Parallel Generalized Born Implicit Solvent Calculations with NAMD

From quantum to subcellular scales: multi-scale simulation approaches and the SIRAH force field

Modern molecular and cellular biology profits from astonishing resolution structural methods, currently even reaching the whole cell level. This is encompassed by the development of computational methods providing a deep view into the structure and dynamics of molecular processes happening at very different scales in time and space. Linking such scales is of paramount importance when aiming at far-reaching biological questions. Computational methods at the interface between classical and coarse-grained resolutions are gaining momentum with several research groups dedicating important efforts to their development and tuning. An overview of such methods is addressed herein, with special emphasis on the SIRAH force field for coarse-grained and multi-scale simulations. Moreover, we provide proof of concept calculations on the implementation of a multi-scale simulation scheme including quantum calculations on a classical fine-grained/coarse-grained representation of double-stranded DNA. This opens the possibility to include the effect of large conformational fluctuations in chromatin segments on, for instance, the reactivity of particular base pairs within the same simulation framework.

Structural Impact of Phosphorylation and Dielectric Constant Variation on Synaptotagmin's IDR

We used time-resolved Förster resonance energy transfer, circular dichroism, and molecular dynamics simulation to investigate the structural dependence of synaptotagmin 1's intrinsically disordered region (IDR) on phosphorylation and dielectric constant. We found that a peptide corresponding to the full-length IDR sequence, a ∼60-residue strong polyampholyte, can sample structurally collapsed states in aqueous solution, consistent with its κ-predicted behavior, where κ is a sequence-dependent parameter that is used to predict IDR compaction. In implicit solvent simulations of this same sequence, lowering the dielectric constant to more closely mimic the environment near a lipid bilayer surface promoted further sampling of collapsed structures. We then examined the structural tendencies of central region residues of the IDR in isolation. We found that the exocytosis-modulating phosphorylation of Thr¹¹² disrupts a local disorder-to-order transition induced by trifluoroethanol/water mixtures that decrease the solution dielectric constant and stabilize helical structure. Implicit solvent simulations on these same central region residues testing the impact of dielectric constant alone converge on a similar result, showing that helical structure is formed with higher probability at a reduced dielectric. In these helical conformers, lysine-aspartic acid salt bridges contribute to stabilization of transient secondary structure. In contrast, phosphorylation results in formation of salt bridges unsuitable for helix formation. Collectively, these results suggest a model in which phosphorylation and compaction of the IDR sequence regulate structural transitions that in turn modulate neuronal exocytosis.

Acceleration of cryo-EM Flexible Fitting for Large Biomolecular Systems by Efficient Space Partitioning

Flexible fitting is a powerful technique to build the 3D structures of biomolecules from cryoelectron microscopy (cryo-EM) density maps. One popular method is a cross-correlation coefficient-based approach, where the molecular dynamics (MD) simulation is carried out with the biasing potential that includes the cross-correlation coefficient between the experimental and simulated density maps. Here, we propose efficient parallelization schemes for the calculation of the cross-correlation coefficient to accelerate flexible fitting. Our schemes are tested for small, medium, and large biomolecules using CPU and hybrid CPU + GPU architectures. The scheme for the atomic decomposition MD is suitable for small proteins such as Ca²⁺-ATPase with the all-atom Go model, while that for the domain decomposition MD is better for larger systems such as ribosome with the all-atom Go or the all-atom explicit solvent models. Our methods allow flexible fitting for various biomolecules with reasonable computational cost. This approach also connects high-resolution structure refinements with investigation of protein structure-function relationship.

Replica-Based Protein Structure Sampling Methods: Compromising between Explicit and Implicit Solvents

The structure of a protein is often not completely accessible by experiments. In silico, replica exchange molecular dynamics (REMD) is the standard sampling method for predicting the secondary and tertiary structures from the amino acid sequence, but it is computationally very expensive. Two recent adaptations from REMD, temperature intervals with global exchange of replicas (TIGER2) and TIGER2A, have been tested here in implicit and explicit solvents. Additionally, explicit, implicit, and hybrid solvent REMD are compared. On the basis of the hybrid REMD (REMDh) method, we present a new hybrid TIGER2h algorithm for faster structural sampling, while retaining good accuracy. The implementations of REMDh, TIGER2, TIGER2A, and TIGER2h are provided for nanoscale molecular dynamics (NAMD). All the methods were tested with two model peptides of known structure, (AAQAA)₃ and HP7, with helix and sheet motifs, respectively. The TIGER2 methods and REMDh were also applied to the unknown structure of the collagen type I telopeptides, which represent bigger proteins with some degree of disorder. We present simulations covering more than 180 μs and analyze the performance and convergence of the distributions of states between the particular methods by dihedral principal component and secondary structure analysis.

The effects of implicit modeling of nonpolar solvation on protein folding simulations

Implicit solvent models, in which the polar and nonpolar solvation free-energies of solute molecules are treated separately, have been widely adopted for molecular dynamics simulation of protein folding. While the development of the implicit models is mainly focused on the methodological improvement and key parameter optimization for polar solvation, nonpolar solvation has been either ignored or described by a simplistic surface area (SA) model. In this work, we performed the folding simulations of multiple β-hairpin and α-helical proteins with varied surface tension coefficients embedded in the SA model to clearly demonstrate the effects of nonpolar solvation treated by a popular SA model on protein folding. The results indicate that the change in the surface tension coefficient does not alter the ability of implicit solvent simulations to reproduce a protein native structure but indeed controls the components of the equilibrium conformational ensemble and modifies the energetic characterization of the folding transition pathway. The suitably set surface tension coefficient can yield explicit solvent simulations and/or experimentally suggested folding mechanism of protein. In addition, the implicit treatment of both polar and nonpolar components of solvation free-energy contributes to the overestimation of the secondary structure in implicit solvent simulations.

The six metal binding domains in human copper transporter, ATP7B: molecular biophysics and disease-causing mutations

Wilson Disease (WD) is a hereditary genetic disorder, which coincides with a dysfunctional copper (Cu) metabolism caused by mutations in ATP7B, a membrane-bound P1B-type ATPase responsible for Cu export from hepatic cells. The N-terminal part (~ 600 residues) of the multi-domain 1400-residue ATP7B constitutes six metal binding domains (MBDs), each of which can bind a copper ion, interact with other ATP7B domains as well as with different proteins. Although the ATP7B's MBDs have been investigated in vitro and in vivo intensively, it remains unclear how these domains modulate overall structure, dynamics, stability and function of ATP7B. The presence of six MBDs is unique to mammalian ATP7B homologs, and many WD causing missense mutations are found in these domains. Here, we have summarized previously reported in vitro biophysical data on the MBDs of ATP7B and WD point mutations located in these domains. Besides the demonstration of where the research field stands today, this review showcasts the need for further biophysical investigation about the roles of MBDs in ATP7B function. Molecular mechanisms of ATP7B are important not only in the development of new WD treatment but also for other aspects of human physiology where Cu transport plays a role.

