Are kuravirus capsid diameters quantized? The first all-atom genome tracing method for double-stranded DNA viruses.

The revolution in cryo-electron microscopy has resulted in unprecedented power to resolve large macromolecular complexes including viruses. Many methods exist to explain density corresponding to proteins and thus entire protein capsids have been solved at the all-atom level. However methods for nucleic acids lag behind, and no all-atom viral double-stranded DNA genomes have been published at all. We here present a method which exploits the spiral winding patterns of DNA in icosahedral capsids. The method quickly generates shells of DNA wound in user-specified, idealized spherical or cylindrical spirals. For transition regions, the method allows guided semiflexible fitting. For the kuravirus SU10, our method explains most of the density in a semiautomated fashion. The results suggest rules for DNA turns in the end caps under which two discrete parameters determine the capsid inner diameter. We suggest that other kuraviruses viruses may follow the same winding scheme, producing a discrete rather than continuous spectrum of capsid inner diameters. Our software may be used to explain the published density maps of other double-stranded DNA viruses and uncover their genome packaging principles.

Hydrogel-embedded gold nanorods activated by plasmonic photothermy with potent antimicrobial activity.

Plasmonic photothermal therapy (PPTT) has been used as an alternative to chemotherapy for the elimination of resistant microorganisms; however, its in situ evaluation has not been well studied. In the present study, we assessed the antimicrobial activity of a chitosan-based hydrogel embedded with gold nanorods (Ch/AuNRs) using a low power infrared diode laser. The antibacterial activity was measured in both Gram-positive and -negative strains, including clinical isolates of multidrug-resistant pathogens. The cytotoxic effect, cellular proliferation, and the expression of the pro-inflammatory (IL-6 and TNF-α) and anti-inflammatory (IL-10) cytokines were quantified in a murine model of macrophages. Results showed a potent antimicrobial activity of the Ch/AuNRs with MICs ≤4 µg/mL, very low cytotoxicity with cell viability above 80%, and the macrophage proliferation was not affected for a period of 48 h. These results suggest that our Ch/AuNR-embedded hydrogel could be an option to locally control chronic nosocomial infections using PPTT.

MMB-GUI: a fast morphing method demonstrates a possible ribosomal tRNA translocation trajectory.

Easy-to-use macromolecular viewers, such as UCSF Chimera, are a standard tool in structural biology. They allow rendering and performing geometric operations on large complexes, such as viruses and ribosomes. Dynamical simulation codes enable modeling of conformational changes, but may require considerable time and many CPUs. There is an unmet demand from structural and molecular biologists for software in the middle ground, which would allow visualization combined with quick and interactive modeling of conformational changes, even of large complexes. This motivates MMB-GUI. MMB uses an internal-coordinate, multiscale approach, yielding as much as a 2000-fold speedup over conventional simulation methods. We use Chimera as an interactive graphical interface to control MMB. We show how this can be used for morphing of macromolecules that can be heterogeneous in biopolymer type, sequence, and chain count, accurately recapitulating structural intermediates. We use MMB-GUI to create a possible trajectory of EF-G mediated gate-passing translocation in the ribosome, with all-atom structures. This shows that the GUI makes modeling of large macromolecules accessible to a wide audience. The morph highlights similarities in tRNA conformational changes as tRNA translocates from A to P and from P to E sites and suggests that tRNA flexibility is critical for translocation completion.

Fast fitting to low resolution density maps: elucidating large-scale motions of the ribosome.

Determining the conformational rearrangements of large macromolecules is challenging experimentally and computationally. Case in point is the ribosome; it has been observed by high-resolution crystallography in several states, but many others are known only from low-resolution methods including cryo-electron microscopy. Combining these data into dynamical trajectories that may aid understanding of its largest-scale conformational changes has so far remained out of reach of computational methods. Most existing methods either model all atoms explicitly, resulting in often prohibitive cost, or use approximations that lose interesting structural and dynamical detail. In this work, I introduce Internal Coordinate Flexible Fitting, which uses full atomic forces and flexibility in limited regions of a model, capturing extensive conformational rearrangements at low cost. I use it to turn multiple low-resolution density maps, crystallographic structures and biochemical information into unified all-atoms trajectories of ribosomal translocation. Internal Coordinate Flexible Fitting is three orders of magnitude faster than the most comparable existing method.

