Bad housekeeping: why do aphids leave their exuviae inside the colony?

Background  

Animals can gain protection against predators and parasites by living in groups. The encounter-dilution effect provides protection when the probability of detection of a group does not increase in proportion to group size (i.e. encounter effect), so that predators do not offset the encounter effect by attacking more members of the group (i.e. dilution effect). In this paper, we propose a novel mechanism by which prey insects could gain by producing decoys that act as multiple targets for predators or parasitoids if these decoys are recognised as preys or hosts and negatively affect the patch foraging strategy of these predators and parasitoids. Such a decoy mechanism could be present in aphid colonies in which aphid exuviae are recognised and attacked by Aphidiine wasps.     

Recognizing protein–protein interfaces with empirical potentials and reduced amino acid alphabets

Background  

In structural genomics, an important goal is the detection and classification of protein–protein interactions, given the structures of the interacting partners. We have developed empirical energy functions to identify native structures of protein–protein complexes among sets of decoy structures. To understand the role of amino acid diversity, we parameterized a series of functions, using a hierarchy of amino acid alphabets of increasing complexity, with 2, 3, 4, 6, and 20 amino acid groups. Compared to previous work, we used the simplest possible functional form, with residue–residue interactions and a stepwise distance-dependence. We used increased computational ressources, however, constructing 290,000 decoys for 219 protein–protein complexes, with a realistic docking protocol where the protein partners are flexible and interact through a molecular mechanics energy function. The energy parameters were optimized to correctly assign as many native complexes as possible. To resolve the multiple minimum problem in parameter space, over 64000 starting parameter guesses were tried for each energy function. The optimized functions were tested by cross validation on subsets of our native and decoy structures, by blind tests on series of native and decoy structures available on the Web, and on models for 13 complexes submitted to the CAPRI structure prediction experiment.     

A novel side-chain orientation dependent potential derived from random-walk reference state for protein fold selection and structure prediction

Background

An accurate potential function is essential to attack protein folding and structure prediction problems. The key to developing efficient knowledge-based potential functions is to design reference states that can appropriately counteract generic interactions. The reference states of many knowledge-based distance-dependent atomic potential functions were derived from non-interacting particles such as ideal gas, however, which ignored the inherent sequence connectivity and entropic elasticity of proteins.

Methodology

We developed a new pair-wise distance-dependent, atomic statistical potential function (RW), using an ideal random-walk chain as reference state, which was optimized on CASP models and then benchmarked on nine structural decoy sets. Second, we incorporated a new side-chain orientation-dependent energy term into RW (RWplus) and found that the side-chain packing orientation specificity can further improve the decoy recognition ability of the statistical potential.

Significance

RW and RWplus demonstrate a significantly better ability than the best performing pair-wise distance-dependent atomic potential functions in both native and near-native model selections. It has higher energy-RMSD and energy-TM-score correlations compared with other potentials of the same type in real-life structure assembly decoys. When benchmarked with a comprehensive list of publicly available potentials, RW and RWplus shows comparable performance to the state-of-the-art scoring functions, including those combining terms from multiple resources. These data demonstrate the usefulness of random-walk chain as reference states which correctly account for sequence connectivity and entropic elasticity of proteins. It shows potential usefulness in structure recognition and protein folding simulations. The RW and RWplus potentials, as well as the newly generated I-TASSER decoys, are freely available in http://zhanglab.ccmb.med.umich.edu/RW.     

Using neural networks and evolutionary information in decoy discrimination for protein tertiary structure prediction

Background  

We present a novel method of protein fold decoy discrimination using machine learning, more specifically using neural networks. Here, decoy discrimination is represented as a machine learning problem, where neural networks are used to learn the native-like features of protein structures using a set of positive and negative training examples. A set of native protein structures provides the positive training examples, while negative training examples are simulated decoy structures obtained by reversing the sequences of native structures. Various features are extracted from the training dataset of positive and negative examples and used as inputs to the neural networks.     

HopDock: a probabilistic search algorithm for decoy sampling in protein-protein docking

Background

Elucidating the three-dimensional structure of a higher-order molecular assembly formed by interacting molecular units, a problem commonly known as docking, is central to unraveling the molecular basis of cellular activities. Though protein assemblies are ubiquitous in the cell, it is currently challenging to predict the native structure of a protein assembly in silico.

Methods

This work proposes HopDock, a novel search algorithm for protein-protein docking. HopDock efficiently obtains an ensemble of low-energy dimeric configurations, also known as decoys, that can be effectively used by ab-initio docking protocols. HopDock is based on the Basin Hopping (BH) framework which perturbs the structure of a dimeric configuration and then follows it up with an energy minimization to explicitly sample a local minimum of a chosen energy function. This process is repeated in order to sample consecutive energy minima in a trajectory-like fashion. HopDock employs both geometry and evolutionary conservation analysis to narrow down the interaction search space of interest for the purpose of efficiently obtaining a diverse decoy ensemble.

