Haddock3: A Modular and Versatile Platform for Integrative Modeling of Biomolecular Complexes

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Abstract

HADDOCK is a widely used resource for integrative modeling of a variety of biomolecular complexes that is able to incorporate experimental knowledge into physics-based calculations during complex prediction, refinement, scoring and analysis. Here we introduce HADDOCK3, the new modular version of the program, in which the original, parametrizable albeit rigid pipeline has been first broken down into a catalogue of independent modules and then enriched with powerful analysis tools and third-party integrations. Thanks to this increased flexibility, HADDOCK3 can now handle multiple integrative modeling scenarios, providing a valuable, physics-based tool to enrich and complement the predictions made by machine learning algorithms in the post-AlphaFold era. We present examples of successful applications of HADDOCK3 that were not feasible with the previous versions of HADDOCK, highlighting its expanded capabilities. The HADDOCK3 software source code is freely available from the GitHub repository (https://github.com/haddocking/haddock3) and comes with an online user guide (www.bonvinlab.org/haddock3-user-manual). All example data described in this manuscript are available at https://github.com/haddocking/haddock3-paper-data.

Original languageEnglish
Pages (from-to)7315-7324
Number of pages10
JournalJournal of Chemical Information and Modeling
Volume65
Issue number13
Early online date17 Jun 2025
DOIs
Publication statusPublished - 14 Jul 2025

Bibliographical note

Publisher Copyright:
© 2025 The Authors. Published by American Chemical Society.

Funding

Financial support from Horizon Europe and from the European High Performance Computing Joint Undertaking, projects BioExcel (823830 and 101093290), and from The Netherlands e-Science Center (027.020.G13) is acknowledged.

FundersFunder number
HORIZON EUROPE Framework Programme
European High Performance Computing Joint Undertaking823830, 101093290, G13, 027.020

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