Side-chain Fluctuations Research Articles

Structural and Computational Insights into Dynamics and Intermediate States of Orexin 2 Receptor Signaling.

Orexin 2 receptor (OX2R) is a G protein-coupled receptor (GPCR) whose activation is crucial to regulation of the sleep-wake cycle. Recently, inactive and active state structures were determined from X-ray crystallography and cryo-electron microscopy single particle analysis, and the activation mechanisms have been discussed based on these static data. GPCRs have multiscale intermediate states during activation, and insights into these dynamics and intermediate states may aid the precise control of intracellular signaling by ligands in drug discovery. Molecular dynamics (MD) simulations are used to investigate dynamics induced in response to thermal perturbations, such as structural fluctuations of main and side chains. In this study, we proposed collective motions of the TM domain during activation by performing 30 independent microsecond-scale MD simulations for various OX2R systems and applying relaxation mode analysis. The analysis results suggested that TM3 had a vertical structural movement relative to the membrane surface during activation. In addition, we extracted three characteristic amino acid residues on TM3, i.e., Q1343.32, V1423.40, and R1523.50, which exhibited large conformational fluctuations. We quantitatively evaluated the changes in their equilibrium during activation in relation to the movement of TM3. We also discuss the regulation of ligand binding recognition and intracellular signal selectivity by changes in the equilibrium of Q1343.32 and R1523.50, respectively, according to MD simulations and GPCR database. Additionally, the OX2R-Gi signaling complex is stabilized in the conformation resembling a non-canonical (NC) state, which was previously proposed as an intermediate state during activation of neurotensin 1 receptor. Insights into the dynamics and intermediate states during activation gained from this study may be useful for developing biased agonists for OX2R.

Data-Efficient Generation of Protein Conformational Ensembles with Backbone-to-Side-Chain Transformers.

Excitement at the prospect of using data-driven generative models to sample configurational ensembles of biomolecular systems stems from the extraordinary success of these models on a diverse set of high-dimensional sampling tasks. Unlike image generation or even the closely related problem of protein structure prediction, there are currently no data sources with sufficient breadth to parametrize generative models for conformational ensembles. To enable discovery, a fundamentally different approach to building generative models is required: models should be able to propose rare, albeit physical, conformations that may not arise in even the largest data sets. Here we introduce a modular strategy to generate conformations based on "backmapping" from a fixed protein backbone that (1) maintains conformational diversity of the side chains and (2) couples the side-chain fluctuations using global information about the protein conformation. Our model combines simple statistical models of side-chain conformations based on rotamer libraries with the now ubiquitous transformer architecture to sample with atomistic accuracy. Together, these ingredients provide a strategy for rapid data acquisition and hence a crucial ingredient for scalable physical simulation with generative neural networks.

Mutant anaplastic lymphoma kinase inhibitor identification by integrated in silico approaches

ABSTRACT Non-small-cell lung cancer (NSCLC) is the primary form of lung cancer globally and remains a leading cause of mortality. Anaplastic lymphoma kinase (ALK) mutations, such as I1171N + L1198H, have been discovered to confer resistance to current ALK inhibitors, reducing their therapeutic effectiveness. Addressing drug resistance necessitates exploring selective inhibitors for innovative therapeutic approaches. In this study, a structure-based pharmacophore model, using ALK-approved inhibitors, was developed to screen an In-house database for potential mutant ALK inhibitors. Compounds with requisite pharmacophoric features were evaluated for binding potential against the I1171N + L1198H ALK mutant phenotype. Selected hits underwent assessment for chemical reactivity, and dynamics stability. The study identified five chemical scaffolds (NS1-5) with favorable binding modes and pharmacokinetic properties. The conformational ensembles featured the average RMSD values, ranging from 0.4 to 0.6 nm. RMSF analysis revealed consistent side chain fluctuations with reduced flexibility, while Rog analysis indicated convergence of most complexes. NS1 and NS5, in particular emerged as promising candidates, exhibiting remarkable performance than others, with binding free energies of −210.12 ± 9.94 and −163.68 ± 11.14 kcal/mol, respectively. These findings thus suggest further exploration and optimisation of NS1 and NS5 for mutant ALK inhibitors for the treatment of NSCLC.

