Dynamic Cross-correlation Research Articles

Induced Mutation Proves a Potential Target for TB Therapy: A Molecular Dynamics Study on LprG.

Molecular dynamics (MD) simulations of wild-type and V91W mutant Mycobacterium tuberculosis-LprG (Mtb-LprG) were performed with the goal to provide a comprehensive understanding of the Mtb-LprG as a potential antimycobacterial target. A long-range MD simulations and post-MD analyzes led us to various results that plainly explained the impact of V91W mutation on Mtb-LprG. Herein, the results revealed that the wild-type is less stable compared to V91W mutant. This was further supported by root mean square fluctuation, where the V91W mutant showed a higher degree of flexibility compared to the wild-type. Dynamic cross-correlation analysis revealed that induced mutation leads to higher residual flexibility in the mutant structure as compared to the wild-type structure thus resulting in the existence of negatively correlated motions. The difference in principal component analysis scatter plot across the first two normal modes suggests a greater mobility of the V91W mutant conformation compared to the wild-type. Thermodynamic calculations revealed that the van der Waals (Evdw) forces contribute the most towards binding free energy in a case of the V91W mutant as compared to the wild-type LprG complex. In addition, the residue interaction networks revealed more of Evdw interaction existence among residues in case of the V91W mutant. This study supports the Mtb-LprG as a potential antimycobacterial target and also serves as a cornerstone to identifying new potential targets that have no inhibitors.

Mutational analysis of phenolic acid decarboxylase from Enterobacter sp. Px6-4. towards enhancement of binding affinity: A computational approach

Microbial Ferulic Acid Decarboxylase (FADase) catalyses the conversion of ferulic acid to 4-hydroxy-3-methoxystyrene (4-vinylguaiacol) via non-oxidative decarboxylation. In this article, we present a computational, three-dimensional structural and functional analysis of FADase from Enterobacter sp. P × 6-4 (3NX1) which can be used to generate enhanced bindings of substrates. The enzymatic catalytic site and binding sites have been critically evaluated. Sequential site directed mutations on enzyme have also been introduced for formation of a greater number of hydrogen bonds. Four mutants were generated based on our hypothesis. Active sites of mutated FADases have been analyzed with dynamic cross-correlation maps and principle components analysis. All structures were validated and optimized through energy minimization. Docking studies were also carried out between ferulic acid and different mutated enzymes. The protein (wild and mutants) complexes were further validated with molecular simulation. Mutant3 was found to have better affinity towards ferulic acid. Mutant3 also forms a higher number of hydrogen bonds with the substrate to facilitate greater interaction. This current work will help industry to create new and novel mutants to produce vanillin.

Structure and dynamics of a human myelin protein P2 portal region mutant indicate opening of the \u03b2 barrel in fatty acid binding proteins

BackgroundMyelin is a multilayered proteolipid sheath wrapped around selected axons in the nervous system. Its constituent proteins play major roles in forming of the highly regular membrane structure. P2 is a myelin-specific protein of the fatty acid binding protein (FABP) superfamily, which is able to stack lipid bilayers together, and it is a target for mutations in the human inherited neuropathy Charcot-Marie-Tooth disease. A conserved residue that has been proposed to participate in membrane and fatty acid binding and conformational changes in FABPs is Phe57. This residue is thought to be a gatekeeper for the opening of the portal region upon ligand entry and egress.ResultsWe performed a structural characterization of the F57A mutant of human P2. The mutant protein was crystallized in three crystal forms, all of which showed changes in the portal region and helix α2. In addition, the behaviour of the mutant protein upon lipid bilayer binding suggested more unfolding than previously observed for wild-type P2. On the other hand, membrane binding rendered F57A heat-stable, similarly to wild-type P2. Atomistic molecular dynamics simulations showed opening of the side of the discontinuous β barrel, giving important indications on the mechanism of portal region opening and ligand entry into FABPs. The results suggest a central role for Phe57 in regulating the opening of the portal region in human P2 and other FABPs, and the F57A mutation disturbs dynamic cross-correlation networks in the portal region of P2.ConclusionsOverall, the F57A variant presents similar properties to the P2 patient mutations recently linked to Charcot-Marie-Tooth disease. Our results identify Phe57 as a residue regulating conformational changes that may accompany membrane surface binding and ligand exchange in P2 and other FABPs.