Structural and Functional Impact of Parkinson Disease-Associated Mutations in the E3 Ubiquitin Ligase Parkin.

Mutations in the PARKIN/PARK2 gene that result in loss-of-function of the encoded, neuroprotective E3 ubiquitin ligase Parkin cause recessive, familial early-onset Parkinson disease. As an increasing number of rare Parkin sequence variants with unclear pathogenicity are identified, structure-function analyses will be critical to determine their disease relevance. Depending on the specific amino acids affected, several distinct pathomechanisms can result in loss of Parkin function. These include disruption of overall Parkin folding, decreased solubility, and protein aggregation. However pathogenic effects can also result from misregulation of Parkin autoinhibition and of its enzymatic functions. In addition, interference of binding to coenzymes, substrates, and adaptor proteins can affect its catalytic activity too. Herein, we have performed a comprehensive structural and functional analysis of 21 PARK2 missense mutations distributed across the individual protein domains. Using this combined approach, we were able to pinpoint some of the pathogenic mechanisms of individual sequence variants. Similar analyses will be critical in gaining a complete understanding of the complex regulations and enzymatic functions of Parkin. These studies will not only highlight the important residues, but will also help to develop novel therapeutics aimed at activating and preserving an active, neuroprotective form of Parkin.

Cysteines in the neuropilin-2 MAM domain modulate receptor homooligomerization and signal transduction.

Neuropilins (NRPs) are transmembrane receptors involved in angiogenesis, lymphangiogenesis, and neuronal development as well as in cancer metastasis. Previous studies suggest that NRPs exist in heteromeric complexes with vascular endothelial growth factors (VEGFs) and VEGF receptors as well as plexins and semaphorins. We determined via site-directed mutagenesis and bioluminescent resonance energy transfer assays that a conserved cysteine (C711) in the Danio rerio NRP2a MAM (meprin, A-5 protein, and protein tyrosine phosphatase µ) domain modulates NRP2a homomeric interactions. Mutation of this residue also disrupts semaphorin-3F binding in NRP2a-transfected COS-7 cells and prevents the NRP2a overexpression effects in a zebrafish vascular model. Collectively, our results indicate the MAM domain plays an important role in defining the NRP2 homodimer structure, which is important for semaphorin-dependent signal transduction via NRP2.

Phosphorylation by PINK1 releases the UBL domain and initializes the conformational opening of the E3 ubiquitin ligase Parkin.

Loss-of-function mutations in PINK1 or PARKIN are the most common causes of autosomal recessive Parkinson's disease. Both gene products, the Ser/Thr kinase PINK1 and the E3 Ubiquitin ligase Parkin, functionally cooperate in a mitochondrial quality control pathway. Upon stress, PINK1 activates Parkin and enables its translocation to and ubiquitination of damaged mitochondria to facilitate their clearance from the cell. Though PINK1-dependent phosphorylation of Ser65 is an important initial step, the molecular mechanisms underlying the activation of Parkin's enzymatic functions remain unclear. Using molecular modeling, we generated a complete structural model of human Parkin at all atom resolution. At steady state, the Ub ligase is maintained inactive in a closed, auto-inhibited conformation that results from intra-molecular interactions. Evidently, Parkin has to undergo major structural rearrangements in order to unleash its catalytic activity. As a spark, we have modeled PINK1-dependent Ser65 phosphorylation in silico and provide the first molecular dynamics simulation of Parkin conformations along a sequential unfolding pathway that could release its intertwined domains and enable its catalytic activity. We combined free (unbiased) molecular dynamics simulation, Monte Carlo algorithms, and minimal-biasing methods with cell-based high content imaging and biochemical assays. Phosphorylation of Ser65 results in widening of a newly defined cleft and dissociation of the regulatory N-terminal UBL domain. This motion propagates through further opening conformations that allow binding of an Ub-loaded E2 co-enzyme. Subsequent spatial reorientation of the catalytic centers of both enzymes might facilitate the transfer of the Ub moiety to charge Parkin. Our structure-function study provides the basis to elucidate regulatory mechanisms and activity of the neuroprotective Parkin. This may open up new avenues for the development of small molecule Parkin activators through targeted drug design.