Reaction within the coulomb-cage; science in retrospect

The Coulomb-cage is defined as the space where the electrostatic interaction between two bodies is more intensive than the thermal energy (kBT). For small molecule, the Coulomb-cage is a small sphere, extending only few water molecules towards the bulk and its radius is sensitive to the ionic strength of the solution. For charged proteins or membranal structures, the Coulomb-cage can engulf large fraction of the surface and provides a preferred pathway for ion propagation along the surface. Similarly, electrostatic potential at the inner space of a channel can form preferential trajectories passage for ions. The dynamics of ions inside the Coulomb-cage of ions was formulated by the studies of proton-anion recombination of excited photoacids. In the present article, we recount the study of intra- Coulomb-cage reaction taking place on the surface of macro-molecular bodies like micelles, membranes, proteins and intra-protein cavities. The study progressed stepwise, tracing the dynamics of a proton ejected from a photo-acid molecule located at defined sites (on membrane, inter-membrane space, active site of enzyme, inside Large Pore Channels etc.). Accumulation of experimental observations encouraged us to study of the reaction mechanism by molecular dynamics simulations of ions within the Coulomb-cage of proteins surface or inside large pores. The intra-Coulomb-cage proton transfer events follows closely the fine structure of the electrostatic field inside the cage and reflects the shape of nearby dielectric boundaries, the temporal ordering of the solvent molecules and the structural fluctuations of the charged side chains. The article sums some 40 years of research, which in retrospect clarifies the intra-Coulomb-cage reaction mechanism.

A dynamical view of protein-protein complexes: Studies by molecular dynamics simulations.

Protein-protein interactions are at the basis of many protein functions, and the knowledge of 3D structures of protein-protein complexes provides structural, mechanical and dynamical pieces of information essential to understand these functions. Protein-protein interfaces can be seen as stable, organized regions where residues from different partners form non-covalent interactions that are responsible for interaction specificity and strength. They are commonly described as a peripheral region, whose role is to protect the core region that concentrates the most contributing interactions, from the solvent. To get insights into the dynamics of protein-protein complexes, we carried out all-atom molecular dynamics simulations in explicit solvent on eight different protein-protein complexes of different functional class and interface size by taking into account the bound and unbound forms. On the one hand, we characterized structural changes upon binding of the proteins, and on the other hand we extensively analyzed the interfaces and the structural waters involved in the binding. Based on our analysis, in 6 cases out of 8, the interfaces rearranged during the simulation time, in stable and long-lived substates with alternative residue-residue contacts. These rearrangements are not restricted to side-chain fluctuations in the periphery but also affect the core interface. Finally, the analysis of the waters at the interface and involved in the binding pointed out the importance to take into account their role in the estimation of the interaction strength.

Information Transfer in Active States of Human β2-Adrenergic Receptor via Inter-Rotameric Motions of Loop Regions

Two independent 1.5 μs long MD simulations were conducted for the fully atomistic model of the human beta2-adrenergic receptor (β2AR) in a complex with a G protein to investigate the signal transmission in a fully active state via mutual information and transfer entropy based on α-carbon displacements and rotameric states of backbone and side-chain torsion angles. Significant correlations between fluctuations in α-Carbon displacements were mostly detected between transmembrane (TM) helices, especially TM5 and TM6 located at each end of ICL3 and TM7. Signal transmission across β2-AR was quantified by shared mutual information; a high amount of correspondence was distinguished in almost all loop regions when rotameric states were employed. Moreover, polar residues, especially Arg, made the most contribution to signal transmission via correlated side-chain rotameric fluctuations as they were more frequently observed in loop regions than hydrophobic residues. Furthermore, transfer entropy identified all loop regions as major entropy donor sites, which drove future rotameric states of torsion angles of residues in transmembrane helices. Polar residues appeared as donor sites from which entropy flowed towards hydrophobic residues. Overall, loops in β2AR were recognized as potential allosteric hot spot regions, which play an essential role in signal transmission and should likely be used as potential drug targets.

