Catalysing new reactions during evolution: economy of residues and mechanism

High-throughput selection of (new) enzymes: phage display-mediated isolation of alkyl halide hydrolases from a library of active-site mutated epoxide hydrolases

Epoxide hydrolase StEH1, from potato, is similar in overall structural fold and catalytic mechanism to haloalkane dehalogenase DhlA from Xanthobacter autotrophicus. StEH1 displays low (promiscuous) hydrolytic activity with (2-chloro)- and (2-bromo)ethanebenzene producing 2-phenylethanol. To investigate possibilities to amplify these very low dehalogenase activities, StEH1 was subjected to targeted randomized mutagenesis at five active-site amino acid residues and the resulting protein library was challenged for reactivity towards a bait chloride substrate. Enzymes catalyzing the first half-reaction of a hydrolytic cycle were isolated following monovalent phage display of the mutated proteins. Several StEH1 derived enzymes were identified with enhanced dehalogenase activities.

Enzyme function and evolution through the lens of bioinformatics

Enzymes have been shaped by evolution over billions of years to catalyse the chemical reactions that support life on earth. Dispersed in the literature, or organised in online databases, knowledge about enzymes can be structured in distinct dimensions, either related to their quality as biological macromolecules, such as their sequence and structure, or related to their chemical functions, such as the catalytic site, kinetics, mechanism, and overall reaction. The evolution of enzymes can only be understood when each of these dimensions is considered. In addition, many of the properties of enzymes only make sense in the light of evolution. We start this review by outlining the main paradigms of enzyme evolution, including gene duplication and divergence, convergent evolution, and evolution by recombination of domains. In the second part, we overview the current collective knowledge about enzymes, as organised by different types of data and collected in several databases. We also highlight some increasingly powerful computational tools that can be used to close gaps in understanding, in particular for types of data that require laborious experimental protocols. We believe that recent advances in protein structure prediction will be a powerful catalyst for the prediction of binding, mechanism, and ultimately, chemical reactions. A comprehensive mapping of enzyme function and evolution may be attainable in the near future.

The 3D Modules of Enzyme Catalysis: Deconstructing Active Sites into Distinct Functional Entities

Enzyme catalysis is governed by a limited toolkit of residues and organic or inorganic co-factors. Therefore, it is expected that recurring residue arrangements will be found across the enzyme space, which perform a defined catalytic function, are structurally similar and occur in unrelated enzymes. Leveraging the integrated information in the Mechanism and Catalytic Site Atlas (M-CSA) (enzyme structure, sequence, catalytic residue annotations, catalysed reaction, detailed mechanism description), 3D templates were derived to represent compact groups of catalytic residues. A fuzzy template-template search, allowed us to identify those recurring motifs, which are conserved or convergent, that we define as the "modules of enzyme catalysis". We show that a large fraction of these modules facilitate binding of metal ions, co-factors and substrates, and are frequently the result of convergent evolution. A smaller number of convergent modules perform a well-defined catalytic role, such as the variants of the catalytic triad (i.e. Ser-His-Asp/Cys-His-Asp) and the saccharide-cleaving Asp/Glu triad. It is also shown that enzymes whose functions have diverged during evolution preserve regions of their active site unaltered, as shown by modules performing similar or identical steps of the catalytic mechanism. We have compiled a comprehensive library of catalytic modules, that characterise a broad spectrum of enzymes. These modules can be used as templates in enzyme design and for better understanding catalysis in 3D.

Functional annotation of haloacid dehalogenase superfamily structural genomics proteins

Haloacid dehalogenases (HAD) are members of a large superfamily that includes many Structural Genomics proteins with poorly characterized functionality. This superfamily consists of multiple types of enzymes that can act as sugar phosphatases, haloacid dehalogenases, phosphonoacetaldehyde hydrolases, ATPases, or phosphate monoesterases. Here, we report on predicted functional annotations and experimental testing by direct biochemical assay for Structural Genomics proteins from the HAD superfamily. To characterize the functions of HAD superfamily members, nine representative HAD proteins and 21 structural genomics proteins are analyzed. Using techniques based on computed chemical and electrostatic properties of individual amino acids, the functions of five structural genomics proteins from the HAD superfamily are predicted and validated by biochemical assays. A dehalogenase-like hydrolase, RSc1362 (Uniprot Q8XZN3, PDB 3UMB) is predicted to be a dehalogenase and dehalogenase activity is confirmed experimentally. Four proteins predicted to be sugar phosphatases are characterized as follows: a sugar phosphatase from Thermophilus volcanium (Uniprot Q978Y6) with trehalose-6-phosphate phosphatase and fructose-6-phosphate phosphatase activity; haloacid dehalogenase-like hydrolase from Bacteroides thetaiotaomicron (Uniprot Q8A2F3; PDB 3NIW) with fructose-6-phosphate phosphatase and sucrose-6-phosphate phosphatase activity; putative phosphatase from Eubacterium rectale (Uniprot D0VWU2; PDB 3DAO) as a sucrose-6-phosphate phosphatase; and hypothetical protein from Geobacillus kaustophilus (Uniprot Q5L139; PDB 2PQ0) as a fructose-6-phosphate phosphatase. Most of these sugar phosphatases showed some substrate promiscuity.

EzMechanism: an automated tool to propose catalytic mechanisms of enzyme reactions

Over the years, hundreds of enzyme reaction mechanisms have been studied using experimental and simulation methods. This rich literature on biological catalysis is now ripe for use as the foundation of new knowledge-based approaches to investigate enzyme mechanisms. Here, we present a tool able to automatically infer mechanistic paths for a given three-dimensional active site and enzyme reaction, based on a set of catalytic rules compiled from the Mechanism and Catalytic Site Atlas, a database of enzyme mechanisms. EzMechanism (pronounced as 'Easy' Mechanism) is available to everyone through a web user interface. When studying a mechanism, EzMechanism facilitates and improves the generation of hypotheses, by making sure that relevant information is considered, as derived from the literature on both related and unrelated enzymes. We validated EzMechanism on a set of 62 enzymes and have identified paths for further improvement, including the need for additional and more generic catalytic rules.

Cysteine Enrichment Mediates Co-Option of Uricase in Reptilian Skin and Transition to Uricotelism

Uric acid is the main means of nitrogen excretion in uricotelic vertebrates (birds and reptiles) and the end product of purine catabolism in humans and a few other mammals. While uricase is inactivated in mammals unable to degrade urate, the presence of orthologous genes without inactivating mutations in avian and reptilian genomes is unexplained. Here we show that the Gallus gallus gene we name cysteine-rich urate oxidase (CRUOX) encodes a functional protein representing a unique case of cysteine enrichment in the evolution of vertebrate orthologous genes. CRUOX retains the ability to catalyze urate oxidation to hydrogen peroxide and 5-hydroxyisourate (HIU), albeit with a 100-fold reduced efficiency. However, differently from all uricases hitherto characterized, it can also facilitate urate regeneration from HIU, a catalytic property that we propose depends on its enrichment in cysteine residues. X-ray structural analysis highlights differences in the active site compared to known orthologs and suggests a mechanism for cysteine-mediated self-aggregation under H2O2-oxidative conditions. Cysteine enrichment was concurrent with the transition to uricotelism and a shift in gene expression from the liver to the skin where CRUOX is co-expressed with β-keratins. Therefore, the loss of urate degradation in amniotes has followed opposite evolutionary trajectories: while uricase has been eliminated by pseudogenization in some mammals, it has been repurposed as a redox-sensitive enzyme in the reptilian skin.

