Structural dynamics of calmodulin and troponin C

We present the results of computational simulation studies of the structures of calmodulin (CAM) and troponin C (TNC). Possible differences between the structures of these molecules in the crystal and in solution were suggested by results from some recent experimental studies, which implied that their conformations in solution may be more compacted than the characteristic dumbbell shape observed in the crystal. The molecular dynamics simulations were carried out with the CHARMM system of programs, and the environment was modeled with a distance-dependent dielectric permittivity and discrete water molecules surrounding the proteins at starting positions identified in the crystals of CAM and TNC. Methods of macromolecular structure analysis, including linear distance plots, distance matrices and a matrix representation of hydrogen bonding, were used to analyze the nature, the extent and the source of structural differences between the computed structures of the molecules and their conformations in the crystal. Following the longest simulation, in which intradomain structure was conserved, the crystallographically observed dumbbell structure of the molecule changed due to a kinking or bending in the region of the central tether helix connecting the two Ca2+-binding domains which moved into close proximity. The resulting structure correlates with experimental observations of complexes between CAM and peptides such as melittin and mastoparan. Analysis of the corresponding pair distance distribution functions in comparison to experimental results suggests the dynamic existence of a non-negligible fraction of the compacted structure in aqueous solutions of CAM. In this more nearly globular shape, CAM reveals to the environment two interior pockets that contain a number of hydrophobic residues, in agreement with NMR data suggesting involvement of such residues in the binding of inhibitors and proteins to CA

Progress in the Prediction of pKa Values in Proteins

The pKa-cooperative aims to provide a forum for experimental and theoretical researchers interested in protein pKa values and protein electrostatics in general. The first round of the pKa-cooperative, which challenged computational labs to carry out blind predictions against pKas experimentally determined in the laboratory of Bertrand Garcia-Moreno, was completed and results discussed at the Telluride meeting (July 6–10, 2009). This article serves as an introduction to the reports submitted by the blind prediction participants that will be published in a special issue of PROTEINS: Structure, Function and Bioinformatics. Here, we briefly outline existing approaches for pKa calculations, emphasizing methods that were used by the participants in calculating the blind pKa values in the first round of the cooperative. We then point out some of the difficulties encountered by the participating groups in making their blind predictions, and finally try to provide some insights for future developments aimed at improving the accuracy of pKa calculations

Ligand-Dependent Conformations and Dynamics of the Serotonin 5-HT2A Receptor Determine Its Activation and Membrane-Driven Oligomerization Properties

From computational simulations of a serotonin 2A receptor (5-HT2AR) model complexed with pharmacologically and structurally diverse ligands we identify different conformational states and dynamics adopted by the receptor bound to the full agonist 5-HT, the partial agonist LSD, and the inverse agonist Ketanserin. The results from the unbiased all-atom molecular dynamics (MD) simulations show that the three ligands affect differently the known GPCR activation elements including the toggle switch at W6.48, the changes in the ionic lock between E6.30 and R3.50 of the DRY motif in TM3, and the dynamics of the NPxxY motif in TM7. The computational results uncover a sequence of steps connecting these experimentally-identified elements of GPCR activation. The differences among the properties of the receptor molecule interacting with the ligands correlate with their distinct pharmacological properties. Combining these results with quantitative analysis of membrane deformation obtained with our new method (Mondal et al, Biophysical Journal 2011), we show that distinct conformational rearrangements produced by the three ligands also elicit different responses in the surrounding membrane. The differential reorganization of the receptor environment is reflected in (i)-the involvement of cholesterol in the activation of the 5-HT2AR, and (ii)-different extents and patterns of membrane deformations. These findings are discussed in the context of their likely functional consequences and a predicted mechanism of ligand-specific GPCR oligomerization

Dynamics of activation elements in LSD- and KET-bound 5-HT_2AR.

