Tongye Shen

Stability and sugar recognition ability of ricin-like carbohydrate binding domains.

Lectins are a class of proteins known for their novel binding to saccharides. Understanding this sugar recognition process can be crucial in creating structure-based designs of proteins with various biological roles. We focus on the sugar binding of a particular lectin, ricin, which has two β-trefoil carbohydrate-binding domains (CRDs) found in several plant protein toxins. The binding ability of possible sites of ricin-like CRD has been puzzling. The apo and various (multiple) ligand-bound forms of the sugar-binding domains of ricin were studied by molecular dynamics simulations. By evaluating structural stability, hydrogen bond dynamics, flexibility, and binding energy, we obtained a detailed picture of the sugar recognition of the ricin-like CRD. Unlike what was previously believed, we found that the binding abilities of the two known sites are not independent of each other. The binding ability of one site is positively affected by the other site. While the mean positions of different binding scenarios are not altered significantly, the flexibility of the binding pockets visibly decreases upon multiple ligand binding. This change in flexibility seems to be the origin of the binding cooperativity. All the hydrogen bonds that are strong in the monoligand state are also strong in the double-ligand complex, although the stability is much higher in the latter form due to cooperativity. These strong hydrogen bonds in a monoligand state are deemed to be the essential hydrogen bonds. Furthermore, by examining the structural correlation matrix, the two domains are structurally one entity. Galactose hydroxyl groups, OH4 and OH3, are the most critical parts in both site 1α and site 2γ recognition.

Pressure-induced conformational switch of an interfacial protein.

A special class of proteins adopts an inactive conformation in aqueous solution and activates at an interface (such as the surface of lipid droplet) by switching their conformations. Lipase, an essential enzyme for breaking down lipids, serves as a model system for studying such interfacial proteins. The underlying conformational switch of lipase induced by solvent condition is achieved through changing the status of the gated substrate‐access channel. Interestingly, a lipase was also reported to exhibit pressure activation, which indicates it is drastically active at high hydrostatic pressure. To unravel the molecular mechanism of this unusual phenomenon, we examined the structural changes induced by high hydrostatic pressures (up to 1500 MPa) using molecular dynamics simulations. By monitoring the width of the access channel, we found that the protein undergoes a conformational transition and opens the access channel at high pressures (>100 MPa). Particularly, a disordered amphiphilic α5 region of the protein becomes ordered at high pressure. This positive correlation between the channel opening and α5 ordering is consistent with the early findings of the gating motion in the presence of a water–oil interface. Statistical analysis of the ensemble of conformations also reveals the essential collective motions of the protein and how these motions contribute to gating. Arguments are presented as to why heightened sensitivity to high‐pressure perturbation can be a general feature of switchable interfacial proteins. Further mutations are also suggested to validate our observations. Proteins 2016; 84:820–827.

Effects of branched O-glycosylation on a semiflexible peptide linker.

Glycosylation is an essential modification of proteins and lipids by the addition of carbohydrate residues. These attached carbohydrates range from single monomers to elaborate branched glycans. Here, we examine how the level of glycosylation affects the conformation of a semiflexible peptide linker using the example of the hinge peptide from immunoglobulin A. Three sets of atomistic models of this hinge peptide with varying degrees of glycosylation are constructed to probe how glycosylation affects the physical properties of the linker. We found that glycosylation greatly altered the predominant conformations of the peptide, causing it to become elongated in reference to the unglycosylated form. Furthermore, glycosylation restricts the conformational exploration of the peptide. At the residue level, glycans are found to introduce a bias for the formation of more extended secondary structural elements for glycosylated serines. Additionally, the flexibility of this semiflexible proline-rich peptide is significantly reduced by glycosylation.

Swimming motility plays a key role in the stochastic dynamics of cell clumping

Dynamic cell-to-cell interactions are a prerequisite to many biological processes, including development and biofilm formation. Flagellum induced motility has been shown to modulate the initial cell-cell or cell-surface interaction and to contribute to the emergence of macroscopic patterns. While the role of swimming motility in surface colonization has been analyzed in some detail, a quantitative physical analysis of transient interactions between motile cells is lacking. We examined the Brownian dynamics of swimming cells in a crowded environment using a model of motorized adhesive tandem particles. Focusing on the motility and geometry of an exemplary motile bacterium Azospirillum brasilense, which is capable of transient cell-cell association (clumping), we constructed a physical model with proper parameters for the computer simulation of the clumping dynamics. By modulating mechanical interaction (stickiness) between cells and swimming speed, we investigated how equilibrium and active features affect the clumping dynamics. We found that the modulation of active motion is required for the initial aggregation of cells to occur at a realistic time scale. Slowing down the rotation of flagellar motors (and thus swimming speeds) is correlated to the degree of clumping, which is consistent with the experimental results obtained for A. brasilense.

