Cargando…
A general model for predicting the binding affinity of reversibly and irreversibly dimerized ligands
Empirical data has shown that bivalent inhibitors can bind a given target protein significantly better than their monomeric counterparts. However, predicting the corresponding theoretical fold improvements has been challenging. The current work builds off the reacted-site probability approach to pro...
Autor principal: | Foreman, Kenneth W. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5699851/ https://www.ncbi.nlm.nih.gov/pubmed/29166663 http://dx.doi.org/10.1371/journal.pone.0188134 |
Ejemplares similares
-
Reversible domain closure modulates GlnBP ligand binding affinity
por: Chen, Qun, et al.
Publicado: (2022) -
Stoichiometry of irreversible ligand binding to a one-dimensional lattice
por: Tsvetkov, Philipp O.
Publicado: (2020) -
PSnpBind-ML: predicting the effect of binding site mutations on protein-ligand binding affinity
por: Ammar, Ammar, et al.
Publicado: (2023) -
Applied machine learning for predicting the lanthanide-ligand binding affinities
por: Chaube, Suryanaman, et al.
Publicado: (2020) -
Protein-ligand binding affinity prediction based on profiles of intermolecular contacts
por: Wang, Debby D., et al.
Publicado: (2022)