Evolution: a guide to perturb protein function and networks

Design and characterization of a protein fold switching network

To better understand how amino acid sequence encodes protein structure, we engineered mutational pathways that connect three common folds (3α, β-grasp, and α/β-plait). The structures of proteins at high sequence-identity intersections in the pathways (nodes) were determined using NMR spectroscopy and analyzed for stability and function. To generate nodes, the amino acid sequence encoding a smaller fold is embedded in the structure of an ~50% larger fold and a new sequence compatible with two sets of native interactions is designed. This generates protein pairs with a 3α or β-grasp fold in the smaller form but an α/β-plait fold in the larger form. Further, embedding smaller antagonistic folds creates critical states in the larger folds such that single amino acid substitutions can switch both their fold and function. The results help explain the underlying ambiguity in the protein folding code and show that new protein structures can evolve via abrupt fold switching.

Odd one out? Functional tuning of Zymomonas mobilis pyruvate kinase is narrower than its allosteric, human counterpart

Various protein properties are often illuminated using sequence comparisons of protein homologs. For example, in analyses of the pyruvate kinase multiple sequence alignment, the set of positions that changed during speciation ("phylogenetic" positions) were enriched for "rheostat" positions in human liver pyruvate kinase (hLPYK). (Rheostat positions are those which, when substituted with various amino acids, yield a range of functional outcomes). However, the correlation was moderate, which could result from multiple biophysical constraints acting on the same position during evolution and/or various sources of noise. To further examine this correlation, we here tested Zymomonas mobilis PYK (ZmPYK), which has <65% sequence identity to any other PYK sequence. Twenty-six ZmPYK positions were selected based on their phylogenetic scores, substituted with multiple amino acids, and assessed for changes in Kapp-PEP . Although we expected to identify multiple, strong rheostat positions, only one moderate rheostat position was detected. Instead, nearly half of the 271 ZmPYK variants were inactive and most others showed near wild-type function. Indeed, for the active ZmPYK variants, the total range of Kapp,PEP values ("tunability") was 40-fold less than that observed for hLPYK variants. The combined functional studies and sequence comparisons suggest that ZmPYK has evolved functional and/or structural attributes that differ from the rest of the family. We hypothesize that including such "orphan" sequences in MSA analyses obscures the correlations used to predict rheostat positions. Finally, results raise the intriguing biophysical question as to how the same protein fold can support rheostat positions in one homolog but not another.

TP53 Mutations in Acute Myeloid Leukemia: Still a Daunting Challenge?

TP53 is a key tumor suppressor gene with protean functions associated with preservation of genomic balance, including regulation of cellular senescence, apoptotic pathways, metabolism functions, and DNA repair. The vast majority of de novo acute myeloid leukemia (AML) present unaltered TP53 alleles. However, TP53 mutations are frequently detected in AML related to an increased genomic instability, such as therapy‐related (t-AML) or AML with myelodysplasia-related changes. Of note, TP53 mutations are associated with complex cytogenetic abnormalities, advanced age, chemoresistance, and poor outcomes. Recent breakthroughs in AML research and the development of targeted drugs directed at specific mutations have led to an explosion of novel treatments with different mechanisms. However, optimal treatment strategy for patients harboring TP53 mutations remains a critical area of unmet need. In this review, we focus on the incidence and clinical significance of TP53 mutations in de novo and t-AML. The influence of these alterations on response and clinical outcomes as well as the current and future therapeutic perspectives for this hardly treatable setting are discussed.

