Predicting interacting hotspots for nanobodies' binding using triplets of residues

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  • dc.contributor.author Hamdani, Rahma
  • dc.contributor.author Cianferoni, Damiano
  • dc.contributor.author Reche, Raul
  • dc.contributor.author Delgado Blanco, Javier
  • dc.contributor.author Serrano Pubull, Luis, 1982-
  • dc.date.accessioned 2025-10-09T05:49:26Z
  • dc.date.available 2025-10-09T05:49:26Z
  • dc.date.issued 2025
  • dc.description.abstract Protein-protein interactions (PPI) are fundamental to cellular signaling, forming robust networks that govern critical biological processes such as immune response, cell growth, and signal transduction. Nanobody-based therapies have emerged as a key strategy for modulating PPIs, offering exceptional potential due to their high specificity, stability, and ability to access challenging epitopes on PPI interfaces inside cells. The rational design of nanobodies relies mainly on understanding and predicting their binding regions, particularly the residues that contribute the most to the binding energy (binding hotspots). Existing computational methods do not fully provide a scalable solution for hotspot identification in nanobody design, leaving a critical gap in the rational design of these therapeutics. Here, we present a scalable and structure-aware algorithm for hotspot prediction in nanobody design. The algorithm queries a curated database of triplets of interacting residues obtained from ~20,000 non-redundant PDB structures. We showed that these triplets contain structural and energetic information, being able to assess the stability effect of residue variations in protein structures, Pearson R = 0.63 (MSE = 1.58 kcal/mol). More important than effects on stability is the ability of the algorithm to predict binding hotspots of protein-protein generic complexes and more specifically in complexes containing nanobodies. HotspotPred reached an accuracy of 0.73 for hotspot residue identification in a protein interaction dataset of 1160 Alanine mutants and correctly identified in 63.4% of the cases we predicted at least 2 residues on the binding surface.
  • dc.description.sponsorship This publication is part of the grant PRE2022-101389, funded by MICIU/AEI /10.13039/501100011033 and by the ESF+, and of the project PID2021-122341NB-I00, funded by MCIN/ AEI / 10.13039/501100011033 / FEDER, UE). This project has also received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No 101020135).
  • dc.format.mimetype application/pdf
  • dc.identifier.citation Hamdani R, Cianferoni D, Reche R, Delgado J, Serrano L. Predicting interacting hotspots for nanobodies' binding using triplets of residues. Protein Sci. 2025 Aug;34(8):e70220. DOI: 10.1002/pro.70220
  • dc.identifier.doi http://dx.doi.org/10.1002/pro.70220
  • dc.identifier.issn 0961-8368
  • dc.identifier.uri http://hdl.handle.net/10230/71444
  • dc.language.iso eng
  • dc.publisher Wiley
  • dc.relation.ispartof Protein science: a publication of the Protein Society. 2025 Aug;34(8):e70220
  • dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/101020135
  • dc.relation.projectID info:eu-repo/grantAgreement/ES/3PE/PID2021-122341NB-I00
  • dc.relation.projectID info:eu-repo/grantAgreement/ES/3PE/PRE2022-101389
  • dc.rights © 2025 The Author(s). Protein Science published by Wiley Periodicals LLC on behalf of The Protein Society. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
  • dc.rights.accessRights info:eu-repo/semantics/openAccess
  • dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/
  • dc.subject.keyword Binding hotspots
  • dc.subject.keyword Computational prediction
  • dc.subject.keyword Drug discovery
  • dc.subject.keyword Nanobodies
  • dc.subject.keyword Protein–protein interactions
  • dc.subject.keyword Structural biology
  • dc.title Predicting interacting hotspots for nanobodies' binding using triplets of residues
  • dc.type info:eu-repo/semantics/article
  • dc.type.version info:eu-repo/semantics/publishedVersion

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