Multi-kinase inhibitors can associate with heat shock proteins through their NH2-termini by which they suppress chaperone function

We performed proteomic studies using the GRP78 chaperone-inhibitor drug AR-12 (OSU-03012) as bait. Multiple additional chaperone and chaperone-associated proteins were shown to interact with AR-12, including: GRP75, HSP75, BAG2; HSP27; ULK-1; and thioredoxin. AR-12 down-regulated in situ immuno-fluorescence detection of ATP binding chaperones using antibodies directed against the NH₂-termini of the proteins but only weakly reduced detection using antibodies directed against the central and COOH portions of the proteins. Traditional SDS-PAGE and western blotting assessment methods did not exhibit any alterations in chaperone detection. AR-12 altered the sub-cellular distribution of chaperone proteins, abolishing their punctate speckled patterning concomitant with changes in protein co-localization. AR-12 inhibited chaperone ATPase activity, which was enhanced by sildenafil; inhibited chaperone – chaperone and chaperone – client interactions; and docked in silico with the ATPase domains of HSP90 and of HSP70. AR-12 combined with sildenafil in a GRP78 plus HSP27 –dependent fashion to profoundly activate an eIF2α/ATF4/CHOP/Beclin1 pathway in parallel with inactivating mTOR and increasing ATG13 phosphorylation, collectively resulting in formation of punctate toxic autophagosomes. Over-expression of [GRP78 and HSP27] prevented: AR-12 –induced activation of ER stress signaling and maintained mTOR activity; AR-12 –mediated down-regulation of thioredoxin, MCL-1 and c-FLIP-s; and preserved tumor cell viability. Thus the inhibition of chaperone protein functions by AR-12 and by multi-kinase inhibitors very likely explains why these agents have anti-tumor effects in multiple genetically diverse tumor cell types.

Structure of FlgK reveals the divergence of the bacterial Hook-Filament Junction of Campylobacter

Evolution of a nano-machine consisting of multiple parts, each with a specific function, is a complex process. A change in one part should eventually result in changes in other parts, if the overall function is to be conserved. In bacterial flagella, the filament and the hook have distinct functions and their respective proteins, FliC and FlgE, have different three-dimensional structures. The filament functions as a helical propeller and the hook as a flexible universal joint. Two proteins, FlgK and FlgL, assure a smooth connectivity between the hook and the filament. Here we show that, in Campylobacter, the 3D structure of FlgK differs from that of its orthologs in Salmonella and Burkholderia, whose structures have previously been solved. Docking the model of the FlgK junction onto the structure of the Campylobacter hook provides some clues about its divergence. These data suggest how evolutionary pressure to adapt to structural constraints, due to the structure of Campylobacter hook, causes divergence of one element of a supra-molecular complex in order to maintain the function of the entire flagellar assembly.

Adsorption of Milk Proteins (β-Casein and β-Lactoglobulin) and BSA onto Hydrophobic Surfaces

Here, we study films of proteins over planar surfaces and protein-coated microspheres obtained from the adsorption of three different proteins ( β -casein, β -lactoglobulin and bovine serum albumin (BSA)). The investigation of protein films in planar surfaces is performed by combining quartz crystal microbalance (QCM) and atomic force microscopy (AFM) measurements with all-atomic molecular dynamics (MD) simulations. We found that BSA and β -lactoglobulin form compact monolayers, almost without interstices between the proteins. However, β -casein adsorbs forming multilayers. The study of the electrokinetic mobility of protein-coated latex microspheres shows substantial condensation of ions from the buffer over the complexes, as predicted from ion condensation theories. The electrokinetic behavior of the latex-protein complexes is dominated by the charge of the proteins and the phenomenon of ion condensation, whereas the charge of the latex colloids plays only a minor role.

Different dynamics and pathway of disulfide bonds reduction of two human defensins, a molecular dynamics simulation study

Human defensins are a class of antimicrobial peptides that are crucial components of the innate immune system. Both human α defensin type 5 (HD5) and human β defensin type 3 (hBD-3) have 6 cysteine residues which form 3 pairs of disulfide bonds in oxidizing condition. Disulfide bond linking is important to the protein structure stabilization, and the disulfide bond linking and breaking order have been shown to influence protein function. In this project, microsecond long molecular dynamics simulations were performed to study the structure and dynamics of HD5 and hBD-3 wildtype and analogs which have all 3 disulfide bonds released in reducing condition. The structure of hBD-3 was found to be more dynamic and flexible than HD5, based on RMSD, RMSF, and radius of gyration calculations. The disulfide bridge breaking order of HD5 and hBD-3 in reducing condition was predicted by two kinds of methods, which gave consistent results. It was found that the disulfide bonds breaking pathways for HD5 and hBD-3 are very different. The breaking of disulfide bonds can influence the dimer interface by making the dimer structure less stable for both kinds of defensin. In order to understand the difference in dynamics and disulfide bond breaking pathway, hydrophilic and hydrophobic accessible surface areas (ASA), buried surface area between cysteine pairs, entropy of cysteine pairs, and internal energy were calculated. Comparing to the wildtype, hBD-3 analog is more hydrophobic, while HD5 is more hydrophilic. For hBD-3, the disulfide breaking is mainly entropy driven, while other factors such as the solvation effects may take the major role in controlling HD5 disulfide breaking pathway. Proteins 2017; 85:665-681. © 2016 Wiley Periodicals, Inc.

CryoEM Structure Refinement by Integrating NMR Chemical Shifts with Molecular Dynamics Simulations

Single particle cryoEM has emerged as a powerful method for structure determination of proteins and complexes, complementing X-ray crystallography and NMR spectroscopy. Yet, for many systems, the resolution of cryoEM density map has been limited to 4-6 Å, which only allows for resolving bulky amino acids side chains, thus hindering accurate model building from the density map. On the other hand, experimental chemical shifts (CS) from solution and solid state MAS NMR spectra provide atomic level data for each amino acid within a molecule or a complex; however, structure determination of large complexes and assemblies based on NMR data alone remains challenging. Here, we present a novel integrated strategy to combine the highly complementary experimental data from cryoEM and NMR computationally by molecular dynamics simulations to derive an atomistic model, which is not attainable by either approach alone. We use the HIV-1 capsid protein (CA) C-terminal domain as well as the large capsid assembly to demonstrate the feasibility of this approach, termed NMR CS-biased cryoEM structure refinement.

Efficient gaussian density formulation of volume and surface areas of macromolecules on graphical processing units

We present an algorithm to efficiently compute accurate volumes and surface areas of macromolecules on graphical processing unit (GPU) devices using an analytic model which represents atomic volumes by continuous Gaussian densities. The volume of the molecule is expressed by means of the inclusion-exclusion formula, which is based on the summation of overlap integrals among multiple atomic densities. The surface area of the molecule is obtained by differentiation of the molecular volume with respect to atomic radii. The many-body nature of the model makes a port to GPU devices challenging. To our knowledge, this is the first reported full implementation of this model on GPU hardware. To accomplish this, we have used recursive strategies to construct the tree of overlaps and to accumulate volumes and their gradients on the tree data structures so as to minimize memory contention. The algorithm is used in the formulation of a surface area-based non-polar implicit solvent model implemented as an open source plug-in (named GaussVol) for the popular OpenMM library for molecular mechanics modeling. GaussVol is 50 to 100 times faster than our best optimized implementation for the CPUs, achieving speeds in excess of 100 ns/day with 1 fs time-step for protein-sized systems on commodity GPUs. © 2017 Wiley Periodicals, Inc.