A multiscale approach to predicting affinity changes in protein-protein interfaces.

Substitution mutations in protein-protein interfaces can have a substantial effect on binding, which has consequences in basic and applied biomedical research. Experimental expression, purification, and affinity determination of protein complexes is an expensive and time-consuming means of evaluating the effect of mutations, making a fast and accurate in silico method highly desirable. When the structure of the wild-type complex is known, it is possible to economically evaluate the effect of point mutations with knowledge based potentials, which do not model backbone flexibility, but these have been validated only for single mutants. Substitution mutations tend to induce local conformational rearrangements only. Accordingly, ZEMu (Zone Equilibration of Mutants) flexibilizes only a small region around the site of mutation, then computes its dynamics under a physics-based force field. We validate with 1254 experimental mutants (with 1-15 simultaneous substitutions) in a wide variety of different protein environments (65 protein complexes), and obtain a significant improvement in the accuracy of predicted ΔΔG.

RNA-Puzzles: a CASP-like evaluation of RNA three-dimensional structure prediction.

We report the results of a first, collective, blind experiment in RNA three-dimensional (3D) structure prediction, encompassing three prediction puzzles. The goals are to assess the leading edge of RNA structure prediction techniques; compare existing methods and tools; and evaluate their relative strengths, weaknesses, and limitations in terms of sequence length and structural complexity. The results should give potential users insight into the suitability of available methods for different applications and facilitate efforts in the RNA structure prediction community in ongoing efforts to improve prediction tools. We also report the creation of an automated evaluation pipeline to facilitate the analysis of future RNA structure prediction exercises.

Multiscale modeling of macromolecular biosystems.

In this article, we review the recent progress in multiresolution modeling of structure and dynamics of protein, RNA and their complexes. Many approaches using both physics-based and knowledge-based potentials have been developed at multiple granularities to model both protein and RNA. Coarse graining can be achieved not only in the length, but also in the time domain using discrete time and discrete state kinetic network models. Models with different resolutions can be combined either in a sequential or parallel fashion. Similarly, the modeling of assemblies is also often achieved using multiple granularities. The progress shows that a multiresolution approach has considerable potential to continue extending the length and time scales of macromolecular modeling.

Obesity and pro-inflammatory mediators are associated with acute kidney injury in patients with A/H1N1 influenza and acute respiratory distress syndrome.

BACKGROUND: The obesity has been shown to increase the severity of A/H1N1 infection and the development of acute respiratory distress syndrome (ARDS) and organ involvement. METHODS: Circulating levels of C-peptide, insulin, glucagon, leptin, acute phase reactants (procalcitonin, C-reactive protein, tissue plasminogen activator, and serum amyloids A and P), were measured in samples from 32 critically ill patients with A/H1N1 virus infection, 17 of whom had ARDS complicated by acute kidney injury (AKI) and 15 of whom had ARDS but did not develop AKI. RESULTS: Patients with ARDS and AKI (ARDS/AKI) had higher BMI and higher levels of C-peptide, insulin, leptin, procalcitonin and serum amyloid A compared to those ARDS patient who did not develop AKI. Adjusting for confounding variables using logistic regression analysis, higher levels of C-peptide (>0.75 ng/mL) (OR=64.8, 95% CI = 2.1-1980, p = 0.0006) and BMI>30 Kg/m(2) (OR = 42.0, 95% CI = 1.2-1478, p = 0.04) were significantly associated with the development of AKI in ARDS patients. CONCLUSION: High levels of C-peptide and BMI>30 kg/m(2) were associated with the development of AKI in ARDS patients due to A/H1N1 infection. These metabolic/obesity indicators, together with the profiles of pro-inflammatory acute phase proteins, may be important links between obesity and poor outcomes in A/H1N1 09 infection.

Community-wide evaluation of methods for predicting the effect of mutations on protein-protein interactions.

