Molecular dynamics simulations of a highly charged peptide from an SH3 domain: possible sequence-function relationship

A seven-residue peptide that is highly conserved in SH3 domains despite being far from the active site has been shown by NMR to be stable in solution. This peptide, biologically important because it is a likely folding nucleus for SH3 domains, provides a challenging subject for molecular dynamics because it is highly charged. We present stable, 10-ns simulations of both the native-like diverging turn structure and a helical model. Free energies of these two conformations, estimated through MM-PBSA analysis using several force fields, suggest a comparable free energy (DeltaDeltaG < or =6 kcal/mol) for native and helix conformations. NOE intensities calculated from the native trajectory reproduce experimental data quite well, suggesting that the conformations sampled by the trajectory reasonably represent those observed in the NMR experiment. The molecular dynamics results, as well as sequence analysis of a diverse 690-member family of SH3 domain proteins, suggest that the presence of two elements is essential for formation of the diverging turn structure: a pair of residues with low helical propensity in the turn region and, as previously recognized, two hydrophobic residues to close the end of the diverging turn. Thus, these two sequence features may form the structural basis for the function of this peptide as a folding nucleus in this family of proteins.     

Prediction of amino acid sequence from structure

We have developed a method for the prediction of an amino acid sequence that is compatible with a three-dimensional backbone structure. Using only a backbone structure of a protein as input, the algorithm is capable of designing sequences that closely resemble natural members of the protein family to which the template structure belongs. In general, the predicted sequences are shown to have multiple sequence profile scores that are dramatically higher than those of random sequences, and sometimes better than some of the natural sequences that make up the superfamily. As anticipated, highly conserved but poorly predicted residues are often those that contribute to the functional rather than structural properties of the protein. Overall, our analysis suggests that statistical profile scores of designed sequences are a novel and valuable figure of merit for assessing and improving protein design algorithms.     

热带假丝酵母1230 POX4、POX5基因及其编码蛋白的研究

根据GenBank中热带假丝酵母菌株pk233(ATCC 20336)POX4和POX5基因序列,设计了两对引物。通过PCR扩增,用一种简易的方法克隆了1230菌株中这两个基因。对POX4、POX5的测序表明,1230菌株的POX5基因与pk233菌株的POX5基因存在菌株间的差异。这种差异对蛋白功能的影响有待进一步研究。对POX4和POX5编码的蛋白PXP4、PXP5进行Pfam分析和二级结构预测后,推测PXP4和PXP5的N端可能是FAD结合部位。     

Prediction of subcellular protein localization based on functional domain composition

Assigning subcellular localization (SL) to proteins is one of the major tasks of functional proteomics. Despite the impressive technical advances of the past decades, it is still time-consuming and laborious to experimentally determine SL on a high throughput scale. Thus, computational predictions are the preferred method for large-scale assignment of protein SL, and if appropriate, followed up by experimental studies. In this report, using a machine learning approach, the Nearest Neighbor Algorithm (NNA), we developed a prediction system for protein SL in which we incorporated a protein functional domain profile. The overall accuracy achieved by this system is 93.96%. Furthermore, comparisons with other methods have been conducted to demonstrate the validity and efficiency of our prediction system. We also provide an implementation of our Subcellular Location Prediction System (SLPS), which is available at http://pcal.biosino.org.     

In depth analysis of rumen microbial and carbohydrate-active enzymes profile in Indian crossbred cattle

Rumen houses a plethora of symbiotic microorganisms empowering the host to hydrolyze plant lignocellulose. In this study, NGS based metagenomic approach coupled with bioinformatic analysis was employed to gain an insight into the deconstruction of lignocellulose by carbohydrate-active enzymes (CAZymes) in Indian crossbred Holstein-Friesian cattle. Cattle rumen metagenomic DNA was sequenced using Illumina-MiSeq and 1.9 gigabases of data generated with an average read length of 871 bp. Analysis of the assembled sequences by Pfam-based Carbohydrate-active enzyme Analysis Toolkit identified 17,164 putative protein-encoding CAZymes belonging to different families of glycoside hydrolases (7574), glycosyltransferases (5185), carbohydrate-binding modules (2418), carbohydrate esterases (1516), auxiliary activities (434) and polysaccharide lyases (37). Phylogenetic analysis of putative CAZymes revealed that a significant proportion of CAZymes were contributed by bacteria belonging to the phylum Bacteroidetes (40%), Firmicutes (30%) and Proteobacteria (10%). The comparative analysis of HF cross rumen metagenome with other herbivore metagenomes indicated that Indian crossbred cattle rumen is endowed with a battery of CAZymes that may play a central role in lignocellulose deconstruction. The extensive catalog of enzymes reported in our study that hydrolyzes plant lignocellulose biomass, can be further explored for the better feed utilization in ruminants and also for different industrial applications.     

