ConSurf: an algorithmic tool for the identification of functional regions in proteins by surface mapping of phylogenetic information

WD40 repeat propellers define a ubiquitin-binding domain that regulates turnover of F box proteins

WD40-repeat β-propellers are found in a wide range of proteins involved in distinct biological activities. We define a large subset of WD40 β-propellers as a class of ubiquitin-binding domains. Using the β-propeller from Doa1/Ufd3 as a paradigm, we find the conserved top surface of the Doa1 β-propeller binds the hydrophobic patch of ubiquitin centered on residues I44, L8, and V70. Mutations that disrupt ubiquitin binding abrogate Doa1 function, demonstrating the importance of this interaction. We further demonstrate that WD40 β-propellers from a functionally diverse set of proteins bind ubiquitin in a similar fashion. This set includes members of the F box family of SCF ubiquitin E3 ligase adaptors. Using mutants defective in binding, we find that ubiquitin interaction by the F box protein Cdc4 promotes its autoubiquitination and turnover. Collectively, our results reveal a molecular mechanism that may account for how ubiquitin controls a broad spectrum of cellular activities.

A comparative study of conservation and variation scores

BACKGROUND

Conservation and variation scores are used when evaluating sites in a multiple sequence alignment, in order to identify residues critical for structure or function. A variety of scores are available today but it is not clear how different scores relate to each other.

RESULTS

We applied 25 conservation and variation scores to alignments from the Catalytic Site Atlas (CSA). We calculated distances among scores based on correlation coefficients, and constructed a dendrogram of the scores by average linking cluster analysis. The cluster analysis showed that most scores fall into one of two groups--substitution matrix based group and frequency based group respectively. We also evaluated the scores' performance in predicting catalytic sites and found that frequency based scores generally perform best.

CONCLUSIONS

Conservation and variation scores can be classified into mainly two large groups. When using a score to predict catalytic sites, frequency based scores that also consider a background distribution are most successful.

In silico identification of functional protein interfaces

Proteins perform many of their biological roles through protein–protein, protein–DNA or protein–ligand interfaces. The identification of the amino acids comprising these interfaces often enhances our understanding of the biological function of the proteins. Many methods for the detection of functional interfaces have been developed, and large-scale analyses have provided assessments of their accuracy. Among them are those that consider the size of the protein interface, its amino acid composition and its physicochemical and geometrical properties. Other methods to this effect use statistical potential functions of pairwise interactions, and evolutionary information. The rationale of the evolutionary approach is that functional and structural constraints impose selective pressure; hence, biologically important interfaces often evolve at a slower pace than do other external regions of the protein. Recently, an algorithm, Rate4Site, and a web-server, ConSurf (http://consurf.tau.ac.il/), for the identification of functional interfaces based on the evolutionary relations among homologous proteins as reflected in phylogenetic trees, were developed in our laboratory. The explicit use of the tree topology and branch lengths makes the method remarkably accurate and sensitive. Here we demonstrate its potency in the identification of the functional interfaces of a hypothetical protein, the structure of which was determined as part of the international structural genomics effort. Finally, we propose to combine complementary procedures, in order to enhance the overall performance of methods for the identification of functional interfaces in proteins.

Conserved residue clusters at protein-protein interfaces and their use in binding site identification

BACKGROUND

Biological evolution conserves protein residues that are important for structure and function. Both protein stability and function often require a certain degree of structural co-operativity between spatially neighboring residues and it has previously been shown that conserved residues occur clustered together in protein tertiary structures, enzyme active sites and protein-DNA interfaces. Residues comprising protein interfaces are often more conserved compared to those occurring elsewhere on the protein surface. We investigate the extent to which conserved residues within protein-protein interfaces are clustered together in three-dimensions.

RESULTS

Out of 121 and 392 interfaces in homodimers and heterocomplexes, 96.7 and 86.7%, respectively, have the conserved positions clustered within the overall interface region. The significance of this clustering was established in comparison to what is seen for the subsets of the same size of randomly selected residues from the interface. Conserved residues occurring in larger interfaces could often be sub-divided into two or more distinct sub-clusters. These structural cluster(s) comprising conserved residues indicate functionally important regions within the protein-protein interface that can be targeted for further structural and energetic analysis by experimental scanning mutagenesis. Almost 60% of experimental hot spot residues (with DeltaDeltaG > 2 kcal/mol) were localized to these conserved residue clusters. An analysis of the residue types that are enriched within these conserved subsets compared to the overall interface showed that hydrophobic and aromatic residues are favored, but charged residues (both positive and negative) are less common. The potential use of this method for discriminating binding sites (interfaces) versus random surface patches was explored by comparing the clustering of conserved residues within each of these regions--in about 50% cases the true interface is ranked among the top 10% of all surface patches.

CONCLUSIONS

Protein-protein interaction sites are much larger than small molecule biding sites, but still conserved residues are not randomly distributed over the whole interface and are distinctly clustered. The clustered nature of evolutionarily conserved residues within interfaces as compared to those within other surface patches not involved in binding has important implications for the identification of protein-protein binding sites and would have applications in docking studies.

Structure, evolutionary conservation, and conformational dynamics of Homo sapiens fascin-1, an F-actin crosslinking protein

Eukaryotes have several highly conserved actin-binding proteins that crosslink filamentous actin into compact ordered bundles present in distinct cytoskeletal processes, including microvilli, stereocilia and filopodia. Fascin is an actin-binding protein that is present predominantly in filopodia, which are believed to play a central role in normal and aberrant cell migration. An important outstanding question regards the molecular basis for the unique localization and functional properties of fascin compared with other actin crosslinking proteins. Here, we present the crystal structure of full-length Homo sapiens fascin-1, and examine its packing, conformational flexibility, and evolutionary sequence conservation. The structure reveals a novel arrangement of four tandem beta-trefoil domains that form a bi-lobed structure with approximate pseudo 2-fold symmetry. Each lobe has internal approximate pseudo 2-fold and pseudo 3-fold symmetry axes that are approximately perpendicular, with beta-hairpin triplets located symmetrically on opposite sides of each lobe that mutational data suggest are actin-binding domains. Sequence conservation analysis confirms the importance of hydrophobic core residues that stabilize the beta-trefoil fold, as well as interfacial residues that are likely to stabilize the overall fascin molecule. Sequence conservation also indicates highly conserved surface patches near the putative actin-binding domains of fascin, which conformational dynamics analysis suggests to be coupled via an allosteric mechanism that might have important functional implications for F-actin crosslinking by fascin.