CAGI5: Objective performance assessments of predictions based on the Evolutionary Action equation

Many computational approaches estimate the effect of coding variants, but their predictions often disagree with each other. These contradictions confound users and raise questions regarding reliability. Performance assessments can indicate the expected accuracy for each method and highlight advantages and limitations. The Critical Assessment of Genome Interpretation (CAGI) community aims to organize objective and systematic assessments: They challenge predictors on unpublished experimental and clinical data and assign independent assessors to evaluate the submissions. We participated in CAGI experiments as predictors, using the Evolutionary Action (EA) method to estimate the fitness effect of coding mutations. EA is untrained, uses homology information, and relies on a formal equation: The fitness effect equals the functional sensitivity to residue changes multiplied by the magnitude of the substitution. In previous CAGI experiments (between 2011 and 2016), our submissions aimed to predict the protein activity of single mutants. In 2018 (CAGI5), we also submitted predictions regarding clinical associations, folding stability, and matching genomic data with phenotype. For all these diverse challenges, we used EA to predict the fitness effect of variants, adjusted to specifically address each question. Our submissions had consistently good performance, suggesting that EA predicts reliably the effects of genetic variants.

The tumor suppressor capability of p53 is dependent on non-muscle myosin IIA function in head and neck cancer

Over 300,000 patients develop squamous cell carcinoma of the head and neck (HNSCC) worldwide with 25-30% of patients ultimately dying from their disease. Currently, molecular biomarkers are not used in HNSCC but several genes have been identified including mutant TP53 (mutp53) Our recent work has identified an approach to stratify patients with tumors harboring high or low risk TP53 mutations. Non-muscle Myosin IIA (NMIIA) was recently identified as a tumor suppressor in HNSCC. We now demonstrate that low MYH9 expression is associated with decreased survival in patients with head and neck cancer harboring low-risk mutp53 but not high-risk mutp53. Furthermore, inhibition of NMIIA leads to increased invasion in cells harboring wildtype p53 (wtp53), which was not observed in high-risk mutp53 cells. This increased invasiveness of wtp53 following NMIIA inhibition was associated with reduced p53 target gene expression and was absent in cells expressing mutp53. This reduced expression may be due, in part, to a decrease in nuclear localization of wtp53. These findings suggest that the tumor suppressor capability of wtp53 is dependent upon functional NMIIA and that the invasive phenotype of high-risk mutp53 is independent of NMIIA.

Molecular cloning and biochemical characterization of two cation chloride cotransporter subfamily members of Hydra vulgaris

Cation Chloride Cotransporters (CCCs) comprise secondary active membrane proteins mainly mediating the symport of cations (Na⁺, K⁺) coupled with chloride (Cl⁻). They are divided into K⁺-Cl⁻ outward transporters (KCCs), the Na⁺-K⁺-Cl⁻ (NKCCs) and Na⁺-Cl⁻ (NCCs) inward transporters, the cation chloride cotransporter interacting protein CIP1, and the polyamine transporter CCC9. KCCs and N(K)CCs are established in the genome since eukaryotes and metazoans, respectively. Most of the physiological and functional data were obtained from vertebrate species. To get insights into the basal functional properties of KCCs and N(K)CCs in the metazoan lineage, we cloned and characterized KCC and N(K)CC from the cnidarian Hydra vulgaris. HvKCC is composed of 1,032 amino-acid residues. Functional analyses revealed that hvKCC mediates a Na⁺-independent, Cl⁻ and K⁺ (Tl⁺)-dependent cotransport. The classification of hvKCC as a functional K-Cl cotransporter is furthermore supported by phylogenetic analyses and a similar structural organization. Interestingly, recently obtained physiological analyses indicate a role of cnidarian KCCs in hyposmotic volume regulation of nematocytes. HvN(K)CC is composed of 965 amino-acid residues. Phylogenetic analyses and structural organization suggest that hvN(K)CC is a member of the N(K)CC subfamily. However, no inorganic ion cotransport function could be detected using different buffer conditions. Thus, hvN(K)CC is a N(K)CC subfamily member without a detectable inorganic ion cotransporter function. Taken together, the data identify two non-bilaterian solute carrier 12 (SLC12) gene family members, thereby paving the way for a better understanding of the evolutionary paths of this important cotransporter family.

