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Article Dans Une Revue Journal of Computational Chemistry Année : 2019

Modeling large protein–glycosaminoglycan complexes using a fragment‐based approach

Résumé

Glycosaminoglycans (GAGs), a major constituant of the extracellular matrix, participate in cell-signaling by binding specific proteins. Structural data on protein-GAG interactions is crucial to understand and modulate these signaling processes, with potential applications in regenerative medicine. However, experimental and theoretical approaches used to study GAG-protein systems are challenged by GAGs high flexibility limiting the conformational sampling above a certain size, and by the scarcity of GAG-specific computational tools. We present for the first-time an automated fragment-based method for docking GAGs on a protein binding site. In this approach, trimeric GAG fragments are flexibly docked to the protein, assembled based on their spacial overlap, and refined by molecular dynamics. The method appeared more successful than the classical full-ligand approach for most of 13 tested complexes with known structure. The approach is particularly promising for docking of long GAG chains, which represents a bottleneck for classical docking approaches applied to these systems.
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Dates et versions

hal-02088192 , version 1 (02-04-2019)

Identifiants

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Sergey Samsonov, Martin Zacharias, Isaure Chauvot de Beauchêne. Modeling large protein–glycosaminoglycan complexes using a fragment‐based approach. Journal of Computational Chemistry, 2019, 40 (14), pp.1429-1439. ⟨10.1002/jcc.25797⟩. ⟨hal-02088192⟩
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