Characterizing the variation in chromosome structure ensembles in the context of the nuclear microenvironment.

Inside the nucleus, chromosomes are subjected to direct physical interaction between different components, active forces, and thermal noise, leading to the formation of an ensemble of three-dimensional structures. However, it is still not well understood to what extent and how the structural ensemble varies from one chromosome region or cell-type to another. We designed a statistical analysis technique and applied it to single-cell chromosome imaging data to reveal the heterogeneity of individual chromosome structures. By analyzing the resulting structural landscape, we find that the largest dynamic variation is the overall radius of gyration of the chromatin region, followed by domain reorganization within the region. By comparing different human cell-lines and experimental perturbation data using this statistical analysis technique and a network-based similarity quantification approach, we identify both cell-type and condition-specific features of the structural landscapes. We identify a relationship between epigenetic state and the properties of chromosome structure fluctuation and validate this relationship through polymer simulations. Overall, our study suggests that the types of variation in a chromosome structure ensemble are cell-type as well as region-specific and can be attributed to constraints placed on the structure by factors such as variation in epigenetic state.

Inferring chromosome radial organization from Hi-C data.

BACKGROUND: The nonrandom radial organization of eukaryotic chromosome territories (CTs) inside the nucleus plays an important role in nuclear functional compartmentalization. Increasingly, chromosome conformation capture (Hi-C) based approaches are being used to characterize the genome structure of many cell types and conditions. Computational methods to extract 3D arrangements of CTs from this type of pairwise contact data will thus increase our ability to analyze CT organization in a wider variety of biological situations. RESULTS: A number of full-scale polymer models have successfully reconstructed the 3D structure of chromosome territories from Hi-C. To supplement such methods, we explore alternative, direct, and less computationally intensive approaches to capture radial CT organization from Hi-C data. We show that we can infer relative chromosome ordering using PCA on a thresholded inter-chromosomal contact matrix. We simulate an ensemble of possible CT arrangements using a force-directed network layout algorithm and propose an approach to integrate additional chromosome properties into our predictions. Our CT radial organization predictions have a high correlation with microscopy imaging data for various cell nucleus geometries (lymphoblastoid, skin fibroblast, and breast epithelial cells), and we can capture previously documented changes in senescent and progeria cells. CONCLUSIONS: Our analysis approaches provide rapid and modular approaches to screen for alterations in CT organization across widely available Hi-C data. We demonstrate which stages of the approach can extract meaningful information, and also describe limitations of pairwise contacts alone to predict absolute 3D positions.

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

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.

Effector-Binding-Directed Dimerization and Dynamic Communication between Allosteric Sites of Ribonucleotide Reductase.

Proteins forming dimers or larger complexes can be strongly influenced by their effector-binding status. We investigated how the effector-binding event is coupled with interface formation via computer simulations, and we quantified the correlation of two types of contact interactions: between the effector and its binding pocket and between protein monomers. This was achieved by connecting the protein dynamics at the monomeric level with the oligomer interface information. We applied this method to ribonucleotide reductase (RNR), an essential enzyme for de novo DNA synthesis. RNR contains two important allosteric sites, the s-site (specificity site) and the a-site (activity site), which bind different effectors. We studied these different binding states with atomistic simulation and used their coarse-grained contact information to analyze the protein dynamics. The results reveal that the effector-protein dynamics at the s-site and dimer interface formation are positively coupled. We further quantify the resonance level between these two events, which can be applied to other similar systems. At the a-site, different effector-binding states (ATP vs dATP) drastically alter the protein dynamics and affect the activity of the enzyme. On the basis of these results, we propose a new mechanism of how the a-site regulates enzyme activation.

Regulatory Mechanics of Constitutive Androstane Receptors: Basal and Ligand-Directed Actions.