A common substrate recognition mode conserved between katanin p60 and VPS4 governs microtubule severing and membrane skeleton reorganization

Katanin p60 (kp60), a microtubule-severing enzyme, plays a key role in cytoskeletal reorganization during various cellular events in an ATP-dependent manner. We show that a single domain isolated from the N terminus of mouse katanin p60 (kp60-NTD) binds to tubulin. The solution structure of kp60-NTD was determined by NMR. Although their sequence similarities were as low as 20%, the structure of kp60-NTD revealed a striking similarity to those of the microtubule interacting and trafficking (MIT) domains, which adopt anti-parallel three-stranded helix bundle. In particular, the arrangement of helices 2 and 3 is well conserved between kp60-NTD and the MIT domain from Vps4, which is a homologous protein that promotes disassembly of the endosomal sorting complexes required for transport III membrane skeleton complex. Mutation studies revealed that the positively charged surface formed by helices 2 and 3 binds tubulin. This binding mode resembles the interaction between the MIT domain of Vps4 and Vps2/CHMP1a, a component of endosomal sorting complexes required for transport III. Our results show that both the molecular architecture and the binding modes are conserved between two AAA-ATPases, kp60 and Vps4. A common mechanism is evolutionarily conserved between two distinct cellular events, one that drives microtubule severing and the other involving membrane skeletal reorganization.

A novel and efficient tool for locating and characterizing protein cavities and binding sites

Systematic investigation of a protein and its binding site characteristics are crucial for designing small molecules that modulate protein functions. However, fundamental uncertainties in binding site interactions and insufficient knowledge of the properties of even well-defined binding pockets can make it difficult to design optimal drugs. Herein, we report the development and implementation of a cavity detection algorithm built with HINT toolkit functions that we are naming Vectorial Identification of Cavity Extents (VICE). This very efficient algorithm is based on geometric criteria applied to simple integer grid maps. In testing, we carried out a systematic investigation on a very diverse data set of proteins and protein-protein/protein-polynucleotide complexes for locating and characterizing the indentations, cavities, pockets, grooves, channels, and surface regions. Additionally, we evaluated a curated data set of unbound proteins for which a ligand-bound protein structures are also known; here the VICE algorithm located the actual ligand in the largest cavity in 83% of the cases and in one of the three largest in 90% of the cases. An interactive front-end provides a quick and simple procedure for locating, displaying and manipulating cavities in these structures. Information describing the cavity, including its volume and surface area metrics, and lists of atoms, residues, and/or chains lining the binding pocket, can be easily obtained and analyzed. For example, the relative cross-sectional surface area (to total surface area) of cavity openings in well-enclosed cavities is 0.06 +/- 0.04 and in surface clefts or crevices is 0.25 +/- 0.09. Proteins 2010. (c) 2009 Wiley-Liss, Inc.

Targeting mechanism of the retinoblastoma tumor suppressor by a prototypical viral oncoprotein. Structural modularity, intrinsic disorder and phosphorylation of human papillomavirus E7

DNA tumor viruses ensure genome amplification by hijacking the cellular replication machinery and forcing infected cells to enter the S phase. The retinoblastoma (Rb) protein controls the G1/S checkpoint, and is targeted by several viral oncoproteins, among these the E7 protein from human papillomaviruses (HPVs). A quantitative investigation of the interaction mechanism between the HPV16 E7 protein and the RbAB domain in solution revealed that 90% of the binding energy is determined by the LxCxE motif, with an additional binding determinant (1.0 kcal.mol(-1)) located in the C-terminal domain of E7, establishing a dual-contact mode. The stoichiometry and subnanomolar affinity of E7 indicated that it can bind RbAB as a monomer. The low-risk HPV11 E7 protein bound 2.0 kcal.mol(-1) more weakly than the high-risk HPV16 and HPV18 type counterparts, but the modularity and binding mode were conserved. Phosphorylation at a conserved casein kinase II site in the natively unfolded N-terminal domain of E7 affected the local conformation by increasing the polyproline II content and stabilizing an extended conformation, which allowed for a tighter interaction with the Rb protein. Thus, the E7-RbAB interaction involves multiple motifs within the N-terminal domain of E7 and at least two conserved interaction surfaces in RbAB. We discussed a mechanistic model of the interaction of the Rb protein with a viral target in solution, integrated with structural data and the analysis of other cellular and viral proteins, which provided information about the balance of interactions involving the Rb protein and how these determine the progression into either the normal cell cycle or transformation.

Comparison of structure-based and threading-based approaches to protein functional annotation

To exploit the vast amount of sequence information provided by the Genomic revolution, the biological function of these sequences must be identified. As a practical matter, this is often accomplished by functional inference. Purely sequence-based approaches, particularly in the "twilight zone" of low sequence similarity levels, are complicated by many factors. For proteins, structure-based techniques aim to overcome these problems; however, most require high-quality crystal structures and suffer from complex and equivocal relations between protein fold and function. In this study, in extensive benchmarking, we consider a number of aspects of structure-based functional annotation: binding pocket detection, molecular function assignment and ligand-based virtual screening. We demonstrate that protein threading driven by a strong sequence profile component greatly improves the quality of purely structure-based functional annotation in the "twilight zone." By detecting evolutionarily related proteins, it considerably reduces the high false positive rate of function inference derived on the basis of global structure similarity alone. Combined evolution/structure-based function assignment emerges as a powerful technique that can make a significant contribution to comprehensive proteome annotation.

In silico identification of catalytic residues in azobenzene reductase from Bacillus subtilis and its docking studies with azo dyes

Prediction of catalytic residues of an enzyme molecule is of great importance for a range of applications including molecular docking, drug design, structural identification and comparison of binding sites. Over the last decades, many studies have been conducted to identify the enzyme catalytic site. But, the catalytic residues of the azobenzene reductase from bacillus subtilis are still unknown. Investigation shows that under anaerobic conditions, azo dyes can be reduced by this enzyme and other environmental microorganisms to colorless amines, which may be toxic, mutagenic, and carcinogenic to humans and animals. To assess and estimate the toxicity, it is essential to identify the catalytic residues of this enzyme. The computational methods developed that address this issue are few. In this approach, we identify the catalytic residues of azobenzene reductase from bacillus subtilis, which were then analyzed in terms of properties including function, conservation, hydrogen bonding, B-factor, solvent accessibility, and flexibility. The results indicate that, Lys (83) and Tyr (74) play an important role as catalytic site residues in the azobenzene reductase from bacillus subtilis. It is hoped that this information will provide a better understanding of the molecular mechanisms involved in catalysis and a heuristic basis for predicting the catalytic residues in enzymes of unknown function. In this study, our approach mainly looks for a better understanding of the biodegradation of the Sudan I, Sudan II, Sudan III and Sudan IV dyes mediated by azobenzene reductase from bacillus subtilis. Further more, the catalytic site residues information is essential for understanding and altering substrate specificity and for the design of enzyme inhibitors.

