Topological variation in the evolution of new reactions in functionally diverse enzyme superfamilies.
Ontology highlight
ABSTRACT:
SUBMITTER: Meng EC
PROVIDER: S-EPMC3551608 | biostudies-literature | 2011 Jun
REPOSITORIES: biostudies-literature
Publications
Topological variation in the evolution of new reactions in functionally diverse enzyme superfamilies.
Meng Elaine C EC Babbitt Patricia C PC
Current opinion in structural biology 20110401 3
In functionally diverse enzyme superfamilies (SFs), conserved structural and active site features reflect catalytic capabilities 'hard-wired' in each SF architecture. Overlaid on this foundation, evolutionary changes in active site machinery, structural topology and other aspects of structural organization and interactions support the emergence of new reactions, mechanisms, and substrate specificity. This review connects topological with functional variation in each of the haloalkanoic acid deha ...[more]
Similar Datasets
Project description:Superfamily and family analyses provide an effective tool for the functional classification of proteins, but must be automated for use on large datasets. We describe a 'gold standard' set of enzyme superfamilies, clustered according to specific sequence, structure, and functional criteria, for use in the validation of family and superfamily clustering methods. The gold standard set represents four fold classes and differing clustering difficulties, and includes five superfamilies, 91 families, 4,887 sequences and 282 structures.
| S-EPMC1431709 | biostudies-literature
Project description:In order to understand the evolution of enzyme reactions and to gain an overview of biological catalysis we have combined sequence and structural data to generate phylogenetic trees in an analysis of 276 structurally defined enzyme superfamilies, and used these to study how enzyme functions have evolved. We describe in detail the analysis of two superfamilies to illustrate different paradigms of enzyme evolution. Gathering together data from all the superfamilies supports and develops the observation that they have all evolved to act on a diverse set of substrates, whilst the evolution of new chemistry is much less common. Despite that, by bringing together so much data, we can provide a comprehensive overview of the most common and rare types of changes in function. Our analysis demonstrates on a larger scale than previously studied, that modifications in overall chemistry still occur, with all possible changes at the primary level of the Enzyme Commission (E.C.) classification observed to a greater or lesser extent. The phylogenetic trees map out the evolutionary route taken within a superfamily, as well as all the possible changes within a superfamily. This has been used to generate a matrix of observed exchanges from one enzyme function to another, revealing the scale and nature of enzyme evolution and that some types of exchanges between and within E.C. classes are more prevalent than others. Surprisingly a large proportion (71%) of all known enzyme functions are performed by this relatively small set of 276 superfamilies. This reinforces the hypothesis that relatively few ancient enzymatic domain superfamilies were progenitors for most of the chemistry required for life.
| S-EPMC3291543 | biostudies-literature
Project description:Substantial improvements in enzyme activity demand multiple mutations at spatially proximal positions in the active site. Such mutations, however, often exhibit unpredictable epistatic (non-additive) effects on activity. Here we describe FuncLib, an automated method for designing multipoint mutations at enzyme active sites using phylogenetic analysis and Rosetta design calculations. We applied FuncLib to two unrelated enzymes, a phosphotriesterase and an acetyl-CoA synthetase. All designs were active, and most showed activity profiles that significantly differed from the wild-type and from one another. Several dozen designs with only 3-6 active-site mutations exhibited 10- to 4,000-fold higher efficiencies with a range of alternative substrates, including hydrolysis of the toxic organophosphate nerve agents soman and cyclosarin and synthesis of butyryl-CoA. FuncLib is implemented as a web server (http://FuncLib.weizmann.ac.il); it circumvents iterative, high-throughput experimental screens and opens the way to designing highly efficient and diverse catalytic repertoires.
