Protein dynamics play a critical role in ligand binding, and different models have been proposed to explain the relationships between protein motion and molecular recognition. Here, we present a study of ligand-binding processes associated with large conformational changes of a protein to elucidate the critical choices in ensemble-docking approaches for effective prediction of the binding geometry. Two study cases were selected in which binding involves different protein motions and intermolecular interactions and, accordingly, conformational selection and induced-fit mechanisms play different roles: binding of multiple ligands to the acetylcholine binding protein and highly specific binding of D-allose to the allose binding protein. Our results indicated that the ensemble-docking technique can provide reliable predictions of the structure of ligand-protein complexes, starting from simulations of the apo systems, when suitable methodological choices are made according to the different mechanistic scenarios. In particular, accelerated molecular dynamics simulations are suitable for conformational sampling when the unbound and bound states are separated by high energy barriers, provided that the acceleration parameters are carefully set to extensively sample the relevant conformations. A strategy specifically developed for geometric clustering of the binding site proved to be effective for selecting a set of conformations relevant to binding from the MD trajectory. Specific strategies have to be selected to incorporate different degrees of ligand-induced protein flexibility into the docking or pose-refinement steps.

Motta, S., & Bonati, L. (2017). Modeling Binding with Large Conformational Changes: Key Points in Ensemble-Docking Approaches. JOURNAL OF CHEMICAL INFORMATION AND MODELING, 57(7), 1563-1578 [10.1021/acs.jcim.7b00125].

Modeling Binding with Large Conformational Changes: Key Points in Ensemble-Docking Approaches

MOTTA, STEFANO
Primo
;
BONATI, LAURA
2017

Abstract

Protein dynamics play a critical role in ligand binding, and different models have been proposed to explain the relationships between protein motion and molecular recognition. Here, we present a study of ligand-binding processes associated with large conformational changes of a protein to elucidate the critical choices in ensemble-docking approaches for effective prediction of the binding geometry. Two study cases were selected in which binding involves different protein motions and intermolecular interactions and, accordingly, conformational selection and induced-fit mechanisms play different roles: binding of multiple ligands to the acetylcholine binding protein and highly specific binding of D-allose to the allose binding protein. Our results indicated that the ensemble-docking technique can provide reliable predictions of the structure of ligand-protein complexes, starting from simulations of the apo systems, when suitable methodological choices are made according to the different mechanistic scenarios. In particular, accelerated molecular dynamics simulations are suitable for conformational sampling when the unbound and bound states are separated by high energy barriers, provided that the acceleration parameters are carefully set to extensively sample the relevant conformations. A strategy specifically developed for geometric clustering of the binding site proved to be effective for selecting a set of conformations relevant to binding from the MD trajectory. Specific strategies have to be selected to incorporate different degrees of ligand-induced protein flexibility into the docking or pose-refinement steps.
No
Articolo in rivista - Articolo scientifico
Scientifica
Accelerated Molecular Dynamics; Ensemble-Docking; Ligand Binding; Clustering; Conformational selection; Induced Fit; Acetylcholine Binding Protein; Allose Binding Protein
English
1563
1578
16
Motta, S., & Bonati, L. (2017). Modeling Binding with Large Conformational Changes: Key Points in Ensemble-Docking Approaches. JOURNAL OF CHEMICAL INFORMATION AND MODELING, 57(7), 1563-1578 [10.1021/acs.jcim.7b00125].
Motta, S; Bonati, L
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10281/169346
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