<p>(<b>A–E</b>) Left and right panels show the evolution of active state components in the 5-HT_2AR complexed with LSD and KET, respectively (for details see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002473#pcbi-1002473-g003" target="_blank">Figure 3</a>). (<b>F</b>) Cartoon representation of TM3 and TM6 in the structures averaged over the last 100 ns of the LSD (cyan) and KET (green) trajectories, showing positions of R3.50 and E6.30 residues (in sticks).</p

The position and dynamic sequence of Structural Motifs recognized as Functional Microdomains (SM/FMs) in the molecular model of the 5-HT_2AR.

<p>(<b>A</b>) Known structural elements of GPCR activation (SM/FM) in the homology model of the <b>5-HT_2AR</b>. (<b>B</b>) The time-ordered sequence of events identified from the MD simulations of the agonist-bound 5-HT_2AR.</p

Structures of ligands with different efficacy and their interactions with 5-HT_2AR during MD simulations.

<p>(<b>A</b>) Chemical structures of 5-HT, LSD and KET. Amines interacting with D3.32, S3.36 or S5.46 <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002473#pcbi.1002473-Almaula1" target="_blank">[6]</a>, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002473#pcbi.1002473-Ebersole1" target="_blank">[7]</a>, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002473#pcbi.1002473-Wang2" target="_blank">[116]</a>, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002473#pcbi.1002473-Kristiansen1" target="_blank">[117]</a>, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002473#pcbi.1002473-Braden1" target="_blank">[118]</a>, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002473#pcbi.1002473-Almaula2" target="_blank">[119]</a> are labeled. (<b>B</b>,<b>C</b>,<b>D</b>) Docking poses in the initial structures (<i>left panels</i>) and during the simulations (<i>right panels</i>) for 5-HT (<b>B</b>), LSD (<b>C</b>) and KET (<b>D</b>), respectively. For clarity, only TM 3, 5 and 6 are shown in grey ribbons. Sidechains of residues D3.32, S3.36, S5.43, S5.46, F5.47, F6.44, W6.48, F6.51, F6.52 and N6.55 are depicted as sticks, and 5-HT (carbons colored in orange), LSD (cyan) and KET (green) are rendered in spheres. Note that, due to its large-size, and because its quinazoline ring penetrates deep into the binding pocket close to W6.48, KET is in direct contact with all the residues in the aromatic cluster, including F5.47. (<b>E</b>) Time-evolution of backbone TM RMSDs of 5-HT_2AR (<i>upper panel</i>) and of the distances between the carboxyl/hydroxyl oxygens in D3.32, S3.36 and S5.46 on 5-HT_2AR and their interacting amine nitrogens on ligands (see panel <b>A</b>) during the simulations (<i>lower panels</i>). Traces are shown in orange for 5-HT, in cyan for LSD, and in green for KET. Data were collected every 100 ps. Running averages were calculated every 10 data points and are shown in bold shades. N_α atom of 5-HT maintains a salt-bridge with D3.32 and forms an H-bond with S3.36 (Figure S2 in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002473#pcbi.1002473.s001" target="_blank">Text S1</a>); N₁ atom of 5-HT forms an H-bond with S5.46 either directly or through a water-bridge.</p

Comb-ED analysis of the conformational spaces visited by 5-HT_2AR bound to 5-HT, LSD and KET.

<p>(<b>A</b>) Projections along the first and second eigenvectors obtained from the Comb-ED analysis on the concatenated 5-HT-LSD (upper panel), 5-HT-KET (middle panel), and LSD-KET (lower panel) trajectories. The centers of the conformational space sampled by ligands are in black dots and are connected by black dotted lines. (<b>B</b>) Extreme projections along the first eigenvector of the combined 5-HT-LSD (top panel), 5-HT-KET (middle panel) and LSD-KET (bottom panel) trajectories. The receptor is rendered and colored as in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002473#pcbi-1002473-g005" target="_blank">Figure 5B</a>. (<b>C</b>) Comparison of the 5-HT_2AR structures in complex with 5-HT, LSD or KET averaged over the final 100 ns aligned with seven most conserved residues in each TM <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002473#pcbi.1002473-Ballesteros1" target="_blank">[18]</a>. The receptor structures in complex with different ligands are shown in cartoon and are colored as in panel <b>A</b>.</p