Objective assessment of the evolutionary action equation for the fitness effect of missense mutations across CAGI-blinded contests

A major challenge in genome interpretation is to estimate the fitness effect of coding variants of unknown significance (VUS). Labor, limited understanding of protein functions, and lack of assays generally limit direct experimental assessment of VUS, and make robust and accurate computational approaches a necessity. Often, however, algorithms that predict mutational effect disagree among themselves and with experimental data, slowing their adoption for clinical diagnostics. To objectively assess such methods, the Critical Assessment of Genome Interpretation (CAGI) community organizes contests to predict unpublished experimental data, available only to CAGI assessors. We review here the CAGI performance of evolutionary action (EA) predictions of mutational impact. EA models the fitness effect of coding mutations analytically, as a product of the gradient of the fitness landscape times the perturbation size. In practice, these terms are computed from phylogenetic considerations as the functional sensitivity of the mutated site and as the magnitude of amino acid substitution, respectively, and yield the percentage loss of wild-type activity. In five CAGI challenges, EA consistently performed on par or better than sophisticated machine learning approaches. This objective assessment suggests that a simple differential model of evolution can interpret the fitness effect of coding variations, opening diverse clinical applications.

Genomic insights into head and neck cancer

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide and is frequently impervious to curative treatment efforts. Similar to other cancers associated with prolonged exposure to carcinogens, HNSCCs often have a high burden of mutations, contributing to substantial inter- and intra-tumor heterogeneity. The heterogeneity of this malignancy is further increased by the rising rate of human papillomavirus (HPV)-associated (HPV+) HNSCC, which defines an etiological subtype significantly different from the more common tobacco and alcohol associated HPV-negative (HPV-) HNSCC. Since 2011, application of large scale genome sequencing projects by The Cancer Genome Atlas (TCGA) network and other groups have established extensive datasets to characterize HPV- and HPV+ HNSCC, providing a foundation for advanced molecular diagnoses, identification of potential biomarkers, and therapeutic insights. Some genomic lesions are now appreciated as widely dispersed. For example, HPV- HNSCC characteristically inactivates the cell cycle suppressors TP53 (p53) and CDKN2A (p16), and often amplifies CCND1 (cyclin D), which phosphorylates RB1 to promote cell cycle progression from G1 to S. By contrast, HPV+ HNSCC expresses viral oncogenes E6 and E7, which inhibit TP53 and RB1, and activates the cell cycle regulator E2F1. Frequent activating mutations in PIK3CA and inactivating mutations in NOTCH1 are seen in both subtypes of HNSCC, emphasizing the importance of these pathways. Studies of large patient cohorts have also begun to identify less common genetic alterations, predominantly found in HPV- tumors, which suggest new mechanisms relevant to disease pathogenesis. Targets of these alterations including AJUBA and FAT1, both involved in the regulation of NOTCH/CTNNB1 signaling. Genes involved in oxidative stress, particularly CUL3, KEAP1 and NFE2L2, strongly associated with smoking, have also been identified, and are less well understood mechanistically. Application of sophisticated data-mining approaches, integrating genomic information with profiles of tumor methylation and gene expression, have helped to further yield insights, and in some cases suggest additional approaches to stratify patients for clinical treatment. We here discuss some recent insights built on TCGA and other genomic foundations.

Solution structure and properties of AlgH from Pseudomonas aeruginosa

In Pseudomonas aeruginosa, the algH gene regulates the cellular concentrations of a number of enzymes and the production of several virulence factors, and is suggested to serve a global regulatory function. The precise mechanism by which the algH gene product, the AlgH protein, functions is unknown. The same is true for AlgH family members from other bacteria. In order to lay the groundwork for understanding the physical underpinnings of AlgH function, we examined the structure and physical properties of AlgH in solution. Under reducing conditions, results of NMR, electrophoretic mobility, and sedimentation equilibrium experiments indicate AlgH is predominantly monomeric and monodisperse in solution. Under nonreducing conditions intra and intermolecular disulfide bonds form, the latter promoting AlgH oligomerization. The high-resolution solution structure of AlgH reveals alpha/beta-sandwich architecture fashioned from ten beta strands and seven alpha helices. Comparison with available structures of orthologues indicates conservation of overall structural topology. The region of the protein most strongly conserved structurally also shows the highest amino acid sequence conservation and, as revealed by hydrogen-deuterium exchange studies, is also the most stable. In this region, evolutionary trace analysis identifies two clusters of amino acid residues with the highest evolutionary importance relative to all other AlgH residues. These frame a partially solvent exposed shallow hydrophobic cleft, perhaps identifying a site for intermolecular interactions. The results establish a physical foundation for understanding the structure and function of AlgH and AlgH family proteins and should be of general importance for further investigations of these and related proteins.