Structure and Dynamics of the Isozymes II and IX of Human Carbonic Anhydrase.

Human carbonic anhydrases (HCAs) are responsible for the pH control and sensing in our body and constitute key components in the central pH paradigm connected to cancer therapeutics. However, little or no molecular level studies are available on the pH-dependent stability and functional dynamics of the known isozymes of HCA. The main objective of this Article is to report the first bench-marking study on the structure and dynamics of the two most efficient isozymes, HCA II and IX, at neutral pH using classical molecular dynamics (MD) and constant pH MD (CpHMD) simulations combined with umbrella sampling, transition path sampling, and Markov state models. Starting from the known crystal structures of HCA II and the monomeric catalytic domain of HCA IX (labeled as HCA IX-c), we have generated classical MD and CpHMD trajectories (of length 1 μs each). In all cases, the overall stability, RMSD, and secondary structure segments of the two isozymes are found to be quite similar. Functionally important dynamics of these two enzymes have been probed in terms of active site hydration, coordination of the Zn(II) ion to a transient excess water, and the formation of putative proton transfer paths. The most important difference between the two isozymes is observed for the side-chain fluctuations of His-64 that is expected to shuttle an excess proton out of the active site as a part of the rate-determining intramolecular proton transfer reaction. The relative stability of the stable inward and outward conformations of the His-64 side-chain and the underlying free energy surfaces are found to depend strongly on the isozyme. In each case, a lower free energy barrier is detected between predominantly inward conformations from predominantly outward ones when simulated under constant pH conditions. The kinetic rate constants of interconversion between different free energy basins are found to span 107–108 s–1 with faster conformational transitions predicted at constant pH condition. The estimated rate constants and free energies are expected to validate if the fluctuation of the His-64 side-chain in HCA IX may have a significance similar to that known in the multistep catalytic cycle of HCA II.

Correlating the Local and Global Dynamics of an Enzyme in the Crowded Milieu.

Enzymes are dynamic biological macromolecules, with their catalytic function(s) being largely influenced by the changes in local fluctuations of amino acid side chains as well as global structural modulations that the enzyme undergoes. Such local and global motions can be highly affected inside the crowded physiological interior of the cell. Here, we have addressed the role of dynamic structural flexibility in affecting the activation energy barrier of a flexible multidomain enzyme adenylate kinase (AK3L1, UniProtKB: Q9UIJ7). Activation energy profiles of both local (at three different sites along the polypeptide backbone) and global dynamics of the enzyme have been monitored using solvation studies on the subnanosecond time scale and tryptophan quenching studies over the temperature range of 278-323 K, respectively, under crowded conditions (Ficoll 70, Dextran 40, Dextran 70, and PEG 8). This study not only provides the site-specific mapping of dynamics but reveals that the activation energies associated with these local motions undergo a significant decrease in the presence of macromolecular crowders, providing new insights into how crowding affects internal protein dynamics. The crowded scenario also aids in enhancing the coupling between the local and global motions of the enzyme. Moreover, select portions/regions of the enzyme when taken together can well mirror the overall dynamics of the biomolecule, showing possible energy hotspots along the polypeptide backbone.

Pseudokinases repurpose flexibility signatures associated with the protein kinase fold for noncatalytic roles.

The bilobal protein kinase-like fold in pseudokinases lack one or more catalytic residues, conserved in canonical protein kinases, and are considered enzymatically deficient. Tertiary structures of pseudokinases reveal that their loops topologically equivalent to activation segments of kinases adopt contracted configurations, which is typically extended in active conformation of kinases. Herein, anisotropic network model based normal mode analysis (NMA) was conducted on 51 active conformation structures of protein kinases and 26 crystal structures of pseudokinases. Our observations indicate that although backbone fluctuation profiles are similar for individual kinase-pseudokinase families, low intensity mean square fluctuations in pseudo-activation segment and other sub-structures impart rigidity to pseudokinases. Analyses of collective motions from functional modes reveal that pseudokinases, compared to active kinases, undergo distinct conformational transitions using the same structural fold. All-atom NMA of protein kinase-pseudokinase pairs from each family, sharing high amino acid sequence identities, yielded distinct community clusters, partitioned by residues exhibiting highly correlated fluctuations. It appears that atomic fluctuations from equivalent activation segments guide community membership and network topologies for respective kinase and pseudokinase. Our findings indicate that such adaptations in backbone and side-chain fluctuations render pseudokinases competent for catalysis-independent roles.

