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Coarse-grained elastic networks, normal mode analysis and robotics-inspired methods for modeling protein conformational transitions

Ibrahim Al Bluwi 1 Marc Vaisset 2 Thierry Simeon 1 Juan Cortés 1
1 LAAS-RIS - Équipe Robotique et InteractionS
LAAS - Laboratoire d'analyse et d'architecture des systèmes
2 LAAS-IDEA - Service Informatique : Développement, Exploitation et Assistance
LAAS - Laboratoire d'analyse et d'architecture des systèmes
Abstract : This paper presents a method, inspired by robot motion planning algorithms, to model conformational transitions in proteins. The capacity of normal mode analysis to predict directions of collective large-amplitude motions is exploited to bias the conformational exploration. A coarse-grained elastic network model built on short fragments of three residues is proposed for the rapid computation of normal modes. The accurate reconstruction of the all-atom model from the coarse-grained one is achieved using closed-form inverse kinematics. Results show the capacity of the method to model conformational transitions of proteins within a few hours of computing time on a single processor. Tests on a set of ten proteins demonstrate that the computing time scales linearly with the protein size, independently of the protein topology. Further experiments on adenylate kinase show that main features of the transition between the open and closed conformations of this protein are well captured in the computed path.
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https://hal.laas.fr/hal-01981799
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Ibrahim Al Bluwi, Marc Vaisset, Thierry Simeon, Juan Cortés. Coarse-grained elastic networks, normal mode analysis and robotics-inspired methods for modeling protein conformational transitions. IEEE International Conference on Bioinformatics and Biomedicine Workshops, Oct 2012, Philadelphia, United States. pp.40-47, ⟨10.1109/BIBMW.2012.6470359⟩. ⟨hal-01981799⟩

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