In silico engineering a CD80 variant with increased affinity to CTLA-4 and decreased affinity to CD28 for optimized cancer immunotherapy

CD80 or cluster of differentiation 80, also known as B7-1, is a member of the immunoglobulin super family, which binds to CTLA-4 and CD28 T cell receptors and induces inhibitory and inductive signals respectively. Although CTLA-4 and CD28 receptors belong to the same protein family, slight differences in their structures leads to CD80 having a higher binding affinity to CTLA-4 (-14.55 kcal/mol) compared with CD28(-12.51 kcal/mol). In this study, we constructed a variant of CD80 protein with increased binding affinity to CTLA-4 and decreased binding affinity to CD28. This variant has no signaling capability, and can act as a cap for these receptors to protect them from natural CD80 proteins existing in the body. The first step was the evolutionary and alanine scanning analysis of CD80 protein to determine conserved regions in this protein. Next, complex alanine scanning technique was employed to determine CD80 protein hotspots in CD80-CTLA-4 and CD80-CD28 protein complexes. This information was fed into a computational model developed in R for in silico mutagenesis and CD80 variant library construction. The 3D structures of variants were modeled using the Swiss model webserver. After modeling the 3D structures, HADDOCK server was employed to build all protein-protein complexes, which contain CTLA-4-CD80 variant complexes, Wild type CD80-CD28 complexes and CD28-CD80 variant complexes. Protein-protein binding free energy was determined using FoldX and the variant number 316 with mutations at 29, 31, 33 positions showed increased binding affinity to CTLA-4 (-21.43 kcal/mol) and decreased binding affinity to CD28 (- 9.54 kcal/mol). Finally, molecular dynamics (MD) simulations confirmed the stability of variant 316. In conclusion, we designed a new CD80 protein variant with potential immunotherapeutic applications.

Using mechanism similarity to understand enzyme evolution

Enzyme reactions take place in the active site through a series of catalytic steps, which are collectively termed the enzyme mechanism. The catalytic step is thereby the individual unit to consider for the purposes of building new enzyme mechanisms - i.e. through the mix and match of individual catalytic steps, new enzyme mechanisms and reactions can be conceived. In the case of natural evolution, it has been shown that new enzyme functions have emerged through the tweaking of existing mechanisms by the addition, removal, or modification of some catalytic steps, while maintaining other steps of the mechanism intact. Recently, we have extracted and codified the information on the catalytic steps of hundreds of enzymes in a machine-readable way, with the aim of automating this kind of evolutionary analysis. In this paper, we illustrate how these data, which we called the "rules of enzyme catalysis", can be used to identify similar catalytic steps across enzymes that differ in their overall function and/or structural folds. A discussion on a set of three enzymes that share part of their mechanism is used as an exemplar to illustrate how this approach can reveal divergent and convergent evolution of enzymes at the mechanistic level.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12551-022-01022-9.

Capturing the geometry, function, and evolution of enzymes with 3D templates

Structural templates are 3D signatures representing protein functional sites, such as ligand binding cavities, metal coordination motifs, or catalytic sites. Here we explore methods to generate template libraries and algorithms to query structures for conserved 3D motifs. Applications of templates are discussed, as well as some exemplar cases for examining evolutionary links in enzymes. We also introduce the concept of using more than one template per structure to represent flexible sites, as an approach to better understand catalysis through snapshots captured in enzyme structures. Functional annotation from structure is an important topic that has recently resurfaced due to the new more accurate methods of protein structure prediction. Therefore, we anticipate that template‐based functional site detection will be a powerful tool in the task of characterizing a vast number of new protein models.

Conformational variation in enzyme catalysis: A structural study on catalytic residues

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We introduce a pipeline to compare and contrast active sites from homologous enzymes in 3D.

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Comprehensive structural study covering enzymes from a large functional space.

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High heterogeneity in magnitude of active site flexibililty between enzyme families.

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Diffferent catalytic residue types and functions relate to different degrees of flexibility.

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Four paradigms classify enzymes according to the structural behaviour during catalysis.

Conformational variation in catalytic residues can be captured as alternative snapshots in enzyme crystal structures. Addressing the question of whether active site flexibility is an intrinsic and essential property of enzymes for catalysis, we present a comprehensive study on the 3D variation of active sites of 925 enzyme families, using explicit catalytic residue annotations from the Mechanism and Catalytic Site Atlas and structural data from the Protein Data Bank. Through weighted pairwise superposition of the functional atoms of active sites, we captured structural variability at single-residue level and examined the geometrical changes as ligands bind or as mutations occur. We demonstrate that catalytic centres of enzymes can be inherently rigid or flexible to various degrees according to the function they perform, and structural variability most often involves a subset of the catalytic residues, usually those not directly involved in the formation or cleavage of bonds. Moreover, data suggest that 2/3 of active sites are flexible, and in half of those, flexibility is only observed in the side chain. The goal of this work is to characterise our current knowledge of the extent of flexibility at the heart of catalysis and ultimately place our findings in the context of the evolution of catalysis as enzymes evolve new functions and bind different substrates.

The Role of Gene Duplication in the Divergence of Enzyme Function: A Comparative Approach

Gene duplication is a crucial process involved in the appearance of new genes and functions. It is thought to have played a major role in the growth of enzyme families and the expansion of metabolism at the biosphere's dawn and in recent times. Here, we analyzed paralogous enzyme content within each of the seven enzymatic classes for a representative sample of prokaryotes by a comparative approach. We found a high ratio of paralogs for three enzymatic classes: oxidoreductases, isomerases, and translocases, and within each of them, most of the paralogs belong to only a few subclasses. Our results suggest an intricate scenario for the evolution of prokaryotic enzymes, involving different fates for duplicated enzymes fixed in the genome, where around 20-40% of prokaryotic enzymes have paralogs. Intracellular organisms have a lesser ratio of duplicated enzymes, whereas free-living enzymes show the highest ratios. We also found that phylogenetically close phyla and some unrelated but with the same lifestyle share similar genomic and biochemical traits, which ultimately support the idea that gene duplication is associated with environmental adaptation.

Analyses of displacements resulting from a point mutation in proteins

The effects of a single residue substitution on the protein backbone are frequently quite small and there are many other potential sources of structural variation for protein. We present here a methodology considering different sources of distortions in order to isolate the very effect of the mutation. To validate our methodology, we consider a well-studied family with many single mutants: the human lysozyme. Most of the perturbations are expected to be at the very localisation of the mutation, but in many cases the effects are propagated at long range. We show that the distances between the mutated residue and the 5% most disturbed residues exponentially decreases. One third of the affected residues are in direct contact with the mutated position; the remaining two thirds are potential allosteric effects. We confirm the reliability of the residues identified as significantly perturbed by comparing our results to experimental studies. We confirm with the present method all the previously identified perturbations. This study shows that mutations have long-range impact on protein backbone that can be detected, although the displacement of the affected atoms is small.

