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Devoy C, Flores Bueso Y, Buckley S, Walker S, Tangney M. Synthetic protein protease sensor platform. Front Bioeng Biotechnol 2024; 12:1347953. [PMID: 38646011 PMCID: PMC11026627 DOI: 10.3389/fbioe.2024.1347953] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Accepted: 02/21/2024] [Indexed: 04/23/2024] Open
Abstract
Introduction: Protease activity can serve as a highly specific biomarker for application in health, biotech, and beyond. The aim of this study was to develop a protease cleavable synthetic protein platform to detect protease activity in a rapid cell-free setting. Methods: The protease sensor is modular, with orthogonal peptide tags at the N and C terminal ends, which can be uncoupled via a protease responsive module located in between. The sensor design allows for several different readouts of cleavage signal. A protein 'backbone' [Green fluorescent protein (GFP)] was designed in silico to have both a C-terminal Flag-tag and N-Terminal 6x histidine tag (HIS) for antibody detection. A protease cleavage site, which can be adapted for any known protease cleavage sequence, enables the uncoupling of the peptide tags. Three different proteases-Tobacco, Etch Virus (TEV), the main protease from coronavirus SARS-COV-2 (Mpro) and Matrix Metallopeptidase 9 (MMP9)-a cancer-selective human protease-were examined. A sandwich Enzyme-Linked Immunosorbent Assay (ELISA) was developed based on antibodies against the HIS and Flag tags. As an alternative readout, a C-terminal quencher peptide separable by protease cleavage from the GFP was also included. Purified proteins were deployed in cell-free cleavage assays with their respective protease. Western blots, fluorescence assays and immunoassay were performed on samples. Results: Following the design, build and validation of protein constructs, specific protease cleavage was initially demonstrated by Western blot. The novel ELISA proved to afford highly sensitive detection of protease activity in all cases. By way of alternative readout, activation of fluorescence signal upon protease cleavage was also demonstrated but did not match the sensitivity provided by the ELISA method. Discussion: This platform, comprising a protease-responsive synthetic protein device and accompanying readout, is suitable for future deployment in a rapid, low-cost, lateral flow setting. The modular protein device can readily accommodate any desired protease-response module (target protease cleavage site). This study validates the concept with three disparate proteases and applications-human infectious disease, cancer and agricultural crop infection.
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Affiliation(s)
- Ciaran Devoy
- Cancer Research@UCC, University College Cork, Cork, Ireland
| | - Yensi Flores Bueso
- Cancer Research@UCC, University College Cork, Cork, Ireland
- APC Microbiome Ireland, University College Cork, Cork, Ireland
| | | | - Sidney Walker
- Cancer Research@UCC, University College Cork, Cork, Ireland
| | - Mark Tangney
- Cancer Research@UCC, University College Cork, Cork, Ireland
- IEd Hub, University College Cork, Cork, Ireland
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Mi Y, Marcu SB, Tabirca S, Yallapragada VVB. PROFASA-a web-based protein fragment and structure analysis workstation. Front Bioeng Biotechnol 2023; 11:1192094. [PMID: 37545885 PMCID: PMC10401835 DOI: 10.3389/fbioe.2023.1192094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 07/10/2023] [Indexed: 08/08/2023] Open
Abstract
Introduction: In the field of bioinformatics and computational biology, protein structure modelling and analysis is a crucial aspect. However, most existing tools require a high degree of technical expertise and lack a user-friendly interface. To address this problem, we developed a protein workstation called PROFASA. Methods: PROFASA is an innovative protein workstation that combines state-of-the-art protein structure visualisation techniques with cutting-edge tools and algorithms for protein analysis. Our goal is to provide users with a comprehensive platform for all protein sequence and structure analyses. PROFASA is designed with the idea of simplifying complex protein analysis workflows into one-click operations, while providing powerful customisation options to meet the needs of professional users. Results: PROFASA provides a one-stop solution that enables users to perform protein structure evaluation, parametric analysis and protein visualisation. Users can use I-TASSER or AlphaFold2 to construct protein models with one click, generate new protein sequences, models, and calculate protein parameters. In addition, PROFASA offers features such as real-time collaboration, note sharing, and shared projects, making it an ideal tool for researchers and teaching professionals. Discussion: PROFASA's innovation lies in its user-friendly interface and one-stop solution. It not only lowers the barrier to entry for protein computation, analysis and visualisation tools, but also opens up new possibilities for protein research and education. We expect PROFASA to advance the study of protein design and engineering and open up new research areas.
