Reduced C(beta) statistical potentials can outperform all-atom potentials in decoy identification

We developed a series of statistical potentials to recognize the native protein from decoys, particularly when using only a reduced representation in which each side chain is treated as a single C(beta) atom. Beginning with a highly successful all-atom statistical potential, the Discrete Optimized Protein Energy function (DOPE), we considered the implications of including additional information in the all-atom statistical potential and subsequently reducing to the C(beta) representation. One of the potentials includes interaction energies conditional on backbone geometries. A second potential separates sequence local from sequence nonlocal interactions and introduces a novel reference state for the sequence local interactions. The resultant potentials perform better than the original DOPE statistical potential in decoy identification. Moreover, even upon passing to a reduced C(beta) representation, these statistical potentials outscore the original (all-atom) DOPE potential in identifying native states for sets of decoys. Interestingly, the backbone-dependent statistical potential is shown to retain nearly all of the information content of the all-atom representation in the C(beta) representation. In addition, these new statistical potentials are combined with existing potentials to model hydrogen bonding, torsion energies, and solvation energies to produce even better performing potentials. The ability of the C(beta) statistical potentials to accurately represent protein interactions bodes well for computational efficiency in protein folding calculations using reduced backbone representations, while the extensions to DOPE illustrate general principles for improving knowledge-based potentials.     

Purpose-driven biomaterials research in liver-tissue engineering

Bottom-up engineering of microscale tissue ("microtissue") constructs to recapitulate partially the complex structure-function relationships of liver parenchyma has been realized through the development of sophisticated biomaterial scaffolds, liver-cell sources, and in vitro culture techniques. With regard to in vivo applications, the long-lived stem/progenitor cell constructs can improve cell engraftment, whereas the short-lived, but highly functional hepatocyte constructs stimulate host liver regeneration. With regard to in vitro applications, microtissue constructs are being adapted or custom-engineered into cell-based assays for testing acute, chronic and idiosyncratic toxicities of drugs or pathogens. Systems-level methods and computational models that represent quantitative relationships between biomaterial scaffolds, cells and microtissue constructs will further enable their rational design for optimal integration into specific biomedical applications.     

Statistical optimization of growth media for Paecilomyces lilacinus 6029 using non-edible oil cakes

The development of biofriendly and economical alternatives to chemical pesticides is a globally important scientific challenge. In this work, Karanja-based media conditions were optimized for obtaining high production of biomass and spores of a biocontrol agent, the entomopathogenic fungus Paecilomyces lilacinus 6029, using a two-step statistical approach coupled with rigorous experimentation. In the first step, non-edible Karanja cake was screened out as a major substrate from other oil cakes. In the second step, biomass production was maximized by applying response surface methodology to experimental variations in key physico-chemical factors: carbon/nitrogen (C/N) ratio and pH. This approach eventually predicted a maximum biomass production of 10.559 g/l with a medium having a C/N ratio of 35.88 and pH 5.9. An experimental production of 10.529 g/l biomass was obtained. The remarkable agreement between the predicted and the experimentally obtained biomass confirm the validity of the approach utilized to maximize production of P. lilacinus.     

Floral volatiles with colour cues from two cucurbitaceous plants causing attraction of Aulacophora foveicollis

Aulacophora foveicollis Lucas (Coleoptera: Chrysomelidae) is an important phytophagous pest of two cucurbitaceous plants, Momordica cochinchinensis Spreng and Solena amplexicaulis (Lam.) Gandhi. The volatile organic compound profiles from flowers of M. cochinchinensis and S. amplexicaulis were identified and quantified by gas chromatography‐mass spectrometry (GC‐MS) and GC‐flame ionization detector (FID) analyses. Twenty nine and 28 compounds were identified in volatiles of M. cochinchinensis and S. amplexicaulis flowers, respectively. Methyl jasmonate and 3‐octanol were the predominant volatiles of M. cochinchinensis flowers, whereas 1‐octadecanol and 1‐hexanol were most found in the headspace of S. amplexicaulis flowers. Aulacophora foveicollis were more attracted by the flower volatiles of M. cochinchinensis than by those of S. amplexicaulis in a glass Y‐tube olfactometer. A mixture of 1‐heptanol, linalool oxide, 1‐octanol, and nonanal in the proportions present in the headspace of both flower types elicited attraction in the insect. From 25 cm distance, A. foveicollis displayed a preference for artificial flowers of 6.5 cm diameter of S. amplexicaulis flower colour (white) over M. cochinchinensis flower colour (white‐yellow). Finally, a synthetic blend (0.43 μg 1‐heptanol + 1.44 μg linalool oxide + 0.14 μg 1‐octanol + 1.77 μg nonanal dissolved in 25 μl methylene chloride) attracted more beetles when applied in a white artificial flower than when applied in a white‐yellow artificial flower from 40 cm distance. This finding may be helpful in the development of traps for pest management strategies.     