The dynamic cross-correlations between foreign news, local news and stock returns

Plenty of literature has proven the existence of local media bias in stock market from the perspective of trading volume. Given to the cross-listings of AH stocks in China, we explore the dynamics relationship between stock prices and media coverage by means of MF-DCCA. We mainly find that H-share prices seem to move more consistently with foreign media coverage in contrast to mainland media coverage, while A-share prices react to different media coverage at the similar intensity. These findings are robust to alternative measurements of returns. Generally speaking, our findings support the existence of local bias in media choosing.

Protein dynamic communities from elastic network models align closely to the communities defined by molecular dynamics.

Dynamic communities in proteins comprise the cohesive structural units that individually exhibit rigid body motions. These can correspond to structural domains, but are usually smaller parts that move with respect to one another in a protein’s internal motions, key to its functional dynamics. Previous studies emphasized their importance to understand the nature of ligand-induced allosteric regulation. These studies reported that mutations to key community residues can hinder transmission of allosteric signals among the communities. Usually molecular dynamic (MD) simulations (~ 100 ns or longer) have been used to identify the communities—a demanding task for larger proteins. In the present study, we propose that dynamic communities obtained from MD simulations can also be obtained alternatively with simpler models–the elastic network models (ENMs). To verify this premise, we compare the specific communities obtained from MD and ENMs for 44 proteins. We evaluate the correspondence in communities from the two methods and compute the extent of agreement in the dynamic cross-correlation data used for community detection. Our study reveals a strong correspondence between the communities from MD and ENM and also good agreement for the residue cross-correlations. Importantly, we observe that the dynamic communities from MD can be closely reproduced with ENMs. With ENMs, we also compare the community structures of stable and unstable mutant forms of T4 Lysozyme with its wild-type. We find that communities for unstable mutants show substantially poorer agreement with the wild-type communities than do stable mutants, suggesting such ENM-based community structures can serve as a means to rapidly identify deleterious mutants.

Molecular Docking and Dynamic Simulation of AZD3293 and Solanezumab Effects Against BACE1 to Treat Alzheimer's Disease.

The design of novel inhibitors to target BACE1 with reduced cytotoxicity effects is a promising approach to treat Alzheimer's disease (AD). Multiple clinical drugs and antibodies such as AZD3293 and Solanezumab are being tested to investigate their therapeutical potential against AD. The current study explores the binding pattern of AZD3293 and Solanezumab against their target proteins such as β-secretase (BACE1) and mid-region amyloid-beta (Aβ) (PDBIDs: 2ZHV & 4XXD), respectively using molecular docking and dynamic simulation (MD) approaches. The molecular docking results show that AZD3293 binds within the active region of BACE1 by forming hydrogen bonds against Asp32 and Lys107 with distances 2.95 and 2.68 Å, respectively. However, the heavy chain of Solanezumab interacts with Lys16 and Asp23 of amyloid beta having bond length 2.82, 2.78, and 3.00 Å, respectively. The dynamic cross correlations and normal mode analyses show that BACE1 depicted good residual correlated motions and fluctuations, as compared to Solanezumab. Using MD, the Root Mean Square Deviation and Fluctuation (RMSD/F) graphs show that AZD3293 residual fluctuations and RMSD value (0.2 nm) was much better compared to Solanezumab (0.7 nm). Moreover, the radius of gyration (Rg) results also depicts the significance of AZD3293 docked complex compared to Solanezumab through residual compactness. Our comparative results show that AZD3293 is a better therapeutic agent for treating AD than Solanezumab.

Molecular Mechanism Behind the Resistance of the G1202R-Mutated Anaplastic Lymphoma Kinase to the Approved Drug Ceritinib.