Evolutionary Action Score of TP53 Identifies High-Risk Mutations Associated with Decreased Survival and Increased Distant Metastases in Head and Neck Cancer

TP53 is the most frequently altered gene in head and neck squamous cell carcinoma, with mutations occurring in over two-thirds of cases, but the prognostic significance of these mutations remains elusive. In the current study, we evaluated a novel computational approach termed evolutionary action (EAp53) to stratify patients with tumors harboring TP53 mutations as high or low risk, and validated this system in both in vivo and in vitro models. Patients with high-risk TP53 mutations had the poorest survival outcomes and the shortest time to the development of distant metastases. Tumor cells expressing high-risk TP53 mutations were more invasive and tumorigenic and they exhibited a higher incidence of lung metastases. We also documented an association between the presence of high-risk mutations and decreased expression of TP53 target genes, highlighting key cellular pathways that are likely to be dysregulated by this subset of p53 mutations that confer particularly aggressive tumor behavior. Overall, our work validated EAp53 as a novel computational tool that may be useful in clinical prognosis of tumors harboring p53 mutations.

The functional importance of co-evolving residues in proteins

Computational approaches for detecting co-evolution in proteins allow for the identification of protein-protein interaction networks in different organisms and the assignment of function to under-explored proteins. The detection of co-variation of amino acids within or between proteins, moreover, allows for the discovery of residue-residue contacts and highlights functional residues that can affect the binding affinity, catalytic activity, or substrate specificity of a protein. To explore the functional impact of co-evolutionary changes in proteins, a combined experimental and computational approach must be recruited. Here, we review recent studies that apply computational and experimental tools to obtain novel insight into the structure, function, and evolution of proteins. Specifically, we describe the application of co-evolutionary analysis for predicting high-resolution three-dimensional structures of proteins. In addition, we describe computational approaches followed by experimental analysis for identifying specificity-determining residues in proteins. Finally, we discuss studies addressing the importance of such residues in terms of the functional divergence of proteins, allowing proteins to evolve new functions while avoiding crosstalk with existing cellular pathways or forming reproductive barriers and hence promoting speciation.

Differential effects of collagen prolyl 3-hydroxylation on skeletal tissues

Mutations in the genes encoding cartilage associated protein (CRTAP) and prolyl 3-hydroxylase 1 (P3H1 encoded by LEPRE1) were the first identified causes of recessive Osteogenesis Imperfecta (OI). These proteins, together with cyclophilin B (encoded by PPIB), form a complex that 3-hydroxylates a single proline residue on the α1(I) chain (Pro986) and has cis/trans isomerase (PPIase) activity essential for proper collagen folding. Recent data suggest that prolyl 3-hydroxylation of Pro986 is not required for the structural stability of collagen; however, the absence of this post-translational modification may disrupt protein-protein interactions integral for proper collagen folding and lead to collagen over-modification. P3H1 and CRTAP stabilize each other and absence of one results in degradation of the other. Hence, hypomorphic or loss of function mutations of either gene cause loss of the whole complex and its associated functions. The relative contribution of losing this complex's 3-hydroxylation versus PPIase and collagen chaperone activities to the phenotype of recessive OI is unknown. To distinguish between these functions, we generated knock-in mice carrying a single amino acid substitution in the catalytic site of P3h1 (Lepre1^H662A). This substitution abolished P3h1 activity but retained ability to form a complex with Crtap and thus the collagen chaperone function. Knock-in mice showed absence of prolyl 3-hydroxylation at Pro986 of the α1(I) and α1(II) collagen chains but no significant over-modification at other collagen residues. They were normal in appearance, had no growth defects and normal cartilage growth plate histology but showed decreased trabecular bone mass. This new mouse model recapitulates elements of the bone phenotype of OI but not the cartilage and growth phenotypes caused by loss of the prolyl 3-hydroxylation complex. Our observations suggest differential tissue consequences due to selective inactivation of P3H1 hydroxylase activity versus complete ablation of the prolyl 3-hydroxylation complex.

