Artículo
FrustraPocket: A protein–ligand binding site predictor using energetic local frustration
Freiberger, Maria Ines
; Clemente, Camila Mara
; Valero, Eneko; Pombo, Jorge G.; Leonetti, César O.; Ravetti, Soledad
; Parra, Rodrigo Gonzalo
; Ferreiro, Diego
Fecha de publicación:
12/2022
Editorial:
Cold Spring Harbor Laboratory Press
Revista:
bioRxiv
ISSN:
2692-8205
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
Proteins are evolved polymers that minimize their free energy upon folding to their native states. Still, many folded proteins display energetic conflict between residues in various regions that can be identified as highly frustrated, and these have been shown to be related to several physiological functions. Here we show that small-ligand binding sites are typically enriched in locally frustrated interactions in the unbound state. We built a tool using a simple machine learning algorithm named FrustraPocket that combines the notion of small-molecule binding pockets and the localization of clusters of highly frustrated interactions to identify potential protein-ligand binding sites solely from the unbound forms.
Palabras clave:
Frustration
,
Predictor
,
Ligand binding sites
,
Machine Learning
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Identificadores
Colecciones
Articulos(CCT - CORDOBA)
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - CORDOBA
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - CORDOBA
Articulos(IQUIBICEN)
Articulos de INSTITUTO DE QUIMICA BIOLOGICA DE LA FACULTAD DE CS. EXACTAS Y NATURALES
Articulos de INSTITUTO DE QUIMICA BIOLOGICA DE LA FACULTAD DE CS. EXACTAS Y NATURALES
Citación
Freiberger, Maria Ines; Clemente, Camila Mara; Valero, Eneko; Pombo, Jorge G.; Leonetti, César O.; et al.; FrustraPocket: A protein–ligand binding site predictor using energetic local frustration; Cold Spring Harbor Laboratory Press; bioRxiv; 12-2022; 1-9
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