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Cyclooxygenase-2 [(COX-2) or prostaglandin endoperoxide H2 synthase-2 (PTGS-2)] induces the production of prostaglandins as part of the host-immune response to infections. Although a number of studies have demonstrated the effects of COX-2 promoter variants on autoimmune and inflammatory diseases, their role in malaria remains undefined. As such, we investigated the relationship between four COX-2 promoter variants (COX-2 −512 C > T, −608 T > C, −765 G > C, and −1195 A > G) and susceptibility to malaria and severe malarial anemia (SMA) upon enrollment and longitudinally over a 36-month follow-up period. All-cause mortality was also explored. The investigation was carried out in children (n = 1081, age; 2–70 months) residing in a holoendemic Plasmodium falciparum transmission region of western Kenya. At enrollment, genotypes/haplotypes (controlling for anemia-promoting covariates) did not reveal any strong effects on susceptibility to either malaria or SMA. Longitudinal analyses showed decreased malaria episodes in children who inherited the −608 CC mutant allele (RR = 0.746, P = 1.811 × 10(−4)) and −512C/−608T/−765G/−1195G (CTGG) haplotype (RR = 0.856, P = 0.011), and increased risk in TTCA haplotype carriers (RR = 1.115, P = 0.026). Over the follow-up period, inheritance of the rare TTCG haplotype was associated with enhanced susceptibility to both malaria (RR = 1.608, P = 0.016) and SMA (RR = 5.714, P = 0.004), while carriage of the rare TTGG haplotype increased the risk of malaria (RR = 1.755, P = 0.007), SMA (RR = 8.706, P = 3.97 × 10(−4)), and all-cause mortality (HR = 110.000, P = 0.001). Collectively, these results show that SNP variations in the COX-2 promoter, and their inherited combinations, are associated with the longitudinal risk of malaria, SMA, and all-cause mortality among children living in a high transmission area for P. falciparum.

International audience; The scattering of neutrons can be used to provide information on the structure and dynamics of biological systems on multiple length and time scales. Pursuant to a National Science Foundation-funded workshop in February 2018, recent developments in this field are reviewed here, as well as future prospects that can be expected given recent advances in sources, instrumentation and computational power and methods. Crystallography, solution scattering, dynamics, membranes, labeling and imaging are examined. For the extraction of maximum information, the incorporation of judicious specific deuterium labeling, the integration of several types of experiment, and interpretation using high-performance computer simulation models are often found to be particularly powerful.

A versatile, interactive model to predict geographically resolved epidemic progression after pathogen introduction into a population is presented. Deterministic simulations incorporating a compartmental disease model run rapidly, facilitating the analysis of mitigations such as vaccination and transmission reduction on epidemic spread and progression. We demonstrate the simulation model using rinderpest infection of cattle, a devastating livestock disease. Rinderpest has been extinguished in the wild, but it is still a threat due to stored virus in some laboratories. Comparison of simulations to historical outbreaks provides some validation of the model. Simulations of potential outbreaks demonstrate potential consequences of rinderpest virus release for a variety of possible disease parameters and mitigations. Our results indicate that a rinderpest outbreak could result in severe social and economic consequences.

The glass transition is one of the few unsolved problems in condensed matter physics: agreement on the cause of the slowing down of structural relaxation in glass-forming liquids is lacking. Glasses are amorphous solids, which do not possess the long-range crystalline order, yet display arrested dynamics and the shear elastic modulus characteristic of equilibrium elasticity. It has been suggested that due to the influence of intramolecular interactions and chain connectivity, the nature of the glass transition in polymers and in standard glass-formers is fundamentally different. Here, we discuss the role of connectivity in polymer glasses, demonstrating that although covalent bonding promotes glass formation, bonding sequentiality that defines a polymer chain is not critical in the bulk: glassy dynamics is purely a result of the number of connections per particle, independently of how these connections are formed, agreeing with the classical Phillips-Thorpe topological constraint theory. We show that bonding sequentiality does play an important role in the surface effects of the glass, highlighting a major difference between polymeric and colloidal glasses. Further, we identify the heterogenous dynamics of model coarse-grained polymer chains both in ‘bulk’ and near the free surface, and demonstrate characteristic domain patterns in local displacement and connectivity.

