Understanding Hydrogen-Bond Patterns in Proteins using a Novel Statistical Model

Proteins are built from basic structural elements and their systematic characterization is of interest. Searching for recurring patterns in protein contact maps, we found several network motifs, patterns that occur more frequently in experimentally determined protein contact maps than in randomized contact maps with the same properties. Some of these network motifs correspond to sub-structures of alpha helices, including topologies not previously recognized in this context. Other motifs characterize beta-sheets, again some of which appear to be novel. This topological characterization of patterns serves as a tool to characterize proteins, and to reveal a high detailed differences map for comparing protein structures solved by X-ray crystallography, NMR and molecular dynamics (MD) simulations. Both NMR and MD show small but consistent differences from the crystal structures of the same proteins, possibly due to the pair-wise energy functions used. Network motifs analysis can serve as a base for many-body energy statistical energy potential, and suggests a dictionary of basic elements of which protein secondary structure is made

On the conservation of the slow conformational dynamics within the amino acid kinase family: NAGK the paradigm

N-Acetyl-L-Glutamate Kinase (NAGK) is the structural paradigm for examining the catalytic mechanisms and dynamics of amino acid kinase family members. Given that the slow conformational dynamics of the NAGK (at the microseconds time scale or slower) may be rate-limiting, it is of importance to assess the mechanisms of the most cooperative modes of motion intrinsically accessible to this enzyme. Here, we present the results from normal mode analysis using an elastic network model representation, which shows that the conformational mechanisms for substrate binding by NAGK strongly correlate with the intrinsic dynamics of the enzyme in the unbound form. We further analyzed the potential mechanisms of allosteric signalling within NAGK using a Markov model for network communication. Comparative analysis of the dynamics of family members strongly suggests that the low-frequency modes of motion and the associated intramolecular couplings that establish signal transduction are highly conserved among family members, in support of the paradigm sequence→structure→dynamics→function © 2010 Marcos et al

metaSHARK: software for automated metabolic network prediction from DNA sequence and its application to the genomes of Plasmodium falciparum and Eimeria tenella

The metabolic SearcH And Reconstruction Kit (metaSHARK) is a new fully automated software package for the detection of enzyme-encoding genes within unannotated genome data and their visualization in the context of the surrounding metabolic network. The gene detection package (SHARKhunt) runs on a Linux systemand requires only a set of raw DNA sequences (genomic, expressed sequence tag and/ or genome survey sequence) as input. Its output may be uploaded to our web-based visualization tool (SHARKview) for exploring and comparing data from different organisms. We first demonstrate the utility of the software by comparing its results for the raw Plasmodium falciparum genome with the manual annotations available at the PlasmoDB and PlasmoCyc websites. We then apply SHARKhunt to the unannotated genome sequences of the coccidian parasite Eimeria tenella and observe that, at an E-value cut-off of 10(-20), our software makes 142 additional assertions of enzymatic function compared with a recent annotation package working with translated open reading frame sequences. The ability of the software to cope with low levels of sequence coverage is investigated by analyzing assemblies of the E.tenella genome at estimated coverages from 0.5x to 7.5x. Lastly, as an example of how metaSHARK can be used to evaluate the genomic evidence for specific metabolic pathways, we present a study of coenzyme A biosynthesis in P.falciparum and E.tenella

Rigidity and flexibility of biological networks

The network approach became a widely used tool to understand the behaviour of complex systems in the last decade. We start from a short description of structural rigidity theory. A detailed account on the combinatorial rigidity analysis of protein structures, as well as local flexibility measures of proteins and their applications in explaining allostery and thermostability is given. We also briefly discuss the network aspects of cytoskeletal tensegrity. Finally, we show the importance of the balance between functional flexibility and rigidity in protein-protein interaction, metabolic, gene regulatory and neuronal networks. Our summary raises the possibility that the concepts of flexibility and rigidity can be generalized to all networks.Comment: 21 pages, 4 figures, 1 tabl

Revealing nascent proteomics in signaling pathways and cell differentiation.

Regulation of gene expression at the level of protein synthesis is a crucial element in driving how the genetic landscape is expressed. However, we are still limited in technologies that can quantitatively capture the immediate proteomic changes that allow cells to respond to specific stimuli. Here, we present a method to capture and identify nascent proteomes in situ across different cell types without disturbing normal growth conditions, using O-propargyl-puromycin (OPP). Cell-permeable OPP rapidly labels nascent elongating polypeptides, which are subsequently conjugated to biotin-azide, using click chemistry, and captured with streptavidin beads, followed by digestion and analysis, using liquid chromatography-tandem mass spectrometry. Our technique of OPP-mediated identification (OPP-ID) allows detection of widespread proteomic changes within a short 2-hour pulse of OPP. We illustrate our technique by recapitulating alterations of proteomic networks induced by a potent mammalian target of rapamycin inhibitor, MLN128. In addition, by employing OPP-ID, we identify more than 2,100 proteins and uncover distinct protein networks underlying early erythroid progenitor and differentiation states not amenable to alternative approaches such as amino acid analog labeling. We present OPP-ID as a method to quantitatively identify nascent proteomes across an array of biological contexts while preserving the subtleties directing signaling in the native cellular environment

Disordered proteins and network disorder in network descriptions of protein structure, dynamics and function. Hypotheses and a comprehensive review

