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Sánchez-Morán H, Kaar JL, Schwartz DK. Supra-biological performance of immobilized enzymes enabled by chaperone-like specific non-covalent interactions. Nat Commun 2024; 15:2299. [PMID: 38485940 PMCID: PMC10940687 DOI: 10.1038/s41467-024-46719-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 03/01/2024] [Indexed: 03/18/2024] Open
Abstract
Designing complex synthetic materials for enzyme immobilization could unlock the utility of biocatalysis in extreme environments. Inspired by biology, we investigate the use of random copolymer brushes as dynamic immobilization supports that enable supra-biological catalytic performance of immobilized enzymes. This is demonstrated by immobilizing Bacillus subtilis Lipase A on brushes doped with aromatic moieties, which can interact with the lipase through multiple non-covalent interactions. Incorporation of aromatic groups leads to a 50 °C increase in the optimal temperature of lipase, as well as a 50-fold enhancement in enzyme activity. Single-molecule FRET studies reveal that these supports act as biomimetic chaperones by promoting enzyme refolding and stabilizing the enzyme's folded and catalytically active state. This effect is diminished when aromatic residues are mutated out, suggesting the importance of π-stacking and π-cation interactions for stabilization. Our results underscore how unexplored enzyme-support interactions may enable uncharted opportunities for using enzymes in industrial biotransformations.
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Affiliation(s)
- Héctor Sánchez-Morán
- Department of Chemical and Biological Engineering, University of Colorado Boulder, Campus Box 596, Boulder, CO, 80309, USA
| | - Joel L Kaar
- Department of Chemical and Biological Engineering, University of Colorado Boulder, Campus Box 596, Boulder, CO, 80309, USA.
| | - Daniel K Schwartz
- Department of Chemical and Biological Engineering, University of Colorado Boulder, Campus Box 596, Boulder, CO, 80309, USA.
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2
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Chen LH, Hu JN. Development of nano-delivery systems for loaded bioactive compounds: using molecular dynamics simulations. Crit Rev Food Sci Nutr 2024:1-22. [PMID: 38206576 DOI: 10.1080/10408398.2023.2301427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2024]
Abstract
Over the past decade, a remarkable surge in the development of functional nano-delivery systems loaded with bioactive compounds for healthcare has been witnessed. Notably, the demanding requirements of high solubility, prolonged circulation, high tissue penetration capability, and strong targeting ability of nanocarriers have posed interdisciplinary research challenges to the community. While extensive experimental studies have been conducted to understand the construction of nano-delivery systems and their metabolic behavior in vivo, less is known about these molecular mechanisms and kinetic pathways during their metabolic process in vivo, and lacking effective means for high-throughput screening. Molecular dynamics (MD) simulation techniques provide a reliable tool for investigating the design of nano-delivery carriers encapsulating these functional ingredients, elucidating the synthesis, translocation, and delivery of nanocarriers. This review introduces the basic MD principles, discusses how to apply MD simulation to design nanocarriers, evaluates the ability of nanocarriers to adhere to or cross gastrointestinal mucosa, and regulates plasma proteins in vivo. Moreover, we presented the critical role of MD simulation in developing delivery systems for precise nutrition and prospects for the future. This review aims to provide insights into the implications of MD simulation techniques for designing and optimizing nano-delivery systems in the healthcare food industry.
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Affiliation(s)
- Li-Hang Chen
- SKL of Marine Food Processing & Safety Control, National Engineering Research Center of Seafood, Collaborative Innovation Center of Seafood Deep Processing, School of Food Science and Technology, Dalian Polytechnic University, Dalian, China
| | - Jiang-Ning Hu
- SKL of Marine Food Processing & Safety Control, National Engineering Research Center of Seafood, Collaborative Innovation Center of Seafood Deep Processing, School of Food Science and Technology, Dalian Polytechnic University, Dalian, China
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3
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Wang J, Waltmann C, Harms C, Hu S, Hegarty J, Shindel B, Wang Q, Dravid V, Shull KR, Torkelson JM, Olvera de la Cruz M. Tailoring Interactions of Random Copolymer Polyelectrolyte Complexes to Remove Nanoplastic Contaminants from Water. LANGMUIR : THE ACS JOURNAL OF SURFACES AND COLLOIDS 2023; 39:7514-7523. [PMID: 37196238 DOI: 10.1021/acs.langmuir.3c01028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]
Abstract
We investigate the usage of polyelectrolyte complex materials for water remediation purposes, specifically their ability to remove nanoplastics from water, on which there is currently little to no prior research. We demonstrate that oppositely charged random copolymers are effective at quantitatively removing nanoplastic contamination from aqueous solution. The mechanisms underlying this remediation ability are explored through computational simulations, with corroborating quartz crystal microbalance adsorption experiments. We find that hydrophobic nanostructures and interactions likely play an important role.