Objective We present a mathematical framework for non-parametric estimation of the force of infection, together with statistical upper and lower confidence bands. The resulting estimates allow to assess how well simpler models, such as SEIR, fit the observed time series of incidence data. Introduction Uncertainty Quantification (UQ), the ability to quantify the impact of sample-to-sample variations and model misspecification on predictions and forecasts, is a critical aspect of disease surveillance. While quantifying the impact of stochastic uncertainty in the data is well understood, quantifying the impact of model misspecification is significantly harder. For the latter, one needs a "universal model" to which more restrictive parametric models are compared too. Methods This talk presents a useful modeling framework for time series of incidence data from contagious diseases that enables one to identify and quantify the impact of model form uncertainty. Specifically, we propose to focus on estimating the time dependent force of infection. The latter is a universal parameters for all contagious disease model. Using a machine learning technique for estimating monotone functions, i.e., isotonic regression and its variants, one can estimate the force of infection without addtional assumptions. We note that most contagious disease model do satisfy this monotonicity assumption, due to a combination of factors: depletion of susceptibles, implementation of mitigation strategies, behavior change, etc. Comparing the resulting "non-parametric" estimate with parametric estimates, obtained by fitting an SEIR for example, can reveal model deficiencies and help quantify model form uncertainties. Finally, we discuss how ideas from "strict bound theory" can be used to develop upper and lower uncertainty bands for force of infection that acknowledge the intrinsic stochasticity in the data. Results We demonstrate the application of the methodology to weekly Influenza Like Illness (ILI) incidence data from France and compare the results to fitted SIR and SEIR models. This comparison can be seen as a nonparametric goodness of fit test, providing one with tools to do simple model selection. Conclusions We present a novel and flexible model to statistically describe the force of infection as a function of time. Comparing the fit to incidence data of that model with the fit of simpler parametric models enables the quantification of model form uncertainty and associated model selection.

Objective We will demonstrate tools that allow mechanistic contraints on disease progression and epidemic spread to play off against interventions, mitigation, and control measures. The fundamental mechanisms of disease progression and epidemic spread provide important constraints on interpreting changing epidemic cases counts with time and geography in the context of on-going interventions, mitigations, and controls. Models such as these that account for the effects of human actions can also allow evaluation of the importance of categories of epidemic and disease controls. Introduction We present the EpiEarly, EpiGrid, and EpiCast tools for mechanistically-based biological decision support. The range of tools covers coarse-, medium-, and fine-grained models. The coarse-grained, aggregated time-series only data tool (EpiEarly) provides a statistic quantifying epidemic growth potential and associated uncertainties. The medium grained, geographically-resolved model (EpiGrid) is based on differential equation type simulations of disease and epidemic progression in the presence of various human interventions geared toward understanding the role of infection control, early vs. late diagnosis, vaccination, etc. in outbreak control. A fine-grained hybrid-agent epidemic model (EpiCast) with diurnal agent travel and contagion allows the analysis of the importance of contact-networks, travel, and detailed intervention strategies for the control of outbreaks and epidemics. Methods We use three types of methods for simulation and analysis. They are: (1) Bayesian and regression methods allowing estimation of the basic reproductive number from case-count data; (2) ordinary-differential equation integration with modifications to account for discreteness of disease spread when case counts are small (we include space- and time-dependent effects); and (3) methods that hybridize agent-based travel, mixing, and disease progression with nested-mass action contagion (i.e. not fully agent-based). From the perspective of decision support, the crucial feature of mechanistic infectious epidemiological models is a way to capture the human interventions that determine epidemic outcome. Categorizing types of mitigation into those that change the force of infection , and those that branch disease progression allows a common framework that can be extended from medium-grained models through fine-grained. Our canonical example is our EpiGrid tool which allows for the modulation of the force of infection (i.e. contagion) with time (and potentially space), the vaccination of a susceptible population in a geographically-targeted manner, movement controls, and branching our disease progression model to account for early- vs. late-intervention during host disease progression. Results We will present analysis of diseases that exemplify the various aspects of analysis in support of outbreak and epidemic control. Human and animal diseases relevant to this demonstration include rinderpest, avian influenza, and measles. We will begin with EpiEarly’s estimate of epidemic potential using aggregated time-dependent case-count data. The key observation for EpiEarly is that under a wide range of situations a disease's reproductive number should be generalized to a distribution of possibilities to account for inherent randomness and other factors (including the variability of a disease contact network). We will then continue with a demonstration of EpiGrid’s capabilities for understanding and modelling the role of interventions including contagion control (the force of infection), treatment (changing disease progression and infectiousness depending on treatment), vaccination, culling, and movement controls. We will briefly touch on the capabilities of EpiCast for more detailed analysis of specific intervention strategies. Conclusions We will demonstrate examples where modeling either contributed or plausibly would contribute to informing epidemic and outbreak control constrained by the possibilities of the underlying epidemic and disease dynamics.

Membrane fusion proteins are responsible for viral entry into host cells—a crucial first step in viral infection. These proteins undergo large conformational changes from pre-fusion to fusion-initiation structures, and, despite differences in viral genomes and disease etiology, many fusion proteins are arranged as trimers. Structural information for both pre-fusion and fusion-initiation states is critical for understanding virus neutralization by the host immune system. In the case of Ebola virus glycoprotein (EBOV GP) and Zika virus envelope protein (ZIKV E), pre-fusion state structures have been identified experimentally, but only partial structures of fusion-initiation states have been described. While the fusion-initiation structure is in an energetically unfavorable state that is difficult to solve experimentally, the existing structural information combined with computational approaches enabled the modeling of fusion-initiation state structures of both proteins. These structural models provide an improved understanding of four different neutralizing antibodies in the prevention of viral host entry.

