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Hydration and antibiofouling of TMAO-derived zwitterionic polymers surfaces studied with atomistic molecular dynamics simulations. Colloids Surf A Physicochem Eng Asp 2022. [DOI: 10.1016/j.colsurfa.2022.129943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Chen J, Xu E, Wei Y, Chen M, Wei T, Zheng S. Graph Clustering Analyses of Discontinuous Molecular Dynamics Simulations: Study of Lysozyme Adsorption on a Graphene Surface. LANGMUIR : THE ACS JOURNAL OF SURFACES AND COLLOIDS 2022; 38:10817-10825. [PMID: 36001808 DOI: 10.1021/acs.langmuir.2c01331] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Understanding the interfacial behaviors of biomolecules is crucial to applications in biomaterials and nanoparticle-based biosensing technologies. In this work, we utilized autoencoder-based graph clustering to analyze discontinuous molecular dynamics (DMD) simulations of lysozyme adsorption on a graphene surface. Our high-throughput DMD simulations integrated with a Go̅-like protein-surface interaction model makes it possible to explore protein adsorption at a large temporal scale with sufficient accuracy. The graph autoencoder extracts a low-dimensional feature vector from a contact map. The sequence of the extracted feature vectors is then clustered, and thus the evolution of the protein molecule structure in the absorption process is segmented into stages. Our study demonstrated that the residue-surface hydrophobic interactions and the π-π stacking interactions play key roles in the five-stage adsorption. Upon adsorption, the tertiary structure of lysozyme collapsed, and the secondary structure was also affected. The folding stages obtained by autoencoder-based graph clustering were consistent with detailed analyses of the protein structure. The combination of machine learning analysis and efficient DMD simulations developed in this work could be an important tool to study biomolecules' interfacial behaviors.
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Affiliation(s)
- Jing Chen
- College of Materials and Chemistry & Chemical Engineering, Chengdu University of Technology, Chengdu, Sichuan 610059, P. R. China
| | | | - Yong Wei
- Department of Computer Science, High Point University, High Point, North Carolina 27268, United States
| | | | - Tao Wei
- Department of Chemical Engineering, Howard University, Washington, D.C. 20059, United States
| | - Size Zheng
- College of Materials and Chemistry & Chemical Engineering, Chengdu University of Technology, Chengdu, Sichuan 610059, P. R. China
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Correira JM, Handali PR, Webb LJ. Characterizing Protein-Surface and Protein-Nanoparticle Conjugates: Activity, Binding, and Structure. J Chem Phys 2022; 157:090902. [DOI: 10.1063/5.0101406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Many sensors and catalysts composed of proteins immobilized on inorganic materials have been reported over the past few decades. Despite some examples of functional protein-surface and protein-nanoparticle conjugates, thorough characterization of the biological-abiological interface at the heart of these materials and devices is often overlooked in lieu of demonstrating acceptable system performance. This has resulted in a focus on generating functioning protein-based devices without a concerted effort to develop reliable tools necessary to measure the fundamental properties of the bio-abio interface such as surface concentration, biomolecular structure, and activity. In this Perspective we discuss current methods used to characterize these critical properties of devices that operate by integrating a protein into both flat surfaces and nanoparticle materials. We highlight the advantages and drawbacks of each method as they relate to understanding the function of the protein-surface interface, and explore the manner in which an informed understanding of this complex interaction leads directly to the advancement of protein-based materials and technology.
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Affiliation(s)
| | - Paul R Handali
- The University of Texas at Austin, United States of America
| | - Lauren J. Webb
- Chemistry, The University of Texas at Austin Department of Chemistry, United States of America
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Chen SH, Bell DR, Luan B. Understanding interactions between biomolecules and two-dimensional nanomaterials using in silico microscopes. Adv Drug Deliv Rev 2022; 186:114336. [PMID: 35597306 PMCID: PMC9212071 DOI: 10.1016/j.addr.2022.114336] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 04/08/2022] [Accepted: 05/06/2022] [Indexed: 12/28/2022]
Abstract
Two-dimensional (2D) nanomaterials such as graphene are increasingly used in research and industry for various biomedical applications. Extensive experimental and theoretical studies have revealed that 2D nanomaterials are promising drug delivery vehicles, yet certain materials exhibit toxicity under biological conditions. So far, it is known that 2D nanomaterials possess strong adsorption propensities for biomolecules. To mitigate potential toxicity and retain favorable physical and chemical properties of 2D nanomaterials, it is necessary to explore the underlying mechanisms of interactions between biomolecules and nanomaterials for the subsequent design of biocompatible 2D nanomaterials for nanomedicine. The purpose of this review is to integrate experimental findings with theoretical observations and facilitate the study of 2D nanomaterial interaction with biomolecules at the molecular level. We discuss the current understanding and progress of 2D nanomaterial interaction with proteins, lipid membranes, and DNA based on molecular dynamics (MD) simulation. In this review, we focus on the 2D graphene nanosheet and briefly discuss other 2D nanomaterials. With the ever-growing computing power, we can image nanoscale processes using MD simulation that are otherwise not observable in experiment. We expect that molecular characterization of the complex behavior between 2D nanomaterials and biomolecules will help fulfill the goal of designing effective 2D nanomaterials as drug delivery platforms.