Influence of conservation on calculations of amino acid covariance in multiple sequence alignments

It has long been argued that algorithms that find correlated mutations in multiple sequence alignments can be used to find structurally or functionally important residues in proteins. We examined the properties of four different methods for detecting these correlated mutations. On both simple, artificial alignments and real alignments from the Pfam database, we found a surprising lack of agreement between the four correlated mutation methods. We argue that these differences are caused in part by differing sensitivities to background conservation. Correlated mutation algorithms can be envisioned as "filters" of background conservation with each algorithm searching for correlated mutations that occur at a different background conservation frequency.     

Density peaks of paralog pairs in human and mouse genomes

Paralog gene trees, which reflect the increase of genomic complexity in the evolution, can be complicated and ambiguous. A simpler complementary approach is analysis of density distribution of paralog pairs. It can reveal general features of genome evolution, which may be hidden in the forest of gene trees. It is known that distribution of human paralog pairs along the axis of protein divergence between pair members forms two main peaks. Here I show that there are three main peaks in the mouse genome. Thus, the multimodality of paralog pair distribution seems to be a fundamental feature of mammalian genomes. Despite the great diversity of domains presented in small amounts or in multidomain architectures with a few predominant domains, both in human and mouse the first peak consists mostly of gene pairs with zinc finger domains or olfactory receptor domain. In the mouse the olfactory receptor predominates, which stipulates the three-peak distribution (since in the olfactory receptors the second peak is closer to the first peak than in other genes). The mammalian-wide zinc finger orthologs are biased towards the second peak. Thus, the marsupial orthologs are nearly absent in the first peak of human and mouse. The gene pairs in the first peak show a lower ratio of nonsynonymous to synonymous substitutions, which suggests that their evolution is more constrained. The plausible explanation is that they are in subfunctionalization state (partition of initial function of ancestral gene), whereas the second peak contains gene pairs that are already in neofunctionalization state (acquiring of novel functions). These data suggest that the adaptive radiation of mammals was accompanied by a burst of duplication of zinc finger genes, which are located in the first (most recent) peak of paralog pairs.     

Genome-wide identification and expression analysis of MAPK and MAPKK gene family in Malus domestica

MAPK signal transduction modules play crucial roles in regulating many biological processes in plants, which are composed of three classes of hierarchically organized protein kinases, namely MAPKKKs, MAPKKs, and MAPKs. Although genome-wide analysis of this family has been carried out in some species, little is known about MAPK and MAPKK genes in apple (Malus domestica). In this study, a total of 26 putative apple MAPK genes (MdMPKs) and 9 putative apple MAPKK genes (MdMKKs) have been identified and located within the apple genome. Phylogenetic analysis revealed that MdMAPKs and MdMAPKKs could be divided into 4 subfamilies (groups A, B, C and D), respectively. The predicted MdMAPKs and MdMAPKKs were distributed across 13 out of 17 chromosomes with different densities. In addition, analysis of exon–intron junctions and of intron phase inside the predicted coding region of each candidate gene has revealed high levels of conservation within and between phylogenetic groups. According to the microarray and expressed sequence tag (EST) analysis, the different expression patterns indicate that they may play different roles during fruit development and rootstock–scion interaction process. Moreover, MAPK and MAPKK genes were performed expression profile analyses in different tissues (root, stem, leaf, flower and fruit), and all of the selected genes were expressed in at least one of the tissues tested, indicating that the MAPKs and MAPKKs are involved in various aspects of physiological and developmental processes of apple. To our knowledge, this is the first report of a genome-wide analysis of the apple MAPK and MAPKK gene family. This study provides valuable information for understanding the classification and putative functions of the MAPK signal in apple.