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Affiliation(s)
- Yanlin Mi
- School of Computer Science and Information Technology, University College Cork, Cork, Ireland
- SFI Centre for Research Training in Artificial Intelligence, University College Cork, Cork, Ireland
| | - Stefan-Bogdan Marcu
- School of Computer Science and Information Technology, University College Cork, Cork, Ireland
| | - Sabin Tabirca
- School of Computer Science and Information Technology, University College Cork, Cork, Ireland
- Faculty of Mathematics and Informatics, Transylvania University of Brasov, Brasov, Romania
| | - Venkata V. B. Yallapragada
- Centre for Advanced Photonics and Process Analytics, Munster Technological University, Cork, Ireland
- Tyndall National Institute, Cork, Ireland
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Chen Z, Wang X, Chen X, Huang J, Wang C, Wang J, Wang Z. Accelerating therapeutic protein design with computational approaches toward the clinical stage. Comput Struct Biotechnol J 2023; 21:2909-2926. [PMID: 38213894 PMCID: PMC10781723 DOI: 10.1016/j.csbj.2023.04.027] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 04/11/2023] [Accepted: 04/27/2023] [Indexed: 01/13/2024] Open
Abstract
Therapeutic protein, represented by antibodies, is of increasing interest in human medicine. However, clinical translation of therapeutic protein is still largely hindered by different aspects of developability, including affinity and selectivity, stability and aggregation prevention, solubility and viscosity reduction, and deimmunization. Conventional optimization of the developability with widely used methods, like display technologies and library screening approaches, is a time and cost-intensive endeavor, and the efficiency in finding suitable solutions is still not enough to meet clinical needs. In recent years, the accelerated advancement of computational methodologies has ushered in a transformative era in the field of therapeutic protein design. Owing to their remarkable capabilities in feature extraction and modeling, the integration of cutting-edge computational strategies with conventional techniques presents a promising avenue to accelerate the progression of therapeutic protein design and optimization toward clinical implementation. Here, we compared the differences between therapeutic protein and small molecules in developability and provided an overview of the computational approaches applicable to the design or optimization of therapeutic protein in several developability issues.
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Affiliation(s)
- Zhidong Chen
- Department of Pathology, The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen 518033, China
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
| | - Xinpei Wang
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
| | - Xu Chen
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
| | - Juyang Huang
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
| | - Chenglin Wang
- Shenzhen Qiyu Biotechnology Co., Ltd, Shenzhen 518107, China
| | - Junqing Wang
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
| | - Zhe Wang
- Department of Pathology, The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen 518033, China
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Soler MA, Minovski N, Rocchia W, Fortuna S. Replica-exchange optimization of antibody fragments. Comput Biol Chem 2023; 103:107819. [PMID: 36657284 DOI: 10.1016/j.compbiolchem.2023.107819] [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: 10/10/2022] [Revised: 12/16/2022] [Accepted: 01/13/2023] [Indexed: 01/15/2023]
Abstract
In the framework of the rational design of macromolecules capable of binding to a specific target for biosensing applications, we here further develop an evolutionary protocol designed to optimize the binding affinity of protein binders. In particular we focus on the optimization of the binding portion of small antibody fragments known as nanobodies (or VHH) and choose the hen egg white lysozyme (HEWL) as our target. By implementing a replica exchange scheme for this optimization, we show that an initial hit is not needed and similar solutions can be found by either optimizing an already known anti-HEWL VHH or a randomly selected binder (here a VHH selective towards another macromolecule). While we believe that exhaustive searches of the mutation space are most appropriate when only few key residues have to be optimized, in case a lead binder is not available the proposed evolutionary algorithm should be instead the method of choice.
