-TEM and AFM. Our method can be used for fitting low-resolution electron density maps when structural insights cannot be deciphered from experiments, as well as enable in-silico validation of nanostructured systems before their experimental realization. These tools will facilitate the design of complex hybrid protein-DNA nanostructures that seamlessly integrate the two different biomolecules.

KW - DNA nanotechnology

KW - coarse-grained models

KW - cryo-EM fitting

KW - molecular dynamics

KW - protein-DNA

UR - http://www.scopus.com/inward/record.url?scp=85136661568&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85136661568&partnerID=8YFLogxK

U2 - 10.1021/acsnano.2c04013

DO - 10.1021/acsnano.2c04013

M3 - Article

C2 - 35980981

AN - SCOPUS:85136661568

SN - 1936-0851

VL - 16

SP - 14086

EP - 14096

JO - ACS nano

JF - ACS nano

IS - 9

ER -

Coarse-Grained Simulations for the Characterization and Optimization of Hybrid Protein-DNA Nanostructures

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this