Community-wide blind prediction experiments such as CAPRI and CASP provide an objective measure of the current state of predictive methodology. Here we describe a community-wide assessment of methods to predict the effects of mutations on protein-protein interactions. Twenty-two groups predicted the effects of comprehensive saturation mutagenesis for two designed influenza hemagglutinin binders and the results were compared with experimental yeast display enrichment data obtained using deep sequencing. The most successful methods explicitly considered the effects of mutation on monomer stability in addition to binding affinity, carried out explicit side-chain sampling and backbone relaxation, evaluated packing, electrostatic, and solvation effects, and correctly identified around a third of the beneficial mutations. Much room for improvement remains for even the best techniques, and large-scale fitness landscapes should continue to provide an excellent test bed for continued evaluation of both existing and new prediction methodologies.

Amino acid substitutions in human growth hormone affect secondary structure and receptor binding.

The interaction between human Growth Hormone (hGH) and hGH Receptor (hGHR) has basic relevance to cancer and growth disorders, and hGH is the scaffold for Pegvisomant, an anti-acromegaly therapeutic. For the latter reason, hGH has been extensively engineered by early workers to improve binding and other properties. We are particularly interested in E174 which belongs to the hGH zinc-binding triad; the substitution E174A is known to significantly increase binding, but to now no explanation has been offered. We generated this and several computationally-selected single-residue substitutions at the hGHR-binding site of hGH. We find that, while many successfully slow down dissociation of the hGH-hGHR complex once bound, they also slow down the association of hGH to hGHR. The E174A substitution induces a change in the Circular Dichroism spectrum that suggests the appearance of coiled-coiling. Here we show that E174A increases affinity of hGH against hGHR because the off-rate is slowed down more than the on-rate. For E174Y (and certain mutations at other sites) the slowdown in on-rate was greater than that of the off-rate, leading to decreased affinity. The results point to a link between structure, zinc binding, and hGHR-binding affinity in hGH.

Turning limited experimental information into 3D models of RNA.

Our understanding of RNA functions in the cell is evolving rapidly. As for proteins, the detailed three-dimensional (3D) structure of RNA is often key to understanding its function. Although crystallography and nuclear magnetic resonance (NMR) can determine the atomic coordinates of some RNA structures, many 3D structures present technical challenges that make these methods difficult to apply. The great flexibility of RNA, its charged backbone, dearth of specific surface features, and propensity for kinetic traps all conspire with its long folding time, to challenge in silico methods for physics-based folding. On the other hand, base-pairing interactions (either in runs to form helices or isolated tertiary contacts) and motifs are often available from relatively low-cost experiments or informatics analyses. We present RNABuilder, a novel code that uses internal coordinate mechanics to satisfy user-specified base pairing and steric forces under chemical constraints. The code recapitulates the topology and characteristic L-shape of tRNA and obtains an accurate noncrystallographic structure of the Tetrahymena ribozyme P4/P6 domain. The algorithm scales nearly linearly with molecule size, opening the door to the modeling of significantly larger structures.

The use of the tracer methodology to assess the quality of care for patients enrolled in Medical Insurance for a New Generation.

OBJECTIVE: To assess the quality of care provided at medical units that provide services to Medical Insurance for a New Generation (SMNG) enrollees. MATERIALS AND METHODS: The tracer methodology was used in a sample of 82 medical units selected in fifteen states of Mexico and data collected in November 2009. RESULTS: Problems were found to locate the minimal number of the 18 medical charts requested in three of the tracers. The first level of care on the average reports that the quality of the process of care is 6, in a 10 point scale. In the second level improves and the third level of care is better qualified. CONCLUSIONS: The tracer methodology has enabled us to assess the quality of care. There is room for improvement in the medical units of the state health services, to that end should be directed the efforts in the health system in Mexico.

A new diterpene and bioactivities of labdanes isolated from Buddleja marrubiifolia.

The new labdane [(3R*,4aR*,7S*,10aS*,10bR*)-3-ethenyl-3,4a,7,10a-tetramethyl-dodecahydro-1H-naphtho-[2,1-b]-pyran-7-yl]-methylbenzoate together with other 7 labdanes were isolated from the aerial parts of Buddleja marrubiifolia. Compound structures were elucidated by spectroscopic methods. Some compounds showed moderate to weak antimicrobial activity towards a panel of bacterial and fungal pathogens. In addition, trans-biformene (2) and ribenol acetate (8) showed to be highly cytotoxic with LC50 < 1 µg/mL, the other compounds showed moderate cytotoxic effect with a LC50 range of 6.008-15.26 µg/mL. For all isolated compounds, no inflammatory response was observed.