The Evolution, Gene Expression Profile, and Secretion of Digestive Peptidases in Lepidoptera Species

Serine peptidases (SPs) are responsible for most primary protein digestion in Lepidoptera species. An expansion of the number of genes encoding trypsin and chymotrypsin enzymes and the ability to upregulate the expression of some of these genes in response to peptidase inhibitor (PI) ingestion have been associated with the adaptation of Noctuidae moths to herbivory. To investigate whether these gene family expansion events are common to other Lepidoptera groups, we searched for all genes encoding putative trypsin and chymotrypsin enzymes in 23 publicly available genomes from this taxon. Phylogenetic analysis showed that several gene family expansion events may have occurred in the taxon’s evolutionary history and that these events gave rise to a very diverse group of enzymes, including proteins lacking the canonical SP catalytic triad. The expression profile of these enzymes along the midgut and the secretion mechanisms by which these enzymes enter the luminal content were also analyzed in Spodoptera frugiperda larvae using RNA-seq and proteomics. These results support the proposal of a midgut countercurrent flux responsible for the direction of these proteins to the anterior portion of the midgut and show that these enzymes reach the midgut lumen via both exocytosis and microapocrine secretion mechanisms.

Structural Dynamics Behind Clinical Mutants of PncA-Asp12Ala, Pro54Leu, and His57Pro of Mycobacterium tuberculosis Associated With Pyrazinamide Resistance

Pyrazinamide (PZA) is one of the main FDA approved drugs to be used as the first line of defense against Mycobacterium Tuberculosis (MTB). It is activated into pyrazinoic acid (POA) via MTB's pncA gene-encoded pyrazinamidase (PZase). Mutations are most commonly responsible for PZA-resistance in nearly 70% of the resistant samples. In the present work, MTB positive samples were chosen for PZA drug susceptibility testing (DST) against critical concentration (100 ug/ml) of PZA. The resistant samples were subjected to pncA sequencing. As a result, 36 various mutations have been observed in the PZA resistant samples, uploaded to the NCBI (GeneBank accession no. MH461111). Here we report the mechanism of PZA resistance behind the three mutants (MTs), Asp12Ala, Pro54Leu, and His57Pro in comparison with the wild type (WT) through molecular dynamics simulation to unveil how these mutations affect the overall conformational stability. The post-simulation analyses revealed notable deviations as compared to the WT structure. Molecular docking studies of PZA with MTs and WT, pocket volume inspection and overall shape complementarity analysis confirmed the deleterious nature of these mutations and gave an insight into the mechanism behind PZA-resistance. These analyses provide vital information regarding MTB drug resistance and could be extremely useful in therapy management and overcoming its global burden.

A global analysis of function and conservation of catalytic residues in enzymes

The catalytic residues of an enzyme comprise the amino acids located in the active center responsible for accelerating the enzyme-catalyzed reaction. These residues lower the activation energy of reactions by performing several catalytic functions. Decades of enzymology research has established general themes regarding the roles of specific residues in these catalytic reactions, but it has been more difficult to explore these roles in a more systematic way. Here, we review the data on the catalytic residues of 648 enzymes, as annotated in the Mechanism and Catalytic Site Atlas (M-CSA), and compare our results with those in previous studies. We structured this analysis around three key properties of the catalytic residues: amino acid type, catalytic function, and sequence conservation in homologous proteins. As expected, we observed that catalysis is mostly accomplished by a small set of residues performing a limited number of catalytic functions. Catalytic residues are typically highly conserved, but to a smaller degree in homologues that perform different reactions or are nonenzymes (pseudoenzymes). Cross-analysis yielded further insights revealing which residues perform particular functions and how often. We obtained more detailed specificity rules for certain functions by identifying the chemical group upon which the residue acts. Finally, we show the mutation tolerance of the catalytic residues based on their roles. The characterization of the catalytic residues, their functions, and conservation, as presented here, is key to understanding the impact of mutations in evolution, disease, and enzyme design. The tools developed for this analysis are available at the M-CSA website and allow for user specific analysis of the same data.

Structural and free energy landscape of novel mutations in ribosomal protein S1 (rpsA) associated with pyrazinamide resistance

Resistance to key first-line drugs is a major hurdle to achieve the global end tuberculosis (TB) targets. A prodrug, pyrazinamide (PZA) is the only drug, effective in latent TB, recommended in drug resistance and susceptible Mycobacterium tuberculosis (MTB) isolates. The prodrug conversion into active form, pyrazinoic acid (POA), required the activity of pncA gene encoded pyrazinamidase (PZase). Although pncA mutations have been commonly associated with PZA resistance but a small number of resistance cases have been associated with mutationss in RpsA protein. Here in this study a total of 69 PZA resistance isolates have been sequenced for pncA mutations. However, samples that were found PZA resistant but pncA wild type (pncAWT), have been sequenced for rpsA and panD genes mutation. We repeated a drug susceptibility testing according to the WHO guidelines on 18 pncAWT MTB isolates. The rpsA and panD genes were sequenced. Out of total 69 PZA resistant isolates, 51 harbored 36 mutations in pncA gene (GeneBank Accession No. MH46111) while, fifteen different mutations including seven novel, were detected in the fourth S1 domain of RpsA known as C-terminal (MtRpsACTD) end. We did not detect any mutations in panD gene. Among the rpsA mutations, we investigated the molecular mechanism of resistance behind mutations, D342N, D343N, A344P, and I351F, present in the MtRpsACTD through molecular dynamic simulations (MD). WT showed a good drug binding affinity as compared to mutants (MTs), D342N, D343N, A344P, and I351F. Binding pocket volume, stability, and fluctuations have been altered whereas the total energy, protein folding, and geometric shape analysis further explored a significant variation between WT and MTs. In conclusion, mutations in MtRpsACTD might be involved to alter the RpsA activity, resulting in drug resistance. Such molecular mechanism behind resistance may provide a better insight into the resistance mechanism to achieve the global TB control targets.

To what extent do structural changes in catalytic metal sites affect enzyme function?

About half of known enzymatic reactions involve metals. Enzymes belonging to the same superfamily often evolve to catalyze different reactions on the same structural scaffold. The work presented here investigates how functional differentiation, within superfamilies that contain metalloenzymes, relates to structural changes at the catalytic metal site. In general, when the catalytic metal site is unchanged across the enzymes of a superfamily, the functional differentiation within the superfamily tends to be low and the mechanism conserved. Conversely, all types of structural changes in the metal binding site are observed for superfamilies with high functional differentiation. Overall, the catalytic role of the metal ions appears to be one of the most conserved features of the enzyme mechanism within metalloenzyme superfamilies. In particular, when the catalytic role of the metal ion does not involve a redox reaction (i.e. there is no exchange of electrons with the substrate), this role is almost always maintained even when the site undergoes significant structural changes. In these enzymes, functional diversification is most often associated with modifications in the surrounding protein matrix, which has changed so much that the enzyme chemistry is significantly altered. On the other hand, in more than 50% of the examples where the metal has a redox role in catalysis, changes at the metal site modify its catalytic role. Further, we find that there are no examples in our dataset where metal sites with a redox role are lost during evolution.

