HIV-host interactions: vital to the virus and key to its inhibition

Much progress has been made in recent years in the investigation of the interplay between HIV-1 and its host cells. Most of these interactions are complex and have not yet been fully unraveled. Nevertheless, current knowledge on the molecular interactions between HIV and host-cell factors has substantially broadened our understanding of the viral life cycle and opened new investigative areas for drug intervention.     

Application of hierarchical thermodynamic interactions to the protonation equilibria of organic polyprotic acids

A general method for formulating complex thermodynamic systems in terms of hierarchical interactions has been developed, and has been applied in a previous analyses to the theoretical analysis of cooperativity in a dimeric protein, to the statistical analysis of hemoglobin oxygen binding data, and to the protonation equilibria of inorganic polyprotic acids. Organic polyprotic acids have served as a demonstration system for the development of concepts and methods for treating complex biochemical equilibria. Glutamic acid is the classic test case for understanding proton-proton interactions in organic polyprotic acids, and this system is analyzed using the concept of hierarchical interactions. Second order interactions were apparent between all three possible proton interactions, as has been established previously. The third order interaction between the three protons was found to be insignificant, indicating that protonation of one site on glutamate has no effect on the interaction between the other two protonation sites. This further reinforces the premise that higher order terms, representing more complex interactions, are less likely to be significant than lower order terms. To allow correlation of the interaction values from glutamate with other organic acids, pairwise interaction values between protonation events were then calculated from known pKd values for a number of diprotic acids and bases. For simple straight chain acids and bases a linear log-log relationship was apparent between the number of intervening atoms between the protons and the pK(d,hh) (pKd of interaction). This relationship extended from three atoms (carbonate) up to 11 atoms (azelaic acid) and applied to both dicarboxylic acids and diamine bases. The pairwise interactions in glutamate also followed this simple relationship.     

Molecular Modeling-Based Energy Analysis of Dimeric Binding of Ligands to the Minor DNA Groove

Molecular-modeling methods have been used to perform energy analysis of dimeric complex formation between lexitropsins and double-stranded DNA. Stabilization of dimeric complexes by hydrophobic and van der Waals interactions has been demonstrated. Electrostatic interactions and the contributions of hydrogen bonds and changes in the number of degrees of freedom had a destabilizing influence. The energy of monomeric and dimeric binding has been compared.     

多种病原物混合侵染的昆虫流行病模型

两种或两种以上的病原物同时侵染昆虫寄主时,病原物之间的相互作用表现为偏利、偏害、中性及竞争等类型,寄生群体的病症可呈多种形式．根据单种病菌的重叠侵染原理,建立了多种病原物混合侵染时以温度、病原接种量、虫龄及湿度为因子的昆虫流行病模型．由模型可计算寄生群体中不同病原物的致病比率,及寄主群体的总发病率,给出了模型的参数求解算法,以及病原物相互作用类型的判定准则．这类模型可用于多种病原物混合侵染的昆虫流行病预测,也可作为多种病原物混合施用防治害虫的最优化模型．     

A novel biclustering approach to association rule mining for predicting HIV-1-human protein interactions

Identification of potential viral-host protein interactions is a vital and useful approach towards development of new drugs targeting those interactions. In recent days, computational tools are being utilized for predicting viral-host interactions. Recently a database containing records of experimentally validated interactions between a set of HIV-1 proteins and a set of human proteins has been published. The problem of predicting new interactions based on this database is usually posed as a classification problem. However, posing the problem as a classification one suffers from the lack of biologically validated negative interactions. Therefore it will be beneficial to use the existing database for predicting new viral-host interactions without the need of negative samples. Motivated by this, in this article, the HIV-1-human protein interaction database has been analyzed using association rule mining. The main objective is to identify a set of association rules both among the HIV-1 proteins and among the human proteins, and use these rules for predicting new interactions. In this regard, a novel association rule mining technique based on biclustering has been proposed for discovering frequent closed itemsets followed by the association rules from the adjacency matrix of the HIV-1-human interaction network. Novel HIV-1-human interactions have been predicted based on the discovered association rules and tested for biological significance. For validation of the predicted new interactions, gene ontology-based and pathway-based studies have been performed. These studies show that the human proteins which are predicted to interact with a particular viral protein share many common biological activities. Moreover, literature survey has been used for validation purpose to identify some predicted interactions that are already validated experimentally but not present in the database. Comparison with other prediction methods is also discussed.     