Predicting protein ligand binding motions with the conformation explorer.

BACKGROUND: Knowledge of the structure of proteins bound to known or potential ligands is crucial for biological understanding and drug design. Often the 3D structure of the protein is available in some conformation, but binding the ligand of interest may involve a large scale conformational change which is difficult to predict with existing methods. RESULTS: We describe how to generate ligand binding conformations of proteins that move by hinge bending, the largest class of motions. First, we predict the location of the hinge between domains. Second, we apply an Euler rotation to one of the domains about the hinge point. Third, we compute a short-time dynamical trajectory using Molecular Dynamics to equilibrate the protein and ligand and correct unnatural atomic positions. Fourth, we score the generated structures using a novel fitness function which favors closed or holo structures. By iterating the second through fourth steps we systematically minimize the fitness function, thus predicting the conformational change required for small ligand binding for five well studied proteins. CONCLUSIONS: We demonstrate that the method in most cases successfully predicts the holo conformation given only an apo structure.

Mining the Protein Data Bank to improve prediction of changes in protein-protein binding.

Predicting the effect of mutations on protein-protein interactions is important for relating structure to function, as well as for in silico affinity maturation. The effect of mutations on protein-protein binding energy (ΔΔG) can be predicted by a variety of atomic simulation methods involving full or limited flexibility, and explicit or implicit solvent. Methods which consider only limited flexibility are naturally more economical, and many of them are quite accurate, however results are dependent on the atomic coordinate set used. In this work we perform a sequence and structure based search of the Protein Data Bank to find additional coordinate sets and repeat the calculation on each. The method increases precision and Positive Predictive Value, and decreases Root Mean Square Error, compared to using single structures. Given the ongoing growth of near-redundant structures in the Protein Data Bank, our method will only increase in applicability and accuracy.

Molecular Dynamics Simulations Suggest a Non-Doublet Decoding Model of -1 Frameshifting by tRNASer3.

In-frame decoding in the ribosome occurs through canonical or wobble Watson-Crick pairing of three mRNA codon bases (a triplet) with a triplet of anticodon bases in tRNA. Departures from the triplet-triplet interaction can result in frameshifting, meaning downstream mRNA codons are then read in a different register. There are many mechanisms to induce frameshifting, and most are insufficiently understood. One previously proposed mechanism is doublet decoding, in which only codon bases 1 and 2 are read by anticodon bases 34 and 35, which would lead to -1 frameshifting. In E. coli, tRNASer3GCU can induce -1 frameshifting at alanine (GCA) codons. The logic of the doublet decoding model is that the Ala codon's GC could pair with the tRNASer3's GC, leaving the third anticodon residue U36 making no interactions with mRNA. Under that model, a U36C mutation would still induce -1 frameshifting, but experiments refute this. We perform all-atom simulations of wild-type tRNASer3, as well as a U36C mutant. Our simulations revealed a hydrogen bond between U36 of the anticodon and G1 of the codon. The U36C mutant cannot make this interaction, as it lacks the hydrogen-bond-donating H3. The simulation thus suggests a novel, non-doublet decoding mechanism for -1 frameshifting by tRNASer3 at Ala codons.

HingeMaster: normal mode hinge prediction approach and integration of complementary predictors.

Protein motion is often the link between structure and function and a substantial fraction of proteins move through a domain hinge bending mechanism. Predicting the location of the hinge from a single structure is thus a logical first step towards predicting motion. Here, we describe ways to predict the hinge location by grouping residues with correlated normal-mode motions. We benchmarked our normal-mode based predictor against a gold standard set of carefully annotated hinge locations taken from the Database of Macromolecular Motions. We then compared it with three existing structure-based hinge predictors (TLSMD, StoneHinge, and FlexOracle), plus HingeSeq, a sequence-based hinge predictor. Each of these methods predicts hinges using very different sources of information-normal modes, experimental thermal factors, bond constraint networks, energetics, and sequence, respectively. Thus it is logical that using these algorithms together would improve predictions. We integrated all the methods into a combined predictor using a weighted voting scheme. Finally, we encapsulated all our results in a web tool which can be used to run all the predictors on submitted proteins and visualize the results.