ProPhylER: a curated online resource for protein function and structure based on evolutionary constraint analyses

ProPhylER (Protein Phylogeny and Evolutionary Rates) is a next-generation curated proteome resource that uses comparative sequence analysis to predict constraint and mutation impact for eukaryotic proteins. Its purpose is to inform any research program for which protein function and structure are relevant, by the predictive power of evolutionary constraint analyses. ProPhylER currently has nearly 9000 clusters of related proteins, including more than 200,000 sequences. It serves data via two interfaces. The "ProPhylER Interface" displays predictive analyses in sequence space; the "CrystalPainter" maps evolutionary constraints onto solved protein structures. Here we summarize ProPhylER's data content and analysis pipeline, demonstrate the use of ProPhylER's interfaces, and evaluate ProPhylER's unique regional analysis of evolutionary constraint. The high accuracy of ProPhylER's regional analysis complements the high resolution of its single-site analysis to effectively guide and inform structure-function investigations and predict the impact of polymorphisms.

Comparing the functional roles of nonconserved sequence positions in homologous transcription repressors: implications for sequence/function analyses

The explosion of protein sequences deduced from genetic code has led to both a problem and a potential resource: Efficient data use requires interpreting the functional impact of sequence change without experimentally characterizing each protein variant. Several groups have hypothesized that interpretation could be aided by analyzing the sequences of naturally occurring homologues. To that end, myriad sequence/function analyses have been developed to predict which conserved, semi-conserved, and nonconserved positions are functionally important. These positions must be discriminated from the nonconserved positions that are functionally silent. However, the assumptions that underlie sequence analyses are based on experimental results that are sparse and usually designed to address different questions. Here, we use three homologues from a test family common to bioinformatics-the LacI/GalR transcription repressors-to test a common assumption: If a position is functionally important for one family member, it has similar importance in all homologues. We generated experimental sequence/function information for each nonconserved position in the 18 amino acids that link the DNA-binding and regulatory domains of three LacI/GalR homologues. We find that the functional importance of each position is preserved among the three linkers, albeit to different degrees. We also find that every linker position contributes to function, which has twofold implications. (1) Since the linker positions range from highly conserved to semi-conserved to nonconserved and contribute to affinity, selectivity, and allosteric response, we assert that sequence/function analyses must identify positions in the LacI/GalR linkers to be qualified as "successful". Many analyses overlook this region since most of the residues do not directly contact ligand. (2) No position in the LacI/GalR linker is functionally silent. This finding is inconsistent with another underlying principle of many analyses: Using sequence sets to discriminate important from non-contributing positions obligates silent positions, which denotes that most homologues tolerate a variety of amino acid substitutions at the position without functional change. Instead, additional combinatorial mutants in the LacI/GalR linkers show that particular substitutions can be silent in a context-dependent manner. Thus, specific permutations of sequence change (rather than change at silent positions) would facilitate neutral drift during evolution. Finally, the combinatorial mutants also reveal functional synergy between semi- and nonconserved positions. Such functional relationships would be missed by analyses that rely primarily upon co-evolution.

Prediction of protein-protein interfaces on G-protein beta subunits reveals a novel phospholipase C beta2 binding domain

Gbeta subunits from heterotrimeric G-proteins (guanine nucleotide-binding proteins) directly bind diverse proteins, including effectors and regulators, to modulate a wide array of signaling cascades. These numerous interactions constrained the evolution of the molecular surface of Gbeta. Although mammals contain five Gbeta genes comprising two classes (Gbeta1-like and Gbeta5-like), plants and fungi have a single ortholog, and organisms such as Caenorhabditis elegans and Drosophila melanogaster contain one copy from each class. A limited number of crystal structures of complexes containing Gbeta subunits and complementary biochemical data highlight specific sites within Gbetas needed for protein interactions. It is difficult to determine from these interaction sites what, if any, additional regions of the Gbeta molecular surface comprise interaction interfaces essential to Gbeta's role as a nexus in numerous signaling cascades. We used a comparative evolutionary approach to identify five known and eight previously unknown putative interfaces on the surface of Gbeta. We show that one such novel interface occurs between Gbeta and phospholipase C beta2 (PLC-beta2), a mammalian Gbeta interacting protein. Substitutions of residues within this Gbeta-PLC-beta2 interface reduce the activation of PLC-beta2 by Gbeta1, confirming that our de novo comparative evolutionary approach predicts previously unknown Gbeta-protein interfaces. Similarly, we hypothesize that the seven remaining untested novel regions contribute to putative interfaces for other Gbeta interacting proteins. Finally, this comparative evolutionary approach is suitable for application to any protein involved in a significant number of protein-protein interactions.

Trm13p, the tRNA:Xm4 modification enzyme from Saccharomyces cerevisiae is a member of the Rossmann-fold MTase superfamily: prediction of structure and active site

2'-O-ribose methylation is one of the most common posttranscriptional modifications in RNA. Methylations at different positions are introduced by enzymes from at least two unrelated superfamilies. Recently, a new family of eukaryotic RNA methyltransferases (MTases) has been identified, and its representative from yeast (Yol125w, renamed as Trm13p) has been shown to 2'-O-methylate position 4 of tRNA. Trm13 is conserved in Eukaryota, but exhibits no sequence similarity to other known MTases. Here, I present the results of bioinformatics analysis which suggest that Trm13 is a strongly diverged member of the Rossmann-fold MTase (RFM) superfamily, and therefore is evolutionarily related to 2'-O-MTases such as Trm7 and fibrillarin. However, the character of conserved residues in the predicted active site of the Trm13 family suggests it may use a different mechanism of ribose methylation than its relatives. A molecular model of the Trm13p structure has been constructed and evaluated for potential accuracy using model quality assessment methods. The predicted structure will facilitate experimental analyses of the Trm13p mechanism of action.

