In-Cell Dynamics: The Next Focus of All-Atom Simulations

Enzymes in a human cytoplasm model organize into submetabolon complexes

Enzyme-enzyme interactions are fundamental to the function of cells. Their atomistic mechanisms remain elusive mainly due to limitations of in-cell measurements. We address this challenge by atomistically modeling, for a total of ≈80 μs, a slice of the human cell cytoplasm that includes three successive enzymes along the glycolytic pathway: glyceraldehyde-3-phosphate dehydrogenase (GAPDH), phosphoglycerate kinase (PGK), and phosphoglycerate mutase (PGM). We tested the model for nonspecific protein stickiness, an artifact of current atomistic force fields in crowded environments. The simulations reveal that the human enzymes co-organize in-cell into transient submetabolon complexes, consistent with previous experimental results. Our data both reiterate known specificity between GAPDH and PGK and reveal extensive direct interactions between GAPDH and PGM. Our simulations further reveal, through force field benchmarking, the critical role of protein solvation in facilitating these enzyme-enzyme interactions. Transient interenzyme interactions with μs lifetime occur repeatedly in our simulations via specific sticky protein surface patches, with interactions often mediated by charged patch residues. Some of the residues that interact frequently with one another lie in or near the active site of the enzymes. We show that some of these patches correspond to a general mode to interact with several partners for promiscuous enzymes like GAPDH. We further show that the non-native yeast PGK is stickier than human PGK in our human cytoplasm model, supporting the idea of evolutionary pressure to reduce sticking. Our cytoplasm modeling paves the way toward capturing the atomistic dynamics of an entire enzymatic pathway in-cell.

Identifying the minimal sets of distance restraints for FRET-assisted protein structural modeling

Proteins naturally occur in crowded cellular environments and interact with other proteins, nucleic acids, and organelles. Since most previous experimental protein structure determination techniques require that proteins occur in idealized, non-physiological environments, the effects of realistic cellular environments on protein structure are largely unexplored. Recently, Förster resonance energy transfer (FRET) has been shown to be an effective experimental method for investigating protein structure in vivo. Inter-residue distances measured in vivo can be incorporated as restraints in molecular dynamics (MD) simulations to model protein structural dynamics in vivo. Since most FRET studies only obtain inter-residue separations for a small number of amino acid pairs, it is important to determine the minimum number of restraints in the MD simulations that are required to achieve a given root-mean-square deviation (RMSD) from the experimental structural ensemble. Further, what is the optimal method for selecting these inter-residue restraints? Here, we implement several methods for selecting the most important FRET pairs and determine the number of pairsN r $$ {N}_r $$ that are needed to induce conformational changes in proteins between two experimentally determined structures. We find that enforcing only a small fraction of restraints,N r / N ≲ 0.08 $$ {N}_r/N\lesssim 0.08 $$ , whereN $$ N $$ is the number of amino acids, can induce the conformational changes. These results establish the efficacy of FRET-assisted MD simulations for atomic scale structural modeling of proteins in vivo.

Modeling membranes in situ

Molecular dynamics simulations of cellular membranes have come a long way-from simple model lipid bilayers to multicomponent systems capturing the crowded and complex nature of real cell membranes. In this opinionated minireview, we discuss the current challenge to simulate the dynamics of membranes in their native environment, in situ, with the prospect of reaching the level of whole cells and cell organelles using an integrative modeling framework.

Metastable States in the Hinge-Bending Landscape of an Enzyme in an Atomistic Cytoplasm Simulation

Many enzymes undergo major conformational changes to function in cells, particularly when they bind to more than one substrate. We quantify the large-amplitude hinge-bending landscape of human phosphoglycerate kinase (PGK) in a human cytoplasm. Approximately 70 μs of all-atom simulations, upon coarse graining, reveal three metastable states of PGK with different hinge angle distributions and additional substates. The "open" state was more populated than the "semi-open" or "closed" states. In addition to free energies and barriers within the landscape, we characterized the average transition state passage time of ≈0.3 μs and reversible substrate and product binding. Human PGK in a dilute solution simulation shows a transition directly from the open to closed states, in agreement with previous SAXS experiments, suggesting that the cell-like model environment promotes stability of the human PGK semi-open state. Yeast PGK also sampled three metastable states within the cytoplasm model, with the closed state favored in our simulation.