Comparing side chain packing in soluble proteins, protein-protein interfaces, and transmembrane proteins.

We compare side chain prediction and packing of core and non-core regions of soluble proteins, protein-protein interfaces, and transmembrane proteins. We first identified or created comparable databases of high-resolution crystal structures of these 3 protein classes. We show that the solvent-inaccessible cores of the 3 classes of proteins are equally densely packed. As a result, the side chains of core residues at protein-protein interfaces and in the membrane-exposed regions of transmembrane proteins can be predicted by the hard-sphere plus stereochemical constraint model with the same high prediction accuracies (>90%) as core residues in soluble proteins. We also find that for all 3 classes of proteins, as one moves away from the solvent-inaccessible core, the packing fraction decreases as the solvent accessibility increases. However, the side chain predictability remains high (80% within 30°) up to a relative solvent accessibility, rSASA≲0.3, for all 3 protein classes. Our results show that ≈40% of the interface regions in protein complexes are "core", that is, densely packed with side chain conformations that can be accurately predicted using the hard-sphere model. We propose packing fraction as a metric that can be used to distinguish real protein-protein interactions from designed, non-binding, decoys. Our results also show that cores of membrane proteins are the same as cores of soluble proteins. Thus, the computational methods we are developing for the analysis of the effect of hydrophobic core mutations in soluble proteins will be equally applicable to analyses of mutations in membrane proteins.

Packing in protein cores.

Proteins are biological polymers that underlie all cellular functions. The first high-resolution protein structures were determined by x-ray crystallography in the 1960s. Since then, there has been continued interest in understanding and predicting protein structure and stability. It is well-established that a large contribution to protein stability originates from the sequestration from solvent of hydrophobic residues in the protein core. How are such hydrophobic residues arranged in the core; how can one best model the packing of these residues, and are residues loosely packed with multiple allowed side chain conformations or densely packed with a single allowed side chain conformation? Here we show that to properly model the packing of residues in protein cores it is essential that amino acids are represented by appropriately calibrated atom sizes, and that hydrogen atoms are explicitly included. We show that protein cores possess a packing fraction of [Formula: see text], which is significantly less than the typically quoted value of 0.74 obtained using the extended atom representation. We also compare the results for the packing of amino acids in protein cores to results obtained for jammed packings from discrete element simulations of spheres, elongated particles, and composite particles with bumpy surfaces. We show that amino acids in protein cores pack as densely as disordered jammed packings of particles with similar values for the aspect ratio and bumpiness as found for amino acids. Knowing the structural properties of protein cores is of both fundamental and practical importance. Practically, it enables the assessment of changes in the structure and stability of proteins arising from amino acid mutations (such as those identified as a result of the massive human genome sequencing efforts) and the design of new folded, stable proteins and protein-protein interactions with tunable specificity and affinity.

Collective repacking reveals that the structures of protein cores are uniquely specified by steric repulsive interactions.

Protein core repacking is a standard test of protein modeling software. A recent study of six different modeling software packages showed that they are more successful at predicting side chain conformations of core compared to surface residues. All the modeling software tested have multicomponent energy functions, typically including contributions from solvation, electrostatics, hydrogen bonding and Lennard-Jones interactions in addition to statistical terms based on observed protein structures. We investigated to what extent a simplified energy function that includes only stereochemical constraints and repulsive hard-sphere interactions can correctly repack protein cores. For single residue and collective repacking, the hard-sphere model accurately recapitulates the observed side chain conformations for Ile, Leu, Phe, Thr, Trp, Tyr and Val. This result shows that there are no alternative, sterically allowed side chain conformations of core residues. Analysis of the same set of protein cores using the Rosetta software suite revealed that the hard-sphere model and Rosetta perform equally well on Ile, Leu, Phe, Thr and Val; the hard-sphere model performs better on Trp and Tyr and Rosetta performs better on Ser. We conclude that the high prediction accuracy in protein cores obtained by protein modeling software and our simplified hard-sphere approach reflects the high density of protein cores and dominance of steric repulsion.

Steric interactions determine side-chain conformations in protein cores.

We investigate the role of steric interactions in defining side-chain conformations in protein cores. Previously, we explored the strengths and limitations of hard-sphere dipeptide models in defining sterically allowed side-chain conformations and recapitulating key features of the side-chain dihedral angle distributions observed in high-resolution protein structures. Here, we show that modeling residues in the context of a particular protein environment, with both intra- and inter-residue steric interactions, is sufficient to specify which of the allowed side-chain conformations is adopted. This model predicts 97% of the side-chain conformations of Leu, Ile, Val, Phe, Tyr, Trp and Thr core residues to within 20°. Although the hard-sphere dipeptide model predicts the observed side-chain dihedral angle distributions for both Thr and Ser, the model including the protein environment predicts side-chain conformations to within 20° for only 60% of core Ser residues. Thus, this approach can identify the amino acids for which hard-sphere interactions alone are sufficient and those for which additional interactions are necessary to accurately predict side-chain conformations in protein cores. We also show that our approach can predict alternate side-chain conformations of core residues, which are supported by the observed electron density.