The prolyl 3-hydroxylase complex serves to hydroxylate a single residue in type I collagen and also serves as a collagen chaperone. The complex is comprised of prolyl 3-hydroxylase 1, cartilage associated protein, and cyclophilin B. Mutations have been identified in the genes encoding the complex members in patients with recessive Osteogenesis Imperfecta. Recent data suggest that prolyl 3-hydroxylation of collagen does not alter the stability of collagen but may rather mediate protein-protein interactions. Additionally, the collagen chaperoning function of the complex is an important rate limiting step in the modification of type I collagen. Irrespective of whether patients with mutations in the genes encoding the members of the prolyl 3-hydroxylase complex have hypomorphic or complete loss of function alleles, either circumstance leads to the loss of both functions of the prolyl 3-hydroxylase complex. Thus, it is unknown how collagen chaperoning and/or hydroxylation affect bone and cartilage homeostasis. In this study, we generated a mouse model lacking the prolyl 3-hydroxylation activity of the complex while maintaining the chaperoning function. We found that the hydroxylase mutant mice have normal cartilage and normal cortical bone but decreased trabecular bone, suggesting that there is a differential requirement for hydroxylation in different tissues.

Accounting for epistatic interactions improves the functional analysis of protein structures

Motivation: The constraints under which sequence, structure and function coevolve are not fully understood. Bringing this mutual relationship to light can reveal the molecular basis of binding, catalysis and allostery, thereby identifying function and rationally guiding protein redesign. Underlying these relationships are the epistatic interactions that occur when the consequences of a mutation to a protein are determined by the genetic background in which it occurs. Based on prior data, we hypothesize that epistatic forces operate most strongly between residues nearby in the structure, resulting in smooth evolutionary importance across the structure.

Methods and Results: We find that when residue scores of evolutionary importance are distributed smoothly between nearby residues, functional site prediction accuracy improves. Accordingly, we designed a novel measure of evolutionary importance that focuses on the interaction between pairs of structurally neighboring residues. This measure that we term pair-interaction Evolutionary Trace yields greater functional site overlap and better structure-based proteome-wide functional predictions.

Conclusions: Our data show that the structural smoothness of evolutionary importance is a fundamental feature of the coevolution of sequence, structure and function. Mutations operate on individual residues, but selective pressure depends in part on the extent to which a mutation perturbs interactions with neighboring residues. In practice, this principle led us to redefine the importance of a residue in terms of the importance of its epistatic interactions with neighbors, yielding better annotation of functional residues, motivating experimental validation of a novel functional site in LexA and refining protein function prediction.

Contact:lichtarge@bcm.edu

Supplementary information:Supplementary data are available at Bioinformatics online.

Are predicted protein structures of any value for binding site prediction and virtual ligand screening?

The recently developed field of ligand homology modeling (LHM) that extends the ideas of protein homology modeling to the prediction of ligand binding sites and for use in virtual ligand screening has emerged as a powerful new approach. Unlike traditional docking methodologies, LHM can be applied to low-to-moderate resolution predicted as well as experimental structures with little if any diminution in performance; thereby enabling ≈ 75% of an average proteome to have potentially significant virtual screening predictions. In large scale benchmarking, LHM is able to predict off-target ligand binding. Thus, despite the widespread belief to the contrary, low-to-moderate resolution predicted structures have considerable utility for biochemical function prediction.

Protein co-evolution: how do we combine bioinformatics and experimental approaches?

