Effect of the Solvent Temperatures on Dynamics of Serine Protease Proteinase K.

To obtain detailed information about the effect of the solvent temperatures on protein dynamics, multiple long molecular dynamics (MD) simulations of serine protease proteinase K with the solute and solvent coupled to different temperatures (either 300 or 180 K) have been performed. Comparative analyses demonstrate that the internal flexibility and mobility of proteinase K are strongly dependent on the solvent temperatures but weakly on the protein temperatures. The constructed free energy landscapes (FELs) at the high solvent temperatures exhibit a more rugged surface, broader spanning range, and higher minimum free energy level than do those at the low solvent temperatures. Comparison between the dynamic hydrogen bond (HB) numbers reveals that the high solvent temperatures intensify the competitive HB interactions between water molecules and protein surface atoms, and this in turn exacerbates the competitive HB interactions between protein internal atoms, thus enhancing the conformational flexibility and facilitating the collective motions of the protein. A refined FEL model was proposed to explain the role of the solvent mobility in facilitating the cascade amplification of microscopic motions of atoms and atomic groups into the global collective motions of the protein.

Insights into Protein-Ligand Interactions: Mechanisms, Models, and Methods.

Molecular recognition, which is the process of biological macromolecules interacting with each other or various small molecules with a high specificity and affinity to form a specific complex, constitutes the basis of all processes in living organisms. Proteins, an important class of biological macromolecules, realize their functions through binding to themselves or other molecules. A detailed understanding of the protein-ligand interactions is therefore central to understanding biology at the molecular level. Moreover, knowledge of the mechanisms responsible for the protein-ligand recognition and binding will also facilitate the discovery, design, and development of drugs. In the present review, first, the physicochemical mechanisms underlying protein-ligand binding, including the binding kinetics, thermodynamic concepts and relationships, and binding driving forces, are introduced and rationalized. Next, three currently existing protein-ligand binding models--the "lock-and-key", "induced fit", and "conformational selection"--are described and their underlying thermodynamic mechanisms are discussed. Finally, the methods available for investigating protein-ligand binding affinity, including experimental and theoretical/computational approaches, are introduced, and their advantages, disadvantages, and challenges are discussed.

The DAF-16/FOXO transcription factor functions as a regulator of epidermal innate immunity.

The Caenorhabditis elegans DAF-16 transcription factor is critical for diverse biological processes, particularly longevity and stress resistance. Disruption of the DAF-2 signaling cascade promotes DAF-16 activation, and confers resistance to killing by pathogenic bacteria, such as Pseudomonas aeruginosa, Staphylococcus aureus, and Enterococcus faecalis. However, daf-16 mutants exhibit similar sensitivity to these bacteria as wild-type animals, suggesting that DAF-16 is not normally activated by these bacterial pathogens. In this report, we demonstrate that DAF-16 can be directly activated by fungal infection and wounding in wild-type animals, which is independent of the DAF-2 pathway. Fungal infection and wounding initiate the Gαq signaling cascade, leading to Ca(2+) release. Ca(2+) mediates the activation of BLI-3, a dual-oxidase, resulting in the production of reactive oxygen species (ROS). ROS then activate DAF-16 through a Ste20-like kinase-1/CST-1. Our results indicate that DAF-16 in the epidermis is required for survival after fungal infection and wounding. Thus, the EGL-30-Ca(2+)-BLI-3-CST-1-DAF-16 signaling represents a previously unknown pathway to regulate epidermal damage response.

Phylogenetic relationship among East Asian species of the Stegana genus group (Diptera, Drosophilidae).

The phylogenetic relationship among 27 East Asian species of the Stegana genus group was reconstructed using DNA sequences of mitochondrial (COI and ND2) and nuclear (28S) genes. The results lent support to the current generic/subgeneric taxonomic classification in the genus group with the exceptions of the paraphyly of the genus Parastegana and the subgenus Oxyphortica in the genus Stegana. The ancestral areas and divergence times in the genus group were reconstructed/estimated, and accordingly, the biogeographical history of this important clade was discussed. It was proposed that, the evolution of the plant family Fagaceae, especially Quercus, may have played a certain role in facilitating the diversification of the Stegana genus group.

A Deep Learning Approach for Predicting Antigenic Variation of Influenza A H3N2.

Modeling antigenic variation in influenza (flu) virus A H3N2 using amino acid sequences is a promising approach for improving the prediction accuracy of immune efficacy of vaccines and increasing the efficiency of vaccine screening. Antigenic drift and antigenic jump/shift, which arise from the accumulation of mutations with small or moderate effects and from a major, abrupt change with large effects on the surface antigen hemagglutinin (HA), respectively, are two types of antigenic variation that facilitate immune evasion of flu virus A and make it challenging to predict the antigenic properties of new viral strains. Despite considerable progress in modeling antigenic variation based on the amino acid sequences, few studies focus on the deep learning framework which could be most suitable to be applied to this task. Here, we propose a novel deep learning approach that incorporates a convolutional neural network (CNN) and bidirectional long-short-term memory (BLSTM) neural network to predict antigenic variation. In this approach, CNN extracts the complex local contexts of amino acids while the BLSTM neural network captures the long-distance sequence information. When compared to the existing methods, our deep learning approach achieves the overall highest prediction performance on the validation dataset, and more encouragingly, it achieves prediction agreements of 99.20% and 96.46% for the strains in the forthcoming year and in the next two years included in an existing set of chronological amino acid sequences, respectively. These results indicate that our deep learning approach is promising to be applied to antigenic variation prediction of flu virus A H3N2.

