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Berger S, Seeger F, Yu TY, Aydin M, Yang H, Rosenblum D, Guenin-Macé L, Glassman C, Arguinchona L, Sniezek C, Blackstone A, Carter L, Ravichandran R, Ahlrichs M, Murphy M, Pultz IS, Kang A, Bera AK, Stewart L, Garcia KC, Naik S, Spangler JB, Beigel F, Siebeck M, Gropp R, Baker D. Preclinical proof of principle for orally delivered Th17 antagonist miniproteins. Cell 2024; 187:4305-4317.e18. [PMID: 38936360 PMCID: PMC11316638 DOI: 10.1016/j.cell.2024.05.052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 04/09/2024] [Accepted: 05/29/2024] [Indexed: 06/29/2024]
Abstract
Interleukin (IL)-23 and IL-17 are well-validated therapeutic targets in autoinflammatory diseases. Antibodies targeting IL-23 and IL-17 have shown clinical efficacy but are limited by high costs, safety risks, lack of sustained efficacy, and poor patient convenience as they require parenteral administration. Here, we present designed miniproteins inhibiting IL-23R and IL-17 with antibody-like, low picomolar affinities at a fraction of the molecular size. The minibinders potently block cell signaling in vitro and are extremely stable, enabling oral administration and low-cost manufacturing. The orally administered IL-23R minibinder shows efficacy better than a clinical anti-IL-23 antibody in mouse colitis and has a favorable pharmacokinetics (PK) and biodistribution profile in rats. This work demonstrates that orally administered de novo-designed minibinders can reach a therapeutic target past the gut epithelial barrier. With high potency, gut stability, and straightforward manufacturability, de novo-designed minibinders are a promising modality for oral biologics.
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Affiliation(s)
- Stephanie Berger
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA; Institute for Protein Design, University of Washington, Seattle, WA 98195, USA.
| | - Franziska Seeger
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA; Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Ta-Yi Yu
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA; Institute for Protein Design, University of Washington, Seattle, WA 98195, USA; Department of Bioengineering, University of Washington, Seattle, WA 98195, USA
| | - Merve Aydin
- Department of General, Visceral and Transplantation Surgery, LMU University Hospital, LMU Munich, 81377 Munich, Germany
| | - Huilin Yang
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218, USA; Translational Tissue Engineering Center, Johns Hopkins University, Baltimore, MD 21231, USA
| | - Daniel Rosenblum
- Department of Pathology, NYU Langone Health, New York, NY 10016, USA
| | - Laure Guenin-Macé
- Department of Pathology, NYU Langone Health, New York, NY 10016, USA; Immunobiology and Therapy Unit, INSERM U1224, Institut Pasteur, Paris 75015, France
| | - Caleb Glassman
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94304, USA
| | - Lauren Arguinchona
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA; Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Catherine Sniezek
- Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Alyssa Blackstone
- Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Lauren Carter
- Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Rashmi Ravichandran
- Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Maggie Ahlrichs
- Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Michael Murphy
- Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | | | - Alex Kang
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA; Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Asim K Bera
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA; Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Lance Stewart
- Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - K Christopher Garcia
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94304, USA; Department of Structural Biology, Stanford University School of Medicine, Stanford, CA 94304, USA; Howard Hughes Medical Institute, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Shruti Naik
- Department of Pathology, NYU Langone Health, New York, NY 10016, USA; Department of Medicine, Ronald O. Perelman Department of Dermatology, Perlmutter Cancer Center, NYU Langone Health, New York, NY 10016, USA
| | - Jamie B Spangler
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218, USA; Translational Tissue Engineering Center, Johns Hopkins University, Baltimore, MD 21231, USA; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Florian Beigel
- Department of Medicine II, LMU University Hospital, LMU Munich, 80336 Munich, Germany
| | - Matthias Siebeck
- Department of General, Visceral and Transplantation Surgery, LMU University Hospital, LMU Munich, 81377 Munich, Germany
| | - Roswitha Gropp
- Department of General, Visceral and Transplantation Surgery, LMU University Hospital, LMU Munich, 81377 Munich, Germany
| | - David Baker
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA; Institute for Protein Design, University of Washington, Seattle, WA 98195, USA; Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA.