Correlated Response of Protein Side-Chain Fluctuations and Conformational Entropy to Ligand Binding.

The heterogeneous fast side-chain dynamics of proteins plays crucial roles in molecular recognition and binding. Site-specific NMR experiments quantify these motions by measuring the model-free order parameter (Oaxis2) on a scale of 0 (most flexible) to 1 (least flexible) for each methyl-containing residue of proteins. Here, we have examined ligand-induced variations in the fast side-chain dynamics and conformational entropy of calmodulin (CaM) using five different CaM-peptide complexes. Oaxis2 of CaM in the ligand-free (Oaxis,U2) and ligand-bound (Oaxis,B2) states are calculated from molecular dynamics trajectories and conformational energy surfaces obtained using the adaptive biasing force (ABF) method. ΔOaxis2 = Oaxis,B2 - Oaxis,U2 follows a Gaussian-like unimodal distribution whose second moment is a potential indicator of the binding affinity of these complexes. The probability for the binding-induced Oaxis,U2 → Oaxis,B2 transition decreases with increasing magnitude of ΔOaxis2, indicating that large flexibility changes are improbable for side chains of CaM after ligand binding. A linear correlation established between ΔOaxis2 and the conformational entropy change of the protein makes possible the determination of the conformational entropy of binding of protein-ligand complexes. The results not only underscore the functional importance of fast side-chain fluctuations but also highlight key motional and thermodynamic correlates of protein-ligand binding.

Virtual screening and molecular dynamics study of approved drugs as inhibitors of spike protein S1 domain and ACE2 interaction in SARS-CoV-2

BackgroundThe receptor binding domain (RBD) of spike protein S1 domain SARS-CoV-2 plays a key role in the interaction with ACE2, which leads to subsequent S2 domain mediated membrane fusion and incorporation of viral RNA into host cells. In this study we tend to repurpose already approved drugs as inhibitors of the interaction between S1-RBD and the ACE2 receptor. Methods2456 approved drugs were screened against the RBD of S1 protein of SARS-CoV-2 (target PDB ID: 6M17). As the interacting surface between S1-RBD and ACE2 comprises of bigger region, the interacting surface was divided into 3 sites on the basis of interactions (site 1, 2 and 3) and a total of 5 grids were generated (site 1, site 2, site 3, site 1+site 2 and site 2+site 3). A virtual screening was performed using GLIDE implementing HTVS, SP and XP screening. The top hits (on the basis of docking score) were further screened for MM-GBSA. All the top hits were further evaluated in molecular dynamics studies. Performance of the virtual screening protocol was evaluated using enrichment studies. Resultand discussion: We performed 5 virtual screening against 5 grids generated. A total of 42 compounds were identified after virtual screening. These drugs were further assessed for their interaction dynamics in molecular dynamics simulation. On the basis of molecular dynamics studies, we come up with 10 molecules with favourable interaction profile, which also interacted with physiologically important residues (residues taking part in the interaction between S1-RBD and ACE2. These are antidiabetic (acarbose), vitamins (riboflavin and levomefolic acid), anti-platelet agents (cangrelor), aminoglycoside antibiotics (Kanamycin, amikacin) bronchodilator (fenoterol), immunomodulator (lamivudine), and anti-neoplastic agents (mitoxantrone and vidarabine). However, while considering the relative side chain fluctuations when compared to the S1-RBD: ACE2 complex riboflavin, fenoterol, cangrelor and vidarabine emerged out as molecules with prolonged relative stability. ConclusionWe identified 4 already approved drugs (riboflavin, fenoterol, cangrelor and vidarabine) as possible agents for repurposing as inhibitors of S1:ACE2 interaction. In-vitro validation of these findings are necessary for identification of a safe and effective inhibitor of S1: ACE2 mediated entry of SARS-CoV-2 into the host cell.

