Peroxisome proliferator-activated receptor γ (PPARγ) functions in various biological processes, including macrophage and adipocyte differentiation. Several natural lipid metabolites have been shown to activate PPARγ. Here, we report that some PPARγ ligands, including 15-deoxy-Δ^12,14-prostaglandin J₂, covalently bind to a cysteine residue in the PPARγ ligand binding pocket through a Michael addition reaction by an α,β-unsaturated ketone. Using rhodamine-maleimide as well as mass spectroscopy, we showed that the binding of these ligands is covalent and irreversible. Consistently, mutation at the cysteine residue abolished abilities of these ligands to activate PPARγ, but not of BRL49653, a non-covalent synthetic agonist, indicating that covalent binding of the α,β-unsaturated ketone in the natural ligands was required for their transcriptional activities. Screening of lipid metabolites containing the α,β-unsaturated ketone revealed that several other oxidized metabolites of hydroxyeicosatetraenoic acid, hydroxyeicosadecaenoic acid, and prostaglandins can also function as novel covalent ligands for PPARγ. We propose that PPARγ senses oxidation of fatty acids by recognizing such an α,β-unsaturated ketone as a common moiety.

Protein folding and protein–ligand docking have long persisted as important subjects in biophysics. Using multicanonical molecular dynamics (McMD) simulations with realistic expressions, i.e., all-atom protein models and an explicit solvent, free-energy landscapes have been computed for several systems, such as the folding of peptides/proteins composed of a few amino acids up to nearly 60 amino-acid residues, protein–ligand interactions, and coupled folding and binding of intrinsically disordered proteins. Recent progress in conformational sampling and its applications to biophysical systems are reviewed in this report, including descriptions of several outstanding studies. In addition, an algorithm and detailed procedures used for multicanonical sampling are presented along with the methodology of adaptive umbrella sampling. Both methods control the simulation so that low-probability regions along a reaction coordinate are sampled frequently. The reaction coordinate is the potential energy for multicanonical sampling and is a structural identifier for adaptive umbrella sampling. One might imagine that this probability control invariably enhances conformational transitions among distinct stable states, but this study examines the enhanced conformational sampling of a simple system and shows that reasonably well-controlled sampling slows the transitions. This slowing is induced by a rapid change of entropy along the reaction coordinate. We then provide a recipe to speed up the sampling by loosening the rapid change of entropy. Finally, we report all-atom McMD simulation results of various biophysical systems in an explicit solvent.

The conformational transition states of a β‐hairpin peptide in explicit water were identified from the free energy landscapes obtained from the multicanonical ensemble, using an enhanced conformational sampling calculation. The β‐hairpin conformations were significant at 300 K in the landscape, and the typical nuclear Overhauser effect signals were reproduced, consistent with the previously reported experiment. In contrast, the disordered conformations were predominant at higher temperatures. Among the stable conformations at 300 K, there were several free energy barriers, which were not visible in the landscapes formed with the conventional parameters. We identified the transition states around the saddle points along the putative folding and unfolding paths between the β‐hairpin and the disordered conformations in the landscape. The characteristic features of these transition states are the predominant hydrophobic contacts and the several hydrogen bonds among the side‐chains, as well as some of the backbone hydrogen bonds. The unfolding simulations at high temperatures, 400 K and 500 K, and their principal component analyses also provided estimates for the transition state conformations, which agreed well with those at 400 K and 500 K deduced from the current free energy landscapes at 400 K and 500 K, respectively. However, the transition states at high temperatures were much more widely distributed on the landscape than those at 300 K, and their conformations were different.