SYNOPSIS

In this paper we investigate how functional diversity within superfamilies of metalloenzymes relates to structural changes at the catalytic metal site. Evolution tends to strictly conserve the metal site. When changes occur, they do not modify the catalytic role of non-redox metals whereas they affect the role of redox-active metals.

Resolving protein structure-function-binding site relationships from a binding site similarity network perspective

Functional annotation is seldom straightforward with complexities arising due to functional divergence in protein families or functional convergence between non-homologous protein families, leading to mis-annotations. An enzyme may contain multiple domains and not all domains may be involved in a given function, adding to the complexity in function annotation. To address this, we use binding site information from bound cognate ligands and catalytic residues, since it can help in resolving fold-function relationships at a finer level and with higher confidence. A comprehensive database of 2,020 fold-function-binding site relationships has been systematically generated. A network-based approach is employed to capture the complexity in these relationships, from which different types of associations are deciphered, that identify versatile protein folds performing diverse functions, same function associated with multiple folds and one-to-one relationships. Binding site similarity networks integrated with fold, function, and ligand similarity information are generated to understand the depth of these relationships. Apart from the observed continuity in the functional site space, network properties of these revealed versatile families with topologically different or dissimilar binding sites and structural families that perform very similar functions. As a case study, subtle changes in the active site of a set of evolutionarily related superfamilies are studied using these networks. Tracing of such similarities in evolutionarily related proteins provide clues into the transition and evolution of protein functions. Insights from this study will be helpful in accurate and reliable functional annotations of uncharacterized proteins, poly-pharmacology, and designing enzymes with new functional capabilities. Proteins 2017; 85:1319-1335. © 2017 Wiley Periodicals, Inc.

Assessing in silico the recruitment and functional spectrum of bacterial enzymes from secondary metabolism

BACKGROUND

Microbes, plants, and fungi synthesize an enormous number of metabolites exhibiting rich chemical diversity. For a high-level classification, metabolism is subdivided into primary (PM) and secondary (SM) metabolism. SM products are often not essential for survival of the organism and it is generally assumed that SM enzymes stem from PM homologs.

RESULTS

We wanted to assess evolutionary relationships and function of bona fide bacterial PM and SM enzymes. Thus, we analyzed the content of 1010 biosynthetic gene clusters (BGCs) from the MIBiG dataset; the encoded bacterial enzymes served as representatives of SM. The content of 15 bacterial genomes known not to harbor BGCs served as a representation of PM. Enzymes were categorized on their EC number and for these enzyme functions, frequencies were determined. The comparison of PM/SM frequencies indicates a certain preference for hydrolases (EC class 3) and ligases (EC class 6) in PM and of oxidoreductases (EC class 1) and lyases (EC class 4) in SM. Based on BLAST searches, we determined pairs of PM/SM homologs and their functional diversity. Oxidoreductases, transferases (EC class 2), lyases and isomerases (EC class 5) form a tightly interlinked network indicating that many protein folds can accommodate different functions in PM and SM. In contrast, the functional diversity of hydrolases and especially ligases is significantly limited in PM and SM. For the most direct comparison of PM/SM homologs, we restricted for each BGC the search to the content of the genome it comes from. For each homologous hit, the contribution of the genomic neighborhood to metabolic pathways was summarized in BGC-specific html-pages that are interlinked with KEGG; this dataset can be downloaded from https://www.bioinf.ur.de .

CONCLUSIONS

Only few reaction chemistries are overrepresented in bacterial SM and at least 55% of the enzymatic functions present in BGCs possess PM homologs. Many SM enzymes arose in PM and Nature utilized the evolvability of enzymes similarly to establish novel functions both in PM and SM. Future work aimed at the elucidation of evolutionary routes that have interconverted a PM enzyme into an SM homolog can profit from our BGC-specific annotations.

FunTree: advances in a resource for exploring and contextualising protein function evolution

FunTree is a resource that brings together protein sequence, structure and functional information, including overall chemical reaction and mechanistic data, for structurally defined domain superfamilies. Developed in tandem with the CATH database, the original FunTree contained just 276 superfamilies focused on enzymes. Here, we present an update of FunTree that has expanded to include 2340 superfamilies including both enzymes and proteins with non-enzymatic functions annotated by Gene Ontology (GO) terms. This allows the investigation of how novel functions have evolved within a structurally defined superfamily and provides a means to analyse trends across many superfamilies. This is done not only within the context of a protein's sequence and structure but also the relationships of their functions. New measures of functional similarity have been integrated, including for enzymes comparisons of overall reactions based on overall bond changes, reaction centres (the local environment atoms involved in the reaction) and the sub-structure similarities of the metabolites involved in the reaction and for non-enzymes semantic similarities based on the GO. To identify and highlight changes in function through evolution, ancestral character estimations are made and presented. All this is accessible through a new re-designed web interface that can be found at http://www.funtree.info.

Discovery of an essential nucleotidylating activity associated with a newly delineated conserved domain in the RNA polymerase-containing protein of all nidoviruses

RNA viruses encode an RNA-dependent RNA polymerase (RdRp) that catalyzes the synthesis of their RNA(s). In the case of positive-stranded RNA viruses belonging to the order Nidovirales, the RdRp resides in a replicase subunit that is unusually large. Bioinformatics analysis of this non-structural protein has now revealed a nidoviral signature domain (genetic marker) that is N-terminally adjacent to the RdRp and has no apparent homologs elsewhere. Based on its conservation profile, this domain is proposed to have nucleotidylation activity. We used recombinant non-structural protein 9 of the arterivirus equine arteritis virus (EAV) and different biochemical assays, including irreversible labeling with a GTP analog followed by a proteomics analysis, to demonstrate the manganese-dependent covalent binding of guanosine and uridine phosphates to a lysine/histidine residue. Most likely this was the invariant lysine of the newly identified domain, named nidovirus RdRp-associated nucleotidyltransferase (NiRAN), whose substitution with alanine severely diminished the described binding. Furthermore, this mutation crippled EAV and prevented the replication of severe acute respiratory syndrome coronavirus (SARS-CoV) in cell culture, indicating that NiRAN is essential for nidoviruses. Potential functions supported by NiRAN may include nucleic acid ligation, mRNA capping and protein-primed RNA synthesis, possibilities that remain to be explored in future studies.

De-DUFing the DUFs: Deciphering distant evolutionary relationships of Domains of Unknown Function using sensitive homology detection methods

Background

In the post-genomic era where sequences are being determined at a rapid rate, we are highly reliant on computational methods for their tentative biochemical characterization. The Pfam database currently contains 3,786 families corresponding to “Domains of Unknown Function” (DUF) or “Uncharacterized Protein Family” (UPF), of which 3,087 families have no reported three-dimensional structure, constituting almost one-fourth of the known protein families in search for both structure and function.

Results

We applied a ‘computational structural genomics’ approach using five state-of-the-art remote similarity detection methods to detect the relationship between uncharacterized DUFs and domain families of known structures. The association with a structural domain family could serve as a start point in elucidating the function of a DUF. Amongst these five methods, searches in SCOP-NrichD database have been applied for the first time. Predictions were classified into high, medium and low- confidence based on the consensus of results from various approaches and also annotated with enzyme and Gene ontology terms. 614 uncharacterized DUFs could be associated with a known structural domain, of which high confidence predictions, involving at least four methods, were made for 54 families. These structure-function relationships for the 614 DUF families can be accessed on-line at http://proline.biochem.iisc.ernet.in/RHD_DUFS/. For potential enzymes in this set, we assessed their compatibility with the associated fold and performed detailed structural and functional annotation by examining alignments and extent of conservation of functional residues. Detailed discussion is provided for interesting assignments for DUF3050, DUF1636, DUF1572, DUF2092 and DUF659.