Solution Structure and Conformational Flexibility in the Active State of the Orange Carotenoid Protein. Part II: Quasielastic Neutron Scattering.

Orange carotenoid proteins (OCPs), which are protecting cyanobacterial light-harvesting antennae from photodamage, undergo a pronounced structural change upon light absorption. In addition, the active state is anticipated to boost a significantly higher molecular flexibility similar to a "molten globule" state. Here, we used quasielastic neutron scattering to directly characterize the vibrational and conformational molecular dynamics of OCP in its ground and active states, respectively, on the picosecond time scale. At a temperature of 100 K, we observe mainly (vibronic) inelastic features with peak energies at 5 and 6 meV (40 and 48 cm-1, respectively). At physiological temperatures, however, two (Lorentzian) quasielastic components represent localized protein motions, that is, stochastic structural fluctuations of protein side chains between various conformational substates of the protein. Global diffusion of OCP is not observed on the given time scale. The slower Lorentzian component is affected by illumination and can be well-characterized by a jump-diffusion model. While the jump diffusion constant D is (2.82 ± 0.01) × 10-5 cm2/s at 300 K in the ground state, it is increased by ∼20% to (3.48 ± 0.01) × 10-5 cm2/s in the active state, revealing a strong enhancement of molecular mobility. The increased mobility is also reflected in the average atomic mean square displacement ⟨u2⟩; we determine a ⟨u2⟩ of 1.47 ± 0.05 Å in the ground state, but 1.86 ± 0.05 Å in the active state (at 300 K). This effect is assigned to two factors: (i) the elongated structure of the active state with two widely separated protein domains is characterized by a larger number of surface residues with a concomitantly higher degree of motional freedom and (ii) a larger number of hydration water molecules bound at the surface of the protein. We thus conclude that the active state of the orange carotenoid protein displays an enhanced conformational dynamics. The higher degree of flexibility may provide additional channels for nonradiative decay so that harmful excess energy can be more efficiently converted to heat.

Dynamics of proteins in solution

AbstractThe dynamics of proteins in solution includes a variety of processes, such as backbone and side-chain fluctuations, interdomain motions, as well as global rotational and translational (i.e. center of mass) diffusion. Since protein dynamics is related to protein function and essential transport processes, a detailed mechanistic understanding and monitoring of protein dynamics in solution is highly desirable. The hierarchical character of protein dynamics requires experimental tools addressing a broad range of time- and length scales. We discuss how different techniques contribute to a comprehensive picture of protein dynamics, and focus in particular on results from neutron spectroscopy. We outline the underlying principles and review available instrumentation as well as related analysis frameworks.

Tuning Free Energy by Backbone Conformational Entropy: A Strategy from Disordered Proteins

Tuning Free Energy by Backbone Conformational Entropy: A Strategy from Disordered Proteins

Origin of diverse time scales in the protein hydration layer solvation dynamics: A simulation study.

In order to inquire the microscopic origin of observed multiple time scales in solvation dynamics, we carry out several computer experiments. We perform atomistic molecular dynamics simulations on three protein-water systems, namely, lysozyme, myoglobin, and sweet protein monellin. In these experiments, we mutate the charges of the neighbouring amino acid side chains of certain natural probes (tryptophan) and also freeze the side chain motions. In order to distinguish between different contributions, we decompose the total solvation energy response in terms of various components present in the system. This allows us to capture the interplay among different self- and cross-energy correlation terms. Freezing the protein motions removes the slowest component that results from side chain fluctuations, but a part of slowness remains. This leads to the conclusion that the slow component approximately in the 20-80 ps range arises from slow water molecules present in the hydration layer. While the more than 100 ps component has multiple origins, namely, adjacent charges in amino acid side chains, hydrogen bonded water molecules and a dynamically coupled motion between side chain and water. In addition, the charges enforce a structural ordering of nearby water molecules and helps to form a local long-lived hydrogen bonded network. Further separation of the spatial and temporal responses in solvation dynamics reveals different roles of hydration and bulk water. We find that the hydration layer water molecules are largely responsible for the slow component, whereas the initial ultrafast decay arises predominantly (approximately 80%) due to the bulk. This agrees with earlier theoretical observations. We also attempt to rationalise our results with the help of a molecular hydrodynamic theory that was developed using classical time dependent density functional theory in a semi-quantitative manner.