A minimal physically realistic protein-like lattice model: designing an energy landscape that ensures all-or-none folding to a unique native state

A simple protein model restricted to the face-centered cubic lattice has been studied. The model interaction scheme includes attractive interactions between hydrophobic (H) residues, repulsive interactions between hydrophobic and polar (P) residues, and orientation-dependent P-P interactions. Additionally, there is a potential that favors extended beta-type conformations. A sequence has been designed that adopts a native structure, consisting of an antiparallel, six-member Greek-key beta-barrel with protein-like structural degeneracy. It has been shown that the proposed model is a minimal one, i.e., all the above listed types of interactions are necessary for cooperative (all-or-none) type folding to the native state. Simulations were performed via the Replica Exchange Monte Carlo method and the numerical data analyzed via a multihistogram method.     

Contribution of the hydrophobic effect to microbial infection

The hydrophobic effect has been known for decades. Numerous researchers have invoked the hydrophobic effect to explain how pathogens adhere to tissues. In some cases, inhibition of adhesion can be brought about by low concentrations of aromatic compounds, such as p-nitrophenol or tryptophan. Because the hydrophobic effect has been considered to be nonspecific, the molecular biology of adhesive hydrophobins has not been studied in as much detail as lectin adhesins. The literature provides compelling evidence that a large number of bacterial and fungal pathogens depend on hydrophobic interactions for successful colonization of a host. Several laboratories are now developing effective antiadhesins, based on inhibition of hydrophobic interactions between the host and the pathogen.     

Dual-polarization interferometry: an analytical technique to measure changes in protein structure in real time, to determine the stoichiometry of binding events, and to differentiate between specific and nonspecific interactions

The study of solution-phase interactions between small molecules and immobilized proteins is of intense interest, especially to the pharmaceutical industry. An optical sensing technique, dual polarization interferometry, has been employed for the detailed study of a model protein system, namely, d-biotin interactions with streptavidin immobilized on a solid surface. Changes in thickness and density of an immobilized streptavidin layer as a result of the binding of d-biotin have been directly measured in solution and in real time. The results obtained from this approach are in excellent agreement with X-ray crystallographic data for the structural changes expected in the streptavidin-D-biotin system. The mass changes measured on binding d-biotin also agree closely with anticipated binding capacity values. Determination of the density changes occurring in the protein adlayer provides a means for differentiation between specific and nonspecific interactions.     

Removal of tropomyosin overlap and the co-operative response to increasing calcium concentrations of the acto-subfragment-1 ATPase

The co-operative response of regulated actomyosin ATPase to increasing concentrations of calcium has been attributed to nearest-neighbor interactions, presumably between troponin-tropomyosin complexes. The degree of co-operativity was not decreased after the carboxy-terminal 11 amino acid residues had been removed from tropomyosin by carboxypeptidase A. This indicates that the interactions between neighboring troponin-tropomyosin complexes do not occur through the overlapping tropomyosin ends.     

From micro- to macroevolution: brood parasitism as a driver of phenotypic diversity in birds

A fundamental question in biology is how diversity evolves and why some clades are more diverse than others. Phenotypic diversity has often been shown to result from morphological adaptation to different habitats. The role of behavioral interactions as a driver of broadscale phenotypic diversity has received comparatively less attention. Behavioral interactions, however, are a key agent of natural selection. Antagonistic behavioral interactions with predators or with parasites can have significant fitness consequences, and hence act as strong evolutionary forces on the phenotype of species, ultimately generating diversity between species of both victims and exploiters. Avian obligate brood parasites lay their eggs in the nests of other species, their hosts, and this behavioral interaction between hosts and parasites is often considered one of the best examples of coevolution in the natural world. In this review, we use the coevolution between brood parasites and their hosts to illustrate the potential of behavioral interactions to drive evolution of phenotypic diversity at different taxonomic scales. We provide a bridge between behavioral ecology and macroevolution by describing how this interaction has increased avian phenotypic diversity not only in the brood parasitic clades but also in their hosts.     