A surface of the kinase domain critical for the allosteric activation of G protein-coupled receptor kinases

G protein-coupled receptor (GPCR) kinases (GRKs) phosphorylate activated GPCRs and initiate their desensitization. Many prior studies suggest that activated GPCRs dock to an allosteric site on the GRKs and thereby stimulate kinase activity. The extreme N-terminal region of GRKs is clearly involved in this process, but its role is not understood. Using our recent structure of bovine GRK1 as a guide, we generated mutants of solvent-exposed residues in the GRK1 kinase domain that are conserved among GRKs but not in the extended protein kinase A, G, and C family and evaluated their catalytic activity. Mutation of select residues in strands beta1 and beta3 of the kinase small lobe, alphaD of the kinase large lobe, and the protein kinase A, G, and C kinase C-tail greatly impaired receptor phosphorylation. The most dramatic effect was observed for mutation of an invariant arginine on the beta1-strand (approximately 1000-fold decrease in k(cat)/K(m)). These residues form a continuous surface that is uniquely available in GRKs for protein-protein interactions. Surprisingly, these mutants, as well as a 19-amino acid N-terminal truncation of GRK1, also show decreased catalytic efficiency for peptide substrates, although to a lesser extent than for receptor phosphorylation. Our data suggest that the N-terminal region and the newly identified surface interact and stabilize the closed, active conformation of the kinase domain. Receptor binding is proposed to promote this interaction, thereby enhancing GRK activity.

Structural mechanisms of inactivation in scabies mite serine protease paralogues

The scabies mite (Sarcoptes scabiei) is a parasite responsible for major morbidity in disadvantaged communities and immuno-compromised patients worldwide. In addition to the physical discomfort caused by the disease, scabies infestations facilitate infection by Streptococcal species via skin lesions, resulting in a high prevalence of rheumatic fever/heart disease in affected communities. The scabies mite produces 33 proteins that are closely related to those in the dust mite group 3 allergen and belong to the S1-like protease family (chymotrypsin-like). However, all but one of these molecules contain mutations in the conserved active-site catalytic triad that are predicted to render them catalytically inactive. These molecules are thus termed scabies mite inactivated protease paralogues (SMIPPs). The precise function of SMIPPs is unclear; however, it has been suggested that these proteins might function by binding and protecting target substrates from cleavage by host immune proteases, thus preventing the host from mounting an effective immune challenge. In order to begin to understand the structural basis for SMIPP function, we solved the crystal structures of SMIPP-S-I1 and SMIPP-S-D1 at 1.85 A and 2.0 A resolution, respectively. Both structures adopt the characteristic serine protease fold, albeit with large structural variations over much of the molecule. In both structures, mutations in the catalytic triad together with occlusion of the S1 subsite by a conserved Tyr200 residue is predicted to block substrate ingress. Accordingly, we show that both proteases lack catalytic function. Attempts to restore function (via site-directed mutagenesis of catalytic residues as well as Tyr200) were unsuccessful. Taken together, these data suggest that SMIPPs have lost the ability to bind substrates in a classical "canonical" fashion, and instead have evolved alternative functions in the lifecycle of the scabies mite.

Fas apoptosis inhibitory molecule contains a novel beta-sandwich in contact with a partially ordered domain

Fas apoptosis inhibitory molecule (FAIM) is a soluble cytosolic protein inhibitor of programmed cell death and is found in organisms throughout the animal kingdom. A short isoform of FAIM is expressed in all tissue types, while an alternatively spliced long isoform is specifically expressed in the brain. Here, the short isoform is shown to consist of two independently folding domains in contact with each other. The NMR solution structure of the C-terminal domain of murine FAIM is solved in isolation and revealed to be a novel protein fold, a noninterleaved seven-stranded beta-sandwich. The structure and sequence reveal several residues that are likely to be involved in functionally significant interactions with the N-terminal domain or other binding partners. Chemical shift perturbation is used to elucidate contacts made between the N-terminal domain and the C-terminal domain.

Joint evolutionary trees: a large-scale method to predict protein interfaces based on sequence sampling

The Joint Evolutionary Trees (JET) method detects protein interfaces, the core residues involved in the folding process, and residues susceptible to site-directed mutagenesis and relevant to molecular recognition. The approach, based on the Evolutionary Trace (ET) method, introduces a novel way to treat evolutionary information. Families of homologous sequences are analyzed through a Gibbs-like sampling of distance trees to reduce effects of erroneous multiple alignment and impacts of weakly homologous sequences on distance tree construction. The sampling method makes sequence analysis more sensitive to functional and structural importance of individual residues by avoiding effects of the overrepresentation of highly homologous sequences and improves computational efficiency. A carefully designed clustering method is parametrized on the target structure to detect and extend patches on protein surfaces into predicted interaction sites. Clustering takes into account residues' physical-chemical properties as well as conservation. Large-scale application of JET requires the system to be adjustable for different datasets and to guarantee predictions even if the signal is low. Flexibility was achieved by a careful treatment of the number of retrieved sequences, the amino acid distance between sequences, and the selective thresholds for cluster identification. An iterative version of JET (iJET) that guarantees finding the most likely interface residues is proposed as the appropriate tool for large-scale predictions. Tests are carried out on the Huang database of 62 heterodimer, homodimer, and transient complexes and on 265 interfaces belonging to signal transduction proteins, enzymes, inhibitors, antibodies, antigens, and others. A specific set of proteins chosen for their special functional and structural properties illustrate JET behavior on a large variety of interactions covering proteins, ligands, DNA, and RNA. JET is compared at a large scale to ET and to Consurf, Rate4Site, siteFiNDER|3D, and SCORECONS on specific structures. A significant improvement in performance and computational efficiency is shown.

Information obtained on the structure of macromolecular complexes is important for identifying functionally important partners but also for determining how such interactions will be perturbed by natural or engineered site mutations. Hence, to fully understand or control biological processes we need to predict in the most accurate manner protein interfaces for a protein structure, possibly without knowing its partners. Joint Evolutionary Trees (JET) is a method designed to detect very different types of interactions of a protein with another protein, ligands, DNA, and RNA. It uses a carefully designed sampling method, making sequence analysis more sensitive to the functional and structural importance of individual residues, and a clustering method parametrized on the target structure for the detection of patches on protein surfaces and their extension into predicted interaction sites. JET is a large-scale method, highly accurate and potentially applicable to search for protein partners.

Identification of functionally important residues/domains in membrane proteins using an evolutionary approach coupled with systematic mutational analysis

Structure-function studies of membrane proteins present a unique challenge to researchers due to the numerous technical difficulties associated with their expression, purification and structural characterization. In the absence of structural information, rational identification of putative functionally important residues/regions is difficult. Phylogenetic relationships could provide valuable information about the functional significance of a particular residue or region of a membrane protein. Evolutionary Trace (ET) analysis is a method developed to utilize this phylogenetic information to predict functional sites in proteins. In this method, residues are ranked according to conservation or divergence through evolution, based on the hypothesis that mutations at key positions should coincide with functional evolutionary divergences. This information can be used as the basis for a systematic mutational analysis of identified residues, leading to the identification of functionally important residues and/or domains in membrane proteins, in the absence of structural information apart from the primary amino acid sequence. This approach is potentially useful in the context of the auditory system, as several key processes in audition involve the action of membrane proteins, many of which are novel and not well characterized structurally or functionally to date.