CHARMM-GUI MDFF/xMDFF Utilizer for Molecular Dynamics Flexible Fitting Simulations in Various Environments

X-ray crystallography and cryo-electron microscopy are two popular methods for the structure determination of biological molecules. Atomic structures are derived through the fitting and refinement of an initial model into electron density maps constructed by both experiments. Two computational approaches, MDFF and xMDFF, have been developed to facilitate this process by integrating the experimental data with molecular dynamics simulation. However, the setup of an MDFF/xMDFF simulation requires knowledge of both experimental and computational methods, which is not straightforward for nonexpert users. In addition, sometimes it is desirable to include realistic environments, such as explicit solvent and lipid bilayers during the simulation, which poses another challenge even for expert users. To alleviate these difficulties, we have developed MDFF/xMDFF Utilizer in CHARMM-GUI that helps users to set up an MDFF/xMDFF simulation. The capability of MDFF/xMDFF Utilizer is greatly enhanced by integration with other CHARMM-GUI modules, including protein structure manipulation, a diverse set of lipid types, and all-atom CHARMM and coarse-grained PACE force fields. With this integration, various simulation environments are available for MDFF Utilizer (vacuum, implicit/explicit solvent, and bilayers) and xMDFF Utilizer (vacuum and solution). In this work, three examples are shown to demonstrate the usage of MDFF/xMDFF Utilizer.

Beyond Antibodies: Development of a Novel Protein Scaffold Based on Human Chaperonin 10

Human Chaperonin 10 (hCpn10) was utilised as a novel scaffold for presenting peptides of therapeutic and diagnostic significance. Molecular dynamic simulations and protein sizing analyses identified a peptide linker (P1) optimal for the formation of the quarternary hCpn10 heptamer structure. hCpn10 scaffold displaying peptides targeting Factor VIIa (CE76_-P1) and CD44 (CP7) were expressed in E. coli. Functional studies of CE76_-P1 indicated nanomolar affinity for Factor VIIa (3 nM) similar to the E-76 peptide (6 nM), with undetectable binding to Factor X. CE76_-P1 was a potent inhibitor of FX activity (via inhibition of Factor VIIa) and prolonged clot formation 4 times longer than achieved by E-76 peptide as determined by prothrombin time (PT) assays. This improvement in clotting function by CE76_-P1, highlights the advantages of a heptamer-based scaffold for improving avidity by multiple peptide presentation. In another example of hCPn10 utility as a scaffold, CP7 bound to native CD44 overexpressed on cancer cells and bound rCD44 with high affinity (K_D 9.6 nM). The ability to present various peptides through substitution of the hCpn10 mobile loop demonstrates its utility as a novel protein scaffold.

Electrostatic component of binding energy: Interpreting predictions from poisson-boltzmann equation and modeling protocols

Macromolecular interactions are essential for understanding numerous biological processes and are typically characterized by the binding free energy. Important component of the binding free energy is the electrostatics, which is frequently modeled via the solutions of the Poisson-Boltzmann Equations (PBE). However, numerous works have shown that the electrostatic component (ΔΔGelec ) of binding free energy is very sensitive to the parameters used and modeling protocol. This prompted some researchers to question the robustness of PBE in predicting ΔΔGelec . We argue that the sensitivity of the absolute ΔΔGelec calculated with PBE using different input parameters and definitions does not indicate PBE deficiency, rather this is what should be expected. We show how the apparent sensitivity should be interpreted in terms of the underlying changes in several numerous and physical parameters. We demonstrate that PBE approach is robust within each considered force field (CHARMM-27, AMBER-94, and OPLS-AA) once the corresponding structures are energy minimized. This observation holds despite of using two different molecular surface definitions, pointing again that PBE delivers consistent results within particular force field. The fact that PBE delivered ΔΔGelec values may differ if calculated with different modeling protocols is not a deficiency of PBE, but natural results of the differences of the force field parameters and potential functions for energy minimization. In addition, while the absolute ΔΔGelec values calculated with different force field differ, their ordering remains practically the same allowing for consistent ranking despite of the force field used. © 2016 Wiley Periodicals, Inc.

Binding Analysis of Methyl-CpG Binding Domain of MeCP2 and Rett Syndrome Mutations

Methyl-CpG binding protein 2 (MeCP2) binds to methylated cytosine in CpG island through its methyl-CpG binding domain (MBD). Here, the effects of the Rett syndrome-causing missense mutations on binding affinity of MBD to cytosine (C), methylcytosine (mC), hydroxymethylcytosine (hmC), formylcytosine (fC), and carboxylcytosine (caC) in CpG dinucleotide are investigated. MeCP2-MBD binds to mC-containing variants of double stranded CpG stronger than any other cytosine modified CpG with the strongest affinity to mC/mC. Thirteen MBD missense mutations show reduced binding affinity for mC/mC ranging with a 2-fold decrease for T158M to 88-fold for R111G. The binding affinities of these mutants to C/C are also reduced to various degrees except for T158M. Consistent with free energy perturbation analysis, correlation of binding affinity with protein unfolding allows for grouping mutations into three clusters. Correlation of the first cluster includes mutations that have a higher tendency to unfold and have lesser affinity to mC/mC and C/C. Mutations in the second cluster have similar structural stability but various affinities to mC/mC and C/C. R111G and A140V belong to the third cluster in which the loss of protein flexibility may underlie their reduction in binding affinity to mC/mC and C/C. Most notably, R111 emerges as the key structural element that modulates the specific contacts with mCpG. Implications of the results for the mCpG binding mechanism of MeCP2-MBD are discussed. These analyses provide new insights on the structure and function relationships in MeCP2-MBD and offer new clues to their roles in the pathology of Rett syndrome.

Modeling and Analysis of Intercalant Effects on Circular DNA Conformation

The large-scale conformation of DNA molecules plays a critical role in many basic elements of cellular functionality and viability. By targeting the structural properties of DNA, many cancer drugs, such as anthracyclines, effectively inhibit tumor growth but can also produce dangerous side effects. To enhance the development of innovative medications, rapid screening of structural changes to DNA can provide important insight into their mechanism of interaction. In this study, we report changes to circular DNA conformation from intercalation with ethidium bromide using all-atom molecular dynamics simulations and characterized experimentally by translocation through a silicon nitride solid-state nanopore. Our measurements reveal three distinct current blockade levels and a 6-fold increase in translocation times for ethidium bromide-treated circular DNA as compared to untreated circular DNA. We attribute these increases to changes in the supercoiled configuration hypothesized to be branched or looped structures formed in the circular DNA molecule. Further evidence of the conformational changes is demonstrated by qualitative atomic force microscopy analysis. These results expand the current methodology for predicting and characterizing DNA tertiary structure and advance nanopore technology as a platform for deciphering structural changes of other important biomolecules.