| S-EPMC6193528 | biostudies-literature
Project description:Enzymes, as biological catalysts, form the basis of all forms of life. How these proteins have evolved their functions remains a fundamental question in biology. Over 100 years of detailed biochemistry studies, combined with the large volumes of sequence and protein structural data now available, means that we are able to perform large-scale analyses to address this question. Using a range of computational tools and resources, we have compiled information on all experimentally annotated changes in enzyme function within 379 structurally defined protein domain superfamilies, linking the changes observed in functions during evolution to changes in reaction chemistry. Many superfamilies show changes in function at some level, although one function often dominates one superfamily. We use quantitative measures of changes in reaction chemistry to reveal the various types of chemical changes occurring during evolution and to exemplify these by detailed examples. Additionally, we use structural information of the enzymes active site to examine how different superfamilies have changed their catalytic machinery during evolution. Some superfamilies have changed the reactions they perform without changing catalytic machinery. In others, large changes of enzyme function, in terms of both overall chemistry and substrate specificity, have been brought about by significant changes in catalytic machinery. Interestingly, in some superfamilies, relatives perform similar functions but with different catalytic machineries. This analysis highlights characteristics of functional evolution across a wide range of superfamilies, providing insights that will be useful in predicting the function of uncharacterised sequences and the design of new synthetic enzymes.
| S-EPMC4751976 | biostudies-literature
Project description:Holins are small "hole-forming" transmembrane proteins that mediate bacterial cell lysis during programmed cell death or following phage infection. We have identified fifty two families of established or putative holins and have included representative members of these proteins in the Transporter Classification Database (TCDB; www.tcdb.org). We have identified the organismal sources of members of these families, calculated their average protein sizes, estimated their topologies and determined their relative family sizes. Topological analyses suggest that these proteins can have 1, 2, 3 or 4 transmembrane ?-helical segments (TMSs), and members of a single family are frequently, but not always, of a single topology. In one case, proteins of a family proved to have either 2 or 4 TMSs, and the latter arose by intragenic duplication of a primordial 2 TMS protein-encoding gene resembling the former. Using established statistical approaches, some of these families have been shown to be related by common descent. Seven superfamilies, including 21 of the 52 recognized families were identified. Conserved motif and Pfam analyses confirmed most superfamily assignments. These results serve to expand upon the scope of channel-forming bacterial holins.
| S-EPMC3788059 | biostudies-literature
Project description:The lack of label-free high-throughput screening technologies presents a major bottleneck in the identification of active and selective biocatalysts, with the number of variants often exceeding the capacity of traditional analytical platforms to assess their activity in a practical time scale. Here, we show the application of direct infusion of biotransformations to the mass spectrometer (DiBT-MS) screening to a variety of enzymes, in different formats, achieving sample throughputs equivalent to ∼40 s per sample. The heat map output allows rapid selection of active enzymes within 96-well plates facilitating identification of industrially relevant biocatalysts. This DiBT-MS screening workflow has been applied to the directed evolution of a phenylalanine ammonia lyase (PAL) as a case study, enhancing its activity toward electron-rich cinnamic acid derivatives which are relevant to lignocellulosic biomass degradation. Additional benefits of the screening platform include the discovery of biocatalysts (kinases, imine reductases) with novel activities and the incorporation of ion mobility technology for the identification of product hits with increased confidence.
| S-EPMC8154213 | biostudies-literature
Project description:Four heme peroxidase superfamilies (peroxidase-catalase, peroxidase-cyclooxygenase, peroxidase-chlorite dismutase and peroxidase-peroxygenase superfamily) arose independently during evolution, which differ in overall fold, active site architecture and enzymatic activities. The redox cofactor is heme b or posttranslationally modified heme that is ligated by either histidine or cysteine. Heme peroxidases are found in all kingdoms of life and typically catalyze the one- and two-electron oxidation of a myriad of organic and inorganic substrates. In addition to this peroxidatic activity distinct (sub)families show pronounced catalase, cyclooxygenase, chlorite dismutase or peroxygenase activities. Here we describe the phylogeny of these four superfamilies and present the most important sequence signatures and active site architectures. The classification of families is described as well as important turning points in evolution. We show that at least three heme peroxidase superfamilies have ancient prokaryotic roots with several alternative ways of divergent evolution. In later evolutionary steps, they almost always produced highly evolved and specialized clades of peroxidases in eukaryotic kingdoms with a significant portion of such genes involved in coding various fusion proteins with novel physiological functions.