Direct link between RACK1 function and localization at the ribosome in vivo

The receptor for activated C-kinase (RACK1), a conserved protein implicated in numerous signaling pathways, is a stoichiometric component of eukaryotic ribosomes located on the head of the 40S ribosomal subunit. To test the hypothesis that ribosome association is central to the function of RACK1 in vivo, we determined the 2.1-A crystal structure of RACK1 from Saccharomyces cerevisiae (Asc1p) and used it to design eight mutant versions of RACK1 to assess roles in ribosome binding and in vivo function. Conserved charged amino acids on one side of the beta-propeller structure were found to confer most of the 40S subunit binding affinity, whereas an adjacent conserved and structured loop had little effect on RACK1-ribosome association. Yeast mutations that confer moderate to strong defects in ribosome binding mimic some phenotypes of a RACK1 deletion strain, including increased sensitivity to drugs affecting cell wall biosynthesis and translation elongation. Furthermore, disruption of RACK1's position at the 40S ribosomal subunit results in the failure of the mRNA binding protein Scp160 to associate with actively translating ribosomes. These results provide the first direct evidence that RACK1 functions from the ribosome, implying a physical link between the eukaryotic ribosome and cell signaling pathways in vivo.

Prediction of protein-protein binding site by using core interface residue and support vector machine

Background

The prediction of protein-protein binding site can provide structural annotation to the protein interaction data from proteomics studies. This is very important for the biological application of the protein interaction data that is increasing rapidly. Moreover, methods for predicting protein interaction sites can also provide crucial information for improving the speed and accuracy of protein docking methods.

Results

In this work, we describe a binding site prediction method by designing a new residue neighbour profile and by selecting only the core-interface residues for SVM training. The residue neighbour profile includes both the sequential and the spatial neighbour residues of an interface residue, which is a more complete description of the physical and chemical characteristics surrounding the interface residue. The concept of core interface is applied in selecting the interface residues for training the SVM models, which is shown to result in better discrimination between the core interface and other residues.

The best SVM model trained was tested on a test set of 50 randomly selected proteins. The sensitivity, specificity, and MCC for the prediction of the core interface residues were 60.6%, 53.4%, and 0.243, respectively. Our prediction results on this test set were compared with other three binding site prediction methods and found to perform better. Furthermore, our method was tested on the 101 unbound proteins from the protein-protein interaction benchmark v2.0. The sensitivity, specificity, and MCC of this test were 57.5%, 32.5%, and 0.168, respectively.

Conclusion

By improving both the descriptions of the interface residues and their surrounding environment and the training strategy, better SVM models were obtained and shown to outperform previous methods. Our tests on the unbound protein structures suggest further improvement is possible.

Large-scale structural modeling of protein complexes at low resolution

Structural aspects of protein-protein interactions provided by large-scale, genome-wide studies are essential for the description of life processes at the molecular level. A methodology is developed that applies the protein docking approach (GRAMM), based on the knowledge of experimentally determined protein-protein structures (DOCKGROUND resource) and properties of intermolecular energy landscapes, to genome-wide systems of protein interactions. The full sequence-to-structure-of-complex modeling pipeline is implemented in the Genome Wide Docking Database (GWIDD) resource. Protein interaction data are imported to GWIDD from external datasets of experimentally determined interaction networks. Essential information is extracted and unified to form the GWIDD database. Structures of individual interacting proteins in the database are retrieved (if available) or modeled, and protein complex structures are predicted by the docking program. All protein sequence, structure, and docking information is conveniently accessible through a Web interface.

The ConSurf-DB: pre-calculated evolutionary conservation profiles of protein structures

ConSurf-DB is a repository for evolutionary conservation analysis of the proteins of known structures in the Protein Data Bank (PDB). Sequence homologues of each of the PDB entries were collected and aligned using standard methods. The evolutionary conservation of each amino acid position in the alignment was calculated using the Rate4Site algorithm, implemented in the ConSurf web server. The algorithm takes into account the phylogenetic relations between the aligned proteins and the stochastic nature of the evolutionary process explicitly. Rate4Site assigns a conservation level for each position in the multiple sequence alignment using an empirical Bayesian inference. Visual inspection of the conservation patterns on the 3D structure often enables the identification of key residues that comprise the functionally important regions of the protein. The repository is updated with the latest PDB entries on a monthly basis and will be rebuilt annually. ConSurf-DB is available online at http://consurfdb.tau.ac.il/

A Myo6 mutation destroys coordination between the myosin heads, revealing new functions of myosin VI in the stereocilia of mammalian inner ear hair cells

Myosin VI, found in organisms from Caenorhabditis elegans to humans, is essential for auditory and vestibular function in mammals, since genetic mutations lead to hearing impairment and vestibular dysfunction in both humans and mice. Here, we show that a missense mutation in this molecular motor in an ENU-generated mouse model, Tailchaser, disrupts myosin VI function. Structural changes in the Tailchaser hair bundles include mislocalization of the kinocilia and branching of stereocilia. Transfection of GFP-labeled myosin VI into epithelial cells and delivery of endocytic vesicles to the early endosome revealed that the mutant phenotype displays disrupted motor function. The actin-activated ATPase rates measured for the D179Y mutation are decreased, and indicate loss of coordination of the myosin VI heads or 'gating' in the dimer form. Proper coordination is required for walking processively along, or anchoring to, actin filaments, and is apparently destroyed by the proximity of the mutation to the nucleotide-binding pocket. This loss of myosin VI function may not allow myosin VI to transport its cargoes appropriately at the base and within the stereocilia, or to anchor the membrane of stereocilia to actin filaments via its cargos, both of which lead to structural changes in the stereocilia of myosin VI-impaired hair cells, and ultimately leading to deafness.

Protein–protein interaction and quaternary structure

Protein–protein recognition plays an essential role in structure and function. Specific non-covalent interactions stabilize the structure of macromolecular assemblies, exemplified in this review by oligomeric proteins and the capsids of icosahedral viruses. They also allow proteins to form complexes that have a very wide range of stability and lifetimes and are involved in all cellular processes. We present some of the structure-based computational methods that have been developed to characterize the quaternary structure of oligomeric proteins and other molecular assemblies and analyze the properties of the interfaces between the subunits. We compare the size, the chemical and amino acid compositions and the atomic packing of the subunit interfaces of protein–protein complexes, oligomeric proteins, viral capsids and protein–nucleic acid complexes. These biologically significant interfaces are generally close-packed, whereas the non-specific interfaces between molecules in protein crystals are loosely packed, an observation that gives a structural basis to specific recognition. A distinction is made within each interface between a core that contains buried atoms and a solvent accessible rim. The core and the rim differ in their amino acid composition and their conservation in evolution, and the distinction helps correlating the structural data with the results of site-directed mutagenesis and in vitro studies of self-assembly.