Characterizing protein conformations by correlation analysis of coarse-grained contact matrices

We have developed a method to capture the essential conformational dynamics of folded biopolymers using statistical analysis of coarse-grained segment-segment contacts. Previously, the residue-residue contact analysis of simulation trajectories was successfully applied to the detection of conformational switching motions in biomolecular complexes. However, the application to large protein systems (larger than 1000 amino acid residues) is challenging using the description of residue contacts. Also, the residue-based method cannot be used to compare proteins with different sequences. To expand the scope of the method, we have tested several coarse-graining schemes that group a collection of consecutive residues into a segment. The definition of these segments may be derived from structural and sequence information, while the interaction strength of the coarse-grained segment-segment contacts is a function of the residue-residue contacts. We then perform covariance calculations on these coarse-grained contact matrices. We monitored how well the principal components of the contact matrices is preserved using various rendering functions. The new method was demonstrated to assist the reduction of the degrees of freedom for describing the conformation space, and it potentially allows for the analysis of a system that is approximately tenfold larger compared with the corresponding residue contact-based method. This method can also render a family of similar proteins into the same conformational space, and thus can be used to compare the structures of proteins with different sequences.

Characterizing the 3D structure and dynamics of chromosomes and proteins in a common contact matrix framework

Abstract Conformational ensembles of biopolymers, whether proteins or chromosomes, can be described using contact matrices. Principal component analysis (PCA) on the contact data has been used to interrogate both protein and chromosome structures and/or dynamics. However, as these fields have developed separately, variants of PCA have emerged. Previously, a variant we hereby term Implicit-PCA (I-PCA) has been applied to chromosome contact matrices and revealed the spatial segregation of active and inactive chromatin. Separately, Explicit-PCA (E-PCA) has previously been applied to proteins and characterized their correlated structure fluctuations. Here, we swapped analysis methods (I-PCA and E-PCA), applying each to a different biopolymer type (chromosome or protein) than the one for which they were initially developed. We find that applying E-PCA to chromosome distance matrices derived from microscopy data can reveal the dominant motion (concerted fluctuation) of these chromosomes. Further, by applying E-PCA to Hi-C data across the human blood cell lineage, we isolated the aspects of chromosome structure that most strongly differentiate cell types. Conversely, when we applied I-PCA to simulation snapshots of proteins, the major component reported the consensus features of the structure, making this a promising approach for future analysis of semi-structured proteins.

CAMERRA: An analysis tool for the computation of conformational dynamics by evaluating residue-residue associations

A computational method which extracts the dominant motions from an ensemble of biomolecular conformations via a correlation analysis of residue–residue contacts is presented. The algorithm first renders the structural information into contact matrices, then constructs the collective modes based on the correlated dynamics of a selected set of dynamic contacts. Associated programs can bridge the results for further visualization using graphics software. The aim of this method is to provide an analysis of conformations of biopolymers from the contact viewpoint. It may assist a systematical uncovering of conformational switching mechanisms existing in proteins and biopolymer systems in general by statistical analysis of simulation snapshots. In contrast to conventional correlation analyses of Cartesian coordinates (such as distance covariance analysis and Cartesian principal component analysis), this program also provides an alternative way to locate essential collective motions in general. Herein, we detail the algorithm in a stepwise manner and comment on the importance of the method as applied to decoding allosteric mechanisms.

Nucleation Dynamics of Active Particles

We present a model of a collection of active and adhesive Brownian particles that are capable of aggregation. Besides the mechanical interaction between particles, a simple active dynamics term (motility) is included to provide an active movement. At a given instant, each particle is either in an active (swim) or unanimated (stop) state, which is controlled by a random process. The model includes important features that are inspired by the phenomenon of biological cell-cell association. One feature is the mean motility that is related to the percentage of the particle being active and the maximum swimming speed. Another feature is the stochastic nature of switching between the swim and stop state. We explored how these key features affect the nucleation dynamics and the stability of the aggregates using simulations. Interestingly, particles can change their collective behavior by solely altering the frequency of switching between the swim and stop state while keeping the mean motility unchanged. These results provide insight into how motor-driven forces can be utilized by active biological systems to modulate the single-to-cluster transition efficiently. A dimensionless parameter is also proposed to measure the overall strength of the nonequilibrium effect on active particles.

DMSO enhanced conformational switch of an interfacial enzyme.

Interfacial proteins function in unique heterogeneous solvent environments, such as water–oil interfaces. One important example is microbial lipase, which is activated in an oil‐water emulsion phase and has many important enzymatic functions. A unique aprotic dipolar organic solvent, dimethyl sulfoxide (DMSO), has been shown to increase the activity of lipases, but the mechanism behind this enhancement is still unknown. Here, all‐atom molecular dynamics simulations of lipase in a binary solution were performed to examine the effects of DMSO on the dynamics of the gating mechanism. The amphiphilic α5 region of the lipase was a focal point for the analysis, since the structural ordering of α5 has been shown to be important for gating under other perturbations. Compared to the closed‐gorge ensemble in an aqueous environment, the conformational ensemble shifts towards open‐gorge structures in the presence of DMSO solvents. Increased width of the access channel is particularly prevalent in 45% and 60% DMSO concentrations (w/w). As the amount of DMSO increases, the α5 region of the lipase becomes more α‐helical, as we previously observed in studies that address water–oil interfacial and high pressure activation. We believe that the structural ordering of α5 plays an essential role on gating and lipase activity.