The cAMP-PKA pathway-mediated fat mobilization is required for cold tolerance in C. elegans.

Low temperature has a great impact on animal life. Homoiotherms such as mammals increase their energy expenditure to produce heat by activating the cAMP-protein kinase A (PKA)-hormone-sensitive lipase (HSL) pathway under cold stress. Although poikilothermic animals do not have the ability to regulate body temperature, whether this pathway is required for cold tolerance remains unknown. We have now achieved this using the genetically tractable model animal Caenorhabditis elegans. We demonstrate that cold stress activates PKA signaling, which in turn up-regulates the expression of a hormone-sensitive lipase hosl-1. The lipase induces fat mobilization, leading to glycerol accumulation, thereby protecting worms against cold stress. Our findings provide an example of an evolutionarily conserved mechanism for cold tolerance that has persisted in both poikilothermic and homoeothermic animals.

Comparative thermal unfolding study of psychrophilic and mesophilic subtilisin-like serine proteases by molecular dynamics simulations.

Molecular dynamics (MD) simulations of a subtilisin-like serine protease VPR from the psychrophilic marine bacterium Vibrio sp. PA-44 and its mesophilic homologue, proteinase K (PRK), have been performed for 20 ns at four different temperatures (300, 373, 473, and 573 K). The comparative analyses of MD trajectories reveal that at almost all temperatures, VPR exhibits greater structural fluctuations/deviations, more unstable regular secondary structural elements, and higher global flexibility than PRK. Although these two proteases follow similar unfolding pathways at high temperatures, VPR initiates unfolding at a lower temperature and unfolds faster at the same high temperatures than PRK. These observations collectively indicate that VPR is less stable and more heat-labile than PRK. Analyses of the structural/geometrical properties reveal that, when compared to PRK, VPR has larger radius of gyration (Rg), less intramolecular contacts and hydrogen bonds (HBs), more protein-solvent HBs, and smaller burial of nonpolar area and larger exposure of polar area. These suggest that the increased flexibility of VPR would be most likely caused by its reduced intramolecular interactions and more favourable protein-solvent interactions arising from the larger exposure of the polar area, whereas the enhanced stability of PRK could be ascribed to its increased intramolecular interactions arising from the better optimized hydrophobicity. The factors responsible for the significant differences in local flexibility between these two proteases were also analyzed and ascertained. This study provides insights into molecular basis of thermostability of homologous serine proteases adapted to different temperatures.

Insight derived from molecular dynamics simulations into molecular motions, thermodynamics and kinetics of HIV-1 gp120.

Although the crystal structures of the HIV-1 gp120 core bound and pre-bound by CD4 are known, the details of dynamics involved in conformational equilibrium and transition in relation to gp120 function have remained elusive. The homology models of gp120 comprising the N- and C-termini and loops V3 and V4 in the CD4-bound and CD4-unbound states were built and subjected to molecular dynamics (MD) simulations to investigate the differences in dynamic properties and molecular motions between them. The results indicate that the CD4-bound gp120 adopted a more compact and stable conformation than the unbound form during simulations. For both the unbound and bound gp120, the large concerted motions derived from essential dynamics (ED) analyses can influence the size/shape of the ligand-binding channel/cavity of gp120 and, therefore, were related to its functional properties. The differences in motion direction between certain structural components of these two forms of gp120 were related to the conformational interconversion between them. The free energy calculations based on the metadynamics simulations reveal a more rugged and complex free energy landscape (FEL) for the unbound than for the bound gp120, implying that gp120 has a richer conformational diversity in the unbound form. The estimated free energy difference of ∼-6.0 kJ/mol between the global minimum free energy states of the unbound and bound gp120 indicates that gp120 can transform spontaneously from the unbound to bound states, revealing that the bound state represents a high-probability "ground state" for gp120 and explaining why the unbound state resists crystallization. Our results provide insight into the dynamics-and-function relationship of gp120, and facilitate understandings of the thermodynamics, kinetics and conformational control mechanism of HIV-1 gp120.

Bacteria can mobilize nematode-trapping fungi to kill nematodes.

In their natural habitat, bacteria are consumed by bacterivorous nematodes; however, they are not simply passive preys. Here we report a defensive mechanism used by certain bacteria to mobilize nematode-trapping fungi to kill nematodes. These bacteria release urea, which triggers a lifestyle switch in the fungus Arthrobotrys oligospora from saprophytic to nematode-predatory form; this predacious form is characterized by formation of specialized cellular structures or 'traps'. The bacteria significantly promote the elimination of nematodes by A. oligospora. Disruption of genes involved in urea transport and metabolism in A. oligospora abolishes the urea-induced trap formation. Furthermore, the urea metabolite ammonia functions as a signal molecule in the fungus to initiate the lifestyle switch to form trap structures. Our findings highlight the importance of multiple predator-prey interactions in prey defense mechanisms.