Binding Site Recognition and Docking Dynamics of a Single Electron Transport Protein: Cytochrome c2

Small diffusible redox proteins facilitate electron transfer in respiration and photosynthesis by alternately binding to their redox partners and integral membrane proteins and exchanging electrons. Diffusive search, recognition, binding, and unbinding of these proteins often amount to kinetic bottlenecks in cellular energy conversion, but despite the availability of structures and intense study, the physical mechanisms controlling redox partner interactions remain largely unknown. The present molecular dynamics study provides an all-atom description of the cytochrome c2-docked bc1 complex in Rhodobacter sphaeroides in terms of an ensemble of favorable docking conformations and reveals an intricate series of conformational changes that allow cytochrome c2 to recognize the bc1 complex and bind or unbind in a redox state-dependent manner. In particular, the role of electron transfer in triggering a molecular switch and in altering water-mediated interface mobility, thereby strengthening and weakening complex formation, is described. The results resolve long-standing discrepancies between structural and functional data.

Albumin-coated SPIONs: an experimental and theoretical evaluation of protein conformation, binding affinity and competition with serum proteins

The variety of nanoparticles (NPs) used in biological applications is increasing and the study of their interaction with biological media is becoming more important. Proteins are commonly the first biomolecules that NPs encounter when they interact with biological systems either in vitro or in vivo. Among NPs, super-paramagnetic iron oxide nanoparticles (SPIONs) show great promise for medicine. In this work, we study in detail the formation, composition, and structure of a monolayer of bovine serum albumin (BSA) on SPIONs. We determine, both by molecular simulations and experimentally, that ten molecules of BSA form a monolayer around the outside of the SPIONs and their binding strength to the SPIONs is about 3.5 × 10(-4) M, ten times higher than the adsorption of fetal bovine serum (FBS) on the same SPIONs. We elucidate a strong electrostatic interaction between BSA and the SPIONs, although the secondary structure of the protein is not affected. We present data that supports the strong binding of the BSA monolayer on SPIONs and the properties of the BSA layer as a protein-resistant coating. We believe that a complete understanding of the behavior and morphology of BSA-SPIONs and how the protein interacts with SPIONs is crucial for improving NP surface design and expanding the potential applications of SPIONs in nanomedicine.

Perturbation Approaches for Exploring Protein Binding Site Flexibility to Predict Transient Binding Pockets

Simulations of the long-time scale motions of a ligand binding pocket in a protein may open up new perspectives for the design of compounds with steric or chemical properties differing from those of known binders. However, slow motions of proteins are difficult to access using standard molecular dynamics (MD) simulations and are thus usually neglected in computational drug design. Here, we introduce two nonequilibrium MD approaches to identify conformational changes of a binding site and detect transient pockets associated with these motions. The methods proposed are based on the rotamerically induced perturbation (RIP) MD approach, which employs perturbation of side-chain torsional motion for initiating large-scale protein movement. The first approach, Langevin-RIP (L-RIP), entails a series of short Langevin MD simulations, each starting with perturbation of one of the side-chains lining the binding site of interest. L-RIP provides extensive sampling of conformational changes of the binding site. In less than 1 ns of MD simulation with L-RIP, we observed distortions of the α-helix in the ATP binding site of HSP90 and flipping of the DFG loop in Src kinase. In the second approach, RIPlig, a perturbation is applied to a pseudoligand placed in different parts of a binding pocket, which enables flexible regions of the binding site to be identified in a small number of 10 ps MD simulations. The methods were evaluated for four test proteins displaying different types and degrees of binding site flexibility. Both methods reveal all transient pocket regions in less than a total of 10 ns of simulations, even though many of these regions remained closed in 100 ns conventional MD. The proposed methods provide computationally efficient tools to explore binding site flexibility and can aid in the functional characterization of protein pockets, and the identification of transient pockets for ligand design.

Molecular dynamics-based refinement and validation for sub-5 Å cryo-electron microscopy maps

Two structure determination methods, based on the molecular dynamics flexible fitting (MDFF) paradigm, are presented that resolve sub-5 Å cryo-electron microscopy (EM) maps with either single structures or ensembles of such structures. The methods, denoted cascade MDFF and resolution exchange MDFF, sequentially re-refine a search model against a series of maps of progressively higher resolutions, which ends with the original experimental resolution. Application of sequential re-refinement enables MDFF to achieve a radius of convergence of ~25 Å demonstrated with the accurate modeling of β-galactosidase and TRPV1 proteins at 3.2 Å and 3.4 Å resolution, respectively. The MDFF refinements uniquely offer map-model validation and B-factor determination criteria based on the inherent dynamics of the macromolecules studied, captured by means of local root mean square fluctuations. The MDFF tools described are available to researchers through an easy-to-use and cost-effective cloud computing resource on Amazon Web Services.

DOI:http://dx.doi.org/10.7554/eLife.16105.001

To understand the roles that proteins and other large molecules play inside cells, it is important to determine their structures. One of the techniques that researchers can use to do this is called cryo-electron microscopy (cryo-EM), which rapidly freezes molecules to fix them in position before imaging them in fine detail.

The cryo-EM images are like maps that show the approximate position of atoms. These images must then be processed in order to build a three-dimensional model of the protein that shows how its atoms are arranged relative to each other. One computational approach called Molecular Dynamics Flexible Fitting (MDFF) works by flexibly fitting possible atomic structures into cryo-EM maps. Although this approach works well with relatively undetailed (or ‘low resolution’) cryo-EM images, it struggles to handle the high-resolution cryo-EM maps now being generated.

Singharoy, Teo, McGreevy et al. have now developed two MDFF methods – called cascade MDFF and resolution exchange MDFF – that help to resolve atomic models of biological molecules from cryo-EM images. Each method can refine poorly guessed models into ones that are consistent with the high-resolution experimental images. The refinement is achieved by interpreting a range of images that starts with a ‘fuzzy’ image. The contrast of the image is then progressively improved until an image is produced that has a resolution that is good enough to almost distinguish individual atoms.

The method works because each cryo-EM image shows not just one, but a collection of atomic structures that the molecule can take on, with the fuzzier parts of the image representing the more flexible parts of the molecule. By taking into account this flexibility, the large-scale features of the protein structure can be determined first from the fuzzier images, and increasing the contrast of the images allows smaller-scale refinements to be made to the structure.

The MDFF tools have been designed to be easy to use and are available to researchers at low cost through cloud computing platforms. They can now be used to unravel the structure of many different proteins and protein complexes including those involved in photosynthesis, respiration and protein synthesis.