Membrane fusion proteins are responsible for viral entry into host cells– a crucial first step in viral infection. These proteins undergo large conformational changes from pre-fusion to fusion initiation structures, and, despite differences in viral genomes and disease etiology, many fusion proteins are arranged as trimers. Structural information for both pre-fusion and fusion initiation states is critical for understanding virus neutralization by the host immune system. In the case of Ebola glycoprotein (GP) and Zika envelope protein (Zika E), pre-fusion state structures have been identified experimentally, but only partial structures of fusion initiation states have been described. While the fusion initiation structure is in an energetically unfavorable state that is difficult to solve experimentally, the existing structural information combined with computational approaches enabled the modeling of fusion initiation state structures of both proteins. These structural models provide an improved understanding of four different neutralizing antibodies in the prevention of viral host entry.

Dr. Wuttke claims in his Letter (1) that our “radical reinterpretation of incoherent neutron scattering” (2) reverses scattering theory and is false. His main assertion is that we overlook the experimental apparatus as a means to break the isotropy of n-p scattering, claimed to occur because the beam direction and detector location define the momentum transfer … [↵][1]1To whom correspondence should be addressed. Email: hansfrauenfelder{at}mac.com. [1]: #xref-corresp-1-1

We recently introduced a model of incoherent quasielastic neutron scattering (QENS) that treats the neutrons as wave packets of finite length and the protein as a random walker in the free energy landscape. We call the model ELM for "energy landscape model." In ELM, the interaction of the wave packet with a proton in a protein provides the dynamic information. During the scattering event, the momentum [Formula: see text] is transferred by the wave packet to the struck proton and its moiety, exerting the force [Formula: see text] The resultant energy [Formula: see text] is stored elastically and returned to the neutron as it exits. The energy is given by [Formula: see text], where [Formula: see text] is the ambient temperature and [Formula: see text] ([Formula: see text] 91 K A) is a new elastobaric coefficient. Experiments yield the scattering intensity (dynamic structure factor) [Formula: see text] as a function of [Formula: see text] and [Formula: see text] To test our model, we use published data on proteins where only thermal vibrations are active. ELM competes with the currently accepted theory, here called the spatial motion model (SMM), which explains [Formula: see text] by motions in real space. ELM is superior to SMM: It can explain the experimental angular and temperature dependence, whereas SMM cannot do so.

Sequence determination of complete or coding-complete genomes of viruses is becoming common practice for supporting the work of epidemiologists, ecologists, virologists, and taxonomists. Sequencing duration and costs are rapidly decreasing, sequencing hardware is under modification for use by non-experts, and software is constantly being improved to simplify sequence data management and analysis. Thus, analysis of virus disease outbreaks on the molecular level is now feasible, including characterization of the evolution of individual virus populations in single patients over time. The increasing accumulation of sequencing data creates a management problem for the curators of commonly used sequence databases and an entry retrieval problem for end users. Therefore, utilizing the data to their fullest potential will require setting nomenclature and annotation standards for virus isolates and associated genomic sequences. The National Center for Biotechnology Information’s (NCBI’s) RefSeq is a non-redundant, curated database for reference (or type) nucleotide sequence records that supplies source data to numerous other databases. Building on recently proposed templates for filovirus variant naming [ ()////-], we report consensus decisions from a majority of past and currently active filovirus experts on the eight filovirus type variants and isolates to be represented in RefSeq, their final designations, and their associated sequences.

Proteins have evolved to perform numerous roles as specific catalysts and nano-machines. Some of the mechanisms exploited by evolution are clear. Hydrophobicity drives the stabilization energy of folding, charges mediate long-range interactions and facilitate catalysis, and specific geometries and hydrogen bonding patterns facilitate molecular recognition and catalysis. In this work, we examine the energy landscape of protein dynamics in terms of the continuous and discrete water structures that control protein dynamics. We observe that the internal structures at the active site of proteins are constantly shaped by strong interactions with hydration shell and bulk water motions. By describing the energy landscape of proteins in terms of its three component motions; conformational, hydration and protonation, and electronic structure, it is possible to systematically understand protein function.

Bacteremia and malaria coinfection is a common and life-threatening condition in children residing in sub-Saharan Africa. We previously showed that coinfection with Gram negative (G[−]) enteric Bacilli andPlasmodium falciparum(Pf[+]) was associated with reduced high-density parasitemia (HDP, >10,000 parasites/μL), enhanced respiratory distress, and severe anemia. Since inflammatory mediators are largely unexplored in such coinfections, circulating cytokines were determined in four groups of children (n=206, aged Pf[+] alone; G[−] coinfected; and G[+] coinfected.Staphylococcus aureusand non-TyphiSalmonellawere the most frequently isolated G[+] and G[−] organisms, respectively. Coinfected children, particularly those with G[−] pathogens, had lower parasite burden (peripheral and geometric mean parasitemia and HDP). In addition, both coinfected groups had increased IL-4, IL-5, IL-7, IL-12, IL-15, IL-17, IFN-γ, and IFN-αand decreased TNF-αrelative to malaria alone. Children with G[−] coinfection had higher IL-1βand IL-1Ra and lower IL-10 than thePf[+] group and higher IFN-γthan the G[+] group. To determine how the immune response to malaria regulates parasitemia, cytokine production was investigated with a multiple mediation model. Cytokines with the greatest mediational impact on parasitemia were IL-4, IL-10, IL-12, and IFN-γ. Results here suggest that enhanced immune activation, especially in G[−] coinfected children, acts to reduce malaria parasite burden.