Constitutive androstane receptor (CAR) is a nuclear hormone receptor that primarily functions in sensing and metabolizing xenobiotics. The basal activity of this receptor is relatively high, and CAR is deemed active in the absence of ligand. The (over)activation can promote drug toxicity and tumor growth. Thus, therapeutic treatments seek inverse agonists to inhibit or modulate CAR activities. To advance our understanding of the regulatory mechanisms of CAR, we used computational and experimental approaches to elucidate three aspects of CAR activation and inactivation: (1) ligand-dependent actions, (2) ligand-orthologue specificity, and (3) constitutive activity. For ligand-dependent actions, we examined the ligand-bound simulations and identified two sets of ligand-induced contacts promoting CAR activation via coactivator binding (H11-H12 contact) or inactivation via corepressor binding (H4-H11 contact). For orthologue specificity, we addressed a puzzling fact that murine CAR (mCAR) and human CAR (hCAR) respond differently to the same ligand (CITCO), despite their high sequence homology. We found that the helix H7 of hCAR is responsible for a stronger binding of the ligand CITCO compared to mCAR, hence a stronger CITCO-induced activation. For basal activity, we reported computer-generated unliganded CAR structures and critical mutagenesis (mCAR's V209A and N333D) results of a cell-based transcription assay. Our results reveal that the basal conformation of CAR shares prominent features with the agonist-bound form, and helix HX has an important contribution to the constitutive activity. These findings altogether can be useful for the understanding of constitutively active receptors and the design of drug molecules targeting them.

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. © 2018 Wiley Periodicals, Inc.

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.

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. © 2016 Wiley Periodicals, Inc.

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.

Mapping allostery through computational glycine scanning and correlation analysis of residue-residue contacts.

Understanding allosteric mechanisms is essential for the physical control of molecular switches and downstream cellular responses. However, it is difficult to decode essential allosteric motions in a high-throughput scheme. A general two-pronged approach to performing automatic data reduction of simulation trajectories is presented here. The first step involves coarse-graining and identifying the most dynamic residue-residue contacts. The second step is performing principal component analysis of these contacts and extracting the large-scale collective motions expressed via these residue-residue contacts. We demonstrated the method using a protein complex of nuclear receptors. Using atomistic modeling and simulation, we examined the protein complex and a set of 18 glycine point mutations of residues that constitute the binding pocket of the ligand effector. The important motions that are responsible for the allostery are reported. In contrast to conventional induced-fit and lock-and-key binding mechanisms, a novel "frustrated-fit" binding mechanism of RXR for allosteric control was revealed.

Investigation of Carbohydrate Recognition via Computer Simulation.

Carbohydrate recognition by proteins, such as lectins and other (bio)molecules, can be essential for many biological functions. Recently, interest has arisen due to potential protein and drug design and future bioengineering applications. A quantitative measurement of carbohydrate-protein interaction is thus important for the full characterization of sugar recognition. We focus on the aspect of utilizing computer simulations and biophysical models to evaluate the strength and specificity of carbohydrate recognition in this review. With increasing computational resources, better algorithms and refined modeling parameters, using state-of-the-art supercomputers to calculate the strength of the interaction between molecules has become increasingly mainstream. We review the current state of this technique and its successful applications for studying protein-sugar interactions in recent years.

Node features of chromosome structure networks and their connections to genome annotation.

The 3D conformations of chromosomes can encode biological significance, and the implications of such structures have been increasingly appreciated recently. Certain chromosome structural features, such as A/B compartmentalization, are frequently extracted from Hi-C pairwise genome contact information (physical association between different regions of the genome) and compared with linear annotations of the genome, such as histone modifications and lamina association. We investigate how additional properties of chromosome structure can be deduced using an abstract graph representation of the contact heatmap, and describe specific network properties that can have a strong connection with some of these biological annotations. We constructed chromosome structure networks (CSNs) from bulk Hi-C data and calculated a set of site-resolved (node-based) network properties. These properties are useful for characterizing certain aspects of chromosomal structure. We examined the ability of network properties to differentiate several scenarios, such as haploid vs diploid cells, partially inverted nuclei vs conventional architecture, depletion of chromosome architectural proteins, and structural changes during cell development. We also examined the connection between network properties and a series of other linear annotations, such as histone modifications and chromatin states including poised promoter and enhancer labels. We found that semi-local network properties exhibit greater capability in characterizing genome annotations compared to diffusive or ultra-local node features. For example, the local square clustering coefficient can be a strong classifier of lamina-associated domains. We demonstrated that network properties can be useful for highlighting large-scale chromosome structure differences that emerge in different biological situations.

Surface plasmon resonance aptasensing and computational analysis of Staphylococcus aureus IsdA surface protein.