Molecular dynamics simulations of diffusion and clustering along critical isotherms of medium-chain n-alkanes.

Understanding the transport properties of molecular fluids in the critical region is important for a number of industrial and natural systems. In the literature, there are conflicting reports on the behavior of the self diffusion coefficient D(s) in the critical region of single-component molecular systems. For example, D(s) could decrease to zero, reach a maximum, or remain unchanged and finite at the critical point. Moreover, there is no molecular-scale understanding of the behavior of diffusion coefficients in molecular fluids in the critical regime. We perform extensive molecular dynamics simulations in the critical region of single-component fluids composed of medium-chain n-alkanes-n-pentane, n-decane, and n-dodecane-that interact via anisotropic united-atom potentials. For each system, we calculate D(s), and average molecular cluster sizes κ(cl) and numbers N(cl) at various cluster lifetimes τ, as a function of density ρ in the range 0.2ρ(c) ≤ ρ ≤ 2.0ρ(c) at the critical temperature T(c). We find that D(s) decreases with increasing ρ but remains finite at the critical point. Moreover, for any given τ < 1.2 × 10(-12) s, κ(cl) increases with increasing ρ but is also finite at the critical point.

Microstructure evolution during impact on granular matter.

We study the impact of an intruder on a dense granular material. The process of impact and interaction between the intruder and the granular particles is modeled using discrete element simulations in two spatial dimensions. In the first part of the paper we discuss how the intruder's dynamics depends on (1) the intruder's properties, including its size, shape and composition, (2) the properties of the grains, including friction, polydispersity, structural order, and elasticity, and (3) the properties of the system, including its size and gravitational field. It is found that polydispersity and related structural order, and frictional properties of the granular particles, play a crucial role in determining impact dynamics. In the second part of the paper we consider the response of the granular system itself. We discuss the force networks that develop, including their topological evolution. The influence of friction and structural order on force propagation, including the transition from hyperbolic-like to elastic-like behavior is discussed, as well as the affine and nonaffine components of the grain dynamics. Several broad observations include the following: tangential forces between granular particles are found to play a crucial role in determining impact dynamics; both force networks and particle dynamics are correlated with the dynamics of the intruder itself.

Short-range order and near-field effects on optical scattering and structural coloration.

We have investigated wavelength-dependent light scattering in biomimetic structures with short-range order. Coherent backscattering experiments are performed to measure the transport mean free path over a wide wavelength range. Overall scattering strength is reduced significantly due to short-range order and near-field effects. Our analysis explains why single scattering of light is dominant over multiple scattering in similar biological structures and is responsible for color generation.

Stress correlations in granular materials: an entropic formulation.

We study the response of dry granular materials to external stress using experiment, simulation, and theory. We derive a Ginzburg-Landau functional that enforces mechanical stability and positivity of contact forces. In this framework, the elastic moduli depend only on the applied stress. A combination of this feature and the positivity constraint leads to stress correlations whose shape and magnitude are extremely sensitive to the nature of the applied stress. The predictions from the theory describe the stress correlations for both simulations and experiments semiquantitatively.

Minimal model for kinetic arrest.

To elucidate slow dynamics in glassy materials, we introduce the figure-8 model in which N hard blocks undergo Brownian motion around a circuit in the shape of a figure 8. This system undergoes kinetic arrest at a critical packing fraction phi=phi g<1 , and for phi approximately phi g long-time diffusion is controlled by rare, cooperative, "junction-crossing" particle rearrangements. We find that the average time between junction crossings tau JC, and hence the structural relaxation time, does not simply scale with the configurational volume Omega c of transition states, because tau JC also depends on the time to complete a junction crossing. The importance of these results in understanding cage-breaking dynamics in glassy systems is discussed.

Structural properties of the sliding columnar phase in layered liquid crystalline systems.

Under appropriate conditions, mixtures of cationic and neutral lipids and DNA in water condense into complexes in which DNA strands form local two-dimensional (2D) smectic lattices intercalated between lipid bilayer membranes in a lamellar stack. These lamellar DNA-cationic-lipid complexes can in principle exhibit a variety of equilibrium phases, including a columnar phase in which parallel DNA strands form a 2D lattice, a nematic lamellar phase in which DNA strands align along a common direction but exhibit no long-range positional order, and a possible new intermediate phase, the sliding columnar (SC) phase, characterized by a vanishing shear modulus for relative displacement of DNA lattices but a nonvanishing modulus for compressing these lattices. We develop a model capable of describing all phases and transitions among them and use it to calculate structural properties of the sliding columnar phase. We calculate displacement and density correlation functions and x-ray scattering intensities in this phase and show, in particular, that density correlations within a layer have an unusual exp(-const x ln(2)r) dependence on separation r. We investigate the stability of the SC phase with respect to shear couplings leading to the columnar phase and dislocation unbinding leading to the lamellar nematic phase. For models with interactions only between nearest neighbor planes, we conclude that the SC phase is not thermodynamically stable. Correlation functions in the nematic lamellar phase, however, exhibit SC behavior over a range of length scales.