Immunological control of hepatitis C virus (HCV) is possible and is probably mediated by host T-cell responses, but the genetic diversity of the virus poses a major challenge to vaccine development. We considered monovalent and polyvalent candidates for an HCV vaccine, including natural, consensus and synthetic 'mosaic' sequence cocktails. Mosaic vaccine reagents were designed using a computational approach first applied to and demonstrated experimentally for human immunodeficiency virus type 1 (HIV-Delta). Mosaic proteins resemble natural proteins, but are assembled from fragments of natural sequences via a genetic algorithm and optimized to maximize the coverage of potential T-cell epitopes (all 9-mers) found in natural sequences and to minimize the inclusion of rare 9-mers to avoid vaccine-specific responses. Genotype 1-specific and global vaccine cocktails were evaluated. Among vaccine candidates considered, polyvalent mosaic sequences provided the best coverage of both known and potential epitopes and had the fewest rare epitopes. A global vaccine based on conserved proteins across genotypes may be feasible, as a five-antigen mosaic cocktail provided 90, 77 and 70% coverage of the Core, NS3 and NS4 proteins, respectively; protein coverage diminished with increased protein variability, dropping to 38% for NS2. For the genotype 1-specific vaccine, the H77 prototype vaccine sequence matched only 50% of the potential epitopes in the population, whilst a polyprotein three-antigen mosaic cocktail increased potential epitope coverage to 83%. More than 75% coverage of all HCV proteins was achieved with a three-antigen mosaic cocktail, suggesting that genotype-specific vaccines could also include the more variable proteins.

Protein functions require conformational motions. We show here that the dominant conformational motions are slaved by the hydration shell and the bulk solvent. The protein contributes the structure necessary for function. We formulate a model that is based on experiments, insights from the physics of glass-forming liquids, and the concepts of a hierarchically organized energy landscape. To explore the effect of external fluctuations on protein dynamics, we measure the fluctuations in the bulk solvent and the hydration shell with broadband dielectric spectroscopy and compare them with internal fluctuations measured with the Mössbauer effect and neutron scattering. The result is clear. Large-scale protein motions are slaved to the fluctuations in the bulk solvent. They are controlled by the solvent viscosity, and are absent in a solid environment. Internal protein motions are slaved to the beta fluctuations of the hydration shell, are controlled by hydration, and are absent in a dehydrated protein. The model quantitatively predicts the rapid increase of the mean-square displacement above ≈200 K, shows that the external beta fluctuations determine the temperature- and time-dependence of the passage of carbon monoxide through myoglobin, and explains the nonexponential time dependence of the protein relaxation after photodissociation.

Glasses, supercooled liquids and proteins share common properties, in particular the existence of an energy landscape and the presence of two types of fluctuations, alpha and beta. While the effect of alpha fluctuations on proteins has been known for a few years, the effect of beta fluctuations has not been fully understood. By comparing neutron-scattering data on the protein myoglobin with beta fluctuations in the hydration shell measured by dielectric relaxation spectroscopy, we show that the internal protein motions are slaved to these fluctuations. We also show that there is no 'dynamical transition' in proteins near 200 K. The rapid increase in the mean-square displacement with temperature in many neutron-scattering experiments can be quantitatively predicted by beta fluctuations in the hydration shell.

Dengue, a vector-borne disease, thrives in tropical and subtropical regions worldwide. A retrospective analysis of the 2002 dengue epidemic in Colima located on the Mexican central Pacific coast is carried out. We estimate the reproduction number from spatial epidemic data at the level of municipalities using two different methods: (1) Using a standard dengue epidemic model and assuming pure exponential initial epidemic growth and (2) Fitting a more realistic epidemic model to the initial phase of the dengue epidemic curve. Using Method I, we estimate an overall mean reproduction number of 3.09 (95% CI: 2.34,3.84) as well as local reproduction numbers whose values range from 1.24 (1.15,1.33) to 4.22 (2.90,5.54). Using Method II, the overall mean reproduction number is estimated to be 2.0 (1.75,2.23) and local reproduction numbers ranging from 0.49 (0.0,1.0) to 3.30 (1.63,4.97). Method I systematically overestimates the reproduction number relative to the refined Method II, and hence it would overestimate the intensity of interventions required for containment. Moreover, optimal intervention with defined resources demands different levels of locally tailored mitigation. Local epidemic peaks occur between the 24th and 35th week of the year, and correlate positively with the final local epidemic sizes (rho=0.92, P-value0.001). Moreover, final local epidemic sizes are found to be linearly related to the local population size (P-value0.001). This observation supports a roughly constant number of female mosquitoes per person across urban and rural regions.