Observation of the Global Dynamic Collectivity of a Hydration Shell around Apomyoglobin.

Protein surface hydration is critical to the protein's structural properties and biological activities. However, it is still unknown whether the hydration shell is intrinsically connected and how its fluctuations dynamically interact with protein motion. Here, by selecting five site-specific locations with distinctly different environments around the surface of apomyoglobin, we used a tryptophan scan with femtosecond fluorescence spectroscopy and simultaneously detected hydration water dynamics and tryptophan side-chain relaxations with temperature dependence. We observed two types of relaxations for both interfacial hydration water and the tryptophan side chain. The former is always faster than the latter, and both motions show direct linear correlations with temperature changes, indicating one origin of their motions and hydration water driving of side-chain fluctuations. Significantly, we found the relaxation energy barriers are uniform across the entire protein surface, all less than 20 kJ/mol, strongly suggesting highly extended cooperative water networks and the nature of global dynamic collectivity of the entire hydration shell.

Direct Investigation of Slow Correlated Dynamics in Proteins via Dipolar Interactions.

The synchronization of native state motions as they transition between microstates influences catalysis kinetics, mediates allosteric interactions, and reduces the conformational entropy of proteins. However, it has proven difficult to describe native microstates because they are usually minimally frustrated and may interconvert on the micro- to millisecond time scale. Direct observation of concerted equilibrium fluctuations would therefore be an important tool for describing protein native states. Here we propose a strategy that relates NMR cross-correlated relaxation (CCR) rates between dipolar interactions to residual dipolar couplings (RDCs) of individual consecutive H(N)-N and H(α)-C(α) bonds, which act as a proxy for the peptide planes and the side chains, respectively. Using Xplor-NIH ensemble structure calculations restrained with the RDC and CCR data, we observe collective motions on time scales slower than nanoseconds in the backbone for GB3. To directly access the correlations from CCR, we develop a structure-free data analysis. The resulting dynamic correlation map is consistent with the ensemble-restrained simulations and reveals a complex network. In general, we find that the bond motions are on average slightly correlated and that the local environment dominates many observations. Despite this, some patterns are typical over entire secondary structure elements. In the β-sheet, nearly all bonds are weakly correlated, and there is an approximately binary alternation in correlation intensity corresponding to the solvent exposure/shielding alternation of the side chains. For α-helices, there is also a weak correlation in the H(N)-N bonds. The degree of correlation involving H(α)-C(α) bonds is directly affected by side-chain fluctuations, whereas loops show complex and nonuniform behavior.

Protein Binding Pocket Dynamics.