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Affiliation(s)
- Serena H Chen
- Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA
| | - David R Bell
- Advanced Biomedical Computational Science, Frederick National Laboratory for Cancer Research, Frederick, MD 21701, USA
| | - Binquan Luan
- IBM Thomas J. Watson Research, Yorktown Heights, New York 10598, USA.
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Sarker P, Sajib MSJ, Tao X, Wei T. Multiscale Simulation of Protein Corona Formation on Silver Nanoparticles: Study of Ovispirin-1 Peptide Adsorption. J Phys Chem B 2022; 126:601-608. [PMID: 35026946 DOI: 10.1021/acs.jpcb.1c08267] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The exposure of nanoparticles (NPs) to biofluids leads to the rapid coverage of proteins, named protein corona, which alters the NPs' chemicophysical and biological properties. Fundamental studies of the protein corona are thus critical to the increasing applications of NPs in nanotechnology and nanomedicines. The present work utilizes multiscale simulations of a model biological system, small ovispirin-1 peptides, and bare silver nanoparticles (AgNPs) to examine the NPs' size and surface hydrophilicity effects on formation dynamics and the structure of the peptide corona. Our simulations revealed the different adsorption dynamics of ovispirin-1 peptides on the NPs, including the direct adsorption of a single peptide and peptide aggregates and multistep adsorption, as well as an intermediate cycle of desorption and readsorption. Notably, the whole process of peptide adsorption on hydrophilic AgNP surfaces can be generalized as three stages: diffusion to the surface, initial landing via hydrophilic residues, and the final attachment. The decrease in AgNP's size leads to faster adsorption with more heterogeneous peptide interfacial dynamics, a denser and inhomogeneous peptide packing structure, and a wider distribution of adsorption orientations. Subsequent atomistic molecular dynamics simulations demonstrated that on the hydrophilic AgNP surfaces, adsorbed peptides display moderate changes in their secondary structure, resulting in further changes of corona composition, i.e., amino acid residue distribution on the surface.
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Affiliation(s)
- Pranab Sarker
- Department of Chemical Engineering, Howard University, Washington, D.C. 20059, United States
| | - Md Symon Jahan Sajib
- Department of Chemical Engineering, Howard University, Washington, D.C. 20059, United States
| | - Xiuping Tao
- Department of Chemistry, Winston-Salem State University, Winston-Salem, North Carolina 27110, United States
| | - Tao Wei
- Department of Chemical Engineering, Howard University, Washington, D.C. 20059, United States
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Guo W, Zou X, Jiang H, Koebke KJ, Hoarau M, Crisci R, Lu T, Wei T, Marsh ENG, Chen Z. Molecular Structure of the Surface-Immobilized Super Uranyl Binding Protein. J Phys Chem B 2021; 125:7706-7716. [PMID: 34254804 DOI: 10.1021/acs.jpcb.1c03849] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Recently, a super uranyl binding protein (SUP) was developed, which exhibits excellent sensitivity/selectivity to bind uranyl ions. It can be immobilized onto a surface in sensing devices to detect uranyl ions. Here, sum frequency generation (SFG) vibrational spectroscopy was applied to probe the interfacial structures of surface-immobilized SUP. The collected SFG spectra were compared to the calculated orientation-dependent SUP SFG spectra using a one-excitonic Hamiltonian approach based on the SUP crystal structures to deduce the most likely surface-immobilized SUP orientation(s). Furthermore, discrete molecular dynamics (DMD) simulation was applied to refine the surface-immobilized SUP conformations and orientations. The immobilized SUP structures calculated from DMD simulations confirmed the SUP orientations obtained from SFG data analyzed based on the crystal structures and were then used for a new round of SFG orientation analysis to more accurately determine the interfacial orientations and conformations of immobilized SUP before and after uranyl ion binding, providing an in-depth understanding of molecular interactions between SUP and the surface and the effect of uranyl ion binding on the SUP interfacial structures. We believe that the developed method of combining SFG measurements, DMD simulation, and Hamiltonian data analysis approach is widely applicable to study biomolecules at solid/liquid interfaces.
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Affiliation(s)
- Wen Guo
- Department of Chemistry, University of Michigan, 930 North University Avenue, Ann Arbor, Michigan 48109, United States
| | - Xingquan Zou
- Department of Chemistry, University of Michigan, 930 North University Avenue, Ann Arbor, Michigan 48109, United States
| | - Hanjie Jiang
- Department of Chemistry, University of Michigan, 930 North University Avenue, Ann Arbor, Michigan 48109, United States
| | - Karl J Koebke
- Department of Chemistry, University of Michigan, 930 North University Avenue, Ann Arbor, Michigan 48109, United States
| | - Marie Hoarau
- Department of Chemistry, University of Michigan, 930 North University Avenue, Ann Arbor, Michigan 48109, United States
| | - Ralph Crisci
- Department of Chemistry, University of Michigan, 930 North University Avenue, Ann Arbor, Michigan 48109, United States
| | - Tieyi Lu
- Department of Chemistry, University of Michigan, 930 North University Avenue, Ann Arbor, Michigan 48109, United States
| | - Tao Wei
- Department of Chemical Engineering, Howard University, 2366 Sixth Street, NW, Washington, D.C. 20059, United States
| | - E Neil G Marsh
- Department of Chemistry, University of Michigan, 930 North University Avenue, Ann Arbor, Michigan 48109, United States
| | - Zhan Chen
- Department of Chemistry, University of Michigan, 930 North University Avenue, Ann Arbor, Michigan 48109, United States
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