During the last decade, network approaches became a powerful tool to describe protein structure and dynamics. Here we review the links between disordered proteins and the associated networks, and describe the consequences of local, mesoscopic and global network disorder on changes in protein structure and dynamics. We introduce a new classification of protein networks into ‘cumulus-type’, i.e., those similar to puffy (white) clouds, and ‘stratus-type’, i.e., those similar to flat, dense (dark) low-lying clouds, and relate these network types to protein disorder dynamics and to differences in energy transmission processes. In the first class, there is limited overlap between the modules, which implies higher rigidity of the individual units; there the conformational changes can be described by an ‘energy transfer’ mechanism. In the second class, the topology presents a compact structure with significant overlap between the modules; there the conformational changes can be described by ‘multi-trajectories’; that is, multiple highly populated pathways. We further propose that disordered protein regions evolved to help other protein segments reach ‘rarely visited’ but functionally-related states. We also show the role of disorder in ‘spatial games’ of amino acids; highlight the effects of intrinsically disordered proteins (IDPs) on cellular networks and list some possible studies linking protein disorder and protein structure networks

Antigenic diversity is generated by distinct evolutionary mechanisms in African trypanosome species

Antigenic variation enables pathogens to avoid the host immune response by continual switching of surface proteins. The protozoan blood parasite Trypanosoma brucei causes human African trypanosomiasis ("sleeping sickness") across sub-Saharan Africa and is a model system for antigenic variation, surviving by periodically replacing a monolayer of variant surface glycoproteins (VSG) that covers its cell surface. We compared the genome of Trypanosoma brucei with two closely related parasites Trypanosoma congolense and Trypanosoma vivax, to reveal how the variant antigen repertoire has evolved and how it might affect contemporary antigenic diversity. We reconstruct VSG diversification showing that Trypanosoma congolense uses variant antigens derived from multiple ancestral VSG lineages, whereas in Trypanosoma brucei VSG have recent origins, and ancestral gene lineages have been repeatedly co-opted to novel functions. These historical differences are reflected in fundamental differences between species in the scale and mechanism of recombination. Using phylogenetic incompatibility as a metric for genetic exchange, we show that the frequency of recombination is comparable between Trypanosoma congolense and Trypanosoma brucei but is much lower in Trypanosoma vivax. Furthermore, in showing that the C-terminal domain of Trypanosoma brucei VSG plays a crucial role in facilitating exchange, we reveal substantial species differences in the mechanism of VSG diversification. Our results demonstrate how past VSG evolution indirectly determines the ability of contemporary parasites to generate novel variant antigens through recombination and suggest that the current model for antigenic variation in Trypanosoma brucei is only one means by which these parasites maintain chronic infections

Metabolic network percolation quantifies biosynthetic capabilities across the human oral microbiome

The biosynthetic capabilities of microbes underlie their growth and interactions, playing a prominent role in microbial community structure. For large, diverse microbial communities, prediction of these capabilities is limited by uncertainty about metabolic functions and environmental conditions. To address this challenge, we propose a probabilistic method, inspired by percolation theory, to computationally quantify how robustly a genome-derived metabolic network produces a given set of metabolites under an ensemble of variable environments. We used this method to compile an atlas of predicted biosynthetic capabilities for 97 metabolites across 456 human oral microbes. This atlas captures taxonomically-related trends in biomass composition, and makes it possible to estimate inter-microbial metabolic distances that correlate with microbial co-occurrences. We also found a distinct cluster of fastidious/uncultivated taxa, including several Saccharibacteria (TM7) species, characterized by their abundant metabolic deficiencies. By embracing uncertainty, our approach can be broadly applied to understanding metabolic interactions in complex microbial ecosystems.T32GM008764 - NIGMS NIH HHS; T32 GM008764 - NIGMS NIH HHS; R01 DE024468 - NIDCR NIH HHS; R01 GM121950 - NIGMS NIH HHS; DE-SC0012627 - Biological and Environmental Research; RGP0020/2016 - Human Frontier Science Program; NSFOCE-BSF 1635070 - National Science Foundation; HR0011-15-C-0091 - Defense Advanced Research Projects Agency; R37DE016937 - NIDCR NIH HHS; R37 DE016937 - NIDCR NIH HHS; R01GM121950 - NIGMS NIH HHS; R01DE024468 - NIDCR NIH HHS; 1457695 - National Science FoundationPublished versio

Evolutionary and molecular foundations of multiple contemporary functions of the nitroreductase superfamily.

Insight regarding how diverse enzymatic functions and reactions have evolved from ancestral scaffolds is fundamental to understanding chemical and evolutionary biology, and for the exploitation of enzymes for biotechnology. We undertook an extensive computational analysis using a unique and comprehensive combination of tools that include large-scale phylogenetic reconstruction to determine the sequence, structural, and functional relationships of the functionally diverse flavin mononucleotide-dependent nitroreductase (NTR) superfamily (>24,000 sequences from all domains of life, 54 structures, and >10 enzymatic functions). Our results suggest an evolutionary model in which contemporary subgroups of the superfamily have diverged in a radial manner from a minimal flavin-binding scaffold. We identified the structural design principle for this divergence: Insertions at key positions in the minimal scaffold that, combined with the fixation of key residues, have led to functional specialization. These results will aid future efforts to delineate the emergence of functional diversity in enzyme superfamilies, provide clues for functional inference for superfamily members of unknown function, and facilitate rational redesign of the NTR scaffold