Conclusions

This study provides insights into the structure and potential function for nearly 20 % of the DUFs. Use of different computational approaches enables us to reliably recognize distant relationships, especially when they converge to a common assignment because the methods are often complementary. We observe that while pointers to the structural domain can offer the right clues to the function of a protein, recognition of its precise functional role is still ‘non-trivial’ with many DUF domains conserving only some of the critical residues. It is not clear whether these are functional vestiges or instances involving alternate substrates and interacting partners.

Reviewers

This article was reviewed by Drs Eugene Koonin, Frank Eisenhaber and Srikrishna Subramanian.

Electronic supplementary material

The online version of this article (doi:10.1186/s13062-015-0069-2) contains supplementary material, which is available to authorized users.

The nature of chemical innovation: new enzymes by evolution

I describe how we direct the evolution of non-natural enzyme activities, using chemical intuition and information on structure and mechanism to guide us to the most promising reaction/enzyme systems. With synthetic reagents to generate new reactive intermediates and just a few amino acid substitutions to tune the active site, a cytochrome P450 can catalyze a variety of carbene and nitrene transfer reactions. The cyclopropanation, N–H insertion, C–H amination, sulfimidation, and aziridination reactions now demonstrated are all well known in chemical catalysis but have no counterparts in nature. The new enzymes are fully genetically encoded, assemble and function inside of cells, and can be optimized for different substrates, activities, and selectivities. We are learning how to use nature's innovation mechanisms to marry some of the synthetic chemists’ favorite transformations with the exquisite selectivity and tunability of enzymes.

The Classification and Evolution of Enzyme Function

Enzymes are the proteins responsible for the catalysis of life. Enzymes sharing a common ancestor as defined by sequence and structure similarity are grouped into families and superfamilies. The molecular function of enzymes is defined as their ability to catalyze biochemical reactions; it is manually classified by the Enzyme Commission and robust approaches to quantitatively compare catalytic reactions are just beginning to appear. Here, we present an overview of studies at the interface of the evolution and function of enzymes.

Nonenzymatic Reactions above Phospholipid Surfaces of Biological Membranes: Reactivity of Phospholipids and Their Oxidation Derivatives

Phospholipids play multiple and essential roles in cells, as components of biological membranes. Although phospholipid bilayers provide the supporting matrix and surface for many enzymatic reactions, their inherent reactivity and possible catalytic role have not been highlighted. As other biomolecules, phospholipids are frequent targets of nonenzymatic modifications by reactive substances including oxidants and glycating agents which conduct to the formation of advanced lipoxidation end products (ALEs) and advanced glycation end products (AGEs). There are some theoretical studies about the mechanisms of reactions related to these processes on phosphatidylethanolamine surfaces, which hypothesize that cell membrane phospholipids surface environment could enhance some reactions through a catalyst effect. On the other hand, the phospholipid bilayers are susceptible to oxidative damage by oxidant agents as reactive oxygen species (ROS). Molecular dynamics simulations performed on phospholipid bilayers models, which include modified phospholipids by these reactions and subsequent reactions that conduct to formation of ALEs and AGEs, have revealed changes in the molecular interactions and biophysical properties of these bilayers as consequence of these reactions. Then, more studies are desirable which could correlate the biophysics of modified phospholipids with metabolism in processes such as aging and diseases such as diabetes, atherosclerosis, and Alzheimer's disease.

Plasmodium falciparum SERA5 plays a non-enzymatic role in the malarial asexual blood-stage lifecycle

The malaria parasite Plasmodium falciparum replicates in an intraerythrocytic parasitophorous vacuole (PV). The most abundant P. falciparum PV protein, called SERA5, is essential in blood stages and possesses a papain-like domain, prompting speculation that it functions as a proteolytic enzyme. Unusually however, SERA5 possesses a Ser residue (Ser596) at the position of the canonical catalytic Cys of papain-like proteases, and the function of SERA5 or whether it performs an enzymatic role is unknown. In this study, we failed to detect proteolytic activity associated with the Ser596-containing parasite-derived or recombinant protein. However, substitution of Ser596 with a Cys residue produced an active recombinant enzyme with characteristics of a cysteine protease, demonstrating that SERA5 can bind peptides. Using targeted homologous recombination in P. falciparum, we substituted Ser596 with Ala with no phenotypic consequences, proving that SERA5 does not perform an essential enzymatic role in the parasite. We could also replace an internal segment of SERA5 with an affinity-purification tag. In contrast, using almost identical targeting constructs, we could not truncate or C-terminally tag the SERA5 gene, or replace Ser596 with a bulky Arg residue. Our findings show that SERA5 plays an indispensable but non-enzymatic role in the P. falciparum blood-stage life cycle.

Synthetic biology for the directed evolution of protein biocatalysts: navigating sequence space intelligently

The amino acid sequence of a protein affects both its structure and its function. Thus, the ability to modify the sequence, and hence the structure and activity, of individual proteins in a systematic way, opens up many opportunities, both scientifically and (as we focus on here) for exploitation in biocatalysis. Modern methods of synthetic biology, whereby increasingly large sequences of DNA can be synthesised de novo, allow an unprecedented ability to engineer proteins with novel functions. However, the number of possible proteins is far too large to test individually, so we need means for navigating the 'search space' of possible protein sequences efficiently and reliably in order to find desirable activities and other properties. Enzymologists distinguish binding (Kd) and catalytic (kcat) steps. In a similar way, judicious strategies have blended design (for binding, specificity and active site modelling) with the more empirical methods of classical directed evolution (DE) for improving kcat (where natural evolution rarely seeks the highest values), especially with regard to residues distant from the active site and where the functional linkages underpinning enzyme dynamics are both unknown and hard to predict. Epistasis (where the 'best' amino acid at one site depends on that or those at others) is a notable feature of directed evolution. The aim of this review is to highlight some of the approaches that are being developed to allow us to use directed evolution to improve enzyme properties, often dramatically. We note that directed evolution differs in a number of ways from natural evolution, including in particular the available mechanisms and the likely selection pressures. Thus, we stress the opportunities afforded by techniques that enable one to map sequence to (structure and) activity in silico, as an effective means of modelling and exploring protein landscapes. Because known landscapes may be assessed and reasoned about as a whole, simultaneously, this offers opportunities for protein improvement not readily available to natural evolution on rapid timescales. Intelligent landscape navigation, informed by sequence-activity relationships and coupled to the emerging methods of synthetic biology, offers scope for the development of novel biocatalysts that are both highly active and robust.

