Structure‐based computational design of antibody mimetics: challenges and perspectives
The design of antibody mimetics holds great promise for revolutionizing therapeutic interventions by offering alternatives to conventional antibody therapies. Structure‐based computational approaches have emerged as indispensable tools in the rational design of those molecules, enabling the precise...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2025-02-01
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| Series: | FEBS Open Bio |
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| Online Access: | https://doi.org/10.1002/2211-5463.13855 |
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| author | Elton J. F. Chaves Danilo F. Coêlho Carlos H. B. Cruz Emerson G. Moreira Júlio C. M. Simões Manassés J. Nascimento‐Filho Roberto D. Lins |
| author_facet | Elton J. F. Chaves Danilo F. Coêlho Carlos H. B. Cruz Emerson G. Moreira Júlio C. M. Simões Manassés J. Nascimento‐Filho Roberto D. Lins |
| author_sort | Elton J. F. Chaves |
| collection | DOAJ |
| description | The design of antibody mimetics holds great promise for revolutionizing therapeutic interventions by offering alternatives to conventional antibody therapies. Structure‐based computational approaches have emerged as indispensable tools in the rational design of those molecules, enabling the precise manipulation of their structural and functional properties. This review covers the main classes of designed antigen‐binding motifs, as well as alternative strategies to develop tailored ones. We discuss the intricacies of different computational protein–protein interaction design strategies, showcased by selected successful cases in the literature. Subsequently, we explore the latest advancements in the computational techniques including the integration of machine and deep learning methodologies into the design framework, which has led to an augmented design pipeline. Finally, we verse onto the current challenges that stand in the way between high‐throughput computer design of antibody mimetics and experimental realization, offering a forward‐looking perspective into the field and the promises it holds to biotechnology. |
| format | Article |
| id | doaj-art-55916da14f704763b110623382adf5da |
| institution | Kabale University |
| issn | 2211-5463 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | FEBS Open Bio |
| spelling | doaj-art-55916da14f704763b110623382adf5da2025-02-03T10:59:30ZengWileyFEBS Open Bio2211-54632025-02-0115222323510.1002/2211-5463.13855Structure‐based computational design of antibody mimetics: challenges and perspectivesElton J. F. Chaves0Danilo F. Coêlho1Carlos H. B. Cruz2Emerson G. Moreira3Júlio C. M. Simões4Manassés J. Nascimento‐Filho5Roberto D. Lins6Aggeu Magalhães Institute Oswaldo Cruz Foundation Recife BrazilDepartment of Fundamental Chemistry Federal University of Pernambuco Recife BrazilInstitute of Structural and Molecular Biology University College London UKFiocruz Genomics Network BrazilAggeu Magalhães Institute Oswaldo Cruz Foundation Recife BrazilAggeu Magalhães Institute Oswaldo Cruz Foundation Recife BrazilAggeu Magalhães Institute Oswaldo Cruz Foundation Recife BrazilThe design of antibody mimetics holds great promise for revolutionizing therapeutic interventions by offering alternatives to conventional antibody therapies. Structure‐based computational approaches have emerged as indispensable tools in the rational design of those molecules, enabling the precise manipulation of their structural and functional properties. This review covers the main classes of designed antigen‐binding motifs, as well as alternative strategies to develop tailored ones. We discuss the intricacies of different computational protein–protein interaction design strategies, showcased by selected successful cases in the literature. Subsequently, we explore the latest advancements in the computational techniques including the integration of machine and deep learning methodologies into the design framework, which has led to an augmented design pipeline. Finally, we verse onto the current challenges that stand in the way between high‐throughput computer design of antibody mimetics and experimental realization, offering a forward‐looking perspective into the field and the promises it holds to biotechnology.https://doi.org/10.1002/2211-5463.13855de novo designdeep learningmachine learningprotein engineeringprotein structure |
| spellingShingle | Elton J. F. Chaves Danilo F. Coêlho Carlos H. B. Cruz Emerson G. Moreira Júlio C. M. Simões Manassés J. Nascimento‐Filho Roberto D. Lins Structure‐based computational design of antibody mimetics: challenges and perspectives FEBS Open Bio de novo design deep learning machine learning protein engineering protein structure |
| title | Structure‐based computational design of antibody mimetics: challenges and perspectives |
| title_full | Structure‐based computational design of antibody mimetics: challenges and perspectives |
| title_fullStr | Structure‐based computational design of antibody mimetics: challenges and perspectives |
| title_full_unstemmed | Structure‐based computational design of antibody mimetics: challenges and perspectives |
| title_short | Structure‐based computational design of antibody mimetics: challenges and perspectives |
| title_sort | structure based computational design of antibody mimetics challenges and perspectives |
| topic | de novo design deep learning machine learning protein engineering protein structure |
| url | https://doi.org/10.1002/2211-5463.13855 |
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