Insights into subunit interactions in the heterotetrameric structure of potato ADP-glucose pyrophosphorylase

ADP-glucose pyrophosphorylase, a key allosteric enzyme involved in higher plant starch biosynthesis, is composed of pairs of large (LS) and small subunits (SS). Current evidence indicates that the two subunit types play distinct roles in enzyme function. The LS is involved in mainly allosteric regulation through its interaction with the catalytic SS. Recently the crystal structure of the SS homotetramer has been solved, but no crystal structure of the native heterotetrameric enzyme is currently available. In this study, we first modeled the three-dimensional structure of the LS to construct the heterotetrameric enzyme. Because the enzyme has a 2-fold symmetry, six different dimeric (either up-down or side-by-side) interactions were possible. Molecular dynamics simulations were carried out for each of these possible dimers. Trajectories obtained from molecular dynamics simulations of each dimer were then analyzed by the molecular mechanics/Poisson-Boltzmann surface area method to identify the most favorable dimers, one for up-down and the other for side-by-side. Computational results combined with site directed mutagenesis and yeast two hybrid experiments suggested that the most favorable heterotetramer is formed by LS-SS (side-by-side), and LS-SS (up-down). We further determined the order of assembly during the heterotetrameric structure formation. First, side-by-side LS-SS dimers form followed by the up-down tetramerization based on the relative binding free energies.

Predicting protein interaction interfaces from protein sequences: case studies of subtilisin and phycocyanin

Identification of protein interaction interfaces is very important for understanding the molecular mechanisms underlying biological phenomena. Here, we present a novel method for predicting protein interaction interfaces from sequences by using PAM matrix (PIFPAM). Sequence alignments for interacting proteins were constructed and parsed into segments using sliding windows. By calculating distance matrix for each segment, the correlation coefficients between segments were estimated. The interaction interfaces were predicted by extracting highly correlated segment pairs from the correlation map. The predictions achieved an accuracy 0.41-0.71 for eight intraprotein interaction examples, and 0.07-0.60 for four interprotein interaction examples. Compared with three previously published methods, PIFPAM predicted more contacting site pairs for 11 out of the 12 example proteins, and predicted at least 34% more contacting site pairs for eight proteins of them. The factors affecting the predictions were also analyzed. Since PIFPAM uses only the alignments of the two interacting proteins as input, it is especially useful when no three-dimensional protein structure data are available.

Characterization of local geometry of protein surfaces with the visibility criterion

Experimentally determined protein tertiary structures are rapidly accumulating in a database, partly due to the structural genomics projects. Included are proteins of unknown function, whose function has not been investigated by experiments and was not able to be predicted by conventional sequence-based search. Those uncharacterized protein structures highlight the urgent need of computational methods for annotating proteins from tertiary structures, which include function annotation methods through characterizing protein local surfaces. Toward structure-based protein annotation, we have developed VisGrid algorithm that uses the visibility criterion to characterize local geometric features of protein surfaces. Unlike existing methods, which only concerns identifying pockets that could be potential ligand-binding sites in proteins, VisGrid is also aimed to identify large protrusions, hollows, and flat regions, which can characterize geometric features of a protein structure. The visibility used in VisGrid is defined as the fraction of visible directions from a target position on a protein surface. A pocket or a hollow is recognized as a cluster of positions with a small visibility. A large protrusion in a protein structure is recognized as a pocket in the negative image of the structure. VisGrid correctly identified 95.0% of ligand-binding sites as one of the three largest pockets in 5616 benchmark proteins. To examine how natural flexibility of proteins affects pocket identification, VisGrid was tested on distorted structures by molecular dynamics simulation. Sensitivity decreased approximately 20% for structures of a root mean square deviation of 2.0 A to the original crystal structure, but specificity was not much affected. Because of its intuitiveness and simplicity, the visibility criterion will lay the foundation for characterization and function annotation of local shape of proteins.

Bridging protein local structures and protein functions

One of the major goals of molecular and evolutionary biology is to understand the functions of proteins by extracting functional information from protein sequences, structures and interactions. In this review, we summarize the repertoire of methods currently being applied and report recent progress in the field of in silico annotation of protein function based on the accumulation of vast amounts of sequence and structure data. In particular, we emphasize the newly developed structure-based methods, which are able to identify locally structural motifs and reveal their relationship with protein functions. These methods include computational tools to identify the structural motifs and reveal the strong relationship between these pre-computed local structures and protein functions. We also discuss remaining problems and possible directions for this exciting and challenging area.

Tandem duplication, circular permutation, molecular adaptation: how Solanaceae resist pests via inhibitors

Background

The Potato type II (Pot II) family of proteinase inhibitors plays critical roles in the defense system of plants from Solanaceae family against pests. To better understand the evolution of this family, we investigated the correlation between sequence and structural repeats within this family and the evolution and molecular adaptation of Pot II genes through computational analysis, using the putative ancestral domain sequence as the basic repeat unit.

Results

Our analysis discovered the following interesting findings in Pot II family. (1) We classified the structural domains in Pot II family into three types (original repeat domain, circularly permuted domain, the two-chain domain) according to the existence of two linkers between the two domain components, which clearly show the circular permutation relationship between the original repeat domain and circularly permuted domain. (2) The permuted domains appear more stable than original repeat domain, from available structural information. Therefore, we proposed a multiple-repeat sequence is likely to adopt the permuted domain from contiguous sequence segments, with the N- and C-termini forming a single non-contiguous structural domain, linking the bracelet of tandem repeats. (3) The analysis of nonsynonymous/synonymous substitution rates ratio in Pot II domain revealed heterogeneous selective pressures among amino acid sites: the reactive site is under positive Darwinian selection (providing different specificity to target varieties of proteinases) while the cysteine scaffold is under purifying selection (essential for maintaining the fold). (4) For multi-repeat Pot II genes from Nicotiana genus, the proteolytic processing site is under positive Darwinian selection (which may improve the cleavage efficiency).

Conclusion

This paper provides comprehensive analysis and characterization of Pot II family, and enlightens our understanding on the strategies (Gene and domain duplication, structural circular permutation and molecular adaptation) of Solanaceae plants for defending pathogenic attacks through the evolution of Pot II genes.

