Dimensionality of Collective Variables for Describing Conformational Changes of a Multi-Domain Protein.

Collective variables (CVs) are often used in molecular dynamics simulations based on enhanced sampling algorithms to investigate large conformational changes of a protein. The choice of CVs in these simulations is essential because it affects simulation results and impacts the free-energy profile, the minimum free-energy pathway (MFEP), and the transition-state structure. Here we examine how many CVs are required to capture the correct transition-state structure during the open-to-close motion of adenylate kinase using a coarse-grained model in the mean forces string method to search the MFEP. Various numbers of large amplitude principal components are tested as CVs in the simulations. The incorporation of local coordinates into CVs, which is possible in higher dimensional CV spaces, is important for capturing a reliable MFEP. The Bayesian measure proposed by Best and Hummer is sensitive to the choice of CVs, showing sharp peaks when the transition-state structure is captured. We thus evaluate the required number of CVs needed in enhanced sampling simulations for describing protein conformational changes.

Rational design of crystal contact-free space in protein crystals for analyzing spatial distribution of motions within protein molecules.

Contacts with neighboring molecules in protein crystals inevitably restrict the internal motions of intrinsically flexible proteins. The resultant clear electron densities permit model building, as crystallographic snapshot structures. Although these still images are informative, they could provide biased pictures of the protein motions. If the mobile parts are located at a site lacking direct contacts in rationally designed crystals, then the amplitude of the movements can be experimentally analyzed. We propose a fusion protein method, to create crystal contact-free space (CCFS) in protein crystals and to place the mobile parts in the CCFS. Conventional model building fails when large amplitude motions exist. In this study, the mobile parts appear as smeared electron densities in the CCFS, by suitable processing of the X-ray diffraction data. We applied the CCFS method to a highly mobile presequence peptide bound to the mitochondrial import receptor, Tom20, and a catalytically relevant flexible segment in the oligosaccharyltransferase, AglB. These two examples demonstrated the general applicability of the CCFS method to the analysis of the spatial distribution of motions within protein molecules.

CHARMM Force-Fields with Modified Polyphosphate Parameters Allow Stable Simulation of the ATP-Bound Structure of Ca(2+)-ATPase.

Adenosine triphosphate (ATP) is an indispensable energy source in cells. In a wide variety of biological phenomena like glycolysis, muscle contraction/relaxation, and active ion transport, chemical energy released from ATP hydrolysis is converted to mechanical forces to bring about large-scale conformational changes in proteins. Investigation of structure-function relationships in these proteins by molecular dynamics (MD) simulations requires modeling of ATP in solution and ATP bound to proteins with accurate force-field parameters. In this study, we derived new force-field parameters for the triphosphate moiety of ATP based on the high-precision quantum calculations of methyl triphosphate. We tested our new parameters on membrane-embedded sarcoplasmic reticulum Ca(2+)-ATPase and four soluble proteins. The ATP-bound structure of Ca(2+)-ATPase remains stable during MD simulations, contrary to the outcome in shorter simulations using original parameters. Similar results were obtained with the four ATP-bound soluble proteins. The new force-field parameters were also tested by investigating the range of conformations sampled during replica-exchange MD simulations of ATP in explicit water. Modified parameters allowed a much wider range of conformational sampling compared with the bias toward extended forms with original parameters. A diverse range of structures agrees with the broad distribution of ATP conformations in proteins deposited in the Protein Data Bank. These simulations suggest that the modified parameters will be useful in studies of ATP in solution and of the many ATP-utilizing proteins.

Energetics of the presequence-binding poses in mitochondrial protein import through Tom20.

Tom20 is located at the outer membrane of mitochondria and functions as a receptor for the N-terminal presequence of mitochondrial-precursor proteins. Recently, three atomic structures of the Tom20-presequence complex were determined using X-ray crystallography and classified into A-, M-, and Y-poses in terms of their presequence-binding modes. Combined with biochemical and NMR data, a dynamic-equilibrium model between the three poses has been proposed. To investigate this mechanism in further detail, we performed all-atom molecular dynamics (MD) simulations and replica-exchange MD (REMD) simulations of the Tom20-presequence complex in explicit water. In the REMD simulations, one major distribution and another minor one were observed in the converged free-energy landscape at 300 K. In the major distribution, structures similar to A- and M-poses exist, whereas those similar to Y-pose are located in the minor one, suggesting that A-pose in solution is more stable than Y-pose. A k-means clustering algorithm revealed a new pose not yet obtained by X-ray crystallography. This structure has double salt bridges between Arg14' in the presequence and Glu78 or Glu79 in Tom20 and can explain the binding affinity of the complex in previous pull-down assay experiments. Structural clustering and analyses of contacts between Tom20 and the presequence suggest smooth conformational changes from Y- to A-poses through low activation barriers. M-pose lies between Y- and A-poses as a metastable state. The REMD simulations thus provide insights into the energetics of the multiple-binding forms and help to detail the progressive conformational states in the dynamic-equilibrium model based on the experimental data.