Staphylococcus aureus (S. aureus), a common foodborne pathogen, poses significant public health challenges due to its association with various infectious diseases. A key player in its pathogenicity, which is the IsdA protein, is an essential virulence factor in S. aureus infections. In this work, we present an integrated in-silico and experimental approach using MD simulations and surface plasmon resonance (SPR)-based aptasensing measurements to investigate S. aureus biorecognition via IsdA surface protein binding. SPR, a powerful real-time and label-free technique, was utilized to characterize interaction dynamics between the aptamer and IsdA protein, and MD simulations was used to characterize the stable and dynamic binding regions. By characterizing and optimizing pivotal parameters such as aptamer concentration and buffer conditions, we determined the aptamer's binding performance. Under optimal conditions of pH 7.4 and 150 mM NaCl concentration, the kinetic parameters were determined; ka = 3.789 × 104/Ms, kd = 1.798 × 103/s, and KD = 4.745 × 10-8 M. The simulations revealed regions of interest in the IsdA-aptamer complex. Region I, which includes interactions between amino acid residues H106 and R107 and nucleotide residues 9G, 10U, 11G and 12U of the aptamer, had the strongest interaction, based on ΔG and B-factor values, and hence contributed the most to the stability of the interaction. Region II, which covers residue 37A reflects the dynamic nature of the interaction due to frequent contacts. The approach presents a rigorous characterization of aptamer-IsdA binding behavior, supporting the potential application of the IsdA-binding aptamer system for S. aureus biosensing.

Solvent-induced α- to 3(10)-helix transition of an amphiphilic peptide.

The amphiphilic peptide of the triacylglycerol lipase derived from Pseudomonas aeruginosa plays a critical role in guarding the gate for ligand access. Conformations of this peptide at several water-oil interfaces and in protein environments were compared using atomistic simulations with explicit solvents. In oil-containing solvents, this peptide is able to retain a folded structure. Interestingly, when the peptide is immersed in a low-polarity solvent environment, it exhibits a "coalesced" helix structure, which has both α- and 3(10)-helix components. The observation that the 3(10)-helical conformation is populated in a highly nonpolar environment is consistent with a previous report on polymethylalanine. Frequent interconversions of the secondary structure (between α-helix and 3(10)-helix) of the peptide are also observed. We further studied how this solvent-induced structural transition may be connected to the trigger mechanism of lipase gating and how the lipase senses the hydrophobic-hydrophilic interface.

Recurrent signature patterns in HIV-1 B clade envelope glycoproteins associated with either early or chronic infections.

Here we have identified HIV-1 B clade Envelope (Env) amino acid signatures from early in infection that may be favored at transmission, as well as patterns of recurrent mutation in chronic infection that may reflect common pathways of immune evasion. To accomplish this, we compared thousands of sequences derived by single genome amplification from several hundred individuals that were sampled either early in infection or were chronically infected. Samples were divided at the outset into hypothesis-forming and validation sets, and we used phylogenetically corrected statistical strategies to identify signatures, systematically scanning all of Env. Signatures included single amino acids, glycosylation motifs, and multi-site patterns based on functional or structural groupings of amino acids. We identified signatures near the CCR5 co-receptor-binding region, near the CD4 binding site, and in the signal peptide and cytoplasmic domain, which may influence Env expression and processing. Two signatures patterns associated with transmission were particularly interesting. The first was the most statistically robust signature, located in position 12 in the signal peptide. The second was the loss of an N-linked glycosylation site at positions 413-415; the presence of this site has been recently found to be associated with escape from potent and broad neutralizing antibodies, consistent with enabling a common pathway for immune escape during chronic infection. Its recurrent loss in early infection suggests it may impact fitness at the time of transmission or during early viral expansion. The signature patterns we identified implicate Env expression levels in selection at viral transmission or in early expansion, and suggest that immune evasion patterns that recur in many individuals during chronic infection when antibodies are present can be selected against when the infection is being established prior to the adaptive immune response.

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.

Novel Covalent Modifier-Induced Local Conformational Changes within the Intrinsically Disordered Region of the Androgen Receptor.