Molecular co-evolution is manifested by compensatory changes in proteins designed to enable adaptation to their natural environment. In recent years, bioinformatics approaches allowed for the detection of co-evolution at the level of the whole protein or of specific residues. Such efforts enabled prediction of protein-protein interactions, functional assignments of proteins and the identification of interacting residues, thereby providing information on protein structure. Still, despite such advances, relatively little is known regarding the functional implications of sequence divergence resulting from protein co-evolution. While bioinformatics approaches usually analyze thousands of proteins to obtain a broad view of protein co-evolution, experimental evaluation of protein co-evolution serves to study only individual proteins. In this review, we describe recent advances in bioinformatics and experimental efforts aimed at examining protein co-evolution. Accordingly, we discuss possible modes of crosstalk between the bioinformatics and experimental approaches to facilitate the identification of co-evolutionary signals in proteins and to understand their implications for the structure and function of proteins.

Sequence evolution of the intrinsically disordered and globular domains of a model viral oncoprotein

In the present work, we have used the papillomavirus E7 oncoprotein to pursue structure-function and evolutionary studies that take into account intrinsic disorder and the conformational diversity of globular domains. The intrinsically disordered (E7N) and globular (E7C) domains of E7 show similar degrees of conservation and co-evolution. We found that E7N can be described in terms of conserved and coevolving linear motifs separated by variable linkers, while sequence evolution of E7C is compatible with the known homodimeric structure yet suggests other activities for the domain. Within E7N, inter-residue relationships such as residue co-evolution and restricted intermotif distances map functional coupling and co-occurrence of linear motifs that evolve in a coordinate manner. Within E7C, additional cysteine residues proximal to the zinc-binding site may allow redox regulation of E7 function. Moreover, we describe a conserved binding site for disordered domains on the surface of E7C and suggest a putative target linear motif. Both homodimerization and peptide binding activities of E7C are also present in the distantly related host PHD domains, showing that these two proteins share not only structural homology but also functional similarities, and strengthening the view that they evolved from a common ancestor. Finally, we integrate the multiple activities and conformations of E7 into a hierarchy of structure-function relationships.

Identification of amino acid residues responsible for the selectivity of tadalafil binding to two closely related phosphodiesterases, PDE5 and PDE6

The 11 families of the Class I cyclic nucleotide phosphodiesterases (PDEs) are critical for regulation of cyclic nucleotide signaling. PDE5 (important in regulating vascular smooth muscle contraction) and PDE6 (responsible for regulating visual transduction in vertebrate photoreceptors) are structurally similar but have several functional differences whose structural basis is poorly understood. Using evolutionary trace analysis and structural homology modeling in conjunction with site-directed mutagenesis, we have tested the hypothesis that class-specific differences between PDE5 and PDE6 account for the biochemical and pharmacological differences in the two enzyme families. Replacing human PDE5 residues in the M-loop region of the binding site for the PDE5-selective inhibitor tadalafil (Cialis®) with the corresponding class-specific cone PDE6 residues (P773E, I778V, E780L, F787W, E796V, D803P, L804M, N806D, I813L, S815K) reduces tadalafil binding affinity to levels characteristic of PDE6. These mutations fail to alter vardenafil (Levitra®) affinity for the active site. Class-specific differences in PDE5 versus cone PDE6 that contribute to the accelerated catalytic efficiency of PDE6 were identified but required heterologous expression of full-length PDE5 constructs. Introduction of PDE6 residues into the background of the PDE5 protein sequence often led to loss of catalytic activity and reduced protein solubility, supporting the idea that multiple structural elements of PDE6 are highly susceptible to misfolding during heterologous expression. This work validates the use of PDE5 as a template to identify functional differences between PDE5 and PDE6 that will accelerate efforts to develop the next generation of PDE5-selective inhibitors with fewer adverse side effects resulting from PDE6 inhibition.

