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Poster De Conférence Année : 2021

Data-driven identification of structural patterns associated with RNA binding in RNA Recognition Motif domains

Résumé

Proteins containing one or more RNA Recognition Motif (RRM) domains perform important regulation functions through binding to specific RNA sequences. Our project is to help design new RRM proteins by providing data-driven rules and knowledge, based on the 3D structures of RRM domains. Protein domain classifications were screened to identify the most comprehensive set of RRM families for which one or more 3D structures are available. We created a master alignment for all available RRM 3D structures using Pfam (PF00076) seed alignment and the Kpax tool. Amino-acid properties and structural descriptors like torsion angles or accessibility were linked to the nucleotide-binding capacity at each position, and compared in RNA bound versus unbound structures. The extracted patterns will help to predict RNA binding propensity at the domain and residue level, and to model the 3D structure of the complex. Such patterns will be tested in vitro/vivo by our collaborators.
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Dates et versions

hal-03784168 , version 1 (23-09-2022)

Identifiants

  • HAL Id : hal-03784168 , version 1

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Hrishikesh Dhondge, Martínez Joel Roca, Vranken Wim, Marie-Dominique Devignes, Isaure Chauvot de Beauchêne. Data-driven identification of structural patterns associated with RNA binding in RNA Recognition Motif domains. Student Council Symposium (SCS) 2021, Jul 2021, Virtual, France. ⟨hal-03784168⟩
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