ProtChemSI: a network of protein–chemical structural interactions

Progress in structure determination methods means that the set of experimentally determined 3D structures of proteins in complex with small molecules is growing exponentially. ProtChemSI exploits and extends this useful set of structures by both collecting and annotating the existing data as well as providing models of potential complexes inferred by protein or chemical structure similarity. The database currently includes 7704 proteins from 1803 organisms, 11 324 chemical compounds and 202 289 complexes including 178 974 predicted. It is publicly available at http://pcidb.russelllab.org

Estimation of interdomain flexibility of N-terminus of factor H using residual dipolar couplings

Characterization of segmental flexibility is needed to understand the biological mechanisms of the very large category of functionally diverse proteins, exemplified by the regulators of complement activation, that consist of numerous compact modules or domains linked by short, potentially flexible, sequences of amino acid residues. The use of NMR-derived residual dipolar couplings (RDCs), in magnetically aligned media, to evaluate interdomain motion is established but only for two-domain proteins. We focused on the three N-terminal domains (called CCPs or SCRs) of the important complement regulator, human factor H (i.e. FH1-3). These domains cooperate to facilitate cleavage of the key complement activation-specific protein fragment, C3b, forming iC3b that no longer participates in the complement cascade. We refined a three-dimensional solution structure of recombinant FH1-3 based on nuclear Overhauser effects and RDCs. We then employed a rudimentary series of RDC datasets, collected in media containing magnetically aligned bicelles (disk-like particles formed from phospholipids) under three different conditions, to estimate interdomain motions. This circumvents a requirement of previous approaches for technically difficult collection of five independent RDC datasets. More than 80% of conformers of this predominantly extended three-domain molecule exhibit flexions of < 40 °. Such segmental flexibility (together with the local dynamics of the hypervariable loop within domain 3), could facilitate recognition of C3b via initial anchoring and eventual reorganization of modules to the conformation captured in the previously solved crystal structure of a C3b:FH1-4 complex

Content Disputes in Wikipedia Reflect Geopolitical Instability

Indicators that rank countries according socioeconomic measurements are important tools for regional development and political reform. Those currently in widespread use are sometimes criticized for a lack of reproducibility or the inability to compare values over time, necessitating simple, fast and systematic measures. Here, we applied the ‘guilt by association’ principle often used in biological networks to the information network within the online encyclopedia Wikipedia to create an indicator quantifying the degree to which pages linked to a country are disputed by contributors. The indicator correlates with metrics of governance, political or economic stability about as well as they correlate with each other, and though faster and simpler, it is remarkably stable over time despite constant changes in the underlying disputes. For some countries, changes over a four year period appear to correlate with world events related to conflicts or economic problems

Just how versatile are domains?

<p>Abstract</p> <p>Background</p> <p>Creating new protein domain arrangements is a frequent mechanism of evolutionary innovation. While some domains always form the same combinations, others form many different arrangements. This ability, which is often referred to as versatility or promiscuity of domains, its a random evolutionary model in which a domain's promiscuity is based on its relative frequency of domains.</p> <p>Results</p> <p>We show that there is a clear relationship across genomes between the promiscuity of a given domain and its frequency. However, the strength of this relationship differs for different domains. We thus redefine domain promiscuity by defining a new index, <it>DV I </it>("domain versatility index"), which eliminates the effect of domain frequency. We explore links between a domain's versatility, when unlinked from abundance, and its biological properties.</p> <p>Conclusion</p> <p>Our results indicate that domains occurring as single domain proteins and domains appearing frequently at protein termini have a higher <it>DV I</it>. This is consistent with previous observations that the evolution of domain re-arrangements is primarily driven by fusion of pre-existing arrangements and single domains as well as loss of domains at protein termini. Furthermore, we studied the link between domain age, defined as the first appearance of a domain in the species tree, and the <it>DV I</it>. Contrary to previous studies based on domain promiscuity, it seems as if the <it>DV I </it>is age independent. Finally, we find that contrary to previously reported findings, versatility is lower in Eukaryotes. In summary, our measure of domain versatility indicates that a random attachment process is sufficient to explain the observed distribution of domain arrangements and that several views on domain promiscuity need to be revised.</p

Scaling properties of protein family phylogenies

One of the classical questions in evolutionary biology is how evolutionary processes are coupled at the gene and species level. With this motivation, we compare the topological properties (mainly the depth scaling, as a characterization of balance) of a large set of protein phylogenies with a set of species phylogenies. The comparative analysis shows that both sets of phylogenies share remarkably similar scaling behavior, suggesting the universality of branching rules and of the evolutionary processes that drive biological diversification from gene to species level. In order to explain such generality, we propose a simple model which allows us to estimate the proportion of evolvability/robustness needed to approximate the scaling behavior observed in the phylogenies, highlighting the relevance of the robustness of a biological system (species or protein) in the scaling properties of the phylogenetic trees. Thus, the rules that govern the incapability of a biological system to diversify are equally relevant both at the gene and at the species level.Comment: Replaced with final published versio

CODA: Accurate Detection of Functional Associations between Proteins in Eukaryotic Genomes Using Domain Fusion