Anaplastic lymphoma kinase (ALK) has been regarded as an essential target for the treatment of nonsmall cell lung cancer (NSCLC). However, the emergence of the G1202R solvent front mutation that confers resistance to the drugs was reported for the first as well as the second generation ALK inhibitors. It was thought that the G1202R solvent front mutation might hinder the drug binding. In this study, a different fact could be clarified by multiple molecular modeling methodologies through a structural analogue of ceritinib (compound 10, Cpd-10) that is reported to be a potent inhibitor against the G1202R mutation. Herein, molecular docking, accelerated molecular dynamics (aMD) simulations in conjunction with principal component analysis (PCA), and free energy map calculations were used to produce reasonable and representative initial conformations for the conventional MD simulations. Compared with Cpd-10, the binding specificity of ceritinib between ALK wild-type (ALKWT) and ALK G1202R (ALKG1202R) are primarily controlled by the conformational change of the P-loop- and A-loop-induced energetic redistributions, and the variation is nonpolar interactions, as indicated by conventional MD simulations, PCA, dynamic cross-correlation map (DCCM) analysis, and free energy calculations. Furthermore, the umbrella sampling (US) simulations were carried out to make clear the principle of the dissociation processes of ceritinib and Cpd-10 toward ALKWT and ALKG1202R. The calculation results suggest that Cpd-10 has similar dissociation processes from both ALKWT and ALKG1202R, but ceritinib is more easily dissociated from ALKG1202R than from ALKWT, thus less residence time is responsible for the ceritinib resistance. Our results suggest that both the binding specificity and the drug residence time should be emphasized in rational drug design to overcome the G1202R solvent front mutation of ALK resistance.

Usability and Validation of the Smarter Balance System: An Unsupervised Dynamic Balance Exercises System for Individuals With Parkinson's Disease.

Conventional physical and balance rehabilitation programs to improve balance performance and increase postural stability are often limited due to cost, availability of physical therapists, and accessibility to rehabilitation facilities. Exercise compliance is also affected by a loss of memory and decline in motivation in prescribed home-based balance training. We have developed the smarter balance system (SBS) incorporating multimodal biofeedback (visual plus vibrotactile) intended for clinical and home-based balance rehabilitation and assessed its efficacy on physical therapists' recommended dynamic weight-shifting balance exercises (dynamic WSBE) in individuals with Parkinson's disease (PD). The SBS consists of a smartphone and custom belt housing a processing unit, miniaturized sensors, and vibrating actuators (tactors). Visual and vibrotactile biofeedback guidance during dynamic WSBE is generated by the SBS's custom app based on 90% of the user's limits of stability (LOS). Ten individuals with idiopathic PD having impaired postural stability participated in one unsupervised session comprising 24 trials of the dynamic WSBE in a laboratory setting. Participants' limits of stability (LOS) in the anterior-posterior (A/P) and medial-lateral (M/L) direction were measured at the pre- and post-session. To assess the efficacy of SBS to provide guidance during balance rehabilitation using dynamic WSBE, cross-correlation (XCOR), position error (PE), and percent of tactor activation (PTA) were measured. There was a significant increase in LOS between the pre- and post-training session in both A/P and M/L directions. The average XCOR across all participants were 0.87 (SD = 0.11) and 0.76 (SD = 0.11) for the A/P and M/L direction respectively. The average PE and PTA for the A/P direction was 1.17 deg (SD = 0.60) and 65.35% (SD = 15.1) respectively and 0.74 deg (SD = 0.28) and 31.3% (SD = 16.42) in the M/L direction respectively. There was no significant effect of trials for XCOR, PE, and PTA. Participants' LOS significantly increased after one session of the dynamic WSBE. Individuals with PD could accurately follow the target movements during the dynamic WSBE using the SBS. Future studies will assess the efficacy and acceptability of the SBS during long-term in-home rehabilitative training for balance-impaired individuals.