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Affiliation(s)
- Jeremy Wang
- Department of Materials Science and Engineering, Northwestern University, Evanston, Illinois 60208, United States
| | - Curt Waltmann
- Department of Materials Science and Engineering, Northwestern University, Evanston, Illinois 60208, United States
| | - Caroline Harms
- Department of Materials Science and Engineering, Northwestern University, Evanston, Illinois 60208, United States
| | - Sumeng Hu
- Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois 60208, United States
| | - John Hegarty
- Department of Materials Science and Engineering, Northwestern University, Evanston, Illinois 60208, United States
| | - Benjamin Shindel
- Department of Materials Science and Engineering, Northwestern University, Evanston, Illinois 60208, United States
| | - Qifeng Wang
- Department of Materials Science and Engineering, Northwestern University, Evanston, Illinois 60208, United States
| | - Vinayak Dravid
- Department of Materials Science and Engineering, Northwestern University, Evanston, Illinois 60208, United States
| | - Kenneth R Shull
- Department of Materials Science and Engineering, Northwestern University, Evanston, Illinois 60208, United States
| | - John M Torkelson
- Department of Materials Science and Engineering, Northwestern University, Evanston, Illinois 60208, United States
- Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois 60208, United States
| | - Monica Olvera de la Cruz
- Department of Materials Science and Engineering, Northwestern University, Evanston, Illinois 60208, United States
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4
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Cardellini A, Crippa M, Lionello C, Afrose SP, Das D, Pavan GM. Unsupervised Data-Driven Reconstruction of Molecular Motifs in Simple to Complex Dynamic Micelles. J Phys Chem B 2023; 127:2595-2608. [PMID: 36891625 PMCID: PMC10041528 DOI: 10.1021/acs.jpcb.2c08726] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/10/2023]
Abstract
The reshuffling mobility of molecular building blocks in self-assembled micelles is a key determinant of many their interesting properties, from emerging morphologies and surface compartmentalization, to dynamic reconfigurability and stimuli-responsiveness. However, the microscopic details of such complex structural dynamics are typically nontrivial to elucidate, especially in multicomponent assemblies. Here we show a machine-learning approach that allows us to reconstruct the structural and dynamic complexity of mono- and bicomponent surfactant micelles from high-dimensional data extracted from equilibrium molecular dynamics simulations. Unsupervised clustering of smooth overlap of atomic position (SOAP) data enables us to identify, in a set of multicomponent surfactant micelles, the dominant local molecular environments that emerge within them and to retrace their dynamics, in terms of exchange probabilities and transition pathways of the constituent building blocks. Tested on a variety of micelles differing in size and in the chemical nature of the constitutive self-assembling units, this approach effectively recognizes the molecular motifs populating them in an exquisitely agnostic and unsupervised way, and allows correlating them to their composition in terms of constitutive surfactant species.
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Affiliation(s)
- Annalisa Cardellini
- Department of Innovative Technologies, University of Applied Sciences and Arts of Southern Switzerland, Polo Universitario Lugano, Campus Est, Via la Santa 1, 6962 Lugano-Viganello, Switzerland
| | - Martina Crippa
- Department of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
| | - Chiara Lionello
- Department of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
| | - Syed Pavel Afrose
- Department of Chemical Sciences and Centre for Advanced Functional Materials, Indian Institute of Science Education and Research (IISER) Kolkata, Mohanpur 741246, India
| | - Dibyendu Das
- Department of Chemical Sciences and Centre for Advanced Functional Materials, Indian Institute of Science Education and Research (IISER) Kolkata, Mohanpur 741246, India
| | - Giovanni M Pavan
- Department of Innovative Technologies, University of Applied Sciences and Arts of Southern Switzerland, Polo Universitario Lugano, Campus Est, Via la Santa 1, 6962 Lugano-Viganello, Switzerland
- Department of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
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5
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Sánchez-Morán H, Gonçalves LRB, Schwartz DK, Kaar JL. Framework for Optimizing Polymeric Supports for Immobilized Biocatalysts by Computational Analysis of Enzyme Surface Hydrophobicity. ACS Catal 2023. [DOI: 10.1021/acscatal.3c00264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/17/2023]