Patterns of indirect protein interactions suggest a spatial organization to metabolism

It has long been believed that cells organize their cytoplasm so as to efficiently channel metabolites between sequential enzymes. This metabolic channeling has the potential to yield higher metabolic fluxes as well as better regulatory control over metabolism. One mechanism for achieving such channeling is to ensure that sequential enzymes in a pathway are physically close to each other in the cell. We present evidence that indirect protein interactions between related enzymes represent a global mechanism for achieving metabolic channeling; the intuition being that protein interactions between enzymes and non-enzymatic mediator proteins are a powerful means of physically associating enzymes in a modular fashion. By analyzing the metabolic and protein-protein interactions networks of Escherichia coli, yeast and humans, we are able to show that all three species have many more indirect protein interactions linking enzymes that share metabolites than would be expected by chance. Moreover, these interactions are distributed non-randomly in the metabolic network. Our analyses in yeast and E. coli show that reactions possessing such interactions also show higher flux than do those lacking them. On the basis of these observations, we suggest that an important role of protein interactions with mediator proteins is to contribute to the spatial organization of the cell. This hypothesis is supported by the fact that these mediator proteins are also enriched with annotations related to signal transduction, a system where scaffolding proteins are known to limit cross-talk by controlling spatial localization.     

Ecological specialization and susceptibility to disturbance: conjectures and refutations

Niche breadth of species has been hypothesized to be associated with species' responses to disturbance. Disturbance is usually believed to affect specialists negatively, while generalists are believed to benefit from disturbance; we call this the "specialization-disturbance" hypothesis. We also propose an associated hypothesis (the "specialization-asymmetry-disturbance" hypothesis) under which both specialization and asymmetry of interactions would explain species' responses to disturbance. We test these hypotheses using data from a plant-pollinator system that has been grazed by cattle (i.e., a biological disturbance) in southern Argentina. We quantified specialization in species interactions, specialization of interaction partners, and species' responses to disturbance. We found no relationship between degree of specialization and a species' response to disturbance. We also found that plant-pollinator interactions tend to be asymmetric in this system; there was no relationship between the degree of specialization of a given species and the degree of specialization of its interaction partners. However, asymmetry of interactions did not explain the variability in species' responses to disturbance. Thus, both hypotheses are rejected by our data. Possible reasons include failure to assess crucial resources, substantial direct effects of disturbance, inaccurate measures of specialization, difficulty detecting highly nonlinear relationships, and limitations of a nonexperimental approach. Or, in fact, there may be no relationship between specialization and response to disturbance.     

Protein coadaptation and the design of novel approaches to identify protein-protein interactions

Proteins rarely function in isolation but they form part of complex networks of interactions with other proteins within or among cells. The importance of a particular protein for cell viability is directly dependent upon the number of interactions where it participates and the function it performs: the larger the number of interactions of a protein the greater its functional importance is for the cell. With the advent of genome sequencing and "omics" technologies it became feasible conducting large-scale searches for protein interacting partners. Unfortunately, the accuracy of such analyses has been underwhelming owing to methodological limitations and to the inherent complexity of protein interactions. In addition to these experimental approaches, many computational methods have been developed to identify protein-protein interactions by assuming that interacting proteins coevolve resulting from the coadaptation dynamics between the amino acids of their interacting faces. We review the main technological advances made in the field of interactomics and discuss the feasibility of computational methods to identify protein-protein interactions based on the estimation of coevolution. As proof-of-concept, we present a classical case study: the interactions of cell surface proteins (receptors) and their ligands. Finally, we take this discussion one step forward to include interactions between organisms and species to understand the generation of biological complexity. Development of technologies for accurate detection of protein-protein interactions may shed light on processes that go from the fine-tuning of pathways and metabolic networks to the emergence of biological complexity.     

Regulation of channel function due to physical energetic coupling with a lipid bilayer

Regulation of membrane protein functions due to hydrophobic coupling with a lipid bilayer has been investigated. An energy formula describing interactions between lipid bilayer and integral ion channels with different structures, which is based on the screened Coulomb interaction approximation, has been developed. Here the interaction energy is represented as being due to charge-based interactions between channel and lipid bilayer. The hydrophobic bilayer thickness channel length mismatch is found to induce channel destabilization exponentially while negative lipid curvature linearly. Experimental parameters related to channel dynamics are consistent with theoretical predictions. To measure comparable energy parameters directly in the system and to elucidate the mechanism at an atomistic level we performed molecular dynamics (MD) simulations of the ion channel forming peptide–lipid complexes. MD simulations indicate that peptides and lipids experience electrostatic and van der Waals interactions for short period of time when found within each other’s proximity. The energies from these two interactions are found to be similar to the energies derived theoretically using the screened Coulomb and the van der Waals interactions between peptides (in ion channel) and lipids (in lipid bilayer) due to mainly their charge properties. The results of in silico MD studies taken together with experimental observable parameters and theoretical energetic predictions suggest that the peptides induce ion channels inside lipid membranes due to peptide–lipid physical interactions. This study provides a new insight helping better understand of the underlying mechanisms of membrane protein functions in cell membrane leading to important biological implications.     