DOI:http://dx.doi.org/10.7554/eLife.16105.002

Claws, Disorder, and Conformational Dynamics of the C-Terminal Region of Human Desmoplakin

Multicellular organisms consist of cells that interact via elaborate adhesion complexes. Desmosomes are membrane-associated adhesion complexes that mechanically tether the cytoskeletal intermediate filaments (IFs) between two adjacent cells, creating a network of tough connections in tissues such as skin and heart. Desmoplakin (DP) is the key desmosomal protein that binds IFs, and the DP·IF association poses a quandary: desmoplakin must stably and tightly bind IFs to maintain the structural integrity of the desmosome. Yet, newly synthesized DP must traffic along the cytoskeleton to the site of nascent desmosome assembly without "sticking" to the IF network, implying weak or transient DP···IF contacts. Recent work reveals that these contacts are modulated by post-translational modifications (PTMs) in DP's C-terminal tail (DPCTT). Using molecular dynamics simulations, we have elucidated the structural basis of these PTM-induced effects. Our simulations, nearing 2 μs in aggregate, indicate that phosphorylation of S2849 induces an "arginine claw" in desmoplakin's C-terminal tail. If a key arginine, R2834, is methylated, the DPCTT preferentially samples conformations that are geometrically well-suited as substrates for processive phosphorylation by the cognate kinase GSK3. We suggest that DPCTT is a molecular switch that modulates, via its conformational dynamics, DP's overall efficacy as a substrate for GSK3. Finally, we show that the fluctuating DPCTT can contact other parts of DP, suggesting a competitive binding mechanism for the modulation of DP···IF interactions.

QwikMD - Integrative Molecular Dynamics Toolkit for Novices and Experts

The proper functioning of biomolecules in living cells requires them to assume particular structures and to undergo conformational changes. Both biomolecular structure and motion can be studied using a wide variety of techniques, but none offers the level of detail as do molecular dynamics (MD) simulations. Integrating two widely used modeling programs, namely NAMD and VMD, we have created a robust, user-friendly software, QwikMD, which enables novices and experts alike to address biomedically relevant questions, where often only molecular dynamics simulations can provide answers. Performing both simple and advanced MD simulations interactively, QwikMD automates as many steps as necessary for preparing, carrying out, and analyzing simulations while checking for common errors and enabling reproducibility. QwikMD meets also the needs of experts in the field, increasing the efficiency and quality of their work by carrying out tedious or repetitive tasks while enabling easy control of every step. Whether carrying out simulations within the live view mode on a small laptop or performing complex and large simulations on supercomputers or Cloud computers, QwikMD uses the same steps and user interface. QwikMD is freely available by download on group and personal computers. It is also available on the cloud at Amazon Web Services.

Toward High-Throughput Predictive Modeling of Protein Binding/Unbinding Kinetics

One of the unaddressed challenges in drug discovery is that drug potency determined in vitro is not a reliable indicator of drug activity in vivo. Accumulated evidence suggests that in vivo activity is more strongly correlated with the binding/unbinding kinetics than the equilibrium thermodynamics of protein-ligand interactions (PLIs). However, existing experimental and computational techniques are insufficient in studying the molecular details of kinetics processes of PLIs on a large scale. Consequently, we not only have limited mechanistic understanding of the kinetic processes but also lack a practical platform for high-throughput screening and optimization of drug leads on the basis of their kinetic properties. For the first time, we address this unmet need by integrating coarse-grained normal mode analysis with multitarget machine learning (MTML). To test our method, HIV-1 protease is used as a model system. We find that computational models based on the residue normal mode directionality displacement of PLIs can not only recapitulate the results from all-atom molecular dynamics simulations but also predict protein-ligand binding/unbinding kinetics accurately. When this is combined with energetic features, the accuracy of combined kon and koff prediction reaches 74.35%. Furthermore, our integrated model provides us with new insights into the molecular determinants of the kinetics of PLIs. We propose that the coherent coupling of conformational dynamics and thermodynamic interactions between the receptor and the ligand may play a critical role in determining the kinetic rate constants of PLIs. In conclusion, we demonstrate that residue normal mode directionality displacement can serve as a kinetic fingerprint to capture long-time-scale conformational dynamics of the binding/unbinding kinetics. When this is coupled with MTML, it is possible to screen and optimize compounds on the basis of their binding/unbinding kinetics in a high-throughput fashion. The further development of such computational tools will bridge one of the critical missing links between in vitro compound screening and in vivo drug activity.

Constructing Structure Ensembles of Intrinsically Disordered Proteins from Chemical Shift Data

Modeling the structural ensemble of intrinsically disordered proteins (IDPs), which lack fixed structures, is essential in understanding their cellular functions and revealing their regulation mechanisms in signaling pathways of related diseases (e.g., cancers and neurodegenerative disorders). Though the ensemble concept has been widely believed to be the most accurate way to depict 3D structures of IDPs, few of the traditional ensemble-based approaches effectively address the degeneracy problem that occurs when multiple solutions are consistent with experimental data and is the main challenge in the IDP ensemble construction task. In this article, based on a predefined conformational library, we formalize the structure ensemble construction problem into a least squares framework, which provides the optimal solution when the data constraints outnumber unknown variables. To deal with the degeneracy problem, we further propose a regularized regression approach based on the elastic net technique with the assumption that the weights to be estimated for individual structures in the ensemble are sparse. We have validated our methods through a reference ensemble approach as well as by testing the real biological data of three proteins, including alpha-synuclein, the translocation domain of Colocin N, and the K18 domain of Tau protein.

Advances in the molecular dynamics flexible fitting method for cryo-EM modeling

Molecular Dynamics Flexible Fitting (MDFF) is an established technique for fitting all-atom structures of molecules into corresponding cryo-electron microscopy (cryo-EM) densities. The practical application of MDFF is simple but requires a user to be aware of and take measures against a variety of possible challenges presented by each individual case. Some of these challenges arise from the complexity of a molecular structure or the limited quality of available structural models and densities to be interpreted, while others stem from the intricacies of MDFF itself. The current article serves as an overview of the strategies that have been developed since MDFF's inception to overcome common challenges and successfully perform MDFF simulations.

Recognition of Poly-Ubiquitins by the Proteasome through Protein Refolding Guided by Electrostatic and Hydrophobic Interactions

Specificity of protein degradation by cellular proteasomes comes from tetra-ubiquitin recognition. We carry out molecular dynamics simulations to characterize how the ubiquitin receptor Rpn10 recognizes in the 26S proteasome K48-linked tetra-ubiquitin. In the binding pose, ubiquitin and Rpn10 interact primarily through hydrophobic patches. However, K48-linked tetra-ubiquitin mostly assumes a closed form in solution prior to binding, in which its hydrophobic patches are not exposed to solvent. Likewise, the hydrophobic ubiquitin interacting motifs (UIMs) of Rpn10 are mostly protected prior to binding. As a result, ubiquitin recognition in the proteasome requires refolding of both K48-linked tetra-ubiquitin and Rpn10. Simulations suggest that conserved complementary electrostatic patterns of Rpn10 and ubiquitins guide protein association (stage 1 in the recognition process), which induces refolding (stage 2), and then facilitates formation of hydrophobic contacts (stage 3). The simulations also explain why Rpn10 has a higher affinity for K48-linked tetra-ubiquitin than for mono-ubiquitin and K48-linked di- and tri-ubiquitins. Simulation results expand on the current view that the flexible arm of Rpn10 acts as an extended fragment of α-helices and flexible coils in the recognition process.

