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Adrien S. J. Melquiond

Researcher at Utrecht University

Publications -  31
Citations -  3329

Adrien S. J. Melquiond is an academic researcher from Utrecht University. The author has contributed to research in topics: Macromolecular docking & Molecular Docking Simulation. The author has an hindex of 21, co-authored 31 publications receiving 2460 citations. Previous affiliations of Adrien S. J. Melquiond include University of Paris & University Medical Center Utrecht.

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The HADDOCK2.2 Web Server: User-Friendly Integrative Modeling of Biomolecular Complexes.

TL;DR: The updated version 2.2.2 of the HADDOCK portal is presented, which offers new features such as support for mixed molecule types, additional experimental restraints and improved protocols, all of this in a user-friendly interface.
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A unified conformational selection and induced fit approach to protein-peptide docking

TL;DR: An ensemble, flexible protein-peptide docking protocol that combines conformational selection and induced fit mechanisms that should open the route to the modeling of challenging systems such as disorder-order transitions taking place upon binding, significantly expanding the applicability limit of biomolecular interaction modeling by docking.
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Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment.

Marc F. Lensink, +104 more
- 01 Jun 2016 - 
TL;DR: Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations, and that docking procedures tend to perform better than standard homology modeled techniques.
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Building Macromolecular Assemblies by Information-driven Docking INTRODUCING THE HADDOCK MULTIBODY DOCKING SERVER

TL;DR: The High Ambiguity-Driven DOCKing (HADDOCK) as mentioned in this paper is one of the most popular methods for multibody docking, which can deal with multiple molecules simultaneously.
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Clustering biomolecular complexes by residue contacts similarity.

TL;DR: A simple similarity measure for structural clustering based on atomic contacts—the fraction of common contacts—is presented and it is shown that this method produces very compact clusters in remarkably short time when applied to a collection of binary and multicomponent protein–protein and protein–DNA complexes.