Bioelectrical impedance analysis for the prediction of fat-free mass in buffalo calf

The objective of this study has been to develop a prediction equation of fat-free mass (FFM) from buffalo calves. Twenty buffaloes were fed ad libitum access at unifeed, with vitamin-mineral integration, for 14 months. Seven days before slaughtering, the animals were weighed and bioelectrical impedance measurements were collected. The data were analyzed by multiple linear regressions to evaluate the relationship between FFM and various predictor variables. Stepwise regression was used to eliminate variables that did not influence variation in the model. The value of resistance collected showed a decrease when the electrical frequency increases, while the values of reactance (Xc) increase. When using live weight (LW) and reactance at 500 and at 1000 kHz as independent variables, we obtained the best R2 Adj (0.967) and Durbin Watson statistic (2.596) that explain the prediction model (FFM = - 30.59 + 0.993LW + 0.150Xc500 - 0.123Xc1000 + 9.11). These results indicate that the use of bioelectrical impedance analysis has excellent potential as a rapid method, with minimal perturbation for the animal, to predict FFM in buffalo.     

Abundance and functional roles of intrinsic disorder in the antimicrobial peptides of the NK-lysin family

NK-lysins are antimicrobial peptides (AMPs) that participate in the innate immune response and also have several pivotal roles in various biological processes. Such multifunctionality is commonly found among intrinsically disordered proteins. However, NK-lysins have never been systematically analyzed for intrinsic disorder. To fill this gap, the amino acid sequences of NK-lysins from various species were collected from UniProt and used for the comprehensive computational analysis to evaluate the propensity of these proteins for intrinsic disorder and to investigate the potential roles of disordered regions in NK-lysin functions. We analyzed abundance and peculiarities of intrinsic disorder distribution in all-known NK-lysins and showed that many NK-lysins are expected to have substantial levels of intrinsic disorder. Curiously, high level of intrinsic disorder was also found even in two proteins with known 3D-strucutres (NK-lysin from pig and human granulysin). Many of the identified disordered regions can be involved in protein–protein interactions. In fact, NK-lysins are shown to contain three to eight molecular recognition features; i.e. short structure-prone segments which are located within the long disordered regions and have a potential to undergo a disorder-to-order transition upon binding to a partner. Furthermore, these disordered regions are expected to have several sites of various posttranslational modifications. Our study shows that NK-lysins, which are AMPs with a set of prominent roles in the innate immune response, are expected to abundantly possess intrinsically disordered regions that might be related to multifunctionality of these proteins in the signal transduction pathways controlling the host response to pathogenic agents.     

InterPred: A pipeline to identify and model protein–protein interactions

Protein–protein interactions (PPI) are crucial for protein function. There exist many techniques to identify PPIs experimentally, but to determine the interactions in molecular detail is still difficult and very time‐consuming. The fact that the number of PPIs is vastly larger than the number of individual proteins makes it practically impossible to characterize all interactions experimentally. Computational approaches that can bridge this gap and predict PPIs and model the interactions in molecular detail are greatly needed. Here we present InterPred, a fully automated pipeline that predicts and model PPIs from sequence using structural modeling combined with massive structural comparisons and molecular docking. A key component of the method is the use of a novel random forest classifier that integrate several structural features to distinguish correct from incorrect protein–protein interaction models. We show that InterPred represents a major improvement in protein–protein interaction detection with a performance comparable or better than experimental high‐throughput techniques. We also show that our full‐atom protein–protein complex modeling pipeline performs better than state of the art protein docking methods on a standard benchmark set. In addition, InterPred was also one of the top predictors in the latest CAPRI37 experiment. InterPred source code can be downloaded from http://wallnerlab.org/InterPred Proteins 2017; 85:1159–1170. © 2017 Wiley Periodicals, Inc.     

The switch of the binding behaviours between Xe and π system induced by the change of oxidation state of Cu ion

Abstract

The interaction between a xenon atom and aromatic π electron system is generally of van der Waals force with a specifically weak strength. In this work, we suggest the introduction of Cu ion will highly affect the binding behaviour between the xenon and π systems. Once Cu²⁺ ion locates above the benzene ring, the binding is surprisingly strengthened to 11.98 kcal mol^?1 at CCSD(T)/CBS level, which is significantly stronger than average strength of the H-bonds in Watson-Crick guanine-cytosine base pair. If the Cu²⁺ is reduced to Cu⁺, the interaction of interest returns to the weak van der Waals interaction again. This phenomenon indicates the oxidation state shift of Cu ion could regulate the binding strength of Xe with π systems, which would be important for their potential biological functions. This study may provide a plausible understanding of the recent experimental observations of xenon anaesthesia.     

Advances of bioinformatics tools applied in virus epitopes prediction

In recent years, the in silico epitopes prediction tools have facilitated the progress of vaccines development significantly and many have been applied to predict epitopes in viruses successfully. Herein, a general overview of different tools currently available, including T cell and B cell epitopes prediction tools, is presented. And the principles of different prediction algorithms are reviewed briefly. Finally, several examples are present to illustrate the application of the prediction tools.     

From Combinatorial Libraries to MHC Ligand Motifs, T-cell Superagonists and Antagonists

Complete experimental data sets of HLA-ligand motifs and T-cell recognition patterns can be derived from combinatorial peptide libraries. These data provide the exact molecular basis for a fast development of synthetic vaccines, T-cell superagonists and non-peptide antagonists. Patient-specific peptides, peptidomimetics and vaccines of highest reactivity can be derived directly from the data sets via our prediction programme EPIPREDICT. The resulting lead structures may be developed into valuable diagnostics and therapeutic tools for the treatment of viral infections, autoimmune diseases and tumors. As one example, antibody and T cell recognition in the intestinal auto-immune disease, coeliac disease was investigated in more detail concerning the deamidation of gamma-gliadin peptides by tissue transglutaminase 9tTG) leading to autoreactive peptides specific for HLA-DQA1*0501, DQB1*0201.     

Bacillus subtilis YkuK protein is distantly related to RNase H

In addition to one hypothetical viral sequence from Bacteriophage KVP40, the PfamA family of unknown function DUF458 (Pfam Accession No. PF04308) encompasses several uncharacterized bacterial proteins including Bacillus subtilis YkuK protein. Using Meta-BASIC, a highly sensitive method for detection of distant similarity between proteins, we assign DUF458 family members to the ribonuclease H-like (RNase H-like) superfamily. DUF458 sequences maintain all core secondary structure elements of RNase H-like fold and share several conserved, presumably active site residues with RNase HI, including an invariant DDE motif. In addition to providing a model structure for a previously uncharacterized protein family, this finding suggests that DUF458 proteins function as nucleases. The unusual phyletic pattern, together with a presence of DUF458 in several thermophilic organisms, may suggest a potential role of these proteins in DNA repair in stressful conditions such as an extreme heat or other stress that causes spore formation.     

The synergic modeling for the binding of fluoroquinolone antibiotics to the hERG potassium channel

The fluoroquinolone antibiotic binding site in the hERG potassium channel was examined for the residues involved and their position in the tetrameric channel. The blocking effect of the two fluoroquinolones levofloxacin and sparfloxacin to tandem dimers of the hERG mutants were evaluated electrophysiologically. The results indicated that two Tyr652s in the neighboring subunits and one or two Phe656s in the diagonal subunits contributed to the blockade in the case of both compounds, and Ser624 was also involved. The docking studies suggested that the protonated carboxyl group in the compounds strongly interacts with Phe656 as a π acceptor.