TM6SF2 and MAC30, new enzyme homologs in sterol metabolism and common metabolic disease

Carriers of the Glu167Lys coding variant in the TM6SF2 gene have recently been identified as being more susceptible to non-alcoholic fatty liver disease (NAFLD), yet exhibit lower levels of circulating lipids and hence are protected against cardiovascular disease. Despite the physiological importance of these observations, the molecular function of TM6SF2 remains unknown, and no sequence similarity with functionally characterized proteins has been identified. In order to trace its evolutionary history and to identify functional domains, we embarked on a computational protein sequence analysis of TM6SF2. We identified a new domain, the EXPERA domain, which is conserved among TM6SF, MAC30/TMEM97 and EBP (D8, D7 sterol isomerase) protein families. EBP mutations are the cause of chondrodysplasia punctata 2 X-linked dominant (CDPX2), also known as Conradi-Hünermann-Happle syndrome, a defective cholesterol biosynthesis disorder. Our analysis of evolutionary conservation among EXPERA domain-containing families and the previously suggested catalytic mechanism for the EBP enzyme, indicate that TM6SF and MAC30/TMEM97 families are both highly likely to possess, as for the EBP family, catalytic activity as sterol isomerases. This unexpected prediction of enzymatic functions for TM6SF and MAC30/TMEM97 is important because it now permits detailed experiments to investigate the function of these key proteins in various human pathologies, from cardiovascular disease to cancer.

The evolution of enzyme function in the isomerases

The advent of computational approaches to measure functional similarity between enzymes adds a new dimension to existing evolutionary studies based on sequence and structure. This paper reviews research efforts aiming to understand the evolution of enzyme function in superfamilies, presenting a novel strategy to provide an overview of the evolution of enzymes belonging to an individual EC class, using the isomerases as an exemplar.

Structure of a sedoheptulose 7-phosphate cyclase: ValA from Streptomyces hygroscopicus

Sedoheptulose 7-phosphate cyclases (SH7PCs) encompass three enzymes involved in producing the core cyclitol structures of pseudoglycosides and similar bioactive natural products. One such enzyme is ValA from Streptomyces hygroscopicus subsp. jinggangensis 5008, which makes 2-epi-5-epi-valiolone as part of the biosynthesis of the agricultural antifungal agent validamycin A. We present, as the first SH7PC structure, the 2.1 Å resolution crystal structure of ValA in complex with NAD⁺ and Zn²⁺ cofactors. ValA has a fold and active site organization resembling those of the sugar phosphate cyclase dehydroquinate synthase (DHQS) and contains two notable, previously unrecognized interactions between NAD⁺ and Asp side chains conserved in all sugar phosphate cyclases that may influence catalysis. Because the domains of ValA adopt a nearly closed conformation even though no sugar substrate is present, comparisons with a ligand-bound DHQS provide a model for aspects of substrate binding. One striking active site difference is a loop that adopts a distinct conformation as a result of an Asp → Asn change with respect to DHQS and alters the identity and orientation of a key Arg residue. This and other active site differences in ValA are mostly localized to areas where the ValA substrate differs from that of DHQS. Sequence comparisons with a second SH7PC making a product with distinct stereochemistry lead us to postulate that the product stereochemistry of a given SH7PC is not the result of events taking place during catalysis but is accomplished by selective binding of either the α or β pyranose anomer of the substrate.

Exploring the biological and chemical complexity of the ligases

Using a novel method to map and cluster chemical reactions, we have re-examined the chemistry of the ligases [Enzyme Commission (EC) Class 6] and their associated protein families in detail. The type of bond formed by the ligase can be automatically extracted from the equation of the reaction, replicating the EC subclass division. However, this subclass division hides considerable complexities, especially for the C-N forming ligases, which fall into at least three distinct types. The lower levels of the EC classification for ligases are somewhat arbitrary in their definition and add little to understanding their chemistry or evolution. By comparing the multi-domain architecture of the enzymes and using sequence similarity networks, we examined the links between overall reaction and evolution of the ligases. These show that, whilst many enzymes that perform the same overall chemistry group together, both convergent (similar function, different ancestral lineage) and divergent (different function, common ancestor) evolution of function are observed. However, a common theme is that a single conserved domain (often the nucleoside triphosphate binding domain) is combined with ancillary domains that provide the variation in substrate binding and function.

Molecular dynamics simulations of barley and maize lipid transfer proteins show different ligand binding preferences in agreement with experimental data

Experimental studies of barley and maize lipid transfer proteins (LTPs) show that the two proteins bind the ligand palmitate in opposite orientations in their internal cavities. Moreover, maize LTP is reported to bind the ligand caprate in the internal cavity in a mixture of two orientations with approximately equal occupancy. Six 30 ns molecular dynamics (MD) simulations of maize and barley LTP with ligands bound in two orientations (modes M and B) have been used to understand the different ligand binding preferences. The simulations show that both maize and barley LTP could bind palmitate in the orientation observed experimentally for maize LTP (mode M), with the predominant interaction being a salt bridge between the ligand carboxylate headgroup and a conserved arginine side chain. However, the simulation of barley LTP with palmitate in the mode B orientation shows the most favorable protein-ligand interaction energy. In contrast, the simulations of maize LTP with palmitate and with caprate in the mode B orientation show no persistent ligand binding, the ligands leaving the cavity during the simulations. Sequence differences between maize and barley LTP in the AB loop region, in residues at the base of the hydrophobic cavity, and in the helix A region are identified as contributing to the different behavior. The simulations reproduce well the experimentally observed binding preferences for palmitate and suggest that the experimental data for maize LTP with caprate reflect ligand mobility in binding mode M rather than the population of binding modes M and B.

Residue mutations and their impact on protein structure and function: detecting beneficial and pathogenic changes

The present review focuses on the evolution of proteins and the impact of amino acid mutations on function from a structural perspective. Proteins evolve under the law of natural selection and undergo alternating periods of conservative evolution and of relatively rapid change. The likelihood of mutations being fixed in the genome depends on various factors, such as the fitness of the phenotype or the position of the residues in the three-dimensional structure. For example, co-evolution of residues located close together in three-dimensional space can occur to preserve global stability. Whereas point mutations can fine-tune the protein function, residue insertions and deletions (‘decorations’ at the structural level) can sometimes modify functional sites and protein interactions more dramatically. We discuss recent developments and tools to identify such episodic mutations, and examine their applications in medical research. Such tools have been tested on simulated data and applied to real data such as viruses or animal sequences. Traditionally, there has been little if any cross-talk between the fields of protein biophysics, protein structure–function and molecular evolution. However, the last several years have seen some exciting developments in combining these approaches to obtain an in-depth understanding of how proteins evolve. For example, a better understanding of how structural constraints affect protein evolution will greatly help us to optimize our models of sequence evolution. The present review explores this new synthesis of perspectives.

Comparing proteins by their internal dynamics: exploring structure-function relationships beyond static structural alignments

The growing interest for comparing protein internal dynamics owes much to the realisation that protein function can be accompanied or assisted by structural fluctuations and conformational changes. Analogously to the case of functional structural elements, those aspects of protein flexibility and dynamics that are functionally oriented should be subject to evolutionary conservation. Accordingly, dynamics-based protein comparisons or alignments could be used to detect protein relationships that are more elusive to sequence and structural alignments. Here we provide an account of the progress that has been made in recent years towards developing and applying general methods for comparing proteins in terms of their internal dynamics and advance the understanding of the structure-function relationship.

Exploring the evolution of novel enzyme functions within structurally defined protein superfamilies

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.

