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Review

VHH Structural Modelling Approaches: A Critical Review

by
Poonam Vishwakarma
1,2,†,
Akhila Melarkode Vattekatte
1,2,†,
Nicolas Shinada
3,‡,
Julien Diharce
1,‡,
Carla Martins
1,2,
Frédéric Cadet
2,4,
Fabrice Gardebien
2,
Catherine Etchebest
1,
Aravindan Arun Nadaradjane
1,2,§ and
Alexandre G. de Brevern
1,2,*,§
1
INSERM UMR_S 1134, BIGR, DSIMB Team, Université de Paris and Université de la Réunion, F-75015 Paris, France
2
INSERM UMR_S 1134, BIGR, DSIMB Team, Université de Paris and Université de la Réunion, F-97715 Saint Denis Messag, France
3
3 SBX Corp., Tokyo-to, Shinagawa-ku, Tokyo 141-0022, Japan
4
PEACCEL, Artificial Intelligence Department, Square Albin Cachot, F-75013 Paris, France
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
‡
These authors contributed equally to this work.
§
These authors contributed equally to this work.
Int. J. Mol. Sci. 2022, 23(7), 3721; https://doi.org/10.3390/ijms23073721
Submission received: 25 February 2022 / Revised: 23 March 2022 / Accepted: 23 March 2022 / Published: 28 March 2022
(This article belongs to the Section Molecular Informatics)
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Abstract

VHH, i.e., VH domains of camelid single-chain antibodies, are very promising therapeutic agents due to their significant physicochemical advantages compared to classical mammalian antibodies. The number of experimentally solved VHH structures has significantly improved recently, which is of great help, because it offers the ability to directly work on 3D structures to humanise or improve them. Unfortunately, most VHHs do not have 3D structures. Thus, it is essential to find alternative ways to get structural information. The methods of structure prediction from the primary amino acid sequence appear essential to bypass this limitation. This review presents the most extensive overview of structure prediction methods applied for the 3D modelling of a given VHH sequence (a total of 21). Besides the historical overview, it aims at showing how model software programs have been shaping the structural predictions of VHHs. A brief explanation of each methodology is supplied, and pertinent examples of their usage are provided. Finally, we present a structure prediction case study of a recently solved VHH structure. According to some recent studies and the present analysis, AlphaFold 2 and NanoNet appear to be the best tools to predict a structural model of VHH from its sequence.
Keywords: antibodies; frameworks; Complementarity Determining Regions; single-domain antibody; secondary structure; sequence–structure relationship; homology and comparative modelling; threading; deep learning; docking antibodies; frameworks; Complementarity Determining Regions; single-domain antibody; secondary structure; sequence–structure relationship; homology and comparative modelling; threading; deep learning; docking

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MDPI and ACS Style

Vishwakarma, P.; Vattekatte, A.M.; Shinada, N.; Diharce, J.; Martins, C.; Cadet, F.; Gardebien, F.; Etchebest, C.; Nadaradjane, A.A.; de Brevern, A.G. VHH Structural Modelling Approaches: A Critical Review. Int. J. Mol. Sci. 2022, 23, 3721. https://doi.org/10.3390/ijms23073721

AMA Style

Vishwakarma P, Vattekatte AM, Shinada N, Diharce J, Martins C, Cadet F, Gardebien F, Etchebest C, Nadaradjane AA, de Brevern AG. VHH Structural Modelling Approaches: A Critical Review. International Journal of Molecular Sciences. 2022; 23(7):3721. https://doi.org/10.3390/ijms23073721

Chicago/Turabian Style

Vishwakarma, Poonam, Akhila Melarkode Vattekatte, Nicolas Shinada, Julien Diharce, Carla Martins, Frédéric Cadet, Fabrice Gardebien, Catherine Etchebest, Aravindan Arun Nadaradjane, and Alexandre G. de Brevern. 2022. "VHH Structural Modelling Approaches: A Critical Review" International Journal of Molecular Sciences 23, no. 7: 3721. https://doi.org/10.3390/ijms23073721

APA Style

Vishwakarma, P., Vattekatte, A. M., Shinada, N., Diharce, J., Martins, C., Cadet, F., Gardebien, F., Etchebest, C., Nadaradjane, A. A., & de Brevern, A. G. (2022). VHH Structural Modelling Approaches: A Critical Review. International Journal of Molecular Sciences, 23(7), 3721. https://doi.org/10.3390/ijms23073721

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