Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Structural Modeling of Nanobodies: A Benchmark of State-of-the-Art Artificial Intelligence Programs

Version 1 : Received: 10 April 2023 / Approved: 11 April 2023 / Online: 11 April 2023 (05:13:24 CEST)

A peer-reviewed article of this Preprint also exists.

Valdés-Tresanco, M.S.; Valdés-Tresanco, M.E.; Jiménez-Gutiérrez, D.E.; Moreno, E. Structural Modeling of Nanobodies: A Benchmark of State-of-the-Art Artificial Intelligence Programs. Molecules 2023, 28, 3991. Valdés-Tresanco, M.S.; Valdés-Tresanco, M.E.; Jiménez-Gutiérrez, D.E.; Moreno, E. Structural Modeling of Nanobodies: A Benchmark of State-of-the-Art Artificial Intelligence Programs. Molecules 2023, 28, 3991.

Abstract

The number of applications for nanobodies is steadily expanding, positioning these molecules as fast-growing biologic products in the biotechnology market. Several of their applications require protein engineering, which in turn would greatly benefit from having a reliable structural model of the nanobody of interest. However, as with antibodies, structural modeling of nanobodies is still a challenge. With the rise of artificial intelligence (AI), several methods have been developed in recent years that attempt to solve the problem of protein modeling. In this study, we have compared the performance in nanobody modeling of several state-of-the-art AI-based programs, either designed for general protein modeling, such as AlphaFold2, OmegaFold, ESMFold and Yang-Server, or specifically designed for antibody modeling, such as IgFold, and Nanonet. While all these programs performed rather well in constructing the nanobody framework and CDRs 1 and 2, modeling of CDR3 sill represents a big challenge. Interestingly, tailoring an AI method for antibody modeling does not necessarily translate into better results for nanobodies.

Keywords

artificial intelligence; protein structure; protein modeling; nanobody; antibody

Subject

Biology and Life Sciences, Biochemistry and Molecular Biology

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.

Leave a public comment
Send a private comment to the author(s)
* All users must log in before leaving a comment
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.