Estimation of MD simulation equilibration and analysis of the stability of protein structure.

<p>Time evolutions of a) the backbone RMSD and b) the radius of gyration (<i>R</i>_<i>g</i>) of trypsin in MD simulations. Black color indicates trypsin in catechin-free form; red, blue, dark-cyan and magenta indicate trypsin in the complex with EC, ECG, EGC and EGCG, respectively.</p

Characterization of the conformation changes of catechins.

<p>The distances among the rings of catechins in the optimized structure (a, b, c and d) and their average distances calculated from MD trajectories (a′, b′, c′ and d′). (a and a′) EC; (b and b′) EGC; (c and c′) ECG; (d and d′) EGCG.</p

Characterization of residues flexibility.

<p>The Cα B-factor for each residue in trypsin computed from MD simulation trajectories in the form of catechin-free (black) and complex with EC (red), ECG (blue), EGC (dark-cyan) and EGCG (magenta), respectively. The orange line represents the Cα B-factor from PDB file. The wiring diagram shows the secondary structure of trypsin. The bar chart at the bottom of picture shows the distance range of the Cα atom to the nearest heavy atom of catechins. The inset enlarges the sequence motifs in the S1 pocket.</p

Analysis of contributions of each component in binding free energy.

<p>Comparison of the binding free energy components of trypsin binding with EC (red), EGC (blue), ECG (dark cyan) and EGCG (magenta).</p

Representative trypsin-catechin complex structures.

<p>Representative structure models clustered from MD simulation trajectories for trypsin complex with a) EC, b) EGC, c) ECG and d) EGCG. Catechins are shown as ball-and-stick model, trypsin as cartoon. The catalytic triad (Asp102, His57, Ser195) is shown in stick. Residues interact with catechins by hydrogen bond and hydrophobic interaction highlighted by lines.</p

The binding affinity from semi-flexible docking (kcal/mol) and the possibility (in parenthesis) of four types of catechins and their chemical groups binding to the S1 pocket of trypsin.

<p>^a The possibility of ligand binding to the S1 pocket.</p><p>^b The possibility of different groups in each ligand binding to the S1 pocket.</p><p>The binding affinity from semi-flexible docking (kcal/mol) and the possibility (in parenthesis) of four types of catechins and their chemical groups binding to the S1 pocket of trypsin.</p

Sampling Enrichment toward Target Structures Using Hybrid Molecular Dynamics-Monte Carlo Simulations

<div><p>Sampling enrichment toward a target state, an analogue of the improvement of sampling efficiency (SE), is critical in both the refinement of protein structures and the generation of near-native structure ensembles for the exploration of structure-function relationships. We developed a hybrid molecular dynamics (MD)-Monte Carlo (MC) approach to enrich the sampling toward the target structures. In this approach, the higher SE is achieved by perturbing the conventional MD simulations with a MC structure-acceptance judgment, which is based on the coincidence degree of small angle x-ray scattering (SAXS) intensity profiles between the simulation structures and the target structure. We found that the hybrid simulations could significantly improve SE by making the top-ranked models much closer to the target structures both in the secondary and tertiary structures. Specifically, for the 20 mono-residue peptides, when the initial structures had the root-mean-squared deviation (RMSD) from the target structure smaller than 7 Å, the hybrid MD-MC simulations afforded, on average, 0.83 Å and 1.73 Å in RMSD closer to the target than the parallel MD simulations at 310K and 370K, respectively. Meanwhile, the average SE values are also increased by 13.2% and 15.7%. The enrichment of sampling becomes more significant when the target states are gradually detectable in the MD-MC simulations in comparison with the parallel MD simulations, and provide >200% improvement in SE. We also performed a test of the hybrid MD-MC approach in the real protein system, the results showed that the SE for 3 out of 5 real proteins are improved. Overall, this work presents an efficient way of utilizing solution SAXS to improve protein structure prediction and refinement, as well as the generation of near native structures for function annotation.</p></div

The ratio R₂/R₁, dRMSD_T and dSE for the five representative trajectories shown in Fig 8.

<p>The ratio R₂/R₁, dRMSD_T and dSE for the five representative trajectories shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0156043#pone.0156043.g008" target="_blank">Fig 8</a>.</p

The schematic flowchart of simulations in this work.

<p>The schematic flowchart of simulations in this work.</p

Structural and SAXS profiles comparison among initial (green), target (blue) and simulation (red) structures for ubiquitin and cytochrome C using experimental target SAXS profiles.

<p>The calculated SAXS profiles are the average of all 1,250 conformations in the last 5 ns of hybrid MD-MC simulations.</p