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Noro J, Vilaça-Faria H, Reis RL, Pirraco RP. Extracellular matrix-derived materials for tissue engineering and regenerative medicine: A journey from isolation to characterization and application. Bioact Mater 2024; 34:494-519. [PMID: 38298755 PMCID: PMC10827697 DOI: 10.1016/j.bioactmat.2024.01.004] [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: 10/10/2023] [Revised: 12/19/2023] [Accepted: 01/03/2024] [Indexed: 02/02/2024] Open
Abstract
Biomaterial choice is an essential step during the development tissue engineering and regenerative medicine (TERM) applications. The selected biomaterial must present properties allowing the physiological-like recapitulation of several processes that lead to the reestablishment of homeostatic tissue or organ function. Biomaterials derived from the extracellular matrix (ECM) present many such properties and their use in the field has been steadily increasing. Considering this growing importance, it becomes imperative to provide a comprehensive overview of ECM biomaterials, encompassing their sourcing, processing, and integration into TERM applications. This review compiles the main strategies used to isolate and process ECM-derived biomaterials as well as different techniques used for its characterization, namely biochemical and chemical, physical, morphological, and biological. Lastly, some of their applications in the TERM field are explored and discussed.
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Affiliation(s)
- Jennifer Noro
- 3B's Research Group, I3Bs – Research Institute on Biomaterials, Biodegradables and Biomimetics, University of Minho, Headquarters of the European Institute of Excellence on Tissue Engineering and Regenerative Medicine, AvePark, Parque de Ciência e Tecnologia, Zona Industrial da Gandra, 4805-017, Barco, Guimarães, Portugal
- ICVS/3B's – PT Government Associate Laboratory, Braga, Guimarães, Portugal
| | - Helena Vilaça-Faria
- 3B's Research Group, I3Bs – Research Institute on Biomaterials, Biodegradables and Biomimetics, University of Minho, Headquarters of the European Institute of Excellence on Tissue Engineering and Regenerative Medicine, AvePark, Parque de Ciência e Tecnologia, Zona Industrial da Gandra, 4805-017, Barco, Guimarães, Portugal
- ICVS/3B's – PT Government Associate Laboratory, Braga, Guimarães, Portugal
| | - Rui L. Reis
- 3B's Research Group, I3Bs – Research Institute on Biomaterials, Biodegradables and Biomimetics, University of Minho, Headquarters of the European Institute of Excellence on Tissue Engineering and Regenerative Medicine, AvePark, Parque de Ciência e Tecnologia, Zona Industrial da Gandra, 4805-017, Barco, Guimarães, Portugal
- ICVS/3B's – PT Government Associate Laboratory, Braga, Guimarães, Portugal
| | - Rogério P. Pirraco
- 3B's Research Group, I3Bs – Research Institute on Biomaterials, Biodegradables and Biomimetics, University of Minho, Headquarters of the European Institute of Excellence on Tissue Engineering and Regenerative Medicine, AvePark, Parque de Ciência e Tecnologia, Zona Industrial da Gandra, 4805-017, Barco, Guimarães, Portugal
- ICVS/3B's – PT Government Associate Laboratory, Braga, Guimarães, Portugal
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Koch J, Romero‐Romero S, Höcker B. Stepwise introduction of stabilizing mutations reveals nonlinear additive effects in de novo TIM barrels. Protein Sci 2024; 33:e4926. [PMID: 38380781 PMCID: PMC10880431 DOI: 10.1002/pro.4926] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Revised: 01/29/2024] [Accepted: 01/30/2024] [Indexed: 02/22/2024]
Abstract
Over the past decades, the TIM-barrel fold has served as a model system for the exploration of how changes in protein sequences affect their structural, stability, and functional characteristics, and moreover, how this information can be leveraged to design proteins from the ground up. After numerous attempts to design de novo proteins with this specific fold, sTIM11 was the first validated de novo design of an idealized four-fold symmetric TIM barrel. Subsequent efforts to enhance the stability of this initial design resulted in the development of DeNovoTIMs, a family of de novo TIM barrels with various stabilizing mutations. In this study, we present an investigation into the biophysical and thermodynamic effects upon introducing a varying number of stabilizing mutations per quarter along the sequence of a four-fold symmetric TIM barrel. We compared the base design DeNovoTIM0 without any stabilizing