Protein motions are complex and a good way to describe them is in terms of a very high-dimensional conformation space. We give here a simple explanation of the conformation space and the energy landscape, the conformational motions and protein reactions, based on an analogy to a traffic problem. The analogy provides insight into the slaving of protein processes to bulk solvent fluctuations, in both the native and unfolded states.

Proteins are ideal systems to experimentally study stochastic complexity. They share many properties with supercooled liquids and glasses, but are functionally organized, perform biological work, and interact strongly with their surroundings. We describe the complexity of proteins, expressed through their hierarchically organized energy landscape, and characterize how fluctuations in the hydration shell and the bulk environment influence protein motions and functions.

Despite improved control measures, Ebola remains a serious public health risk in African regions where recurrent outbreaks have been observed since the initial epidemic in 1976. Using epidemic modeling and data from two well-documented Ebola outbreaks (Congo 1995 and Uganda 2000), we estimate the number of secondary cases generated by an index case in the absence of control interventions R0. Our estimate of R0 is 1.83 (SD 0.06) for Congo (1995) and 1.34 (SD 0.03) for Uganda (2000). We model the course of the outbreaks via an SEIR (susceptible-exposed-infectious-removed) epidemic model that includes a smooth transition in the transmission rate after control interventions are put in place. We perform an uncertainty analysis of the basic reproductive number R0 to quantify its sensitivity to other disease-related parameters. We also analyse the sensitivity of the final epidemic size to the time interventions begin and provide a distribution for the final epidemic size. The control measures implemented during these two outbreaks (including education and contact tracing followed by quarantine) reduce the final epidemic size by a factor of 2 relative the final size with a 2-week delay in their implementation.

In this article we use global and regional data from the SARS epidemic in conjunction with a model of susceptible, exposed, infective, diagnosed, and recovered classes of people ("SEIJR") to extract average properties and rate constants for those populations. The model is fitted to data from the Ontario (Toronto) in Canada, Hong Kong in China and Singapore outbreaks and predictions are made based on various assumptions and observations, including the current effect of isolating individuals diagnosed with SARS. The epidemic dynamics for Hong Kong and Singapore appear to be different from the dynamics in Toronto, Ontario. Toronto shows a very rapid increase in the number of cases between March 31st and April 6th, followed by a significant slowing in the number of new cases. We explain this as the result of an increase in the diagnostic rate and in the effectiveness of patient isolation after March 26th. Our best estimates are consistent with SARS eventually being contained in Toronto, although the time of containment is sensitive to the parameters in our model. It is shown that despite the empirically modeled heterogeneity in transmission, SARS' average reproductive number is 1.2, a value quite similar to that computed for some strains of influenza (J. Math. Biol. 27 (1989) 233). Although it would not be surprising to see levels of SARS infection higher than 10% in some regions of the world (if unchecked), lack of data and the observed heterogeneity and sensitivity of parameters prevent us from predicting the long-term impact of SARS. The possibility that 10 or more percent of the world population at risk could eventually be infected with the virus in conjunction with a mortality rate of 3-7% or more, and indications of significant improvement in Toronto support the stringent measures that have been taken to isolate diagnosed cases.

Protein dynamics is crucial for protein function. Proteins in living systems are not isolated, but operate in networks and in a carefully regulated environment. Understanding the external control of protein dynamics is consequently important. Hydration and solvent viscosity are among the salient properties of the environment. Dehydrated proteins and proteins in a rigid environment do not function properly. It is consequently important to understand the effect of hydration and solvent viscosity in detail. We discuss experiments that separate the two effects. These experiments have predominantly been performed with wild-type horse and sperm whale myoglobin, using the binding of carbon monoxide over a broad range of temperatures as a tool. The experiments demonstrate that data taken only in the physiological temperature range are not sufficient to understand the effect of hydration and solvent on protein relaxation and function. While the actual data come from myoglobin, it is expected that the results apply to most or all globular proteins.

We use Molecular Dynamics simulations to study single chain polymer dynamics and collapse to imitate the early stages of protein folding, as well as polymer brush collapse, to understand the physics and morphology of collapsing polymer brushes. Simulations of this nature can help us understand complex phenomena such as glass transition, molecular crowding and complex higher order organisation. As an example, we demonstrate a study of the physical origin of the polymer glass transition from the point of view of marginal rigidity, which is achieved above a certain number of intermolecular contacts. We find that when the average number of contacts per monomer (covalent and non-covalent) exceeds the critical value z∗=4, the system becomes solid and the dynamics arrested - a state that we declare the glass. We also look at polymer brushes and describe spinodal decomposition-like processes that take place upon brush collapse. It is often impossible to simulate large systems without a certain level of sophisticated coarse graining. We introduce a possible model for studying higher order organisation of chromatin, a biological complex of DNA and histone proteins within the nucleus of a cell. Chromatin organisation is a fascinating topic that resembles protein folding, however, it is much more complex due to multiple levels at which chromatin folding and dynamics have to be understood. Using a simplified force field, we also study helical structures formed by peptoids, small peptidomimetic molecules that are of importance to the pharmacological industry.