Available Instruments for Analyzing Molecular Dynamics Trajectories

Molecular dynamics trajectories are the result of molecular dynamics simulations. Trajectories are sequential snapshots of simulated molecular system which represents atomic coordinates at specific time periods. Based on the definition, in a text format trajectory files are characterized by their simplicity and uselessness. To obtain information from such files, special programs and information processing techniques are applied: from molecular dynamics animation to finding characteristics along the trajectory (versus time). In this review, we describe different programs for processing molecular dynamics trajectories. The performance of these programs, usefulness for analyses of molecular dynamics trajectories, strong and weak aspects are discussed.

A β-solenoid model of the Pmel17 repeat domain: insights to the formation of functional amyloid fibrils

Pmel17 is a multidomain protein involved in biosynthesis of melanin. This process is facilitated by the formation of Pmel17 amyloid fibrils that serve as a scaffold, important for pigment deposition in melanosomes. A specific luminal domain of human Pmel17, containing 10 tandem imperfect repeats, designated as repeat domain (RPT), forms amyloid fibrils in a pH-controlled mechanism in vitro and has been proposed to be essential for the formation of the fibrillar matrix. Currently, no three-dimensional structure has been resolved for the RPT domain of Pmel17. Here, we examine the structure of the RPT domain by performing sequence threading. The resulting model was subjected to energy minimization and validated through extensive molecular dynamics simulations. Structural analysis indicated that the RPT model exhibits several distinct properties of β-solenoid structures, which have been proposed to be polymerizing components of amyloid fibrils. The derived model is stabilized by an extensive network of hydrogen bonds generated by stacking of highly conserved polar residues of the RPT domain. Furthermore, the key role of invariant glutamate residues is proposed, supporting a pH-dependent mechanism for RPT domain assembly. Conclusively, our work attempts to provide structural insights into the RPT domain structure and to elucidate its contribution to Pmel17 amyloid fibril formation.

Molecular dynamics simulations of biological membranes and membrane proteins using enhanced conformational sampling algorithms

This paper reviews various enhanced conformational sampling methods and explicit/implicit solvent/membrane models, as well as their recent applications to the exploration of the structure and dynamics of membranes and membrane proteins. Molecular dynamics simulations have become an essential tool to investigate biological problems, and their success relies on proper molecular models together with efficient conformational sampling methods. The implicit representation of solvent/membrane environments is reasonable approximation to the explicit all-atom models, considering the balance between computational cost and simulation accuracy. Implicit models can be easily combined with replica-exchange molecular dynamics methods to explore a wider conformational space of a protein. Other molecular models and enhanced conformational sampling methods are also briefly discussed. As application examples, we introduce recent simulation studies of glycophorin A, phospholamban, amyloid precursor protein, and mixed lipid bilayers and discuss the accuracy and efficiency of each simulation model and method. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov.

Path Similarity Analysis: A Method for Quantifying Macromolecular Pathways

Diverse classes of proteins function through large-scale conformational changes and various sophisticated computational algorithms have been proposed to enhance sampling of these macromolecular transition paths. Because such paths are curves in a high-dimensional space, it has been difficult to quantitatively compare multiple paths, a necessary prerequisite to, for instance, assess the quality of different algorithms. We introduce a method named Path Similarity Analysis (PSA) that enables us to quantify the similarity between two arbitrary paths and extract the atomic-scale determinants responsible for their differences. PSA utilizes the full information available in 3N-dimensional configuration space trajectories by employing the Hausdorff or Fréchet metrics (adopted from computational geometry) to quantify the degree of similarity between piecewise-linear curves. It thus completely avoids relying on projections into low dimensional spaces, as used in traditional approaches. To elucidate the principles of PSA, we quantified the effect of path roughness induced by thermal fluctuations using a toy model system. Using, as an example, the closed-to-open transitions of the enzyme adenylate kinase (AdK) in its substrate-free form, we compared a range of protein transition path-generating algorithms. Molecular dynamics-based dynamic importance sampling (DIMS) MD and targeted MD (TMD) and the purely geometric FRODA (Framework Rigidity Optimized Dynamics Algorithm) were tested along with seven other methods publicly available on servers, including several based on the popular elastic network model (ENM). PSA with clustering revealed that paths produced by a given method are more similar to each other than to those from another method and, for instance, that the ENM-based methods produced relatively similar paths. PSA was applied to ensembles of DIMS MD and FRODA trajectories of the conformational transition of diphtheria toxin, a particularly challenging example. For the AdK transition, the new concept of a Hausdorff-pair map enabled us to extract the molecular structural determinants responsible for differences in pathways, namely a set of conserved salt bridges whose charge-charge interactions are fully modelled in DIMS MD but not in FRODA. PSA has the potential to enhance our understanding of transition path sampling methods, validate them, and to provide a new approach to analyzing conformational transitions.

Many proteins are nanomachines that perform mechanical or chemical work by changing their three-dimensional shape and cycle between multiple conformational states. Computer simulations of such conformational transitions provide mechanistic insights into protein function but such simulations have been challenging. In particular, it is not clear how to quantitatively compare current simulation methods or to assess their accuracy. To that end, we present a general and flexible computational framework for quantifying transition paths—by measuring mutual geometric similarity—that, compared with existing approaches, requires minimal a-priori assumptions and can take advantage of full atomic detail alongside heuristic information derived from intuition. Using our Path Similarity Analysis (PSA) framework in parallel with several existing quantitative approaches, we examine transitions generated for a toy model of a transition and two biological systems, the enzyme adenylate kinase and diphtheria toxin. Our results show that PSA enables the quantitative comparison of different path sampling methods and aids the identification of potentially important atomistic motions by exploiting geometric information in transition paths. The method has the potential to enhance our understanding of transition path sampling methods, validate them, and to provide a new approach to analyzing macromolecular conformational transitions.

Effects of HCM cTnI mutation R145G on troponin structure and modulation by PKA phosphorylation elucidated by molecular dynamics simulations

Cardiac troponin (cTn) is a key molecule in the regulation of human cardiac muscle contraction. The N-terminal cardiac-specific peptide of the inhibitory subunit of troponin, cTnI (cTnI(1-39)), is a target for phosphorylation by protein kinase A (PKA) during β-adrenergic stimulation. We recently presented evidence indicating that this peptide interacts with the inhibitory peptide (cTnl(137-147)) when S23 and S24 are phosphorylated. The inhibitory peptide is also the target of the point mutation cTnI-R145G, which is associated with hypertrophic cardiomyopathy (HCM), a disease associated with sudden death in apparently healthy young adults. It has been shown that both phosphorylation and this mutation alter the cTnC-cTnI (C-I) interaction, which plays a crucial role in modulating contractile activation. However, little is known about the molecular-level events underlying this modulation. Here, we computationally investigated the effects of the cTnI-R145G mutation on the dynamics of cTn, cTnC Ca(2+) handling, and the C-I interaction. Comparisons were made with the cTnI-R145G/S23D/S24D phosphomimic mutation, which has been used both experimentally and computationally to study the cTnI N-terminal specific effects of PKA phosphorylation. Additional comparisons between the phosphomimic mutations and the real phosphorylations were made. For this purpose, we ran triplicate 150 ns molecular dynamics simulations of cTnI-R145G Ca(2+)-bound cTnC(1-161)-cTnI(1-172)-cTnT(236-285), cTnI-R145G/S23D/S24D Ca(2+)-bound cTnC(1-161)-cTnI(1-172)-cTnT(236-285), and cTnI-R145G/PS23/PS24 Ca(2+)-bound cTnC(1-161)-cTnI(1-172)-cTnT(236-285), respectively. We found that the cTnI-R145G mutation did not impact the overall dynamics of cTn, but stabilized crucial Ca(2+)-coordinating interactions. However, the phosphomimic mutations increased overall cTn fluctuations and destabilized Ca(2+) coordination. Interestingly, cTnI-R145G blunted the intrasubunit interactions between the cTnI N-terminal extension and the cTnI inhibitory peptide, which have been suggested to play a crucial role in modulating troponin function during β-adrenergic stimulation. These findings offer a molecular-level explanation for how the HCM mutation cTnI-R145G reduces the modulation of cTn by phosphorylation of S23/S24 during β-adrenergic stimulation.