mutations with variants containing mutations in one, two, three, and all four quarters-designated TIM1q, TIM2q, TIM3q, and DeNovoTIM6, respectively. This analysis revealed a stepwise and nonlinear change in the thermodynamic properties that correlated with the number of mutated quarters, suggesting positive nonadditive effects. To shed light on the significance of the location of stabilized quarters, we engineered two variants of TIM2q which contain the same number of mutations but positioned in different quarter locations. Characterization of these TIM2q variants revealed that the mutations exhibit varying effects on the overall protein stability, contingent upon the specific region in which they are introduced. These findings emphasize that the amount and location of stabilized interfaces among the four quarters play a crucial role in shaping the conformational stability of these four-fold symmetric TIM barrels. Analysis of de novo proteins, as described in this study, enhances our understanding of how sequence variations can finely modulate stability in both naturally occurring and computationally designed proteins.
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Affiliation(s)
| | | | - Birte Höcker
- Department of BiochemistryUniversity of BayreuthBayreuthGermany
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Kortemme T. De novo protein design-From new structures to programmable functions. Cell 2024; 187:526-544. [PMID: 38306980 PMCID: PMC10990048 DOI: 10.1016/j.cell.2023.12.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 12/03/2023] [Accepted: 12/19/2023] [Indexed: 02/04/2024]
Abstract
Methods from artificial intelligence (AI) trained on large datasets of sequences and structures can now "write" proteins with new shapes and molecular functions de novo, without starting from proteins found in nature. In this Perspective, I will discuss the state of the field of de novo protein design at the juncture of physics-based modeling approaches and AI. New protein folds and higher-order assemblies can be designed with considerable experimental success rates, and difficult problems requiring tunable control over protein conformations and precise shape complementarity for molecular recognition are coming into reach. Emerging approaches incorporate engineering principles-tunability, controllability, and modularity-into the design process from the beginning. Exciting frontiers lie in deconstructing cellular functions with de novo proteins and, conversely, constructing synthetic cellular signaling from the ground up. As methods improve, many more challenges are unsolved.
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Affiliation(s)
- Tanja Kortemme
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA; Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA 94158, USA; Chan Zuckerberg Biohub, San Francisco, CA 94158, USA.
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Min X, Yang C, Xie J, Huang Y, Liu N, Jin X, Wang T, Kong Z, Lu X, Ge S, Zhang J, Xia N. Tpgen: a language model for stable protein design with a specific topology structure. BMC Bioinformatics 2024; 25:35. [PMID: 38254030 PMCID: PMC10804651 DOI: 10.1186/s12859-024-05637-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 01/03/2024] [Indexed: 01/24/2024] Open
Abstract
BACKGROUND Natural proteins occupy a small portion of the protein sequence space, whereas artificial proteins can explore a wider range of possibilities within the sequence space. However, specific requirements may not be met when generating sequences blindly. Research indicates that small proteins have notable advantages, including high stability, accurate resolution prediction, and facile specificity modification. RESULTS This study involves the construction of a neural network model named TopoProGenerator(TPGen) using a transformer decoder. The model is trained with sequences consisting of a maximum of 65 amino acids. The training process of TopoProGenerator incorporates reinforcement learning and adversarial learning, for fine-tuning. Additionally, it encompasses a stability predictive model trained with a dataset comprising over 200,000 sequences. The results demonstrate that TopoProGenerator is capable of designing stable small protein sequences with specified topology structures. CONCLUSION TPGen has the ability to generate protein sequences that fold into the specified topology, and the pretraining and fine-tuning methods proposed in this study can serve as a framework for designing various types of proteins.