Results and conclusions

A detailed analysis and a comparative study on seventeen different dimers shows HopDock obtains a broad view of the energy surface near the native dimeric structure and samples many near-native configurations. The results show that HopDock has high sampling capability and can be employed to effectively obtain a large and diverse ensemble of decoy configurations that can then be further refined in greater structural detail in ab-initio docking protocols.

     

Males of a single-brooded tropical bird species do not show increases in testosterone during social challenges

The challenge hypothesis poses that in socially monogamous vertebrates, males increase circulating testosterone in response to aggressive challenges to promote intense and persistent aggression. However, in bird species that raise only a single brood during short breeding seasons as well as those with essential male parental care, males lack the well-documented testosterone response to social challenges. We tested male behavioral and hormonal responses to social challenges in a neotropical bird species, the buff-breasted wren (Thryothorus leucotis), which is single-brooded with extensive male parental care, but in contrast to most species studied to date, has a long breeding season. We presented live female, male, and paired decoys with song playback for 30 min during pre-breeding and breeding periods. Males responded aggressively to all intruders, but male decoys elicited somewhat weaker responses overall. Responses to female decoys were most intense during pre-breeding, whereas pair decoys elicited stronger responses at breeding. Plasma testosterone concentrations did not differ between challenged and unchallenged males, or among males exposed to different decoys or during different seasons. Plasma corticosterone in pre-breeding males was higher in challenged than unchallenged males and varied positively with the duration of social challenge. Circulating dehydroepiandrosterone concentrations were similar in challenged and unchallenged males, but correlated positively with the proportion of time males spent in close proximity to the decoy. Both testosterone and corticosterone results support recent findings, suggesting that brood number and essential male care, but not breeding-season length, may be important determinants of male hormonal responsiveness during aggressive interactions.     

Developmental expression of the receptor for advanced glycation end-products (RAGE) and its response to hyperoxia in the neonatal rat lung

Background  

The receptor for advanced glycation end products (mRAGE) is associated with pathology in most tissues, while its soluble form (sRAGE) acts as a decoy receptor. The adult lung is unique in that it expresses high amounts of RAGE under normal conditions while other tissues express low amounts normally and up-regulate RAGE during pathologic processes. We sought to determine the regulation of the soluble and membrane isoforms of RAGE in the developing lung, and its expression under hyperoxic conditions in the neonatal lung.     

SVR_CAF: An integrated score function for detecting native protein structures among decoys

An accurate score function for detecting the most native‐like models among a huge number of decoy sets is essential to the protein structure prediction. In this work, we developed a novel integrated score function (SVR_CAF) to discriminate native structures from decoys, as well as to rank near‐native structures and select best decoys when native structures are absent. SVR_CAF is a machine learning score, which incorporates the contact energy based score ( C E_score), amino acid network based score ( A AN_score), and the fast Fourier transform based score ( F FT_score). The score function was evaluated with four decoy sets for its discriminative ability and it shows higher overall performance than the state‐of‐the‐art score functions. Proteins 2014; 82:556–564. © 2013 Wiley Periodicals, Inc.     

A model of local-minima distribution on conformational space and its application to protein structure prediction

A quantitative two-parameter model is developed to describe local energy minima distribution. On a conformational space measured by least-square-fitting root-mean-squared distance (RMSD), the number of local minima in a r RMSD region is proposed to be proportional to exp(-1/r). As part of the model derivations, the minimum RMSD of decoys from the largest cluster, the number of decoys in the largest cluster, and the RMSD distribution of the decoys have inner connections with each other. The model is successfully verified on a 49 helix-packing decoy set and a 30 loop-prediction decoy set, as well as both knowledge-based potential (DFIRE) and physical force-fields (OPLS and CHARMM). One of the model's applications is predicting behaviors of a large amount of decoys (e.g., minimum RMSD of 40,000 decoys) by generating only a small number of decoys (e.g., 500). It may be applied to structure predictions guided by any Lennard-Jones-like potential functions and can be extended to other sampling methods guided by simple energy terms.     

A new pairwise folding potential based on improved decoy generation and side-chain packing

A new force field for pairwise residue interactions as a function of C(alpha) to C(alpha) distances is presented. The force field was developed through the solution of a linear programming formulation with large sets of constraints. The constraints are based on the construction of >80,000 low-energy decoys for a set of proteins and requiring the decoy energies for each protein system to be higher than the native conformation of that particular protein. The generation of a robust force field was facilitated by the use of a novel decoy generation process, which involved the rational selection of proteins to add to the training set and included a significant energy minimization of the decoys. The force field was tested on a large set of decoys for various proteins not included in the training set and shown to perform well compared with a leading force field in identifying the native conformation for these proteins.     

How well can we predict native contacts in proteins based on decoy structures and their energies?