Residue conservation in viral capsid assembly

To evaluate the evolutionary constraints placed on viral proteins by the structure and assembly of the capsid, we calculate Shannon entropies in the aligned sequences of 45 polypeptide chains in 32 icosahedral viruses, and relate these entropies to the residue location in the three-dimensional structure of the capsids. Three categories of residues have entropies lower than the chain average implying that they are better conserved than average: residues that are buried within a subunit (the protein core), residues that contain atoms buried at an interface between subunits (the interface core), and residues that contribute to several such interfaces. The interface core is also conserved in homomeric proteins and in transient protein-protein complexes, which have only one interface whereas capsids have many. In capsids, the subunit interfaces implicate most of the polypeptide chain: on average, 66% of the capsid residues are at an interface, 34% at more than one, and 47% at the interface core. Nevertheless, we observe that the degree of residue conservation can vary widely between interfaces within a capsid and between regions within an interface. The interfaces and regions of interfaces that show a low sequence variability are likely to play major roles in the self-assembly of the capsid, with implications on its mechanism that we discuss taking adeno-associated virus as an example.

Graphical models of residue coupling in protein families

Many statistical measures and algorithmic techniques have been proposed for studying residue coupling in protein families. Generally speaking, two residue positions are considered coupled if, in the sequence record, some of their amino acid type combinations are significantly more common than others. While the proposed approaches have proven useful in finding and describing coupling, a significant missing component is a formal probabilistic model that explicates and compactly represents the coupling, integrates information about sequence,structure, and function, and supports inferential procedures for analysis, diagnosis, and prediction.We present an approach to learning and using probabilistic graphical models of residue coupling. These models capture significant conservation and coupling constraints observable ina multiply-aligned set of sequences. Our approach can place a structural prior on considered couplings, so that all identified relationships have direct mechanistic explanations. It can also incorporate information about functional classes, and thereby learn a differential graphical model that distinguishes constraints common to all classes from those unique to individual classes. Such differential models separately account for class-specific conservation and family-wide coupling, two different sources of sequence covariation. They are then able to perform interpretable functional classification of new sequences, explaining classification decisions in terms of the underlying conservation and coupling constraints. We apply our approach in studies of both G protein-coupled receptors and PDZ domains, identifying and analyzing family-wide and class-specific constraints, and performing functional classification. The results demonstrate that graphical models of residue coupling provide a powerful tool for uncovering, representing, and utilizing significant sequence structure-function relationships in protein families.

Nonspecific base recognition mediated by water bridges and hydrophobic stacking in ribonuclease I from Escherichia coli

The crystal structure of Escherichia coli ribonuclease I (EcRNase I) reveals an RNase T2-type fold consisting of a conserved core of six beta-strands and three alpha-helices. The overall architecture of the catalytic residues is very similar to the plant and fungal RNase T2 family members, but the perimeter surrounding the active site is characterized by structural elements specific for E. coli. In the structure of EcRNase I in complex with a substrate-mimicking decadeoxynucleotide d(CGCGATCGCG), we observe a cytosine bound in the B2 base binding site and mixed binding of thymine and guanine in the B1 base binding site. The active site residues His55, His133, and Glu129 interact with the phosphodiester linkage only through a set of water molecules. Residues forming the B2 base recognition site are well conserved among bacterial homologs and may generate limited base specificity. On the other hand, the B1 binding cleft acquires true base aspecificity by combining hydrophobic van der Waals contacts at its sides with a water-mediated hydrogen-bonding network at the bottom. This B1 base recognition site is highly variable among bacterial sequences and the observed interactions are unique to EcRNaseI and a few close relatives.

Prediction of functional nonsynonymous single nucleotide polymorphisms in human G-protein-coupled receptors

G-protein-coupled receptors (GPCRs) are found in a wide range of organisms and are central to a cellular signaling network that regulates many basic physiological processes. GPCRs are the focus of a significant amount of current pharmaceutical research because they play a key role in many diseases. In this paper, we predict the functional nonsynonymous single nucleotide polymorphisms (nsSNPs) in human GPCRs by defining optimal attributes and using a decision tree method. The predictive power of each attribute was evaluated. A subset of sequences with optimal attributes was obtained using the decision tree method combined with a genetic search algorithm. The subset contains both sequence-based and structure-based information, and the information for each subset consists of a conservation score, the location of the mutation, the BLOSUM62 substitution matrix score, as well as the hydrophobicity change, the solvent accessibility, and the buried charge. Seven important rules were derived from the decision tree. A total of 166 functional nsSNPs in human GPCRs from the dbSNP have been predicted using the optimal attributes subset.

Reverse conservation analysis reveals the specificity determining residues of cytochrome P450 family 2 (CYP 2)

The concept of conservation of amino acids is widely used to identify important alignment positions of orthologs. The assumption is that important amino acid residues will be conserved in the protein family during the evolutionary process. For paralog alignment, on the other hand, the opposite concept can be used to identify residues that are responsible for specificity. Assuming that the function-specific or ligand-specific residue positions will have higher diversity since they are under evolutionary pressure to fit the target specificity, these function-specific or ligand-specific residues positions will have a lower degree of conservation than other positions in a highly conserved paralog alignment. This study assessed the ability of reverse conservation analysis to identify function-specific and ligand-specific residue positions in closely related paralog.

Reverse conservation analysis of paralog alignments successfully identified all six previously reported substrate recognition sites (SRSs) in cytochrome P450 family 2 (CYP 2). Further analysis of each subfamily identified the specificity-determining residues (SDRs) that have been experimentally found. New potential SDRs were also predicted and await confirmation by further experiments or modeling calculations. This concept may be also applied to identify SDRs in other protein families.

Insights into oncogenic mutations of plexin-B1 based on the solution structure of the Rho GTPase binding domain

The plexin family of transmembrane receptors are important for axon guidance, angiogenesis, but also in cancer. Recently, plexin-B1 somatic missense mutations were found in both primary tumors and metastases of breast and prostate cancers, with several mutations mapping to the Rho GTPase binding domain (RBD) in the cytoplasmic region of the receptor. Here we present the NMR solution structure of this domain, confirming that the protein has both a ubiquitin-like fold and surface features. Oncogenic mutations T1795A and T1802A are located in a loop region, perturb the average structure locally, and have no effect on Rho GTPase binding affinity. Mutations L1815F and L1815P are located at the Rho GTPase binding site and are associated with a complete loss of binding for Rac1 and Rnd1. Both are found to disturb the conformation of the beta3-beta4 sheet and the orientation of surrounding side chains. Our study suggests that the oncogenic behavior of the mutants can be rationalized with reference to the structure of the RBD of plexin-B1.