Quasielastic incoherent neutron scattering (QENS) is an important tool for the exploration of the dynamics of complex systems such as biomolecules, liquids, and glasses. The dynamics is reflected in the energy spectra of the scattered neutrons. Conventionally these spectra are decomposed into a narrow elastic line and a broad quasielastic band. The band is interpreted as being caused by Doppler broadening due to spatial motion of the target molecules. We propose a quantum-mechanical model in which there is no separate elastic line. The quasielastic band is composed of sharp lines with twice the natural line width, shifted from the center by a random walk of the protein in the free-energy landscape of the target molecule. The walk is driven by vibrations and by external fluctuations. We first explore the model with the Mossbauer effect. In the subsequent application to QENS we treat the incoming neutron as a de Broglie wave packet. While the wave packet passes the protons in the protein and the hydration shell it exchanges energy with the protein during the passage time of about 100 ns. The energy exchange broadens the ensemble spectrum. Because the exchange involves the free-energy landscape of the protein, the QENS not only provides insight into the protein dynamics, but it may also illuminate the free-energy landscape of the protein–solvent system.

The Mossbauer effect and quasi-elastic neutron scattering (QENS) from hydrated proteins yield sharp elastic lines that are accompanied by broad wings. Conventionally, the elastic line and the broad wings are treated as separate phenomena. We show that there is no separation; the entire spectrum consists of Lorentzians with the natural line width. In protein crystals, the shifts of the individual lines from the elastic center above about 150 K are caused by beta fluctuations in the hydration shell. Vibrations cause shifts in the entire temperature range but are best seen below about 150 K. We construct a microscopic model for the dynamics that is based on a random walk of the proteins in their free-energy landscape. The model yields approximate values for the steps in the energy landscape. Remarkably, the quantum electrodynamic concept of gamma rays is needed to justify the model.

The function of proteins depends crucially on conformational motions. The characteristic times of these motions extend from sub-picosecond to seconds. No single experimental tool can cover the entire time range and provide all necessary parameters for a complete understanding. Moreover, without a solid understanding of the data evaluation it is easy to misinterpret the complex phenomena. Because protein motions are truly complex, the evaluation of the data even from such well-known techniques as neutron scattering (Magazu and Migliardo, 2011 [1]) and the Mossbauer effect (Chen and Yang, 2007 [2]) can lead to erroneous concepts and conclusions. We believe that notions such as the Lamb-Mossbauer relation, the protein dynamic transition, the protein glass transition, and the dynamic crossover are misleading or misapplied. To justify this statement we first briefly describe our view of dynamic proteins and then explain why we believe that these notions should be revised or abandoned. (C) 2013 Elsevier B.V. All rights reserved. (Less)

In a tour de force in this issue of PNAS, Bourgeois et al. (1) have used 2.2-ns x-ray pulses to observe the motion of carbon monoxide (CO) through myoglobin (Mb) and the relaxation of the protein from 3.2 ns to 3 ms after photodissociation. This work follows the pioneering experiments of Moffat and collaborators (2). It demonstrates how far advances in x-ray sources and computers have moved the field of protein structure determination since the path-breaking work of Kendrew et al . and Perutz (3, 4). The recent breakthrough shows how careful studies of proteins, in particular of Mb, impact many different fields. Mb is a monomeric protein that gives muscle its red color. Thirty years ago the textbook function of Mb, storage of dioxygen at the heme iron, was considered to be simple, fully understood, and consequently boring. Mb was essentially written off as a topic of serious research. Since then, the situation has changed: Mb is no longer fully understood. It plays roles other than O2 storage, serves as a prototype for complex systems, and yields insight into the chemistry and physics of soft matter and of chemical reactions. Mb consists of 153 amino acids that fold into a structure that is ≈3 nm in diameter, as depicted in Fig. 1 a . Fig. 1 b gives a schematic cross section through Mb that shows the active center: a heme group with a central iron atom. Surrounding the heme group are five cavities, the heme cavity and four cavities denoted by Xe1 to Xe4 (5). The amino acids lining the xenon cavities are much more conserved than other amino acids in mammalian Mb; they are thus likely to be important for function. A major part of Mb is taken up by amino acids that do not appear to …