One strategy for ab initio protein structure prediction is to generate a large number of possible structures (decoys) and select the most fitting ones based on a scoring or free energy function. The conformational space of a protein is huge, and chances are rare that any heuristically generated structure will directly fall in the neighborhood of the native structure. It is desirable that, instead of being thrown away, the unfitting decoy structures can provide insights into native structures so prediction can be made progressively. First, we demonstrate that a recently parameterized physics-based effective free energy function based on the GROMOS96 force field and a generalized Born/surface area solvent model is, as several other physics-based and knowledge-based models, capable of distinguishing native structures from decoy structures for a number of widely used decoy databases. Second, we observe a substantial increase in correlations of the effective free energies with the degree of similarity between the decoys and the native structure, if the similarity is measured by the content of native inter-residue contacts in a decoy structure rather than its root-mean-square deviation from the native structure. Finally, we investigate the possibility of predicting native contacts based on the frequency of occurrence of contacts in decoy structures. For most proteins contained in the decoy databases, a meaningful amount of native contacts can be predicted based on plain frequencies of occurrence at a relatively high level of accuracy. Relative to using plain frequencies, overwhelming improvements in sensitivity of the predictions are observed for the 4_state_reduced decoy sets by applying energy-dependent weighting of decoy structures in determining the frequency. There, approximately 80% native contacts can be predicted at an accuracy of approximately 80% using energy-weighted frequencies. The sensitivity of the plain frequency approach is much lower (20% to 40%). Such improvements are, however, not observed for the other decoy databases. The rationalization and implications of the results are discussed.     

Trapping of European buprestid beetles in oak forests using visual and olfactory cues

Trapping approaches developed for the emerald ash borer (EAB), Agrilus planipennis Fairmaire (Coleoptera: Buprestidae), were adapted for trapping several European oak buprestid species. These approaches included the use of natural leaf surfaces as well as green and purple plastic in sticky trap designs. Plastic surfaces were incorporated into novel ‘branch‐trap’ designs that each presented two 5 × 9‐cm² rectangular surfaces on a cardboard structure wrapped around the leaves of a branch. We used visual adult Agrilus decoys in an attempt to evoke male mating approaches toward the traps. Our first experiment compared the attractiveness of visual characteristics of the surfaces of branch‐traps. The second looked at the effect on trap captures of adding semiochemical lures, including manuka oil, (Z)‐3‐hexen‐1‐ol, and (Z)‐9‐tricosene. In total, 1 962 buprestid specimens including 14 species from the genus Agrilus were caught on 178 traps in a 22‐day time‐span. Overall, the green plastic‐covered branch‐traps significantly out‐performed the other trap designs. We further found that the presence of an EAB visual decoy placed on the trap surface often increased captures on these green traps, but this effect was stronger for certain Agrilus species than for others. The visual decoy was particularly important for the most serious pest detected, Agrilus biguttatus Fabricius, which was captured 13 times on traps with decoys, but only once without a decoy. There were some small but significant effects of odor treatment on the capture of buprestids of two common species, Agrilus angustulus Illiger and Agrilus sulcicollis Lacordaire. There were also 141 Elateridae specimens on these traps, which were not influenced by trap type or decoys. The results suggest that small branch‐traps of this nature can provide a useful new tool for monitoring of buprestids, which have the potential to be further optimized with respect to visual and olfactory cues.     

A protein folding potential that places the native states of a large number of proteins near a local minimum

Background

We present a simple method to train a potential function for the protein folding problem which, even though trained using a small number of proteins, is able to place a significantly large number of native conformations near a local minimum. The training relies on generating decoys by energy minimization of the native conformations using the current potential and using a physically meaningful objective function (derivative of energy with respect to torsion angles at the native conformation) during the quadratic programming to place the native conformation near a local minimum.

Results

We also compare the performance of three different types of energy functions and find that while the pairwise energy function is trainable, a solvation energy function by itself is untrainable if decoys are generated by minimizing the current potential starting at the native conformation. The best results are obtained when a pairwise interaction energy function is used with solvation energy function.

Conclusions

We are able to train a potential function using six proteins which places a total of 42 native conformations within ~4 Å rmsd and 71 native conformations within ~6 Å rmsd of a local minimum out of a total of 91 proteins. Furthermore, the threading test using the same 91 proteins ranks 89 native conformations to be first and the other two as second.     

Ultrasensitive synthetic protein regulatory networks using mixed decoys

Cellular protein interaction networks exhibit sigmoidal input-output relationships with thresholds and steep responses (i.e. ultrasensitivity). Although cooperativity can be a source of ultrasensitivity, we examined whether the presence of "decoy" binding sites that are not coupled to activation could also lead to this effect. To systematically vary key parameters of the system, we designed a synthetic regulatory system consisting of an autoinhibited PDZ domain coupled to an activating SH3 domain binding site. In the absence of a decoy binding site, this system is non-ultrasensitive, as predicted by modeling of this system. Addition of a high-affinity decoy site adds a threshold, but the response is not ultrasensitive. We found that sigmoidal activation profiles can be generated utilizing multiple decoys with mixtures of high and low affinities, where high affinity decoys act to set the threshold and low affinity decoys ensure a sigmoidal response. Placing the synthetic decoy system in a mitotic spindle orientation cell culture system thresholds this physiological activity. Thus, simple combinations of non-activating binding sites can lead to complex regulatory responses in protein interaction networks.