Free-energy-based methods for binding profile determination in a congeneric series of CDK2 inhibitors.

Free-energy pathway methods show great promise in computing the mode of action and the free energy profile associated with the binding of small molecules with proteins, but are generally very computationally demanding. Here we apply a novel approach based on metadynamics and path collective variables. We show that this combination is able to find an optimal reaction coordinate and the free energy profile of binding with explicit solvent and full flexibility, while minimizing human intervention and computational costs.

Dynamic correlation networks in human peroxisome proliferator-activated receptor-γ nuclear receptor protein.

Peroxisome proliferator-activated receptor-γ nuclear receptor (PPAR-γ) belongs to the superfamily of nuclear receptor proteins that function as ligand-dependent transcription factors and plays a specific physiological role as a regulator of lipid metabolism. A number of experimental studies have suggested that allostery plays an important role in the functioning of PPAR-γ. Here we use normal-mode analysis of PPAR-γ to characterize a network of dynamically coupled amino acids that link physiologically relevant binding surfaces such as the ligand-dependent activation domain AF-2 with the ligand binding site and the heterodimer interface.