| S-EPMC4420034 | biostudies-literature
Project description:Although human bitter taste perception is hypothesized to be a dietary adaptation, little is known about genetic signatures of selection and patterns of bitter taste perception variability in ethnically diverse populations with different diets, particularly from Africa. To better understand the genetic basis and evolutionary history of bitter taste sensitivity, we sequenced a 2,975 bp region encompassing TAS2R38, a bitter taste receptor gene, in 611 Africans from 57 populations in West Central and East Africa with diverse subsistence patterns, as well as in a comparative sample of 132 non-Africans. We also examined the association between genetic variability at this locus and threshold levels of phenylthiocarbamide (PTC) bitterness in 463 Africans from the above populations to determine how variation influences bitter taste perception. Here, we report striking patterns of variation at TAS2R38, including a significant excess of novel rare nonsynonymous polymorphisms that recently arose only in Africa, high frequencies of haplotypes in Africa associated with intermediate bitter taste sensitivity, a remarkably similar frequency of common haplotypes across genetically and culturally distinct Africans, and an ancient coalescence time of common variation in global populations. Additionally, several of the rare nonsynonymous substitutions significantly modified levels of PTC bitter taste sensitivity in diverse Africans. While ancient balancing selection likely maintained common haplotype variation across global populations, we suggest that recent selection pressures may have also resulted in the unusually high level of rare nonsynonymous variants in Africa, implying a complex model of selection at the TAS2R38 locus in African populations. Furthermore, the distribution of common haplotypes in Africa is not correlated with diet, raising the possibility that common variation may be under selection due to their role in nondietary biological processes. In addition, our data indicate that novel rare mutations contribute to the phenotypic variance of PTC sensitivity, illustrating the influence of rare variation on a common trait, as well as the relatively recent evolution of functionally diverse alleles at this locus.
| S-EPMC3341826 | biostudies-other
Project description:The evolution of enzymes affects how well a species can adapt to new environmental conditions. During enzyme evolution, certain aspects of molecular function are conserved while other aspects can vary. Aspects of function that are more difficult to change or that need to be reused in multiple contexts are often conserved, while those that vary may indicate functions that are more easily changed or that are no longer required. In analogy to the study of conservation patterns in enzyme sequences and structures, we have examined the patterns of conservation and variation in enzyme function by analyzing graph isomorphisms among enzyme substrates of a large number of enzyme superfamilies. This systematic analysis of substrate substructures establishes the conservation patterns that typify individual superfamilies. Specifically, we determined the chemical substructures that are conserved among all known substrates of a superfamily and the substructures that are reacting in these substrates and then examined the relationship between the two. Across the 42 superfamilies that were analyzed, substantial variation was found in how much of the conserved substructure is reacting, suggesting that superfamilies may not be easily grouped into discrete and separable categories. Instead, our results suggest that many superfamilies may need to be treated individually for analyses of evolution, function prediction, and guiding enzyme engineering strategies. Annotating superfamilies with these conserved and reacting substructure patterns provides information that is orthogonal to information provided by studies of conservation in superfamily sequences and structures, thereby improving the precision with which we can predict the functions of enzymes of unknown function and direct studies in enzyme engineering. Because the method is automated, it is suitable for large-scale characterization and comparison of fundamental functional capabilities of both characterized and uncharacterized enzyme superfamilies.
| S-EPMC2453236 | biostudies-literature
Project description:The dramatic increase in heterogeneous types of biological data--in particular, the abundance of new protein sequences--requires fast and user-friendly methods for organizing this information in a way that enables functional inference. The most widely used strategy to link sequence or structure to function, homology-based function prediction, relies on the fundamental assumption that sequence or structural similarity implies functional similarity. New tools that extend this approach are still urgently needed to associate sequence data with biological information in ways that accommodate the real complexity of the problem, while being accessible to experimental as well as computational biologists. To address this, we have examined the application of sequence similarity networks for visualizing functional trends across protein superfamilies from the context of sequence similarity. Using three large groups of homologous proteins of varying types of structural and functional diversity--GPCRs and kinases from humans, and the crotonase superfamily of enzymes--we show that overlaying networks with orthogonal information is a powerful approach for observing functional themes and revealing outliers. In comparison to other primary methods, networks provide both a good representation of group-wise sequence similarity relationships and a strong visual and quantitative correlation with phylogenetic trees, while enabling analysis and visualization of much larger sets of sequences than trees or multiple sequence alignments can easily accommodate. We also define important limitations and caveats in the application of these networks. As a broadly accessible and effective tool for the exploration of protein superfamilies, sequence similarity networks show great potential for generating testable hypotheses about protein structure-function relationships.
| S-EPMC2631154 | biostudies-literature