Dynamic Hebbian Cross-Correlation Learning Resolves the Spike Timing Dependent Plasticity Conundrum.

Spike Timing-Dependent Plasticity has been found to assume many different forms. The classic STDP curve, with one potentiating and one depressing window, is only one of many possible curves that describe synaptic learning using the STDP mechanism. It has been shown experimentally that STDP curves may contain multiple LTP and LTD windows of variable width, and even inverted windows. The underlying STDP mechanism that is capable of producing such an extensive, and apparently incompatible, range of learning curves is still under investigation. In this paper, it is shown that STDP originates from a combination of two dynamic Hebbian cross-correlations of local activity at the synapse. The correlation of the presynaptic activity with the local postsynaptic activity is a robust and reliable indicator of the discrepancy between the presynaptic neuron and the postsynaptic neuron's activity. The second correlation is between the local postsynaptic activity with dendritic activity which is a good indicator of matching local synaptic and dendritic activity. We show that this simple time-independent learning rule can give rise to many forms of the STDP learning curve. The rule regulates synaptic strength without the need for spike matching or other supervisory learning mechanisms. Local differences in dendritic activity at the synapse greatly affect the cross-correlation difference which determines the relative contributions of different neural activity sources. Dendritic activity due to nearby synapses, action potentials, both forward and back-propagating, as well as inhibitory synapses will dynamically modify the local activity at the synapse, and the resulting STDP learning rule. The dynamic Hebbian learning rule ensures furthermore, that the resulting synaptic strength is dynamically stable, and that interactions between synapses do not result in local instabilities. The rule clearly demonstrates that synapses function as independent localized computational entities, each contributing to the global activity, not in a simply linear fashion, but in a manner that is appropriate to achieve local and global stability of the neuron and the entire dendritic structure.

Emergence of a Promising Lead Compound in the Treatment of Triple Negative Breast Cancer: An Insight into Conformational Features and Ligand Binding Landscape of c-Src Protein with UM-164.

UM-164, a potent Src/p38 inhibitor, is a promising lead compound for developing the first targeted therapeutic strategy against triple-negative breast cancer (TNBC). However, lack of understanding of conformational features of UM-164 in complex with Src serves a challenge in the rational design of novel Src dual inhibitors. Herein, we provide an in-depth insight into conformational features of Src-UM-164 using different computational approaches. This involved molecular dynamics (MD) simulation, principal component analysis (PCA), thermodynamics calculations, dynamic cross-correlation (DCCM) analysis, and hydrogen bond formation. Findings from this study revealed that (1) the binding of UM-164 to Src induces a more stable and compact conformation; (2) the binding of UM-164 results in increased correlation among the active site residue; (3) the presence of multiple phenyl rings and fluorinated phenyl group in UM-164 contributes to the steric effect; (4) a relatively high-binding free energy estimated for the Src-UM-164 system is affirmative of its experimental potency; (5) hydrophobic packing contributes significantly to the drug binding in Src-UM-164; and (6) observed increase in H-bond distance of interacting residue atoms and Dasatinib compared to UM-164. Findings from this study can serve as a baseline in the design of novel Src inhibitors with dual inhibitory properties.

Exploring the effect of D61G mutation on SHP2 cause gain of function activity by a molecular dynamics study

Noonan syndrome (NS) is a common autosomal dominant congenital disorder which could cause the congenital cardiopathy and cancer predisposition. Previous studies reported that the knock-in mouse models of the mutant D61G of SHP2 exhibited the major features of NS, which demonstrated that the mutation D61G of SHP2 could cause NS. To explore the effect of D61G mutation on SHP2 and explain the high activity of the mutant, molecular dynamic simulations were performed on wild type (WT) of SHP2 and the mutated SHP2-D61G, respectively. The principal component analysis and dynamic cross-correlation mapping, associated with secondary structure, showed that the D61G mutation affected the motions of two regions (residues Asn 58-Thr 59 and Val 460-His 462) in SHP2 from β to turn. Moreover, the residue interaction networks analysis, the hydrogen bond occupancy analysis and the binding free energies were calculated to gain detailed insight into the influence of the mutant D61G on the two regions, revealing that the major differences between SHP2-WT and SHP2-D61G were the different interactions between Gly 61 and Gly 462, Gly 61 and Ala 461, Gln 506 and Ile 463, Gly 61 and Asn 58, Ile 463 and Thr 466, Gly 462 and Cys 459. Consequently, our findings here may provide knowledge to understand the increased activity of SHP2 caused by the mutant D61G.

