Cargando…
Simple Coordination Geometry Descriptors Allow to Accurately Predict Metal-Binding Sites in Proteins
[Image: see text] With more than a third of the genome encoding for metal-containing biomolecules, the in silico prediction of how metal ions bind to proteins is crucial in chemistry, biology, and medicine. To date, algorithms for metal-binding site prediction are mainly based on sequence analysis....
Autores principales: | Sciortino, Giuseppe, Garribba, Eugenio, Rodríguez-Guerra Pedregal, Jaime, Maréchal, Jean-Didier |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2019
|
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6648054/ https://www.ncbi.nlm.nih.gov/pubmed/31459585 http://dx.doi.org/10.1021/acsomega.8b03457 |
Ejemplares similares
-
GPathFinder: Identification of Ligand-Binding Pathways by a Multi-Objective Genetic Algorithm
por: Sánchez-Aparicio, José-Emilio, et al.
Publicado: (2019) -
Biospeciation of Potential Vanadium Drugs of Acetylacetonate in the Presence of Proteins
por: Sciortino, Giuseppe, et al.
Publicado: (2020) -
The Effect of Cofactor Binding on the Conformational Plasticity of the Biological Receptors in Artificial Metalloenzymes: The Case Study of LmrR
por: Alonso-Cotchico, Lur, et al.
Publicado: (2019) -
Rationalizing the Decavanadate(V) and Oxidovanadium(IV)
Binding to G-Actin and the Competition with Decaniobate(V)
and ATP
por: Sciortino, Giuseppe, et al.
Publicado: (2020) -
Multiple and Variable Binding of Pharmacologically
Active Bis(maltolato)oxidovanadium(IV) to Lysozyme
por: Ferraro, Giarita, et al.
Publicado: (2022)