Enzymes, as biological catalysts, are crucial to life. Understanding how enzymes have evolved to perform the wide variety of reactions found across all kingdoms of life is fundamental to a broad range of biological studies, especially those leading to new therapeutics. To unravel the evolution of novel enzyme function requires combining information on protein structure, sequence, phylogeny and chemistry (in terms of interacting small molecules and reaction mechanisms). We have developed a protocol for integrating this wide range of data, which we have applied to a relatively large number of families comprising some very diverse relatives. This has permitted us to present an initial overview of the evolution of novel enzyme functions, in which we observe that some changes in function between relatives are more common than others, with most of the functionality observed in nature confined to relatively few families. Moreover, we are able to identify the evolutionary route taken within a superfamily to change the enzyme function from one reaction to another. This information may help in predicting the function of an enzyme that has yet to be experimentally characterised as well as in designing new enzymes for industrial and medical purposes.

FunTree: a resource for exploring the functional evolution of structurally defined enzyme superfamilies

FunTree is a new resource that brings together sequence, structure, phylogenetic, chemical and mechanistic information for structurally defined enzyme superfamilies. Gathering together this range of data into a single resource allows the investigation of how novel enzyme functions have evolved within a structurally defined superfamily as well as providing a means to analyse trends across many superfamilies. This is done not only within the context of an enzyme's sequence and structure but also the relationships of their reactions. Developed in tandem with the CATH database, it currently comprises 276 superfamilies covering ~1800 (70%) of sequence assigned enzyme reactions. Central to the resource are phylogenetic trees generated from structurally informed multiple sequence alignments using both domain structural alignments supplemented with domain sequences and whole sequence alignments based on commonality of multi-domain architectures. These trees are decorated with functional annotations such as metabolite similarity as well as annotations from manually curated resources such the catalytic site atlas and MACiE for enzyme mechanisms. The resource is freely available through a web interface: www.ebi.ac.uk/thorton-srv/databases/FunTree.

Toward mechanistic classification of enzyme functions

Classification of enzyme function should be quantitative, computationally accessible, and informed by sequences and structures to enable use of genomic information for functional inference and other applications. Large-scale studies have established that divergently evolved enzymes share conserved elements of structure and common mechanistic steps and that convergently evolved enzymes often converge to similar mechanisms too, suggesting that reaction mechanisms could be used to develop finer-grained functional descriptions than provided by the Enzyme Commission (EC) system currently in use. Here we describe how evolution informs these structure-function mappings and review the databases that store mechanisms of enzyme reactions along with recent developments to measure ligand and mechanistic similarities. Together, these provide a foundation for new classifications of enzyme function.

Rhomboid family pseudoproteases use the ER quality control machinery to regulate intercellular signaling

Intramembrane proteolysis governs many cellular control processes, but little is known about how intramembrane proteases are regulated. iRhoms are a conserved subfamily of proteins related to rhomboid intramembrane serine proteases that lack key catalytic residues. We have used a combination of genetics and cell biology to determine that these "pseudoproteases" inhibit rhomboid-dependent signaling by the epidermal growth factor receptor pathway in Drosophila, thereby regulating sleep. iRhoms prevent the cleavage of potential rhomboid substrates by promoting their destabilization by endoplasmic reticulum (ER)-associated degradation; this mechanism has been conserved in mammalian cells. The exploitation of the intrinsic quality control machinery of the ER represents a new mode of regulation of intercellular signaling. Inactive cognates of enzymes are common, but their functions are mostly unclear; our data indicate that pseudoenzymes can readily evolve into regulatory proteins, suggesting that this may be a significant evolutionary mechanism.

Classification of chemical reactions and chemoinformatic processing of enzymatic transformations

The automatic perception of chemical similarities between chemical reactions is required for a variety of applications in chemistry and connected fields, namely with databases of metabolic reactions. Classification of enzymatic reactions is required, e.g., for genome-scale reconstruction (or comparison) of metabolic pathways, computer-aided validation of classification systems, or comparison of enzymatic mechanisms. This chapter presents different current approaches for the representation of chemical reactions enabling automatic reaction classification. Representations based on the encoding of the reaction center are illustrated, which use physicochemical features, Reaction Classification (RC) numbers, or Condensed Reaction Graphs (CRG). Representation of differences between the structures of products and reactants include reaction signatures, fingerprint differences, and the MOLMAP approach. The approaches are illustrated with applications to real datasets.

FACT: functional annotation transfer between proteins with similar feature architectures

Background

The increasing number of sequenced genomes provides the basis for exploring the genetic and functional diversity within the tree of life. Only a tiny fraction of the encoded proteins undergoes a thorough experimental characterization. For the remainder, bioinformatics annotation tools are the only means to infer their function. Exploiting significant sequence similarities to already characterized proteins, commonly taken as evidence for homology, is the prevalent method to deduce functional equivalence. Such methods fail when homologs are too diverged, or when they have assumed a different function. Finally, due to convergent evolution, functional equivalence is not necessarily linked to common ancestry. Therefore complementary approaches are required to identify functional equivalents.

Results

We present the Feature Architecture Comparison Tool http://www.cibiv.at/FACT to search for functionally equivalent proteins. FACT uses the similarity between feature architectures of two proteins, i.e., the arrangements of functional domains, secondary structure elements and compositional properties, as a proxy for their functional equivalence. A scoring function measures feature architecture similarities, which enables searching for functional equivalents in entire proteomes. Our evaluation of 9,570 EC classified enzymes revealed that FACT, using the full feature, set outperformed the existing architecture-based approaches by identifying significantly more functional equivalents as highest scoring proteins. We show that FACT can identify functional equivalents that share no significant sequence similarity. However, when the highest scoring protein of FACT is also the protein with the highest local sequence similarity, it is in 99% of the cases functionally equivalent to the query. We demonstrate the versatility of FACT by identifying a missing link in the yeast glutathione metabolism and also by searching for the human GolgA5 equivalent in Trypanosoma brucei.

Conclusions

FACT facilitates a quick and sensitive search for functionally equivalent proteins in entire proteomes. FACT is complementary to approaches using sequence similarity to identify proteins with the same function. Thus, FACT is particularly useful when functional equivalents need to be identified in evolutionarily distant species, or when functional equivalents are not homologous. The most reliable annotation transfers, however, are achieved when feature architecture similarity and sequence similarity are jointly taken into account.

Mechanisms of protein evolution and their application to protein engineering

Protein engineering holds great promise for the development of new biosensors, diagnostics, therapeutics, and agents for bioremediation. Despite some remarkable successes in experimental and computational protein design, engineered proteins rarely achieve the efficiency or specificity of natural enzymes. Current protein design methods utilize evolutionary concepts, including mutation, recombination, and selection, but the inability to fully recapitulate the success of natural evolution suggests that some evolutionary principles have not been fully exploited. One aspect of protein engineering that has received little attention is how to select the most promising proteins to serve as templates, or scaffolds, for engineering. Two evolutionary concepts that could provide a rational basis for template selection are the conservation of catalytic mechanisms and functional promiscuity. Knowledge of the catalytic motifs responsible for conserved aspects of catalysis in mechanistically diverse superfamilies could be used to identify promising templates for protein engineering. Second, protein evolution often proceeds through promiscuous intermediates, suggesting that templates which are naturally promiscuous for a target reaction could enhance protein engineering strategies. This review explores these ideas and alternative hypotheses concerning protein evolution and engineering. Future research will determine if application of these principles will lead to a protein engineering methodology governed by predictable rules for designing efficient, novel catalysts.