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Affiliation(s)
- Miguel A Soler
- Italian Institute of Technology (IIT), Via Melen 83, B Block, Genova, Italy; Department of Mathematics, Computer Science and Physics, University of Udine, Via delle Scienze 206, Udine, Italy
| | - Nikola Minovski
- Theory Department, Laboratory for Cheminformatics, National Institute of Chemistry, Hajdrihova 19, SI-1001 Ljubljana, Slovenia; Department of Chemical and Pharmaceutical Sciences, University of Trieste, Via L. Giorgieri 1, Trieste, Italy
| | - Walter Rocchia
- Italian Institute of Technology (IIT), Via Melen 83, B Block, Genova, Italy
| | - Sara Fortuna
- Italian Institute of Technology (IIT), Via Melen 83, B Block, Genova, Italy; Department of Chemical and Pharmaceutical Sciences, University of Trieste, Via L. Giorgieri 1, Trieste, Italy.
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Ji Z, Huo H, Duan L, Wang S. Design of robust malate dehydrogenases by assembly of motifs of halophilic and thermophilic enzyme based on interaction network. Biochem Eng J 2023. [DOI: 10.1016/j.bej.2022.108758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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Liu Z, Zhang R, Zhang W, Xu Y. Structure-based rational design of hydroxysteroid dehydrogenases for improving and diversifying steroid synthesis. Crit Rev Biotechnol 2022:1-17. [PMID: 35834355 DOI: 10.1080/07388551.2022.2054770] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
A group of steroidogenic enzymes, hydroxysteroid dehydrogenases are involved in steroid metabolism which is very important in the cell: signaling, growth, reproduction, and energy homeostasis. The enzymes show an inherent function in the interconversion of ketosteroids and hydroxysteroids in a position- and stereospecific manner on the steroid nucleus and side-chains. However, the biocatalysis of steroids reaction is a vital and demanding, yet challenging, task to produce the desired enantiopure products with non-natural substrates or non-natural cofactors, and/or in non-physiological conditions. This has driven the use of protein design strategies to improve their inherent biosynthetic efficiency or activate their silent catalytic ability. In this review, the innate features and catalytic characteristics of enzymes based on sequence-structure-function relationships of steroidogenic enzymes are reviewed. Combining structure information and catalytic mechanisms, progress in protein redesign to stimulate potential function, for example, substrate specificity, cofactor dependence, and catalytic stability are discussed.
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Affiliation(s)
- Zhiyong Liu
- Lab of Brewing Microbiology and Applied Enzymology, School of Biotechnology and Key Laboratory of Industrial Biotechnology of Ministry of Education, Jiangnan University, Wuxi, China
| | - Rongzhen Zhang
- Lab of Brewing Microbiology and Applied Enzymology, School of Biotechnology and Key Laboratory of Industrial Biotechnology of Ministry of Education, Jiangnan University, Wuxi, China
| | - Wenchi Zhang
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Yan Xu
- Lab of Brewing Microbiology and Applied Enzymology, School of Biotechnology and Key Laboratory of Industrial Biotechnology of Ministry of Education, Jiangnan University, Wuxi, China
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Cox JR, Blazeck J. Protein engineering: a driving force toward synthetic immunology. Trends Biotechnol 2021; 40:509-521. [PMID: 34627648 DOI: 10.1016/j.tibtech.2021.09.005] [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: 07/09/2021] [Revised: 09/08/2021] [Accepted: 09/10/2021] [Indexed: 11/29/2022]
Abstract
The full application of the diverse toolkit of protein engineering has made it easier to control the immune system. In particular, synthetic cytokine variants and engineered immune receptor platforms have shown promise for the treatment of various indications with dysregulated immune function, particularly cancer. Here, we review recent advances in the control of immune cell signaling and therapeutic potency that have employed protein engineering strategies. We further discuss how safety concerns are driving the design of immunotherapeutics toward 'user-defined' control or requiring multiple distinct inputs before a functional response, highlighting emergent control strategies employed for chimeric antigen receptor (CAR) engineering.
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Affiliation(s)
- John R Cox
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, 311 Ferst St. NW, Atlanta, GA 30332, USA
| | - John Blazeck
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, 311 Ferst St. NW, Atlanta, GA 30332, USA.
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