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Discriminating physiological from non-physiological interfaces in structures of protein complexes: a community-wide study
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  • Hugo Schweke,
  • Qifang Xu,
  • Gerardo Tauriello,
  • Lorenzo Pantolini,
  • Torsten Schwede,
  • Frédéric Cazals,
  • Alix Lhéritier,
  • Juan Fernandez-Recio,
  • Luis Ángel Rodríguez-Lumbreras,
  • Ora Schueler-Furman,
  • Julia K. Varga,
  • Brian Jiménez-García,
  • Manon F. Réau,
  • Alexandre Bonvin,
  • Castrense Savojardo,
  • Pier-Luigi Martelli,
  • Rita Casadio,
  • Jérôme Tubiana,
  • Haim Wolfson,
  • Romina Oliva,
  • Didier Barradas-Bautista,
  • Tiziana Ricciardelli,
  • Luigi Cavallo,
  • Česlovas Venclovas,
  • Kliment Olechnovič,
  • Raphael Guerois,
  • Jessica Andreani,
  • Juliette Martin,
  • Xiao Wang,
  • Daisuke Kihara ,
  • Anthony Marchand,
  • Bruno Correia,
  • Xiaoqin Zou,
  • Sucharita Dey,
  • Roland Dunbrack,
  • Emmanuel Levy,
  • Shoshana Wodak
Hugo Schweke
Weizmann Institute of Science
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Qifang Xu
Fox Chase Cancer Center
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Gerardo Tauriello
University of Basel Department Biozentrum
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Lorenzo Pantolini
University of Basel Department Biozentrum
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Torsten Schwede
University of Basel Department Biozentrum
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Frédéric Cazals
Inria Sophia Antipolis Mediterranean Research Centre
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Alix Lhéritier
Amadeus SAS
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Juan Fernandez-Recio
Instituto de Ciencias de la Vid y del Vino
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Luis Ángel Rodríguez-Lumbreras
Instituto de Ciencias de la Vid y del Vino
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Ora Schueler-Furman
Hebrew University of Jerusalem Institute for Medical Research Israel-Canada
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Julia K. Varga
Hebrew University of Jerusalem Institute for Medical Research Israel-Canada
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Brian Jiménez-García
Utrecht University & Zymvol Biomodeling SL
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Manon F. Réau
Utrecht University Faculty of Science
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Alexandre Bonvin
Utrecht University Faculty of Science
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Castrense Savojardo
University of Bologna
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Pier-Luigi Martelli
University of Bologna
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Rita Casadio
University of Bologna
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Jérôme Tubiana
Tel Aviv University Blavatnik School of Computer Science
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Haim Wolfson
Tel Aviv University Blavatnik School of Computer Science
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Romina Oliva
University of Naples Parthenope
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Didier Barradas-Bautista
King Abdullah University of Science and Technology
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Tiziana Ricciardelli
King Abdullah University of Science and Technology
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Luigi Cavallo
King Abdullah University of Science and Technology
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Česlovas Venclovas
Vilnius University
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Kliment Olechnovič
Vilnius University
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Raphael Guerois
CEA
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Jessica Andreani
CEA
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Juliette Martin
Université Claude Bernard Lyon 1
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Xiao Wang
Purdue University
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Daisuke Kihara
Purdue University
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Anthony Marchand
EPFL
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Bruno Correia
EPFL
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Xiaoqin Zou
Dalton Cardiovascular Research Center, Institute for Data Science and Informatics, University of Missouri
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Sucharita Dey
Indian Institute of Technology Jodhpur
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Roland Dunbrack
Fox Chase Cancer Center
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Emmanuel Levy
Weizmann Institute of Science
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Shoshana Wodak
VIB-VUB Center for Structural Biology

Corresponding Author:shoshana.wodak@gmail.com

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Abstract

Reliably scoring and ranking candidate models of protein complexes and assigning their oligomeric state from the structure of the crystal lattice represent outstanding challenges. A community-wide effort was launched to tackle these challenges. The latest resources on protein complexes and interfaces were exploited to derive a benchmark dataset consisting of 1677 homodimer protein crystal structures, including a balanced mix of physiological and non-physiological complexes. The non-physiological complexes in the benchmark were selected to bury a similar or larger interface area than their physiological counterparts, making it more difficult for scoring functions to differentiate between them. Next, 252 functions for scoring protein-protein interfaces previously developed by 13 groups were collected and evaluated for their ability to discriminate between physiological and non-physiological complexes. A simple consensus score generated using the best performing score of each of the 13 groups, and a cross-validated Random Forest (RF) classifier were created. Both approaches showed excellent performance, with an area under the Receiver Operating Characteristic (ROC) curve of 0.93 and 0.94 respectively, outperforming individual scores developed by different groups. Additionally, AlphaFold2 engines were shown to recall the physiological dimers with significantly higher accuracy than the non-physiological set, lending support for the pertinence of our benchmark dataset. Optimizing the combined power of interface scoring functions and evaluating it on challenging benchmark datasets appears to be a promising strategy.
04 Feb 2023Submitted to PROTEOMICS
06 Feb 2023Submission Checks Completed
06 Feb 2023Assigned to Editor
06 Feb 2023Review(s) Completed, Editorial Evaluation Pending
06 Feb 2023Reviewer(s) Assigned
27 Feb 2023Editorial Decision: Revise Minor
08 May 2023Review(s) Completed, Editorial Evaluation Pending
08 May 20231st Revision Received
11 May 2023Editorial Decision: Accept