The dynamics of protein binding pockets are crucial for their interaction specificity. Structural flexibility allows proteins to adapt to their individual molecular binding partners and facilitates the binding process. This implies the necessity to consider protein internal motion in determining and predicting binding properties and in designing new binders. Although accounting for protein dynamics presents a challenge for computational approaches, it expands the structural and physicochemical space for compound design and thus offers the prospect of improved binding specificity and selectivity. A cavity on the surface or in the interior of a protein that possesses suitable properties for binding a ligand is usually referred to as a binding pocket. The set of amino acid residues around a binding pocket determines its physicochemical characteristics and, together with its shape and location in a protein, defines its functionality. Residues outside the binding site can also have a long-range effect on the properties of the binding pocket. Cavities with similar functionalities are often conserved across protein families. For example, enzyme active sites are usually concave surfaces that present amino acid residues in a suitable configuration for binding low molecular weight compounds. Macromolecular binding pockets, on the other hand, are located on the protein surface and are often shallower. The mobility of proteins allows the opening, closing, and adaptation of binding pockets to regulate binding processes and specific protein functionalities. For example, channels and tunnels can exist permanently or transiently to transport compounds to and from a binding site. The influence of protein flexibility on binding pockets can vary from small changes to an already existent pocket to the formation of a completely new pocket. Here, we review recent developments in computational methods to detect and define binding pockets and to study pocket dynamics. We introduce five different classes of protein pocket dynamics: (1) appearance/disappearance of a subpocket in an existing pocket; (2) appearance/disappearance of an adjacent pocket on the protein surface in the direct vicinity of an already existing pocket; (3) pocket breathing, which may be caused by side-chain fluctuations or backbone or interdomain vibrational motion; (4) opening/closing of a channel or tunnel, connecting a pocket inside the protein with solvent, including lid motion; and (5) the appearance/disappearance of an allosteric pocket at a site on a protein distinct from an already existing pocket with binding of a ligand to the allosteric binding site affecting the original pocket. We suggest that the class of pocket dynamics, as well as the type and extent of protein motion affecting the binding pocket, should be factors considered in choosing the most appropriate computational approach to study a given binding pocket. Furthermore, we examine the relationship between pocket dynamics classes and induced fit, conformational selection, and gating models of ligand binding on binding kinetics and thermodynamics. We discuss the implications of protein binding pocket dynamics for drug design and conclude with potential future directions for computational analysis of protein binding pocket dynamics.

Glass-Transition and Side-Chain Dynamics in Thin Films: Explaining Dissimilar Free Surface Effects for Polystyrene vs Poly(methyl methacrylate).

Despite having very similar bulk properties such as glass-transition temperature (Tg), density, and fragility, polystyrene (PS) and poly(methyl methacrylate) (PMMA) exhibit characteristically different Tg depression in free-standing ultrathin films due to free surface effects. Here we explain this difference using our recently established chemistry-specific coarse-grained (CG) models for these two polymers. Models capture the dissimilar scaling of Tg with free-standing film thickness as seen in experiments and enable us to quantify the size of the regions near free surfaces over which chain relaxation exhibits differences from bulk. Most interestingly, vibrational density of states (VDOS) analysis uncovers a relationship between the amplitude of side-chain fluctuations, associated with side-chain flexibility and Tg-nanoconfinement. We discover that increasing backbone to side-chain mass ratio in CG models increases the amplitude of side-chain fluctuations and suppresses the free-surface effect on Tg. We show that mass distribution and side-chain flexibility are central to explain dissimilar free surface effects on PS and PMMA. Our model predictions are further corroborated by experimental evidence showing the role of mass distribution in styrene thin films. Our study ascertains the significance of molecular characteristics on nanoconfinement and highlights the ability for chemistry-specific CG models to explore the thermomechanical properties of polymer thin films.

Calculated pKa Variations Expose Dynamic Allosteric Communication Networks.

Allosteric regulation of protein function, the process by which binding of an effector molecule provokes a functional response from a distal site, is critical for metabolic pathways. Yet, the way the allosteric signal is communicated remains elusive, especially in dynamic, entropically driven regulation mechanisms for which no major conformational changes are observed. To identify these dynamic allosteric communication networks, we have developed an approach that monitors the pKa variations of ionizable residues over the course of molecular dynamics simulations performed in the presence and absence of an allosteric regulator. As the pKa of ionizable residues depends on their environment, it represents a simple metric to monitor changes in several complex factors induced by binding an allosteric effector. These factors include Coulombic interactions, hydrogen bonding, and solvation, as well as backbone motions and side chain fluctuations. The predictions that can be made with this method concerning the roles of ionizable residues for allosteric communication can then be easily tested experimentally by changing the working pH of the protein or performing single point mutations. To demonstrate the method's validity, we have applied this approach to the subtle dynamic regulation mechanism observed for Neisseria meningitidis 3-deoxy-d-arabino-heptulosonate 7-phosphate synthase, the first enzyme of aromatic biosynthesis. We were able to identify key communication pathways linking the allosteric binding site to the active site of the enzyme and to validate these findings experimentally by reestablishing the catalytic activity of allosterically inhibited enzyme via modulation of the working pH, without compromising the binding affinity of the allosteric regulator.