The contrasting properties of conservation and correlated phylogeny in protein functional residue prediction

Background

Amino acids responsible for structure, core function or specificity may be inferred from multiple protein sequence alignments where a limited set of residue types are tolerated. The rise in available protein sequences continues to increase the power of techniques based on this principle.

Results

A new algorithm, SMERFS, for predicting protein functional sites from multiple sequences alignments was compared to 14 conservation measures and to the MINER algorithm. Validation was performed on an automatically generated dataset of 1457 families derived from the protein interactions database SNAPPI-DB, and a smaller manually curated set of 148 families. The best performing measure overall was Williamson property entropy, with ROC_0.1 scores of 0.0087 and 0.0114 for domain and small molecule contact prediction, respectively. The Lancet method performed worse than random on protein-protein interaction site prediction (ROC_0.1 score of 0.0008). The SMERFS algorithm gave similar accuracy to the phylogenetic tree-based MINER algorithm but was superior to Williamson in prediction of non-catalytic transient complex interfaces. SMERFS predicts sites that are significantly more solvent accessible compared to Williamson.

Conclusion

Williamson property entropy is the the best performing of 14 conservation measures examined. The difference in performance of SMERFS relative to Williamson in manually defined complexes was dependent on complex type. The best choice of analysis method is therefore dependent on the system of interest. Additional computation employed by Miner in calculation of phylogenetic trees did not produce improved results over SMERFS. SMERFS performance was improved by use of windows over alignment columns, illustrating the necessity of considering the local environment of positions when assessing their functional significance.

Robustness of the residue conservation score reflecting both frequencies and physicochemistries

Measuring residue conservation at aligned positions has many applications in biology. Recently, a new conservation score has been defined. Unlike the previous methods, the new approach considers both residue frequencies and physicochemistries. Specifically, it measures physicochemistries based on BLOSUM matrices disregarding the meaning of the entries in such matrices, which may involve the problem of log-log probability. In this paper we present a conservation measure that also reflects both frequencies and physicochemistries while considering the fact that the entries of BLOSUM matrices are already interpreted as log probability. When the supposed score is applied to 14 protein examples, the results show that these two conservation scores are equivalent aside from the different score ranges. The method is also used to score the functional sites of three protein families. Compared with the widely used entropy-based methods, the resulting scores are more robust and consistent in the sense that the functional sites are much more conserved because of functional constraints.

APRIN is a unique Pds5 paralog with features of a chromatin regulator in hormonal differentiation

Activation of steroid receptors results in global changes of gene expression patterns. Recent studies showed that steroid receptors control only a portion of their target genes directly, by promoter binding. The majority of the changes are indirect, through chromatin rearrangements. The mediators that relay the hormonal signals to large-scale chromatin changes are, however, unknown. We report here that APRIN, a novel hormone-induced nuclear phosphoprotein has the characteristics of a chromatin regulator and may link endocrine pathways to chromatin. We showed earlier that APRIN is involved in the hormonal regulation of proliferative arrest in cancer cells. To investigate its function we cloned and characterized APRIN orthologs and performed homology and expression studies. APRIN is a paralog of the cohesin-associated Pds5 gene lineage and arose by gene-duplication in early vertebrates. The conservation and domain differences we found suggest, however, that APRIN acquired novel chromatin-related functions (e.g. the HMG-like domains in APRIN, the hallmarks of chromatin regulators, are absent in the Pds5 family). Our results suggest that in interphase nuclei APRIN localizes in the euchromatin/heterochromatin interface and we also identified its DNA-binding and nuclear import signal domains. The results indicate that APRIN, in addition to its Pds5 similarity, has the features and localization of a hormone-induced chromatin regulator.

Predicting and annotating catalytic residues: an information theoretic approach

We introduce a computational method to predict and annotate the catalytic residues of a protein using only its sequence information, so that we describe both the residues' sequence locations (prediction) and their specific biochemical roles in the catalyzed reaction (annotation). While knowing the chemistry of an enzyme's catalytic residues is essential to understanding its function, the challenges of prediction and annotation have remained difficult, especially when only the enzyme's sequence and no homologous structures are available. Our sequence-based approach follows the guiding principle that catalytic residues performing the same biochemical function should have similar chemical environments; it detects specific conservation patterns near in sequence to known catalytic residues and accordingly constrains what combination of amino acids can be present near a predicted catalytic residue. We associate with each catalytic residue a short sequence profile and define a Kullback-Leibler (KL) distance measure between these profiles, which, as we show, effectively captures even subtle biochemical variations. We apply the method to the class of glycohydrolase enzymes. This class includes proteins from 96 families with very different sequences and folds, many of which perform important functions. In a cross-validation test, our approach correctly predicts the location of the enzymes' catalytic residues with a sensitivity of 80% at a specificity of 99.4%, and in a separate cross-validation we also correctly annotate the biochemical role of 80% of the catalytic residues. Our results compare favorably to existing methods. Moreover, our method is more broadly applicable because it relies on sequence and not structure information; it may, furthermore, be used in conjunction with structure-based methods.

Predicting the phenotypic effects of non-synonymous single nucleotide polymorphisms based on support vector machines

BACKGROUND

Human genetic variations primarily result from single nucleotide polymorphisms (SNPs) that occur approximately every 1000 bases in the overall human population. The non-synonymous SNPs (nsSNPs) that lead to amino acid changes in the protein product may account for nearly half of the known genetic variations linked to inherited human diseases. One of the key problems of medical genetics today is to identify nsSNPs that underlie disease-related phenotypes in humans. As such, the development of computational tools that can identify such nsSNPs would enhance our understanding of genetic diseases and help predict the disease.

RESULTS

We propose a method, named Parepro (Predicting the amino acid replacement probability), to identify nsSNPs having either deleterious or neutral effects on the resulting protein function. Two independent datasets, HumVar and NewHumVar, taken from the PhD-SNP server, were applied to train the model and test the robustness of Parepro. Using a 20-fold cross validation test on the HumVar dataset, Parepro achieved a Matthews correlation coefficient (MCC) of 50% and an overall accuracy (Q2) of 76%, both of which were higher than those predicted by the methods, such as PolyPhen, SIFT, and HydridMeth. Further analysis on an additional dataset (NewHumVar) using Parepro yielded similar results.

CONCLUSION

The performance of Parepro indicates that it is a powerful tool for predicting the effect of nsSNPs on protein function and would be useful for large-scale analysis of genomic nsSNP data.