Affiliation(s)
- Héctor Sánchez-Morán
- Department of Chemical and Biological Engineering, University of Colorado, Campus Box 596, Boulder, Colorado 80309, United States
| | - Luciana Rocha Barros Gonçalves
- Department of Chemical Engineering, Federal University of Ceará, Campus do Pici, Bloco 709, Fortaleza, Ceará CEP 60455-760, Brazil
| | - Daniel K. Schwartz
- Department of Chemical and Biological Engineering, University of Colorado, Campus Box 596, Boulder, Colorado 80309, United States
| | - Joel L. Kaar
- Department of Chemical and Biological Engineering, University of Colorado, Campus Box 596, Boulder, Colorado 80309, United States
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Jin T, Coley CW, Alexander-Katz A. Adsorption of Biomimetic Amphiphilic Heteropolymers onto Graphene and Its Derivatives. Macromolecules 2023. [DOI: 10.1021/acs.macromol.2c02413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
Affiliation(s)
- Tianyi Jin
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Connor W. Coley
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Alfredo Alexander-Katz
- Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
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Heredero M, Beloqui A. Enzyme-Polymer Conjugates for Tuning, Enhancing, and Expanding Biocatalytic Activity. Chembiochem 2023; 24:e202200611. [PMID: 36507915 DOI: 10.1002/cbic.202200611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 12/11/2022] [Accepted: 12/12/2022] [Indexed: 12/15/2022]
Abstract
Combining polymers with functional proteins is an approach that has brought several successful stories in the field of biomedicine with PEGylated therapeutic proteins. The latest advances in polymer chemistry have facilitated the expansion of protein-polymer hybrids to other research areas such as biocatalysis. Polymers can impart stability and novel functionalities to the enzyme of interest, thereby improving the catalytic performance of a given reaction. In this review, we have revisited the main methodologies currently used for the synthesis of enzyme-polymer hybrids, unveiling the interplay between the configuration and the composition of the assembled structure and the eventual traits of the hybrid. Finally, the latest advances, such as the assembly of polymer-based chemoenzymatic nanoreactors and the use of deep learning methodologies to achieve the most suitable polymer compositions for catalysis, are discussed.
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Affiliation(s)
- Marcos Heredero
- POLYMAT and Department of Applied Chemistry, Faculty of Chemistry, University of the Basque Country UPV/EHU, Paseo Manuel Lardizabal 3, 20018, Donostia-San Sebastián, Spain
| | - Ana Beloqui
- POLYMAT and Department of Applied Chemistry, Faculty of Chemistry, University of the Basque Country UPV/EHU, Paseo Manuel Lardizabal 3, 20018, Donostia-San Sebastián, Spain.,IKERBASQUE, Basque Foundation for Science, Plaza Euskadi 5, 48009, Bilbao, Spain
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8
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Jayapurna I, Ruan Z, Eres M, Jalagam P, Jenkins S, Xu T. Sequence Design of Random Heteropolymers as Protein Mimics. Biomacromolecules 2023; 24:652-660. [PMID: 36638823 PMCID: PMC9930114 DOI: 10.1021/acs.biomac.2c01036] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Random heteropolymers (RHPs) have been computationally designed and experimentally shown to recapitulate protein-like phase behavior and function. However, unlike proteins, RHP sequences are only statistically defined and cannot be sequenced. Recent developments in reversible-deactivation radical polymerization allowed simulated polymer sequences based on the well-established Mayo-Lewis equation to more accurately reflect ground-truth sequences that are experimentally synthesized. This led to opportunities to perform bioinformatics-inspired analysis on simulated sequences to guide the design, synthesis, and interpretation of RHPs. We compared batches on the order of 10000 simulated RHP sequences that vary by synthetically controllable and measurable RHP characteristics such as chemical heterogeneity and average degree of polymerization. Our analysis spans across 3 levels: segments along a single chain, sequences within a batch, and batch-averaged statistics. We discuss simulator fidelity and highlight the importance of robust segment definition. Examples are presented that demonstrate the use of simulated sequence analysis for in-silico iterative design to mimic protein hydrophobic/hydrophilic segment distributions in RHPs and compare RHP and protein sequence segments to explain experimental results of RHPs that mimic protein function. To facilitate the community use of this workflow, the simulator and analysis modules have been made available through an open source toolkit, the RHPapp.
