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Brazilian Symposium on Bioinformatics

BSB 2020: Advances in Bioinformatics and Computational Biology pp 93–104Cite as

Unraveling the Role of Nanobodies Tetrad on Their Folding and Stability Assisted by Machine and Deep Learning Algorithms

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Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 12558))

Abstract

Nanobodies (Nbs) achieve high solubility and stability due to four conserved residues referred to as the Nb tetrad. While several studies have highlighted the importance of the Nbs tetrad to their stability, a detailed molecular picture of their role has not been provided. In this work, we have used the Rosetta package to engineer synthetic Nbs lacking the Nb tetrad and used the Rosetta Energy Function to assess the structural features of the native and designed Nbs concerning the presence of the Nb tetrad. To develop a classification model, we have benchmarked three different machine learning (ML) and deep learning (DL) algorithms and concluded that more complex models led to better binary classification for our dataset. Our results show that these two classes of Nbs differ significantly in features related to solvation energy and native-like structural properties. Notably, the loss of stability due to the tetrad’s absence is chiefly driven by the entropic contribution.

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Acknowledgements

This work has been funded by FACEPE, CAPES, CNPq, and FIOCRUZ. We acknowledge the LNCC for the availability of resources and support.

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Authors and Affiliations

  1. Department of Fundamental Chemistry, Federal University of Pernambuco, Recife, PE, 50670-560, Brazil

    Matheus Vitor Ferreira Ferraz & Roberto Dias Lins

  2. Department of Virology, Aggeu Magalhães Institute, Oswaldo Cruz Foundation, Recife, PE, 50670-420, Brazil

    Matheus Vitor Ferreira Ferraz, Wenny Camilla dos Santos Adan & Roberto Dias Lins

Authors
  1. Matheus Vitor Ferreira Ferraz
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  2. Wenny Camilla dos Santos Adan
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  3. Roberto Dias Lins
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Correspondence to Roberto Dias Lins .

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Editors and Affiliations

  1. University of São Paulo, São Paulo, Brazil

    João C. Setubal

  2. Instituto Federal de Goiás, Formosa, Goiás, Brazil

    Waldeyr Mendes Silva

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Ferraz, M.V.F., dos Santos Adan, W.C., Lins, R.D. (2020). Unraveling the Role of Nanobodies Tetrad on Their Folding and Stability Assisted by Machine and Deep Learning Algorithms. In: Setubal, J.C., Silva, W.M. (eds) Advances in Bioinformatics and Computational Biology. BSB 2020. Lecture Notes in Computer Science(), vol 12558. Springer, Cham. https://doi.org/10.1007/978-3-030-65775-8_9

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  • DOI: https://doi.org/10.1007/978-3-030-65775-8_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-65774-1

  • Online ISBN: 978-3-030-65775-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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