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Affiliation(s)
- Xiaoping Min
- School of Informatics, Institute of Artificial Intelligence, Xiamen University, No. 422 Siming South Rd, Xiamen, 361005, China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Collaborative Innovation Centers of Biologic Products, Xiamen University, No. 422 Siming South Rd, Xiamen, 361005, China
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, No. 422 Siming South Rd, Xiamen, 361005, China
| | - Chongzhou Yang
- School of Informatics, Institute of Artificial Intelligence, Xiamen University, No. 422 Siming South Rd, Xiamen, 361005, China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Collaborative Innovation Centers of Biologic Products, Xiamen University, No. 422 Siming South Rd, Xiamen, 361005, China
| | - Jun Xie
- School of Informatics, Institute of Artificial Intelligence, Xiamen University, No. 422 Siming South Rd, Xiamen, 361005, China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Collaborative Innovation Centers of Biologic Products, Xiamen University, No. 422 Siming South Rd, Xiamen, 361005, China
| | - Yang Huang
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Collaborative Innovation Centers of Biologic Products, Xiamen University, No. 422 Siming South Rd, Xiamen, 361005, China
- School of Life Sciences, Xiamen University, No. 422 Siming South Rd, Xiamen, 361005, China
| | - Nan Liu
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Collaborative Innovation Centers of Biologic Products, Xiamen University, No. 422 Siming South Rd, Xiamen, 361005, China
- School of Public Health, Xiamen University, No. 422 Siming South Rd, Xiamen, 361005, China
| | - Xiaocheng Jin
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Collaborative Innovation Centers of Biologic Products, Xiamen University, No. 422 Siming South Rd, Xiamen, 361005, China
- School of Public Health, Xiamen University, No. 422 Siming South Rd, Xiamen, 361005, China
| | - Tianshu Wang
- School of Informatics, Institute of Artificial Intelligence, Xiamen University, No. 422 Siming South Rd, Xiamen, 361005, China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Collaborative Innovation Centers of Biologic Products, Xiamen University, No. 422 Siming South Rd, Xiamen, 361005, China
| | - Zhibo Kong
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Collaborative Innovation Centers of Biologic Products, Xiamen University, No. 422 Siming South Rd, Xiamen, 361005, China
- School of Public Health, Xiamen University, No. 422 Siming South Rd, Xiamen, 361005, China
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, No. 422 Siming South Rd, Xiamen, 361005, China
| | - Xiaoli Lu
- Information and Networking Center, Xiamen University, No. 422 Siming South Rd, Xiamen, 361005, China
| | - Shengxiang Ge
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Collaborative Innovation Centers of Biologic Products, Xiamen University, No. 422 Siming South Rd, Xiamen, 361005, China.
- School of Public Health, Xiamen University, No. 422 Siming South Rd, Xiamen, 361005, China.
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, No. 422 Siming South Rd, Xiamen, 361005, China.
| | - Jun Zhang
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Collaborative Innovation Centers of Biologic Products, Xiamen University, No. 422 Siming South Rd, Xiamen, 361005, China
- School of Public Health, Xiamen University, No. 422 Siming South Rd, Xiamen, 361005, China
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, No. 422 Siming South Rd, Xiamen, 361005, China
| | - Ningshao Xia
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Collaborative Innovation Centers of Biologic Products, Xiamen University, No. 422 Siming South Rd, Xiamen, 361005, China
- School of Public Health, Xiamen University, No. 422 Siming South Rd, Xiamen, 361005, China
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, No. 422 Siming South Rd, Xiamen, 361005, China
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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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