Background: In order to understand how biological systems function it is necessary to determine the interactions and associations between proteins. Gene fusion prediction is one approach to detection of such functional relationships. Its use is however known to be problematic in higher eukaryotic genomes due to the presence of large homologous domain families. Here we introduce CODA (Co-Occurrence of Domains Analysis), a method to predict functional associations based on the gene fusion idiom.Methodology/Principal Findings: We apply a novel scoring scheme which takes account of the genome-specific size of homologous domain families involved in fusion to improve accuracy in predicting functional associations. We show that CODA is able to accurately predict functional similarities in human with comparison to state-of-the-art methods and show that different methods can be complementary. CODA is used to produce evidence that a currently uncharacterised human protein may be involved in pathways related to depression and that another is involved in DNA replication.Conclusions/Significance: The relative performance of different gene fusion methodologies has not previously been explored. We find that they are largely complementary, with different methods being more or less appropriate in different genomes. Our method is the only one currently available for download and can be run on an arbitrary dataset by the user. The CODA software and datasets are freely available from ftp://ftp.biochem.ucl.ac.uk/pub/gene3d_data/v6.1.0/CODA/. Predictions are also available via web services from http://funcnet.eu/

An organelle-specific protein landscape identifies novel diseases and molecular mechanisms

Cellular organelles provide opportunities to relate biological mechanisms to disease. Here we use affinity proteomics, genetics and cell biology to interrogate cilia: poorly understood organelles, where defects cause genetic diseases. Two hundred and seventeen tagged human ciliary proteins create a final landscape of 1,319 proteins, 4,905 interactions and 52 complexes. Reverse tagging, repetition of purifications and statistical analyses, produce a high-resolution network that reveals organelle-specific interactions and complexes not apparent in larger studies, and links vesicle transport, the cytoskeleton, signalling and ubiquitination to ciliary signalling and proteostasis. We observe sub-complexes in exocyst and intraflagellar transport complexes, which we validate biochemically, and by probing structurally predicted, disruptive, genetic variants from ciliary disease patients. The landscape suggests other genetic diseases could be ciliary including 3M syndrome. We show that 3M genes are involved in ciliogenesis, and that patient fibroblasts lack cilia. Overall, this organelle-specific targeting strategy shows considerable promise for Systems Medicine

Generic Algorithm to Predict the Speed of Translational Elongation: Implications for Protein Biogenesis

Synonymous codon usage and variations in the level of isoaccepting tRNAs exert a powerful selective force on translation fidelity. We have developed an algorithm to evaluate the relative rate of translation which allows large-scale comparisons of the non-uniform translation rate on the protein biogenesis. Using the complete genomes of Escherichia coli and Bacillus subtilis we show that stretches of codons pairing to minor tRNAs form putative sites to locally attenuate translation; thereby the tendency is to cluster in near proximity whereas long contiguous stretches of slow-translating triplets are avoided. The presence of slow-translating segments positively correlates with the protein length irrespective of the protein abundance. The slow-translating clusters are predominantly located down-stream of the domain boundaries presumably to fine-tune translational accuracy with the folding fidelity of multidomain proteins. Translation attenuation patterns at highly structurally and functionally conserved domains are preserved across the species suggesting a concerted selective pressure on the codon selection and species-specific tRNA abundance in these regions

Predicting Prokaryotic Ecological Niches Using Genome Sequence Analysis

Automated DNA sequencing technology is so rapid that analysis has become the rate-limiting step. Hundreds of prokaryotic genome sequences are publicly available, with new genomes uploaded at the rate of approximately 20 per month. As a result, this growing body of genome sequences will include microorganisms not previously identified, isolated, or observed. We hypothesize that evolutionary pressure exerted by an ecological niche selects for a similar genetic repertoire in those prokaryotes that occupy the same niche, and that this is due to both vertical and horizontal transmission. To test this, we have developed a novel method to classify prokaryotes, by calculating their Pfam protein domain distributions and clustering them with all other sequenced prokaryotic species. Clusters of organisms are visualized in two dimensions as ‘mountains’ on a topological map. When compared to a phylogenetic map constructed using 16S rRNA, this map more accurately clusters prokaryotes according to functional and environmental attributes. We demonstrate the ability of this map, which we term a “niche map”, to cluster according to ecological niche both quantitatively and qualitatively, and propose that this method be used to associate uncharacterized prokaryotes with their ecological niche as a means of predicting their functional role directly from their genome sequence

Evolution of protein domain architectures

This chapter reviews current research on how protein domain architectures evolve. We begin by summarizing work on the phylogenetic distribution of proteins, as this will directly impact which domain architectures can be formed in different species. Studies relating domain family size to occurrence have shown that they generally follow power law distributions, both within genomes and larger evolutionary groups. These findings were subsequently extended to multi-domain architectures. Genome evolution models that have been suggested to explain the shape of these distributions are reviewed, as well as evidence for selective pressure to expand certain domain families more than others. Each domain has an intrinsic combinatorial propensity, and the effects of this have been studied using measures of domain versatility or promiscuity. Next, we study the principles of protein domain architecture evolution and how these have been inferred from distributions of extant domain arrangements. Following this, we review inferences of ancestral domain architecture and the conclusions concerning domain architecture evolution mechanisms that can be drawn from these. Finally, we examine whether all known cases of a given domain architecture can be assumed to have a single common origin (monophyly) or have evolved convergently (polyphyly). We end by a discussion of some available tools for computational analysis or exploitation of protein domain architectures and their evolution