We report the rational design and in vivo testing of mosaic proteins for a polyvalent pan-filoviral vaccine using a computational strategy designed for the Human Immunodeficiency Virus type 1 (HIV-1) but also appropriate for Hepatitis C virus (HCV) and potentially other diverse viruses. Mosaics are sets of artificial recombinant proteins that are based on natural proteins. The recombinants are computationally selected using a genetic algorithm to optimize the coverage of potential cytotoxic T lymphocyte (CTL) epitopes. Because evolutionary history differs markedly between HIV-1 and filoviruses, we devised an adapted computational technique that is effective for sparsely sampled taxa; our first significant result is that the mosaic technique is effective in creating high-quality mosaic filovirus proteins. The resulting coverage of potential epitopes across filovirus species is superior to coverage by any natural variants, including current vaccine strains with demonstrated cross-reactivity. The mosaic cocktails are also robust: mosaics substantially outperformed natural strains when computationally tested against poorly sampled species and more variable genes. Furthermore, in a computational comparison of cross-reactive potential a design constructed prior to the Bundibugyo outbreak performed nearly as well against all species as an updated design that included Bundibugyo. These points suggest that the mosaic designs would be more resilient than natural-variant vaccines against future Ebola outbreaks dominated by novel viral variants. We demonstrate in vivo immunogenicity and protection against a heterologous challenge in a mouse model. This design work delineates the likely requirements and limitations on broadly-protective filoviral CTL vaccines.

In proteins, the Mossbauer effect and neutron scattering show a broad line and a rapid increase of the conformational mean-square displacement above about 180 K. The increase, dubbed the "dynamical transition," is controversial. We introduce a new interpretation of the Mossbauer effect in proteins and demonstrate that no dynamical transition is required. The increase in the mean-square displacement and the broad line are caused by fluctuations in the protein's hydration shell. Using the dielectric spectrum of these fluctuations, we predict the shape of the Mossbauer spectrum from 80 to 295 K with one dimensionless coefficient.

We review the concepts of protein dynamics developed over the last 35years and extend applications of the unified model of protein dynamics to heat flow and spatial fluctuations in hydrated myoglobin (Mb) powders. Differential scanning calorimetry (DSC) and incoherent neutron scattering (INS) data on hydration Mb powders are explained by the temperature-dependence of the hydration-shell β(h) process measured by dielectric relaxation spectroscopy (DRS). The unified model explains the temperature dependence of DSC and INS data as a kinetic effect due to a fixed experimental time window and a broad distribution of hydration-shell β(h) fluctuation rates. We review the slaving of large scale protein motions to the bulk solvent α process, and the metastability of Mb molecules in glass forming bulk solvent at low temperatures. This article is part of a Special Issue entitled: "Protein Dynamics: Experimental and Computational Approaches".

Bacterial RNA polymerase (RNAP) is responsible for transcribing genes into messenger-RNAs. RNAP is a multi-components protein complex consisting of α, β, β′, Ω-subunits. RNAP, together with one or more initiation factor(s), binds to promoter DNA to yield an RNAP-DNA initiation complex. While many attempts were made to solve structures of various components of the transcription complex, the detailed structure of the RNAP-transcription factor-DNA complex is still not available. We have engaged in an exercise to develop a detailed model structure for an RNAP-σ70-DNA complex. The detailed structure of the complex (as shown in the attached figure) is modeled using a structure and sequence-based approach developed in our laboratory utilizing the low-resolution crystal structure of T. aquaticus RNAP- σ70-DNA (PDB: 1L9Z) as a scaffold and information derived from high-resolution crystal structures of the polymerases (minus the σ-subunit and the promoter DNA duplex) from T. aquaticus (PDB: 1HQM) and T. thermophilus (PDB: 2O5J). The physical constraints for the C-terminal domains of the α-subunits binding to DNA with and/or without other factors (e.g., MarA, CAP) in the presence of the RNAP-σ70-DNA are discussed.View Large Image | View Hi-Res Image | Download PowerPoint Slide

Proteins, the workhorses of living systems, are constructed from chains of amino acids, which are synthesized in the cell based on the instructions of the genetic code and then folded into working proteins. The time for folding varies from microseconds to hours. What controls the folding rate is hotly debated. We postulate here that folding has the same temperature dependence as the α-fluctuations in the bulk solvent but is much slower. We call this behavior slaving. Slaving has been observed in folded proteins: Large-scale protein motions follow the solvent fluctuations with rate coefficient k α but can be slower by a large factor. Slowing occurs because large-scale motions proceed in many small steps, each determined by k α . If conformational motions of folded proteins are slaved, so a fortiori must be the motions during folding. The unfolded protein makes a Brownian walk in the conformational space to the folded structure, with each step controlled by k α . Because the number of conformational substates in the unfolded protein is extremely large, the folding rate coefficient, k f , is much smaller than k α . The slaving model implies that the activation enthalpy of folding is dominated by the solvent, whereas the number of steps n f = k α / k f is controlled by the number of accessible substates in the unfolded protein and the solvent. Proteins, however, undergo not only α- but also β-fluctuations. These additional fluctuations are local protein motions that are essentially independent of the bulk solvent fluctuations and may be relevant at late stages of folding.