Microtubules and nucleoside diphosphate kinase. Nucleoside diphosphate kinase binds to co-purifying contaminants rather than to microtubule proteins.

Nucleoside diphosphate (NDP) kinase has been postulated to generate GTP from the GDP bound to tubulin. The purified chick brain enzyme was studied with respect to its kinetic parameters, and the protein-protein interactions between the NDP kinase and tubulin were examined. No specific interaction is observed between the enzyme and assembled microtubules, tubulin dimers, or tubulin-microtubule-associated protein (MAP) oligomers under a variety of nucleotide conditions. The apparent association is demonstrated to result from NDP kinase binding to a co-purifying contaminant. The absence of detectable NDP kinase-tubulin interactions indicates that NDP kinase does not directly charge up tubulin-GDP.     

Possible Specificity of Cellular Interactions Due to Electrostatic Forces

It is known that the cells from a mixed population in a culture medium will finally segregate. This “social behavior” of the cells is a direct consequence of both physical and chemical interactions between cells. The physical forces involved in cell-cell interactions are considered to be the electrostatic, van der Waals, and very-short-range hydration forces.

It has been believed until now that the electrostatic forces acting between identical cells were always repulsive and nonspecific. In the present work, we try to suggest that even the electrostatic forces could manifest a slightly specific character, so that a completely random Brownian motion of the cells could be influenced, corrected, and transformed into a “docking maneuver,” which could favor the specific interactions between cells suspended in a culture medium. The main point of our approach is that the peculiar patterns of electric charge distribution on the cell surfaces act like specific electrostatic fingerprints that could be responsible for the preferential interactions which precede cellular segregation (1).     

Single-molecule approaches to characterizing kinetics of biomolecular interactions

Single-molecule fluorescence techniques have emerged as powerful tools to study biological processes at the molecular level. This review describes the application of these methods to the characterization of the kinetics of interaction between biomolecules. A large number of single-molecule assays have been developed that visualize association and dissociation kinetics in vitro by fluorescently labeling binding partners and observing their interactions over time. Even though recent progress has been significant, there are certain limitations to this approach. To allow the observation of individual, fluorescently labeled molecules requires low, nanomolar concentrations. I will discuss how such concentration requirements in single-molecule experiments limit their applicability to investigate intermolecular interactions and how recent technical advances deal with this issue.     

Binding of carbon monoxide to alpha-hemocyanin and beta-hemocyanin from Helix pomatia.

The binding of carbon monoxide to alpha and beta-hemocyanin from the snail Helix pomatia was studied under equilibrium conditions. Homotropic interactions upon carbon monoxide binding were much weaker than upon the binding of oxygen. Heterotropic interactions (Bohr effect and calcium-ion effect), however, were just as strong as in the case of the binding of oxygen. For alpha-hemocyanin a linkage has been observed between the binding of carbon monoxide and a change in quaternary structure of the protein.     

Kavalactones fail to inhibit alcohol dehydrogenase in vitro

In recent years, Kava kava (Piper methysticum, Forst. f., Piperaceae), a folkloric beverage and popular herbal remedy, has been implicated in a number of liver failure cases. Many hypotheses as to the mechanism of its hepatotoxicity, for example interactions with other co-ingested medication, have been postulated. This present study investigated whether pharmacokinetic interactions between kava constituents and alcohol via alcohol dehydrogenase (ADH) inhibition by individual kavalactones might explain its claimed hepatotoxic effects. Four kavalactones, (+/-)-kavain, methysticin, yangonin and desmethoxyyangonin, fail to inhibit ADH in vitro at 1, 10 or 100 microM concentrations.     

Systems Approaches to Animal Disease Surveillance and Resource Allocation: Methodological Frameworks for Behavioral Analysis

While demands for animal disease surveillance systems are growing, there has been little applied research that has examined the interactions between resource allocation, cost-effectiveness, and behavioral considerations of actors throughout the livestock supply chain in a surveillance system context. These interactions are important as feedbacks between surveillance decisions and disease evolution may be modulated by their contextual drivers, influencing the cost-effectiveness of a given surveillance system. This paper identifies a number of key behavioral aspects involved in animal health surveillance systems and reviews some novel methodologies for their analysis. A generic framework for analysis is discussed, with exemplar results provided to demonstrate the utility of such an approach in guiding better disease control and surveillance decisions.