New insights into flavivirus biology: the influence of pH over interactions between prM and E proteins

Diseases caused by flaviviruses, such as dengue and zika, are globally recognized as major threats. During infection, a critical point in their replicative cycle is the maturation step, which occurs throughout the cellular exocytic pathway. This step is a pH-dependent process that involves the modification of the viral envelope by converting prM (pre-membrane) into M (membrane) proteins with the release of a "pr peptide". After this reaction, the pr peptides remain bound to the viral envelope while the virions cross the acidic trans-Golgi network, and are released only at neutral pH after secretion of the virus particles. Despite this current knowledge, the molecular basis of the flavivirus maturation step is largely unknown. Here, based on the crystal structure of the dengue pr-E complex ("pr peptide" bound to virus envelope protein) and using molecular dynamics simulations, we found that the pH shift from acidic to neutral yields considerable structural changes in the system. Dynamic cross correlation maps and root mean square deviation analyses revealed that the pr-E junction is clearly unstable under neutral pH. Secondary structure analysis also revealed that the fusion loop region, present in the E protein, is sensitive to pH and tends to unstructure at a neutral environment. Moreover, we found that five residues present in the E protein, Gly102, His244, Thr70, Thr68 and Asn67 are critical to confer stability to the pr-E complex while inside the Golgi apparatus. This work brings details about the dynamical behavior of the pr-E system, helps to better understand the flavivirus biology and may also be of use in the development of novel antiviral strategies.

Insight into interrelation between single-particle and collective diffusion in binary melts

The interrelation between the kinetics of single-particle (tracer) and collective diffusion in a binary melt is investigated theoretically within the framework of the Mori–Zwanzig formalism of statistical mechanics. An analytical expression for the Onsager coefficient for mass transport and two self-diffusion coefficients of species in a binary melt is derived using analysis based on the generalized Langevin equation. The derived expression naturally accounts for manifestation of microscopic (dynamic) cross-correlation effects in the kinetics of collective diffusion. Hence, it presents an explicit extension of the well-known Darken equation which is currently often used for expressing collective interdiffusion in terms of the two self-diffusion coefficients. An application of our analysis for interpretation of recent experimental data on the interrelation between the kinetics of single-particle and collective diffusion in Al-rich Ni–Al melts is demonstrated.

Mutational analysis of microbial hydroxycinnamoyl-CoA hydratase-lyase (HCHL) towards enhancement of binding affinity: A computational approach

Improving the industrial enzyme for better yield of the product is important and a challenging task. One of such important industrial enzymes is microbial Hydroxycinnamoyl-CoA hydratase-lyase (HCHL). It converts feruloyl-CoA to vanillin. We place our efforts towards the improvement of its catalytic activity with comprehensive computational investigation. Catalytic core of the HCHL was explored with molecular modeling and docking approaches. Site-directed mutations were introduced in the catalytic site of HCHL in a sequential manner to generate different mutants of HCHL. Basis of mutation is to increase the interaction between HCHL and substrate feruloyl-CoA through interatomic forces and hydrogen bond formation. A rigorous molecular dynamics (MD) simulation was performed to check the stability of mutant’s structure. Root mean square deviation (RMSD), root mean square fluctuation (RMSF), dynamic cross correlation (DCCM) and principal component analysis (PCA) were also performed to analyze flexibility and stability of structures. Docking studies were carried out between different mutants of HCHL and feruloyl-CoA. Investigation of the different binding sites and the interactions with mutant HCHLs and substrate allowed us to highlight the improved performance of mutants than wild type HCHL. This was further validated with MD simulation of complex consisting of different mutants and substrate. It further confirms all the structures are stable. However, mutant-2 showed better affinity towards substrate by forming hydrogen bond between active site and feruloyl-CoA. We propose that increase in hydrogen bond formation might facilitate in dissociation of vanillin from feruloyl-CoA. The current work may be useful for the future development of ‘tailor-made’ enzymes for better yield of vanillin.