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Affiliation(s)
- Ivan Jayapurna
- Department of Materials Science and Engineering, University of California, Berkeley, Berkeley, California 94720, United States
| | - Zhiyuan Ruan
- Department of Materials Science and Engineering, University of California, Berkeley, Berkeley, California 94720, United States
| | - Marco Eres
- Department of Chemistry, University of California, Berkeley, Berkeley, California 94720, United States
| | - Prajna Jalagam
- Department of Materials Science and Engineering, University of California, Berkeley, Berkeley, California 94720, United States
| | - Spencer Jenkins
- Department of Chemistry, University of California, Berkeley, Berkeley, California 94720, United States
| | - Ting Xu
- Department of Materials Science and Engineering, University of California, Berkeley, Berkeley, California 94720, United States.,Department of Chemistry, University of California, Berkeley, Berkeley, California 94720, United States.,Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
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9
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Jeong KJ, Jeong S, Lee S, Son CY. Predictive Molecular Models for Charged Materials Systems: From Energy Materials to Biomacromolecules. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023; 35:e2204272. [PMID: 36373701 DOI: 10.1002/adma.202204272] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 07/05/2022] [Indexed: 06/16/2023]
Abstract
Electrostatic interactions play a dominant role in charged materials systems. Understanding the complex correlation between macroscopic properties with microscopic structures is of critical importance to develop rational design strategies for advanced materials. But the complexity of this challenging task is augmented by interfaces present in the charged materials systems, such as electrode-electrolyte interfaces or biological membranes. Over the last decades, predictive molecular simulations that are founded in fundamental physics and optimized for charged interfacial systems have proven their value in providing molecular understanding of physicochemical properties and functional mechanisms for diverse materials. Novel design strategies utilizing predictive models have been suggested as promising route for the rational design of materials with tailored properties. Here, an overview of recent advances in the understanding of charged interfacial systems aided by predictive molecular simulations is presented. Focusing on three types of charged interfaces found in energy materials and biomacromolecules, how the molecular models characterize ion structure, charge transport, morphology relation to the environment, and the thermodynamics/kinetics of molecular binding at the interfaces is discussed. The critical analysis brings two prominent field of energy materials and biological science under common perspective, to stimulate crossover in both research field that have been largely separated.
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Affiliation(s)
- Kyeong-Jun Jeong
- Department of Chemistry, Pohang University of Science and Technology (POSTECH), Pohang, 790-784, South Korea
| | - Seungwon Jeong
- Department of Chemistry, Pohang University of Science and Technology (POSTECH), Pohang, 790-784, South Korea
| | - Sangmin Lee
- Department of Chemistry, Pohang University of Science and Technology (POSTECH), Pohang, 790-784, South Korea
| | - Chang Yun Son
- Department of Chemistry, Pohang University of Science and Technology (POSTECH), Pohang, 790-784, South Korea
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Marrink SJ, Monticelli L, Melo MN, Alessandri R, Tieleman DP, Souza PCT. Two decades of Martini: Better beads, broader scope. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2022. [DOI: 10.1002/wcms.1620] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Siewert J. Marrink
- Groningen Biomolecular Sciences and Biotechnology Institute & Zernike Institute for Advanced Materials University of Groningen Groningen The Netherlands
| | - Luca Monticelli
- Molecular Microbiology and Structural Biochemistry (MMSB ‐ UMR 5086) CNRS & University of Lyon Lyon France
| | - Manuel N. Melo
- Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa Oeiras Portugal
| | - Riccardo Alessandri
- Pritzker School of Molecular Engineering University of Chicago Chicago Illinois USA
| | - D. Peter Tieleman
- Centre for Molecular Simulation and Department of Biological Sciences University of Calgary Alberta Canada
| | - Paulo C. T. Souza
- Molecular Microbiology and Structural Biochemistry (MMSB ‐ UMR 5086) CNRS & University of Lyon Lyon France
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Abstract
The use of biological enzyme catalysts could have huge ramifications for chemical industries. However, these enzymes are often inactive in nonbiological conditions, such as high temperatures, present in industrial settings. Here, we show that the enzyme PETase (polyethylene terephthalate [PET]), with potential application in plastic recycling, is stabilized at elevated temperature through complexation with random copolymers. We demonstrate this through simulations and experiments on different types of substrates. Our simulations also provide strategies for designing more enzymatically active complexes by altering polymer composition and enzyme charge distribution. Engineered and native enzymes are poised to solve challenges in medicine, bioremediation, and biotechnology. One important goal is the possibility of upcycling polymers using enzymes. However, enzymes are often inactive in industrial, nonbiological conditions. It is particularly difficult to protect water-soluble enzymes at elevated temperatures by methods that preserve their functionality. Through atomistic and coarse-grained molecular dynamics simulations that capture protein conformational change, we show that an enzyme, PETase (polyethylene terephthalate [PET]), can be stabilized at elevated temperatures by complexation with random copolymers into nanoscale aggregates that do not precipitate into macroscopic phases. We demonstrated the efficiency of the method by simulating complexes of random copolymers and the enzyme PETase, which depolymerizes PET, a highly used polymer. These polymers are more industrially viable than peptides and can target specific domains on an enzyme. We design the mean composition of the random copolymers to control the polymer–enzyme surface contacts and the polymer conformation. When positioned on or near the active site, these polymer contacts can further stabilize the conformation of the active site at elevated temperatures. We explore the experimental implications of this active site stabilization method and show that PETase-random copolymer complexes have enhanced activity on both small molecule substrates and solid PET films. These results provide guidelines for engineering enzyme–polymer complexes with enhanced enzyme functionality in nonbiological environments.
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