Quantitative comparison of catalytic mechanisms and overall reactions in convergently evolved enzymes: implications for classification of enzyme function

Functionally analogous enzymes are those that catalyze similar reactions on similar substrates but do not share common ancestry, providing a window on the different structural strategies nature has used to evolve required catalysts. Identification and use of this information to improve reaction classification and computational annotation of enzymes newly discovered in the genome projects would benefit from systematic determination of reaction similarities. Here, we quantified similarity in bond changes for overall reactions and catalytic mechanisms for 95 pairs of functionally analogous enzymes (non-homologous enzymes with identical first three numbers of their EC codes) from the MACiE database. Similarity of overall reactions was computed by comparing the sets of bond changes in the transformations from substrates to products. For similarity of mechanisms, sets of bond changes occurring in each mechanistic step were compared; these similarities were then used to guide global and local alignments of mechanistic steps. Using this metric, only 44% of pairs of functionally analogous enzymes in the dataset had significantly similar overall reactions. For these enzymes, convergence to the same mechanism occurred in 33% of cases, with most pairs having at least one identical mechanistic step. Using our metric, overall reaction similarity serves as an upper bound for mechanistic similarity in functional analogs. For example, the four carbon-oxygen lyases acting on phosphates (EC 4.2.3) show neither significant overall reaction similarity nor significant mechanistic similarity. By contrast, the three carboxylic-ester hydrolases (EC 3.1.1) catalyze overall reactions with identical bond changes and have converged to almost identical mechanisms. The large proportion of enzyme pairs that do not show significant overall reaction similarity (56%) suggests that at least for the functionally analogous enzymes studied here, more stringent criteria could be used to refine definitions of EC sub-subclasses for improved discrimination in their classification of enzyme reactions. The results also indicate that mechanistic convergence of reaction steps is widespread, suggesting that quantitative measurement of mechanistic similarity can inform approaches for functional annotation.

Classification of nonenzymatic homologues of protein kinases

Protein Kinase-Like Non-kinases (PKLNKs), which are closely related to protein kinases, lack the crucial catalytic aspartate in the catalytic loop, and hence cannot function as protein kinase, have been analysed. Using various sensitive sequence analysis methods, we have recognized 82 PKLNKs from four higher eukaryotic organisms, namely, Homo sapiens, Mus musculus, Rattus norvegicus, and Drosophila melanogaster. On the basis of their domain combination and function, PKLNKs have been classified mainly into four categories: (1) Ligand binding PKLNKs, (2) PKLNKs with extracellular protein-protein interaction domain, (3) PKLNKs involved in dimerization, and (4) PKLNKs with cytoplasmic protein-protein interaction module. While members of the first two classes of PKLNKs have transmembrane domain tethered to the PKLNK domain, members of the other two classes of PKLNKs are cytoplasmic in nature. The current classification scheme hopes to provide a convenient framework to classify the PKLNKs from other eukaryotes which would be helpful in deciphering their roles in cellular processes.

Molecular modeling and dynamics studies with explicit inclusion of electronic polarizability. Theory and applications

A current emphasis in empirical force fields is on the development of potential functions that explicitly treat electronic polarizability. In the present article, the commonly used methodologies for modelling electronic polarization are presented along with an overview of selected application studies. Models presented include induced point-dipoles, classical Drude oscillators, and fluctuating charge methods. The theoretical background of each method is followed by an introduction to extended Langrangian integrators required for computationally tractable molecular dynamics simulations using polarizable force fields. The remainder of the review focuses on application studies using these methods. Emphasis is placed on water models, for which numerous examples exist, with a more thorough discussion presented on the recently published models associated with the Drude-based CHARMM and the AMOEBA force fields. The utility of polarizable models for the study of ion solvation is then presented followed by an overview of studies of small molecules (e.g. CCl(4), alkanes, etc) and macromolecule (proteins, nucleic acids and lipid bilayers) application studies. The review is written with the goal of providing a general overview of the current status of the field and to facilitate future application and developments.

A novel functional element in the N-terminal region of Arum concinnatum alternative oxidase is indispensable for catalytic activity of the enzyme in HeLa cells

Alternative oxidase (AOX) is a quinol-oxygen oxidoreductase, which is known to possess a dicarboxylate diiron reaction center held in structurally postulated alpha-helical bundle. However, little is known about the structural or functional features of its N-terminal region in any organism, with the exception of a regulatory cysteine residue (CysI) in angiosperm plants. Here, we show that transcripts of two AOX1 isozymes (AcoAOX1a and AcoAOX1b) are coexpressed in thermogenic appendices of Arum concinnatum, while their enzymatic activities seem to be distinct. Namely, AcoAOX1a, an abundantly expressed transcript in vivo, shows an apparent cyanide-insensitive and n-propyl gallate-sensitive respiration during ectopic expression of the protein in HeLa cells, whereas AcoAOX1b exhibits a lower transcript expression, and appears to be totally inactive as AOX at the protein level. Our functional analyses further reveal that an E83K substitution in AcoAOX1b, which is located far upstream of CysI in the N-terminal region, is the cause of this loss of function. These results suggest the presence of a naturally occurring inactive AOX homologue in thermogenic plants. Accordingly, our results further imply that the N-terminal region of the AOX protein functionally contributes to the dynamic activities of respiratory control within the mitochondria.

The evolution of protein domain families

Protein domains are the common currency of protein structure and function. Over 10000 such protein families have now been collected in the Pfam database. Using these data along with animal gene phylogenies from TreeFam allowed us to investigate the gain and loss of protein domains. Most gains and losses of domains occur at protein termini. We show that the nature of changes is similar after speciation or duplication events. However, changes in domain architecture happen at a higher frequency after gene duplication. We suggest that the bias towards protein termini is largely because insertion and deletion of domains at most positions in a protein are likely to disrupt the structure of existing domains. We can also use Pfam to trace the evolution of specific families. For example, the immunoglobulin superfamily can be traced over 500 million years during its expansion into one of the largest families in the human genome. It can be shown that this protein family has its origins in basic animals such as the poriferan sponges where it is found in cell-surface-receptor proteins. We can trace how the structure and sequence of this family diverged during vertebrate evolution into constant and variable domains that are found in the antibodies of our immune system as well as in neural and muscle proteins.

Hydration number, topological control, and ion selectivity

The topological control hypothesis presented by Bostick and Brooks [Proc. Natl. Acad. Sci. U.S.A. 2007, 104, 9260] has sought to explain binding selectivity in potassium channels based on the premise that a universal measure of ion solvation in different environments is provided by its average coordination structure in bulk water. This leads to the view that ion selectivity is predominantly controlled by the number of ligands coordinating the ion and that the chemical type of those ligands plays a minor role. The significance of the topological control hypothesis and its ability to predict ion selectivity in protein binding sites are examined. It is shown that the framework encounters increasing difficulties when different protein binding sites with similar coordination numbers are considered.