MD-TASK: a software suite for analyzing molecular dynamics trajectories.

SummaryMolecular dynamics (MD) determines the physical motions of atoms of a biological macromolecule in a cell-like environment and is an important method in structural bioinformatics. Traditionally, measurements such as root mean square deviation, root mean square fluctuation, radius of gyration, and various energy measures have been used to analyze MD simulations. Here, we present MD-TASK, a novel software suite that employs graph theory techniques, perturbation response scanning, and dynamic cross-correlation to provide unique ways for analyzing MD trajectories.Availability and implementationMD-TASK has been open-sourced and is available for download from https://github.com/RUBi-ZA/MD-TASK, implemented in Python and supported on Linux/Unix.

Dynamic cross-correlations between entangled biofilaments as they diffuse

Entanglement in polymer and biological physics involves a state in which linear interthreaded macromolecules in isotropic liquids diffuse in a spatially anisotropic manner beyond a characteristic mesoscopic time and length scale (tube diameter). The physical reason is that linear macromolecules become transiently localized in directions transverse to their backbone but diffuse with relative ease parallel to it. Within the resulting broad spectrum of relaxation times there is an extended period before the longest relaxation time when filaments occupy a time-averaged cylindrical space of near-constant density. Here we show its implication with experiments based on fluorescence tracking of dilutely labeled macromolecules. The entangled pairs of aqueous F-actin biofilaments diffuse with separation-dependent dynamic cross-correlations that exceed those expected from continuum hydrodynamics up to strikingly large spatial distances of ≈15 µm, which is more than 104 times the size of the solvent water molecules in which they are dissolved, and is more than 50 times the dynamic tube diameter, but is almost equal to the filament length. Modeling this entangled system as a collection of rigid rods, we present a statistical mechanical theory that predicts these long-range dynamic correlations as an emergent consequence of an effective long-range interpolymer repulsion due to the de Gennes correlation hole, which is a combined consequence of chain connectivity and uncrossability. The key physical assumption needed to make theory and experiment agree is that solutions of entangled biofilaments localized in tubes that are effectively dynamically incompressible over the relevant intermediate time and length scales.

Inter-diffusion and its correlation with dynamical cross correlation in liquid Ce80Ni20

We reported the inter-diffusion coefficients in liquid Ce $$_{80}$$ Ni $$_{20}$$ measured by the sliding cell technique. Combined with the self-diffusion data of Ni measured by quasi-elastic neutron scattering in the literature, it was found that the relationship between inter-diffusion and self-diffusion in liquid Ce $$_{80}$$ Ni $$_{20}$$ was strongly deviated from the standard Darken equation with an abnormally small dynamical cross correlation factor S (the so called Manning factor) in a range of 0.6–0.8, less than unity in standard systems. Through the calculated distinct diffusion coefficient and its deviation from the standard one, it was discovered that the small S value was directly originated from enhanced distinct diffusion between Ce and Ni atoms and reduced distinct diffusion between Ni and Ni atoms. Because the inter-atomic interaction was not considered in the standard liquids, the present small S factor and intrinsic distinct diffusion coefficients were believed to be resulted from the chemical interaction between Ce and Ni in the liquid. The results provide new evidence of the dynamic cross correlation in liquid diffusion, and thus shed light on the understanding of the correlation between dynamics and structure in liquid alloys.

