The Effect of Box Shape on the Dynamic Properties of Proteins Simulated under Periodic Boundary Conditions

Abstract: The effect of the box shape on the dynamic behavior of proteins simulated under periodic boundary conditions is evaluated. In particular, the influence of simulation boxes defined by the near-densest lattice packing (NDLP) in conjunction with rotational constraints is compared to that of standard box types without these constraints. Three different proteins of varying size, shape, and secondary structure content were examined in the study. The statistical significance of differences in RMSD, radius of gyration, solvent-accessible surface, number of hydrogen bonds, and secondary structure content between proteins, box types, and the application or not of rotational constraints has been assessed. Furthermore, the differences in the collective modes for each protein between different boxes and the application or not of rotational constraints have been examined. In total 105 simulations were performed, and the results compared using a three-way multivariate analysis of variance (MANOVA) for properties derived from the trajectories and a three-way univariate analysis of variance (ANOVA) for collective modes. It is shown that application of roto-translational constraints does not have a statistically significant effect on the results obtained from the different simulations. However, the choice of simulation box was found to have a small (5-10%), but statistically significant effect on the behavior of two of the three proteins included in the study

Computational studies of biomembrane systems: Theoretical considerations, simulation models, and applications

This chapter summarizes several approaches combining theory, simulation and experiment that aim for a better understanding of phenomena in lipid bilayers and membrane protein systems, covering topics such as lipid rafts, membrane mediated interactions, attraction between transmembrane proteins, and aggregation in biomembranes leading to large superstructures such as the light harvesting complex of green plants. After a general overview of theoretical considerations and continuum theory of lipid membranes we introduce different options for simulations of biomembrane systems, addressing questions such as: What can be learned from generic models? When is it expedient to go beyond them? And what are the merits and challenges for systematic coarse graining and quasi-atomistic coarse grained models that ensure a certain chemical specificity

Dynamics of protein-protein encounter: a Langevin equation approach with reaction patches

We study the formation of protein-protein encounter complexes with a Langevin equation approach that considers direct, steric and thermal forces. As three model systems with distinctly different properties we consider the pairs barnase:barstar, cytochrome c:cytochrome c peroxidase and p53:MDM2. In each case, proteins are modeled either as spherical particles, as dipolar spheres or as collection of several small beads with one dipole. Spherical reaction patches are placed on the model proteins according to the known experimental structures of the protein complexes. In the computer simulations, concentration is varied by changing box size. Encounter is defined as overlap of the reaction patches and the corresponding first passage times are recorded together with the number of unsuccessful contacts before encounter. We find that encounter frequency scales linearly with protein concentration, thus proving that our microscopic model results in a well-defined macroscopic encounter rate. The number of unsuccessful contacts before encounter decreases with increasing encounter rate and ranges from 20-9000. For all three models, encounter rates are obtained within one order of magnitude of the experimentally measured association rates. Electrostatic steering enhances association up to 50-fold. If diffusional encounter is dominant (p53:MDM2) or similarly important as electrostatic steering (barnase:barstar), then encounter rate decreases with decreasing patch radius. More detailed modeling of protein shapes decreases encounter rates by 5-95 percent. Our study shows how generic principles of protein-protein association are modulated by molecular features of the systems under consideration. Moreover it allows us to assess different coarse-graining strategies for the future modelling of the dynamics of large protein complexes

DynamO: A free O(N) general event-driven molecular-dynamics simulator

Molecular-dynamics algorithms for systems of particles interacting through discrete or "hard" potentials are fundamentally different to the methods for continuous or "soft" potential systems. Although many software packages have been developed for continuous potential systems, software for discrete potential systems based on event-driven algorithms are relatively scarce and specialized. We present DynamO, a general event-driven simulation package which displays the optimal O(N) asymptotic scaling of the computational cost with the number of particles N, rather than the O(N log(N)) scaling found in most standard algorithms. DynamO provides reference implementations of the best available event-driven algorithms. These techniques allow the rapid simulation of both complex and large (>10^6 particles) systems for long times. The performance of the program is benchmarked for elastic hard sphere systems, homogeneous cooling and sheared inelastic hard spheres, and equilibrium Lennard-Jones fluids. This software and its documentation are distributed under the GNU General Public license and can be freely downloaded from http://marcusbannerman.co.uk/dynamo

New insight into cataract formation -- enhanced stability through mutual attraction

Small-angle neutron scattering experiments and molecular dynamics simulations combined with an application of concepts from soft matter physics to complex protein mixtures provide new insight into the stability of eye lens protein mixtures. Exploring this colloid-protein analogy we demonstrate that weak attractions between unlike proteins help to maintain lens transparency in an extremely sensitive and non-monotonic manner. These results not only represent an important step towards a better understanding of protein condensation diseases such as cataract formation, but provide general guidelines for tuning the stability of colloid mixtures, a topic relevant for soft matter physics and industrial applications.Comment: 4 pages, 4 figures. Accepted for publication on Phys. Rev. Let

IMAGE CHARGE SOLVATION MODEL (ICSM) FOR SIMULATING BIOMOLECULES AND KCSA ION-CHANNELS

We present an order N method for calculating electrostatic interactions that has been integrated into the molecular dynamics portion of the TINKER Molecular Modeling package. This method, termed the Image-Charge Solvation Model (ICSM), and introduced previously by Dr. Lin et al. (1) in 2009, is a hybrid electrostatic approach that combines the strengths of both explicit and implicit representations of the solvent. In this model, a multiple-image method is used to calculate reaction fields due to the implicit solvent while the Fast Multipole Method (FMM) is used to calculate the Coulomb interactions for all charges, including the charges in the explicit solvent part. The integrated package is validated through simulations of liquid water. The results are compared with those obtained by the Particle Mesh Ewald (PME) method that is built in the TINKER package. Timing performance of TINKER with the integrated ICSM is benchmarked on bulk water as a function of the size of the system. In particular, timing analysis results show that the ICSM outperforms the PME for sufficiently large systems with the break-even point at around 30,000 particles in the simulated system. To demonstrate the capability of the package on large macromolecules, the model is used to simulate the potassium channel KcsA