Bringing order to protein disorder through comparative genomics and genetic interactions

Background  

Intrinsically disordered regions are widespread, especially in proteomes of higher eukaryotes. Recently, protein disorder has been associated with a wide variety of cellular processes and has been implicated in several human diseases. Despite its apparent functional importance, the sheer range of different roles played by protein disorder often makes its exact contribution difficult to interpret.     

ASPDock: protein-protein docking algorithm using atomic solvation parameters model

Background  

Atomic Solvation Parameters (ASP) model has been proven to be a very successful method of calculating the binding free energy of protein complexes. This suggests that incorporating it into docking algorithms should improve the accuracy of prediction. In this paper we propose an FFT-based algorithm to calculate ASP scores of protein complexes and develop an ASP-based protein-protein docking method (ASPDock).     

Telomere and ribosomal DNA repeats are chromosomal targets of the bloom syndrome DNA helicase

Background  

Bloom syndrome is one of the most cancer-predisposing disorders and is characterized by genomic instability and a high frequency of sister chromatid exchange. The disorder is caused by loss of function of a 3' to 5' RecQ DNA helicase, BLM. The exact role of BLM in maintaining genomic integrity is not known but the helicase has been found to associate with several DNA repair complexes and some DNA replication foci.     

The relationship between proteome size,structural disorder and organism complexity

Background  

Sequencing the genomes of the first few eukaryotes created the impression that gene number shows no correlation with organism complexity, often referred to as the G-value paradox. Several attempts have previously been made to resolve this paradox, citing multifunctionality of proteins, alternative splicing, microRNAs or non-coding DNA. As intrinsic protein disorder has been linked with complex responses to environmental stimuli and communication between cells, an additional possibility is that structural disorder may effectively increase the complexity of species.     

Protein disorder prediction by condensed PSSM considering propensity for order or disorder

Background  

More and more disordered regions have been discovered in protein sequences, and many of them are found to be functionally significant. Previous studies reveal that disordered regions of a protein can be predicted by its primary structure, the amino acid sequence. One observation that has been widely accepted is that ordered regions usually have compositional bias toward hydrophobic amino acids, and disordered regions are toward charged amino acids. Recent studies further show that employing evolutionary information such as position specific scoring matrices (PSSMs) improves the prediction accuracy of protein disorder. As more and more machine learning techniques have been introduced to protein disorder detection, extracting more useful features with biological insights attracts more attention.     

Protein complex prediction based on <Emphasis Type="Italic">k</Emphasis>-connected subgraphs in protein interaction network

Background  

Protein complexes play an important role in cellular mechanisms. Recently, several methods have been presented to predict protein complexes in a protein interaction network. In these methods, a protein complex is predicted as a dense subgraph of protein interactions. However, interactions data are incomplete and a protein complex does not have to be a complete or dense subgraph.     

MID1 and MID2 homo- and heterodimerise to tether the rapamycin-sensitive PP2A regulatory subunit, Alpha 4, to microtubules: implications for the clinical variability of X-linked Opitz GBBB syndrome and other developmental disorders

Background  

Patients with Opitz GBBB syndrome present with a variable array of developmental defects including craniofacial, cardiac, and genital anomalies. Mutations in the X-linked MID1 gene, which encodes a microtubule-binding protein, have been found in ~50% of Opitz GBBB syndrome patients consistent with the genetically heterogeneous nature of the disorder. A protein highly related to MID1, called MID2, has also been described that similarly associates with microtubules.     

Clinico-pathogenetic findings and management of chondrodystrophic myotonia (Schwartz-Jampel syndrome): a case report

Background  

Chondrodystrophic myotonia or Schwartz-Jampel syndrome is a rare genetic disorder characterized by myotonia and skeletal dysplasia. It may be progressive in nature. Recently, the gene responsible for Schwartz-Jampel syndrome has been found and the defective protein it encodes leads to abnormal cartilage development and anomalous neuromuscular activity.     

Sequence signature analysis of chromosome identity in three <Emphasis Type="Italic">Drosophila</Emphasis> species

Background  

All eukaryotic organisms need to distinguish each of their chromosomes. A few protein complexes have been described that recognise entire, specific chromosomes, for instance dosage compensation complexes and the recently discovered autosome-specific Painting of Fourth (POF) protein in Drosophila. However, no sequences have been found that are chromosome-specific and distributed over the entire length of the respective chromosome. Here, we present a new, unbiased, exhaustive computational method that was used to probe three Drosophila genomes for chromosome-specific sequences.     