The Structural and Dynamic Effects of Inhibitor Binding to Protein Kinase C βII

Protein kinase C βII (PKCβII) regulates diverse cellular signaling pathways involved in B-cell activation, insulin signaling, and oxidative stress-induced apoptosis. Aberrant PKCβII activity has been implicated in a variety of human diseases including diabetic retinopathy and B-cell immunodeficiency. Accordingly, PKCβII has become a popular target for small molecule based inhibition. However, the effects of available inhibitors on the conformational dynamics and allosteric couplings essential for PKCβII function remains largely unknown. This lack of knowledge hampers the development of improved inhibitors and limits our understanding of how disease-associated mutations in distal sites can interfere with inhibitor efficacy. Here we characterize distinct flexibilities and internal dynamical couplings upon inhibitor binding using molecular dynamics (MD) simulations and bioinformatics analysis. MD simulations revealed increased flexibility of the nucleotide-binding P-loop and the regulatory C-terminal tail when bound to the ATP-competitive inhibitor Bisindolylmaleimide I (BIM1). Community partitioning of the dynamical cross-correlations, based on network approaches, reveal further variations between ATP and inhibitor states. Specifically, the inhibitor state exhibits overall dynamical tightening, with stronger couplings between communities encompassing the C-terminal tail in the N-lobe and helices αE, αG, αH and activation loop in the C-lobe. In contrast, the ATP state displays distinct couplings between active-site residues that are lost upon inhibitor binding. Furthermore, mutational simulations of residues exhibiting state specific couplings demonstrate a shift towards inhibitor-state dynamics, indicating their role in allosteric modulation. Collectively, this study elucidates the effect of inhibitor binding on conformational dynamics and furthers our understanding of allosteric mechanisms in PKCβII.

Detection of Side Chain Rearrangements Mediating the Motions of Transmembrane Helices in Molecular Dynamics Simulations of G Protein-Coupled Receptors

Structure and dynamics are essential elements of protein function. Protein structure is constantly fluctuating and undergoing conformational changes, which are captured by molecular dynamics (MD) simulations. We introduce a computational framework that provides a compact representation of the dynamic conformational space of biomolecular simulations. This method presents a systematic approach designed to reduce the large MD simulation spatiotemporal datasets into a manageable set in order to guide our understanding of how protein mechanics emerge from side chain organization and dynamic reorganization. We focus on the detection of side chain interactions that undergo rearrangements mediating global domain motions and vice versa. Side chain rearrangements are extracted from side chain interactions that undergo well-defined abrupt and persistent changes in distance time series using Gaussian mixture models, whereas global domain motions are detected using dynamic cross-correlation. Both side chain rearrangements and global domain motions represent the dynamic components of the protein MD simulation, and are both mapped into a network where they are connected based on their degree of coupling. This method allows for the study of allosteric communication in proteins by mapping out the protein dynamics into an intramolecular network to reduce the large simulation data into a manageable set of communities composed of coupled side chain rearrangements and global domain motions. This computational framework is suitable for the study of tightly packed proteins, such as G protein-coupled receptors, and we present an application on a seven microseconds MD trajectory of CC chemokine receptor 7 (CCR7) bound to its ligand CCL21.

Investigation of intrinsic dynamics of enzymes involved in metabolic pathways using coarse-grained normal mode analysis

AbstractIntrinsic dynamics of proteins are known to play important roles in their function. In particular, collective dynamics of a protein, which are defined by the protein’s overall architecture, are important in promoting the active site conformation that favors substrate binding and effective catalysis. The primary sequence of a protein, which determines its three-dimensional structure, encodes unique dynamics. The intrinsic dynamics of a protein actually link protein structure to its function. In the present study, coarse-grained normal mode analysis was performed to examine the intrinsic dynamic patterns of 24 different enzymes involved in primary metabolic pathways. We observed that each metabolic enzyme exhibits unique patterns of motions, which are conserved across multiple species and functionally relevant. Dynamic cross-correlation matrices (DCCMs) are visibly identical for a given enzyme family but significantly different from DCCMs of other protein families, reinforcing that proteins with sim...