The solution structures of native and patient monomeric human IgA1 reveal asymmetric extended structures: implications for function and IgAN disease

Detailed analytical ultracentrifugation and X-ray/neutron scattering data and a new atomistic modelling approach revealed asymmetric extended solution structures for human IgA1 that account for its receptor-binding function. IgA1 with different hinge O-galactosylation patterns showed similar structures.

Native IgA1, for which no crystal structure is known, contains an O-galactosylated 23-residue hinge region that joins its Fab and Fc regions. IgA nephropathy (IgAN) is a leading cause of chronic kidney disease in developed countries. Because IgA1 in IgAN often has a poorly O-galactosylated hinge region, the solution structures of monomeric IgA1 from a healthy subject and three IgAN patients with four different O-galactosylation levels were studied. Analytical ultracentrifugation showed that all four IgA1 samples were monomeric with similar sedimentation coefficients, s⁰_20,w. X-ray scattering showed that the radius of gyration (R_g) slightly increased with IgA1 concentration, indicating self-association, although their distance distribution curves, P(r), were unchanged with concentration. Neutron scattering indicated similar R_g values and P(r) curves, although IgA1 showed a propensity to aggregate in heavy water buffer. A new atomistic modelling procedure based on comparisons with 177000 conformationally-randomized IgA1 structures with the individual experimental scattering curves revealed similar extended Y-shaped solution structures for all four differentially-glycosylated IgA1 molecules. The final models indicated that the N-glycans at Asn²⁶³ were folded back against the Fc surface, the C-terminal tailpiece conformations were undefined and hinge O-galactosylation had little effect on the solution structure. The solution structures for full-length IgA1 showed extended hinges and the Fab and Fc regions were positioned asymmetrically to provide ample space for the functionally-important binding of two FcαR receptors to its Fc region. Whereas no link between O-galactosylation and the IgA1 solution structure was detected, an increase in IgA1 aggregation with reduced O-galactosylation may relate to IgAN.

Complete Structure of an Epithelial Keratin Dimer: Implications for Intermediate Filament Assembly

Keratins are cytoskeletal proteins that hierarchically arrange into filaments, starting with the dimer sub-unit. They are integral to the structural support of cells, in skin, hair and nails. In skin, keratin is thought to play a critical role in conferring the barrier properties and elasticity of skin. In general, the keratin dimer is broadly described by a tri-domain structure: a head, a central rod and a tail. As yet, no atomistic-scale picture of the entire dimer structure exists; this information is pivotal for establishing molecular-level connections between structure and function in intermediate filament proteins. The roles of the head and tail domains in facilitating keratin filament assembly and function remain as open questions. To address these, we report results of molecular dynamics simulations of the entire epithelial human K1/K10 keratin dimer. Our findings comprise: (1) the first three-dimensional structural models of the complete dimer unit, comprising of the head, rod and tail domains; (2) new insights into the chirality of the rod-domain twist gained from analysis of the full domain structure; (3) evidence for tri-subdomain partitioning in the head and tail domains; and, (4) identification of the residue characteristics that mediate non-covalent contact between the chains in the dimer. Our findings are immediately applicable to other epithelial keratins, such as K8/K18 and K5/K14, and to intermediate filament proteins in general.

Dendrimers in Nanoscale Confinement: The Interplay between Conformational Change and Nanopore Entrance

Hyperbranched dendrimers are nanocarriers for drugs, imaging agents, and catalysts. Their nanoscale confinement is of fundamental interest and occurs when dendrimers with bioactive payload block or pass biological nanochannels or when catalysts are entrapped in inorganic nanoporous support scaffolds. The molecular process of confinement and its effect on dendrimer conformations are, however, poorly understood. Here, we use single-molecule nanopore measurements and molecular dynamics simulations to establish an atomically detailed model of pore dendrimer interactions. We discover and explain that electrophoretic migration of polycationic PAMAM dendrimers into confined space is not dictated by the diameter of the branched molecules but by their size and generation-dependent compressibility. Differences in structural flexibility also rationalize the apparent anomaly that the experimental nanopore current read-out depends in nonlinear fashion on dendrimer size. Nanoscale confinement is inferred to reduce the protonation of the polycationic structures. Our model can likely be expanded to other dendrimers and be applied to improve the analysis of biophysical experiments, rationally design functional materials such as nanoporous filtration devices or nanoscale drug carriers that effectively pass biological pores.

Parameterization of the Hamiltonian Dielectric Solvent (HADES) Reaction-Field Method for the Solvation Free Energies of Amino Acid Side-Chain Analogs

Optimization of the Hamiltonian dielectric solvent (HADES) method for biomolecular simulations in a dielectric continuum is presented with the goal of calculating accurate absolute solvation free energies while retaining the model's accuracy in predicting conformational free-energy differences. The solvation free energies of neutral and polar amino acid side-chain analogs calculated by using HADES, which may optionally include nonpolar contributions, were optimized against experimental data to reach a chemical accuracy of about 0.5 kcal mol(-1). The new parameters were evaluated for charged side-chain analogs. The HADES results were compared with explicit-solvent, generalized Born, Poisson-Boltzmann, and QM-based methods. The potentials of mean force (PMFs) between pairs of side-chain analogs obtained by using HADES and explicit-solvent simulations were used to evaluate the effects of the improved parameters optimized for solvation free energies on intermolecular potentials.

The hexameric structure of the human mitochondrial replicative helicase Twinkle

The mitochondrial replicative helicase Twinkle is involved in strand separation at the replication fork of mitochondrial DNA (mtDNA). Twinkle malfunction is associated with rare diseases that include late onset mitochondrial myopathies, neuromuscular disorders and fatal infantile mtDNA depletion syndrome. We examined its 3D structure by electron microscopy (EM) and small angle X-ray scattering (SAXS) and built the corresponding atomic models, which gave insight into the first molecular architecture of a full-length SF4 helicase that includes an N-terminal zinc-binding domain (ZBD), an intermediate RNA polymerase domain (RPD) and a RecA-like hexamerization C-terminal domain (CTD). The EM model of Twinkle reveals a hexameric two-layered ring comprising the ZBDs and RPDs in one layer and the CTDs in another. In the hexamer, contacts in trans with adjacent subunits occur between ZBDs and RPDs, and between RPDs and CTDs. The ZBDs show important structural heterogeneity. In solution, the scattering data are compatible with a mixture of extended hexa- and heptameric models in variable conformations. Overall, our structural data show a complex network of dynamic interactions that reconciles with the structural flexibility required for helicase activity.