PON-mt-tRNA: a multifactorial probability-based method for classification of mitochondrial tRNA variations

Transfer RNAs (tRNAs) are essential for encoding the transcribed genetic information from DNA into proteins. Variations in the human tRNAs are involved in diverse clinical phenotypes. Interestingly, all pathogenic variations in tRNAs are located in mitochondrial tRNAs (mt-tRNAs). Therefore, it is crucial to identify pathogenic variations in mt-tRNAs for disease diagnosis and proper treatment. We collected mt-tRNA variations using a classification based on evidence from several sources and used the data to develop a multifactorial probability-based prediction method, PON-mt-tRNA, for classification of mt-tRNA single nucleotide substitutions. We integrated a machine learning-based predictor and an evidence-based likelihood ratio for pathogenicity using evidence of segregation, biochemistry and histochemistry to predict the posterior probability of pathogenicity of variants. The accuracy and Matthews correlation coefficient (MCC) of PON-mt-tRNA are 1.00 and 0.99, respectively. In the absence of evidence from segregation, biochemistry and histochemistry, PON-mt-tRNA classifies variations based on the machine learning method with an accuracy and MCC of 0.69 and 0.39, respectively. We classified all possible single nucleotide substitutions in all human mt-tRNAs using PON-mt-tRNA. The variations in the loops are more often tolerated compared to the variations in stems. The anticodon loop contains comparatively more predicted pathogenic variations than the other loops. PON-mt-tRNA is available at http://structure.bmc.lu.se/PON-mt-tRNA/.     

Polypeptide motions are dominated by peptide group oscillations resulting from dihedral angle correlations between nearest neighbors

To identify basic local backbone motions in unfolded chains, simulations are performed for a variety of peptide systems using three popular force fields and for implicit and explicit solvent models. A dominant "crankshaft-like" motion is found that involves only a localized oscillation of the plane of the peptide group. This motion results in a strong anticorrelated motion of the phi angle of the ith residue (phi(i)) and the psi angle of the residue i - 1 (psi(i-1)) on the 0.1 ps time scale. Only a slight correlation is found between the motions of the two backbone dihedral angles of the same residue. Aside from the special cases of glycine and proline, no correlations are found between backbone dihedral angles that are separated by more than one torsion angle. These short time, correlated motions are found both in equilibrium fluctuations and during the transit process between Ramachandran basins, e.g., from the beta to the alpha region. A residue's complete transit from one Ramachandran basin to another, however, occurs in a manner independent of its neighbors' conformational transitions. These properties appear to be intrinsic because they are robust across different force fields, solvent models, nonbonded interaction routines, and most amino acids.     

Why individual thermo sensation and pain perception varies? Clue of disruptive mutations in TRPVs from 2504 human genome data

Every individual varies in character and so do their sensory functions and perceptions. The molecular mechanism and the molecular candidates involved in these processes are assumed to be similar if not same. So far several molecular factors have been identified which are fairly conserved across the phylogenetic tree and are involved in these complex sensory functions. Among all, members belonging to Transient Receptor Potential (TRP) channels have been widely characterized for their involvement in thermo-sensation. These include TRPV1 to TRPV4 channels which reveal complex thermo-gating behavior in response to changes in temperature. The molecular evolution of these channels is highly correlative with the thermal response of different species. However, recent 2504 human genome data suggest that these thermo-sensitive TRPV channels are highly variable and carry possible deleterious mutations in human population. These unexpected findings may explain the individual differences in terms of complex sensory functions.     

The Anaphase-Promoting Complex Protein 5 (AnapC5) Associates with A20 and Inhibits IL-17-Mediated Signal Transduction

IL-17 is the founding member of a family of cytokines and receptors with unique structures and signaling properties. IL-17 is the signature cytokine of Th17 cells, a relatively new T cell population that promotes inflammation in settings of infection and autoimmunity. Despite advances in understanding Th17 cells, mechanisms of IL-17-mediated signal transduction are less well defined. IL-17 signaling requires contributions from two receptor subunits, IL-17RA and IL-17RC. Mutants of IL-17RC lacking the cytoplasmic domain are nonfunctional, indicating that IL-17RC provides essential but poorly understood signaling contributions to IL-17-mediated signaling. To better understand the role of IL-17RC in signaling, we performed a yeast 2-hybrid screen to identify novel proteins associated with the IL-17RC cytoplasmic tail. One of the most frequent candidates was the anaphase promoting complex protein 7 (APC7 or AnapC7), which interacted with both IL-17RC and IL-17RA. Knockdown of AnapC7 by siRNA silencing exerted no detectable impact on IL-17 signaling. However, AnapC5, which associates with AnapC7, was also able to bind IL-17RA and IL-17RC. Moreover, AnapC5 silencing enhanced IL-17-induced gene expression, suggesting an inhibitory activity. Strikingly, AnapC5 also associated with A20 (TNFAIP3), a recently-identified negative feedback regulator of IL-17 signal transduction. IL-17 signaling was not impacted by knockdown of Itch or TAXBP1, scaffolding proteins that mediate A20 inhibition in the TNFα and IL-1 signaling pathways. These data suggest a model in which AnapC5, rather than TAX1BP1 and Itch, is a novel adaptor and negative regulator of IL-17 signaling pathways.