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

Evolutionary conservation of domain-domain interactions

BACKGROUND: Recently, there has been much interest in relating domain-domain interactions (DDIs) to protein-protein interactions (PPIs) and vice versa, in an attempt to understand the molecular basis of PPIs. RESULTS: Here we map structurally derived DDIs onto the cellular PPI networks of different organisms and demonstrate that there is a catalog of domain pairs that is used to mediate various interactions in the cell. We show that these DDIs occur frequently in protein complexes and that homotypic interactions (of a domain with itself) are abundant. A comparison of the repertoires of DDIs in the networks of Escherichia coli, Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster, and Homo sapiens shows that many DDIs are evolutionarily conserved. CONCLUSION: Our results indicate that different organisms use the same 'building blocks' for PPIs, suggesting that the functionality of many domain pairs in mediating protein interactions is maintained in evolution

The Structure-Function Linkage Database

The Structure–Function Linkage Database (SFLD, http://sfld.rbvi.ucsf.edu/) is a manually curated classification resource describing structure–function relationships for functionally diverse enzyme superfamilies. Members of such superfamilies are diverse in their overall reactions yet share a common ancestor and some conserved active site features associated with conserved functional attributes such as a partial reaction. Thus, despite their different functions, members of these superfamilies ‘look alike’, making them easy to misannotate. To address this complexity and enable rational transfer of functional features to unknowns only for those members for which we have sufficient functional information, we subdivide superfamily members into subgroups using sequence information, and lastly into families, sets of enzymes known to catalyze the same reaction using the same mechanistic strategy. Browsing and searching options in the SFLD provide access to all of these levels. The SFLD offers manually curated as well as automatically classified superfamily sets, both accompanied by search and download options for all hierarchical levels. Additional information includes multiple sequence alignments, tab-separated files of functional and other attributes, and sequence similarity networks. The latter provide a new and intuitively powerful way to visualize functional trends mapped to the context of sequence similarity

A Dynamic View of Domain-Motif Interactions

Many protein-protein interactions are mediated by domain-motif interaction, where a domain in one protein binds a short linear motif in its interacting partner. Such interactions are often involved in key cellular processes, necessitating their tight regulation. A common strategy of the cell to control protein function and interaction is by post-translational modifications of specific residues, especially phosphorylation. Indeed, there are motifs, such as SH2-binding motifs, in which motif phosphorylation is required for the domain-motif interaction. On the contrary, there are other examples where motif phosphorylation prevents the domain-motif interaction. Here we present a large-scale integrative analysis of experimental human data of domain-motif interactions and phosphorylation events, demonstrating an intriguing coupling between the two. We report such coupling for SH3, PDZ, SH2 and WW domains, where residue phosphorylation within or next to the motif is implied to be associated with switching on or off domain binding. For domains that require motif phosphorylation for binding, such as SH2 domains, we found coupled phosphorylation events other than the ones required for domain binding. Furthermore, we show that phosphorylation might function as a double switch, concurrently enabling interaction of the motif with one domain and disabling interaction with another domain. Evolutionary analysis shows that co-evolution of the motif and the proximal residues capable of phosphorylation predominates over other evolutionary scenarios, in which the motif appeared before the potentially phosphorylated residue, or vice versa. Our findings provide strengthening evidence for coupled interaction-regulation units, defined by a domain-binding motif and a phosphorylated residue

Metagenomics and sequence similarity networks expose cryptic sequence space to enable enzyme discovery and enhance engineering strategies

Biotechnology is dependent upon the extraordinary efficiency, specificity, and versatility of enzyme function. Over the last decade, the revolution in sequencing technologies has produced vast amounts of sequence information from diverse biological sources. However, we have few functional details about the majority of this data, and therefore have only harnessed a minute fraction of the repertoire of enzymes and metabolic pathways available in Nature. Strategies to predict and characterize the functions of unexplored sequence space are urgently needed. Here, we present an innovative approach to characterize and classify sequence, structure, and functional diversity of a diverse group of enzymes - the FMN-dependent nitroreductase superfamily. This superfamily is comprised of biotechnologically important enzymes1, yet only a small number of enzymes have been characterized. We undertook a comprehensive analysis, using a unique combination of sequence, structural, functional and phylogenetic characterizations (\u3e24,000 sequences, 54 structures and \u3e10 enzymatic functions) to create the first global view of the nitroreductase superfamily2 – of particular interest for biomedical, bioremediation, and biocatalysis applications. The superfamily was delineated into 22 distinct subgroups, 8 of which have no currently known function. Furthermore, we identified three “hot spots” within the nitroreductase scaffold that form the structural basis for the evolution of function, and revealed the key functional residues that have led to evolutionary adaptation through active site profiling. This information is instrumental to the rational redesign of the nitroreductase scaffold. We applied our new knowledge of the nitroreductase superfamily to screen \u3e7,000 metagenomes from public and private repositories to expose the true diversity of NTR enzymes, this approach resulted in an extensive final dataset of ~1M novel nitroreductases. Prominent and subgroup specific enrichment profiles for distinct metagenomic environments were also revealed by subgroup profiling. To further investigate this newly discovered sequence space, we are performing large scale enzymatic activity profiling (\u3e400 enzymes) to provide functional data on a vast number of novel nitroreductase enzymes, and develop an innovative “nitroreductase toolbox”, with wide-ranging potential for biotechnological applications. Roldan et al., FEMS Microbiol Rev 32, 474–500 (2008). Akiva, Copp et al., submitted