A core-attachment based method to detect protein complexes in PPI networks

Background  

How to detect protein complexes is an important and challenging task in post genomic era. As the increasing amount of protein-protein interaction (PPI) data are available, we are able to identify protein complexes from PPI networks. However, most of current studies detect protein complexes based solely on the observation that dense regions in PPI networks may correspond to protein complexes, but fail to consider the inherent organization within protein complexes.     

Sequence-based identification of interface residues by an integrative profile combining hydrophobic and evolutionary information

Background  

Protein-protein interactions play essential roles in protein function determination and drug design. Numerous methods have been proposed to recognize their interaction sites, however, only a small proportion of protein complexes have been successfully resolved due to the high cost. Therefore, it is important to improve the performance for predicting protein interaction sites based on primary sequence alone.     

Inclusion of Scar/WAVE3 in a similar complex to Scar/WAVE1 and 2

Background  

The Scar/WAVE family of proteins mediates signals to actin assembly by direct activation of the Arp2/3 complex. These proteins have been characterised as major regulators of lamellipodia formation downstream of Rac activation and as members of large protein complexes.     

Lysosomal trafficking functions of mucolipin-1 in murine macrophages

Background  

Mucolipidosis Type IV is currently characterized as a lysosomal storage disorder with defects that include corneal clouding, achlorhydria and psychomotor retardation. MCOLN1, the gene responsible for this disease, encodes the protein mucolipin-1 that belongs to the "Transient Receptor Potential" family of proteins and has been shown to function as a non-selective cation channel whose activity is modulated by pH. Two cell biological defects that have been described in MLIV fibroblasts are a hyperacidification of lysosomes and a delay in the exit of lipids from lysosomes.     

Markov clustering versus affinity propagation for the partitioning of protein interaction graphs

Background  

Genome scale data on protein interactions are generally represented as large networks, or graphs, where hundreds or thousands of proteins are linked to one another. Since proteins tend to function in groups, or complexes, an important goal has been to reliably identify protein complexes from these graphs. This task is commonly executed using clustering procedures, which aim at detecting densely connected regions within the interaction graphs. There exists a wealth of clustering algorithms, some of which have been applied to this problem. One of the most successful clustering procedures in this context has been the Markov Cluster algorithm (MCL), which was recently shown to outperform a number of other procedures, some of which were specifically designed for partitioning protein interactions graphs. A novel promising clustering procedure termed Affinity Propagation (AP) was recently shown to be particularly effective, and much faster than other methods for a variety of problems, but has not yet been applied to partition protein interaction graphs.     

Identifying protein complexes directly from high-throughput TAP data with Markov random fields

Background  

Predicting protein complexes from experimental data remains a challenge due to limited resolution and stochastic errors of high-throughput methods. Current algorithms to reconstruct the complexes typically rely on a two-step process. First, they construct an interaction graph from the data, predominantly using heuristics, and subsequently cluster its vertices to identify protein complexes.     

Protein docking prediction using predicted protein-protein interface

Background  

Many important cellular processes are carried out by protein complexes. To provide physical pictures of interacting proteins, many computational protein-protein prediction methods have been developed in the past. However, it is still difficult to identify the correct docking complex structure within top ranks among alternative conformations.     

A high-accuracy consensus map of yeast protein complexes reveals modular nature of gene essentiality

Background  

Identifying all protein complexes in an organism is a major goal of systems biology. In the past 18 months, the results of two genome-scale tandem affinity purification-mass spectrometry (TAP-MS) assays in yeast have been published, along with corresponding complex maps. For most complexes, the published data sets were surprisingly uncorrelated. It is therefore useful to consider the raw data from each study and generate an accurate complex map from a high-confidence data set that integrates the results of these and earlier assays.     

Development and implementation of an algorithm for detection of protein complexes in large interaction networks

Background  

After complete sequencing of a number of genomes the focus has now turned to proteomics. Advanced proteomics technologies such as two-hybrid assay, mass spectrometry etc. are producing huge data sets of protein-protein interactions which can be portrayed as networks, and one of the burning issues is to find protein complexes in such networks. The enormous size of protein-protein interaction (PPI) networks warrants development of efficient computational methods for extraction of significant complexes.     

Predicting protein-protein binding sites in membrane proteins

Background  

Many integral membrane proteins, like their non-membrane counterparts, form either transient or permanent multi-subunit complexes in order to carry out their biochemical function. Computational methods that provide structural details of these interactions are needed since, despite their importance, relatively few structures of membrane protein complexes are available.     

BIPAD: A web server for modeling bipartite sequence elements

Background  

Many dimeric protein complexes bind cooperatively to families of bipartite nucleic acid sequence elements, which consist of pairs of conserved half-site sequences separated by intervening distances that vary among individual sites.