Characterization of monobody scaffold interactions with ligand via force spectroscopy and steered molecular dynamics

Monobodies are antibody alternatives derived from fibronectin that are thermodynamically stable, small in size, and can be produced in bacterial systems. Monobodies have been engineered to bind a wide variety of target proteins with high affinity and specificity. Using alanine-scanning mutagenesis simulations, we identified two scaffold residues that are critical to the binding interaction between the monobody YS1 and its ligand, maltose-binding protein (MBP). Steered molecular dynamics (SMD) simulations predicted that the E47A and R33A mutations in the YS1 scaffold substantially destabilize the YS1-MBP interface by reducing the bond rupture force and the lifetime of single hydrogen bonds. SMD simulations further indicated that the R33A mutation weakens the hydrogen binding between all scaffold residues and MBP and not just between R33 and MBP. We validated the simulation data and characterized the effects of mutations on YS1-MBP binding by using single-molecule force spectroscopy and surface plasmon resonance. We propose that interfacial stability resulting from R33 of YS1 stacking with R344 of MBP synergistically stabilizes both its own bond and the interacting scaffold residues of YS1. Our integrated approach improves our understanding of the monobody scaffold interactions with a target, thus providing guidance for the improved engineering of monobodies.

Combined computational and experimental analysis of a complex of ribonuclease III and the regulatory macrodomain protein, YmdB

Ribonuclease III is a conserved bacterial endonuclease that cleaves double-stranded(ds) structures in diverse coding and noncoding RNAs. RNase III is subject to multiple levels of control that in turn confer global post-transcriptional regulation. The Escherichia coli macrodomain protein YmdB directly interacts with RNase III, and an increase in YmdB amount in vivo correlates with a reduction in RNase III activity. Here, a computational-based structural analysis was performed to identify atomic-level features of the YmdB-RNase III interaction. The docking of monomeric E. coli YmdB with a homology model of the E. coli RNase III homodimer yields a complex that exhibits an interaction of the conserved YmdB residue R40 with specific RNase III residues at the subunit interface. Surface Plasmon Resonance (SPR) analysis provided a K_D of 61 nM for the complex, corresponding to a binding free energy (ΔG) of −9.9 kcal/mol. YmdB R40 and RNase III D128 were identified by in silico alanine mutagenesis as thermodynamically important interacting partners. Consistent with the prediction, the YmdB R40A mutation causes a 16-fold increase in K_D (ΔΔG = +1.8 kcal/mol), as measured by SPR, and the D128A mutation in both RNase III subunits (D128A/D128′A) causes an 83-fold increase in K_D (ΔΔG = +2.7 kcal/mol). The greater effect of the D128A/D128′A mutation may reflect an altered RNase III secondary structure, as revealed by CD spectroscopy, which also may explain the significant reduction in catalytic activity in vitro. The features of the modeled complex relevant to potential RNase III regulatory mechanisms are discussed. Proteins 2015; 83:459–472. © 2014 The Authors. Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.

Structural features of membrane-bound glucocerebrosidase and α-synuclein probed by neutron reflectometry and fluorescence spectroscopy

Mutations in glucocerebrosidase (GCase), the enzyme deficient in Gaucher disease, are a common genetic risk factor for the development of Parkinson disease and related disorders, implicating the role of this lysosomal hydrolase in the disease etiology. A specific physical interaction exists between the Parkinson disease-related protein α-synuclein (α-syn) and GCase both in solution and on the lipid membrane, resulting in efficient enzyme inhibition. Here, neutron reflectometry was employed as a first direct structural characterization of GCase and α-syn·GCase complex on a sparsely-tethered lipid bilayer, revealing the orientation of the membrane-bound GCase. GCase binds to and partially inserts into the bilayer with its active site most likely lying just above the membrane-water interface. The interaction was further characterized by intrinsic Trp fluorescence, circular dichroism, and surface plasmon resonance spectroscopy. Both Trp fluorescence and neutron reflectometry results suggest a rearrangement of loops surrounding the catalytic site, where they extend into the hydrocarbon chain region of the outer leaflet. Taking advantage of contrasting neutron scattering length densities, the use of deuterated α-syn versus protiated GCase showed a large change in the membrane-bound structure of α-syn in the complex. We propose a model of α-syn·GCase on the membrane, providing structural insights into inhibition of GCase by α-syn. The interaction displaces GCase away from the membrane, possibly impeding substrate access and perturbing the active site. GCase greatly alters membrane-bound α-syn, moving helical residues away from the bilayer, which could impact the degradation of α-syn in the lysosome where these two proteins interact.

Structure and response to flow of the glycocalyx layer

The glycocalyx is a sugar-rich layer located at the luminal part of the endothelial cells. It is involved in key metabolic processes and its malfunction is related to several diseases. To understand the function of the glycocalyx, a molecular level characterization is necessary. In this article, we present large-scale molecular-dynamics simulations that provide a comprehensive description of the structure and dynamics of the glycocalyx. We introduce the most detailed, to-date, all-atom glycocalyx model, composed of lipid bilayer, proteoglycan dimers, and heparan sulfate chains with realistic sequences. Our results reveal the folding of proteoglycan ectodomain and the extended conformation of heparan sulfate chains. Furthermore, we study the glycocalyx response under shear flow and its role as a flypaper for binding fibroblast growth factors (FGFs), which are involved in diverse functions related to cellular differentiation, including angiogenesis, morphogenesis, and wound healing. The simulations show that the glycocalyx increases the effective concentration of FGFs, leading to FGF oligomerization, and acts as a lever to transfer mechanical stimulus into the cytoplasmic side of endothelial cells.

xMDFF: molecular dynamics flexible fitting of low-resolution X-ray structures

X-ray crystallography remains the most dominant method for solving atomic structures. However, for relatively large systems, the availability of only medium-to-low-resolution diffraction data often limits the determination of all-atom details. A new molecular dynamics flexible fitting (MDFF)-based approach, xMDFF, for determining structures from such low-resolution crystallographic data is reported. xMDFF employs a real-space refinement scheme that flexibly fits atomic models into an iteratively updating electron-density map. It addresses significant large-scale deformations of the initial model to fit the low-resolution density, as tested with synthetic low-resolution maps of D-ribose-binding protein. xMDFF has been successfully applied to re-refine six low-resolution protein structures of varying sizes that had already been submitted to the Protein Data Bank. Finally, via systematic refinement of a series of data from 3.6 to 7 Å resolution, xMDFF refinements together with electrophysiology experiments were used to validate the first all-atom structure of the voltage-sensing protein Ci-VSP.