Designing of nanobodies against Dengue virus Capsid: a computational affinity maturation approach

Chaudhuri, Dwaipayan; Majumder, Satyabrata; Datta, Joyeeta; Giri, Kalyan

doi:10.1080/07391102.2022.2029773

“…Higher affinity nanobodies can be isolated by random limited mutagenesis ( 16 ) and structure-directed evolution ( 17 ), which is comparable to enhanced intracellular antibody capture ( 18 ). Computational affinity maturation may also be considered, in which residues in the complementary determining regions (CDRs) are altered based on the interface analysis and energy calculations ( 19 , 20 ). The Rosetta software suite addressing protein structure prediction and design ( 21 ) can be used for redesign of antigen-antibody interfaces starting from existing experimental or computational models ( 22 , 23 ).…”

mentioning

confidence: 99%

Evolution of nanobodies specific for BCL11A

Yin

¹

,

Izadi

²

,

Tenglin

³

et al. 2023

Proc. Natl. Acad. Sci. U.S.A.

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Transcription factors (TFs) control numerous genes that are directly relevant to many human disorders. However, developing specific reagents targeting TFs within intact cells is challenging due to the presence of highly disordered regions within these proteins. Intracellular antibodies offer opportunities to probe protein function and validate therapeutic targets. Here, we describe the optimization of nanobodies specific for BCL11A, a validated target for the treatment of hemoglobin disorders. We obtained first-generation nanobodies directed to a region of BCL11A comprising zinc fingers 4 to 6 (ZF456) from a synthetic yeast surface display library, and employed error-prone mutagenesis, structural determination, and molecular modeling to enhance binding affinity. Engineered nanobodies recognized ZF6 and mediated targeted protein degradation (TPD) of BCL11A protein in erythroid cells, leading to the anticipated reactivation of fetal hemoglobin (HbF) expression. Evolved nanobodies distinguished BCL11A from its close paralog BCL11B, which shares an identical DNA-binding specificity. Given the ease of manipulation of nanobodies and their exquisite specificity, nanobody-mediated TPD of TFs should be suitable for dissecting regulatory relationships of TFs and gene targets and validating therapeutic potential of proteins of interest.

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“…Computational affinity maturation of nanobodies refers to the process of using computational techniques to enhance the binding affinity of nanobodies by iteratively designing and optimising nanobody sequences or structures to improve their interactions with target antigens [123]. Computational methods enable the exploration of vast sequence and structural space to identify mutations [136,137], modifications or non-natural amino acid incorporations [108] that enhance nanobody binding affinity while maintaining specificity and stability [107]. A computational protocol based on MD simulations, molecular docking scores, FoldX stability prediction, CamSol and A3D solubility estimations resulted in accurate scoring methodologies for predicting experimental yields and identifying the structural modifications induced by mutations [138].…”

Section: Computational Affinity Maturation Of Nanobodiesmentioning

confidence: 99%

Nanobody Engineering: Computational Modelling and Design for Biomedical and Therapeutic Applications

El Salamouni,

Cater,

Spenkelink

et al. 2024

Preprint

0

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Nanobodies, the smallest functional antibody fragment derived from camelid heavy-chain-only antibodies, have emerged as powerful tools for diverse biomedical applications. In this comprehensive review, we discuss the structural characteristics, functional properties, and computational approaches driving the design and optimisation of synthetic nanobodies. We explore their unique antigen-binding domains, highlighting the critical role of complementarity-determining regions in target recognition and specificity. This review further underscores the advantages of nanobodies over conventional antibodies from a biosynthesis perspective, including their small size, stability, and solubility, which make them ideal candidates for economical antigen capture in diagnostics, therapeutics, and biosensing. We discuss the recent advancements in computational methods for nanobody modelling, epitope prediction, and affinity maturation, shedding light on their intricate antigen-binding mechanisms and conformational dynamics. Finally, we examine a direct example of how computational design strategies were implemented for improving a nanobody-based immunosensor, known as a Quenchbody. Through combining experimental findings and computational insights, this review elucidates the transformative impact of nanobodies in biotechnology and biomedical research, offering a roadmap for future advancements and applications in healthcare and diagnostics.

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“…Computational affinity maturation of nanobodies refers to the process of using computational techniques to enhance the binding affinity of nanobodies by iteratively designing and optimising nanobody sequences or structures to improve their interactions with target antigens [121]. Computational methods enable the exploration of vast sequence and structural space to identify mutations [134,135], modifications or non-natural amino acid incorporations [77] that enhance nanobody binding affinity while maintaining specificity and stability [76]. A computational protocol based on MD simulations, molecular docking scores, FoldX stability prediction, CamSol and A3D solubility estimations resulted in accurate scoring methodologies for predicting experimental yields and identifying the structural modifications induced by mutations [136].…”

Section: Computational Affinity Maturation Of Nanobodiesmentioning

confidence: 99%

Nanobody Engineering: Computational Modelling and Design for Biomedical and Therapeutic Applications

El Salamouni,

Cater,

Spenkelink

et al. 2024

Preprint

0

View full text Add to dashboard Cite

Nanobodies, the smallest functional antibody fragment derived from camelid heavy-chain-only antibodies, have emerged as powerful tools for diverse biomedical applications. In this comprehensive review, we discuss the structural characteristics, functional properties, and computational approaches driving the design and optimisation of synthetic nanobodies. We explore their unique antigen-binding domains, highlighting the critical role of complementarity-determining regions in target recognition and specificity. This review further underscores the advantages of nanobodies over conventional antibodies from a biosynthesis perspective, including their small size, stability, and solubility, which make them ideal candidates for economical antigen capture in diagnostics, therapeutics, and biosensing. We discuss the recent advancements in computational methods for nanobody modelling, epitope prediction, and affinity maturation, shedding light on their intricate antigen-binding mechanisms and conformational dynamics. Finally, we examine a direct example of how computational design strategies were implemented for improving a nanobody-based immunosensor, known as a Quenchbody. Through combining experimental findings and computational insights, this review elucidates the transformative impact of nanobodies in biotechnology and biomedical research, offering a roadmap for future advancements and applications in healthcare and diagnostics.

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Designing of nanobodies against Dengue virus Capsid: a computational affinity maturation approach

Cited by 11 publications

References 29 publications

Evolution of nanobodies specific for BCL11A

Evolution of nanobodies specific for BCL11A

Nanobody Engineering: Computational Modelling and Design for Biomedical and Therapeutic Applications

Nanobody Engineering: Computational Modelling and Design for Biomedical and Therapeutic Applications

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