Separation of recombination and SOS response in Escherichia coli RecA suggests LexA interaction sites

RecA plays a key role in homologous recombination, the induction of the DNA damage response through LexA cleavage and the activity of error-prone polymerase in Escherichia coli. RecA interacts with multiple partners to achieve this pleiotropic role, but the structural location and sequence determinants involved in these multiple interactions remain mostly unknown. Here, in a first application to prokaryotes, Evolutionary Trace (ET) analysis identifies clusters of evolutionarily important surface amino acids involved in RecA functions. Some of these clusters match the known ATP binding, DNA binding, and RecA-RecA homo-dimerization sites, but others are novel. Mutation analysis at these sites disrupted either recombination or LexA cleavage. This highlights distinct functional sites specific for recombination and DNA damage response induction. Finally, our analysis reveals a composite site for LexA binding and cleavage, which is formed only on the active RecA filament. These new sites can provide new drug targets to modulate one or more RecA functions, with the potential to address the problem of evolution of antibiotic resistance at its root.

In eubacteria, genome integrity is in large part orchestrated by RecA, which directly participates in recombination, induction of DNA damage response through LexA repressor cleavage and error-prone DNA synthesis. Yet, most of the interaction sites necessary for these vital processes are largely unknown. By comparing divergences among RecA sequences and computing putative functional regions, we discovered four functional sites of RecA. Targeted point-mutations were then tested for both recombination and DNA damage induction and reveal distinct RecA functions at each one of these sites. In particular, one new set of mutants is deficient in promoting LexA cleavage and yet maintains the ability to induce the DNA damage response. These results reveal specific amino acid determinants of the RecA–LexA interaction and suggest that LexA binds RecA_i and RecA_i+6 at a composite site on the RecA filament, which could explain the role of the active filament during LexA cleavage.

Protein function prediction: towards integration of similarity metrics

Genomic centers discover increasingly many protein sequences and structures, but not necessarily their full biological functions. Thus, currently, less than one percent of proteins have experimentally verified biochemical activities. To fill this gap, function prediction algorithms apply metrics of similarity between proteins on the premise that those sufficiently alike in sequence, or structure, will perform identical functions. Although high sensitivity is elusive, network analyses that integrate these metrics together hold the promise of rapid gains in function prediction specificity.

Accurate protein structure annotation through competitive diffusion of enzymatic functions over a network of local evolutionary similarities

High-throughput Structural Genomics yields many new protein structures without known molecular function. This study aims to uncover these missing annotations by globally comparing select functional residues across the structural proteome. First, Evolutionary Trace Annotation, or ETA, identifies which proteins have local evolutionary and structural features in common; next, these proteins are linked together into a proteomic network of ETA similarities; then, starting from proteins with known functions, competing functional labels diffuse link-by-link over the entire network. Every node is thus assigned a likelihood z-score for every function, and the most significant one at each node wins and defines its annotation. In high-throughput controls, this competitive diffusion process recovered enzyme activity annotations with 99% and 97% accuracy at half-coverage for the third and fourth Enzyme Commission (EC) levels, respectively. This corresponds to false positive rates 4-fold lower than nearest-neighbor and 5-fold lower than sequence-based annotations. In practice, experimental validation of the predicted carboxylesterase activity in a protein from Staphylococcus aureus illustrated the effectiveness of this approach in the context of an increasingly drug-resistant microbe. This study further links molecular function to a small number of evolutionarily important residues recognizable by Evolutionary Tracing and it points to the specificity and sensitivity of functional annotation by competitive global network diffusion. A web server is at http://mammoth.bcm.tmc.edu/networks.

PyETV: a PyMOL evolutionary trace viewer to analyze functional site predictions in protein complexes

SUMMARY

PyETV is a PyMOL plugin for viewing, analyzing and manipulating predictions of evolutionarily important residues and sites in protein structures and their complexes. It seamlessly captures the output of the Evolutionary Trace server, namely ranked importance of residues, for multiple chains of a complex. It then yields a high resolution graphical interface showing their distribution and clustering throughout a quaternary structure, including at interfaces. Together with other tools in the popular PyMOL viewer, PyETV thus provides a novel tool to integrate evolutionary forces into the design of experiments targeting the most functionally relevant sites of a protein.

AVAILABILITY

The PyETV module is written in Python. Installation instructions and video demonstrations may be found at the URL http://mammoth.bcm.tmc.edu/traceview/HelpDocs/PyETVHelp/pyInstructions.html.

CONTACT

lichtarge@bcm.tmc.edu.