Intrinsically disordered regions (IDRs) of transcription factors play an important biological role in liquid condensate formation and gene regulation. It is thus desirable to investigate the druggability of IDRs and how small-molecule binders can alter their conformational stability. For the androgen receptor (AR), certain covalent ligands induce important changes, such as the neutralization of the condensate. To understand the specificity of ligand-IDR interaction and potential implications for the mechanism of neutralizing liquid-liquid phase separation (LLPS), we modeled and performed computer simulations of ligand-bound peptide segments obtained from the human AR. We analyzed how different covalent ligands affect local secondary structure, protein contact map, and protein-ligand contacts for these protein systems. We find that effective neutralizers make specific interactions (such as those between cyanopyrazole and tryptophan) that alter the helical propensity of the peptide segments. These findings on the mechanism of action can be useful for designing molecules that influence IDR structure and condensate of the AR in the future.

Solvent-dependent gating motions of an extremophilic lipase from Pseudomonas aeruginosa.

Understanding how organic solvent-stable proteins can function in anhydrous and often complex solutions is essential for the study of the interaction of protein and molecular immiscible interfaces and the design of efficient industrial enzymes in nonaqueous solvents. Using an extremophilic lipase from Pseudomonas aeruginosa as an example, we investigated the conformational dynamics of an organic solvent-tolerant enzyme in complex solvent milieux. Four 100-ns molecular dynamics simulations of the lipase were performed in solvent systems: water, hexane, and two mixtures of hexane and water, 5% and 95% (w/w) hexane. Our results show a solvent-dependent structural change of the protein, especially in the region that regulates the admission of the substrate. We observed that the lipase is much less flexible in hexane than in aqueous solution or at the immiscible interface. Quantified by the size of the accessible channel, the lipase in water has a closed-gate conformation and no access to the active site, while in the hexane-containing systems, the lipase is at various degrees of open-gate state, with the immiscible interface setup being in the widely open conformation ensembles. The composition of explicit solvents in the access channel showed a significant influence on the conformational dynamics of the protein. Interestingly, the slowest step (bottleneck) of the hexane-induced conformational switch seems to be correlated with the slow dehydration dynamics of the channel.

High-pressure effect on the dynamics of solvated peptides.

The dynamics of peptides has a direct connection to how quickly proteins can alter their conformations. The speed of exploring the free energy landscape depend on many factors, including the physical parameters of the environment, such as pressure and temperature. We performed a series of molecular dynamics simulations to investigate the pressure-temperature effects on peptide dynamics, especially on the torsional angle and peptide-water hydrogen bonding (H-bonding) dynamics. Here, we show that the dynamics of the omega angle and the H-bonding dynamics between water and the peptide are affected by pressure. At high temperature (500 K), both the dynamics of the torsional angle ω and H-bonding slow down significantly with increasing pressure, interestingly, at approximately the same rate. However, at a lower temperature of 300 K, the observed trend on H-bonding dynamics as a function of pressure reverses, i.e., higher pressure speeds up H-bonding dynamics.

Statistical Analysis of Protein-Ligand Interaction Patterns in Nuclear Receptor RORγ.

The receptor RORγ belongs to the nuclear receptor superfamily that senses small signaling molecules and regulates at the gene transcription level. Since RORγ has a high basal activity and plays an important role in immune responses, inhibitors targeting this receptor have been a focus for many studies. The receptor-ligand interaction is complex, and often subtle differences in ligand structure can determine its role as an inverse agonist or an agonist. We examined more than 130 existing RORγ crystal structures that have the same receptor complexed with different ligands. We reported the features of receptor-ligand interaction patterns and the differences between agonist and inverse agonist binding. Specific changes in the contact interaction map are identified to distinguish active and inactive conformations. Further statistical analysis of the contact interaction patterns using principal component analysis reveals a dominant mode which separates allosteric binding vs. canonical binding and a second mode which may indicate active vs. inactive structures. We also studied the nature of constitutive activity by performing a 100-ns computer simulation of apo RORγ. Using constitutively active nuclear receptor CAR as a comparison, we identified a group of conserved contacts that have similar contact strength between the two receptors. These conserved contact interactions, especially a couple key contacts in H11-H12 interaction, can be considered essential to the constitutive activity of RORγ. These protein-ligand and internal protein contact interactions can be useful in the development of new drugs that direct receptor activity.