Tool for estimating basic reproductive number for the SARS outbreak suggests need for multiple methods of control., Control of the 2002–2003 severe acute respiratory syndrome (SARS) outbreak was based on rapid diagnosis coupled with effective patient isolation. We used uncertainty and sensitivity analysis of the basic reproductive number R0 to assess the role that model parameters play in outbreak control. The transmission rate and isolation effectiveness have the largest fractional effect on R0. We estimated the distribution of the reproductive number R0 under perfect isolation conditions. The distribution lies in the interquartile range 0.19–1.08, with a median of 0.49. Even though the median of R0 is 1, even with perfect isolation. This implies the need to simultaneously apply more than one method of control.

Atomic motions and energetics for a phosphate transfer reaction catalyzed by the cAMP-dependent protein kinase (PKA) are calculated by plane-wave density functional theory, starting from structures of proteins crystallized in both the reactant conformation (RC) and the transition-state conformation (TC). In the TC, we calculate that the reactants and products are nearly isoenergetic with a 0.2 eV barrier; while phosphate transfer is unfavorable by over 1.2 eV in the RC, with an even higher barrier. With the protein in the TC, the motions involved in reaction are small, with only P$_\gamma$ and the catalytic proton moving more than 0.5 \AA. Examination of the structures reveals that in the RC the active site cleft is not completely closed and there is insufficient space for the phosphorylated serine residue in the product state. Together, these observations imply that the phosphate transfer reaction occurs rapidly and reversibly in a particular conformation of the protein, and that the reaction can be gated by changes of a few tenths of an \AA in the catalytic site., Comment: revtex4, 7 pages, 4 figures, to be submitted to Science

The science of complexity has moved to center stage within the past few decades. Complex systems range from glasses to the immune system and the brain. Glasses are too simple to possess all aspects of complexity; brains are too complex to expose common concepts and laws of complexity. Proteins, however, are systems where many concepts and laws of complexity can be explored experimentally, theoretically, and computationally. Such studies have elucidated crucial aspects. The energy landscape has emerged as one central concept; it describes the free energy of a system as a function of temperature and the coordinates of all relevant atoms. A second concept is that of fluctuations. Without fluctuations, proteins would be dead and life impossible. A third concept is slaving. Proteins are not isolated systems; they are embedded in cells and membranes. Slaving arises when the fluctuations in the surroundings of a protein dominate many of the motions of the protein proper.

Protein motions are essential for function. Comparing protein processes with the dielectric fluctuations of the surrounding solvent shows that they fall into two classes: nonslaved and slaved. Nonslaved processes are independent of the solvent motions; their rates are determined by the protein conformation and vibrational dynamics. Slaved processes are tightly coupled to the solvent; their rates have approximately the same temperature dependence as the rate of the solvent fluctuations, but they are smaller. Because the temperature dependence is determined by the activation enthalpy, we propose that the solvent is responsible for the activation enthalpy, whereas the protein and the hydration shell control the activation entropy through the energy landscape. Bond formation is the prototype of nonslaved processes; opening and closing of channels are quintessential slaved motions. The prevalence of slaved motions highlights the importance of the environment in cells and membranes for the function of proteins.

The temperature dependence of functional kinetics of hydrated proteins has been related to changes in dynamic behaviour on the microscopic level, as reflected by the transition like variation of the mean square displacement u2 of the hydrogen atoms. We have extended these explorations by a detailed study of the whole quasielastic and inelastic neutron scattering spectra over the broad energy transfer domain of 50 neV to 20 meV by the combination of high precision time-of-flight neutron spectroscopy (TOF) and neutron spin echo (NSE) experiments in H2O and D2O hydrated myoglobin. This allowed us to identify the basic character of the dynamic processes behind the observed un-harmonic variation of u2. We have found that these processes are fully compatible with the extensively studied glassy type β fluctuations, which enter with increasing temperature the 0.2 ps – 10 ns combined TOF – NSE time window of the present study.

A wide variety of protein dynamics are accounted for by two classes of solvent processes: the bulk-solvent viscosity and hydration-shell dynamics. In glass-forming solvents the bulk viscosity arises from the well-characterized microscopic alpha relaxation; in liquid solvents that freeze the alpha process is essentially molecular reorientation. In past work we showed that the solvent alpha relaxation determines the activation enthalpy of alpha-slaved protein motions.We have now measured the dielectric spectrum of the hydration-shell dynamics in myoglobin solutions as a function of hydration, temperature and frequency. These hydration-shell data and a minimal model of protein-solvent coupling predict the temperature- and hydration-dependence of the Mossbauer effect. Furthermore, we show agreement between incoherent neutron scattering data and our measurements of hydration dynamics.These improvements in understanding protein-solvent dynamical coupling will be discussed in terms of earlier work describing the slaving of many protein functional motions to the solvent alpha-process and the slaving of protein folding. We demonstrate that many enthalpy barriers to protein motion arise almost entirely from solvent dynamical processes.