Recognition of analogous and homologous protein folds: analysis of sequence and structure conservation

MALISAM: a database of structurally analogous motifs in proteins

MALISAM (manual alignments for structurally analogous motifs) represents the first database containing pairs of structural analogs and their alignments. To find reliable analogs, we developed an approach based on three ideas. First, an insertion together with a part of the evolutionary core of one domain family (a hybrid motif) is analogous to a similar motif contained within the core of another domain family. Second, a motif at an interface, formed by secondary structural elements (SSEs) contributed by two or more domains or subunits contacting along that interface, is analogous to a similar motif present in the core of a single domain. Third, an artificial protein obtained through selection from random peptides or in sequence design experiments not biased by sequences of a particular homologous family, is analogous to a structurally similar natural protein. Each analogous pair is superimposed and aligned manually, as well as by several commonly used programs. Applications of this database may range from protein evolution studies, e.g. development of remote homology inference tools and discriminators between homologs and analogs, to protein-folding research, since in the absence of evolutionary reasons, similarity between proteins is caused by structural and folding constraints. The database is publicly available at http://prodata.swmed.edu/malisam.

Prediction of apoptosis protein subcellular location using improved hybrid approach and pseudo-amino acid composition

Apoptosis proteins are very important for understanding the mechanism of programmed cell death. The apoptosis protein localization can provide valuable information about its molecular function. The prediction of localization of an apoptosis protein is a challenging task. In our previous work we proposed an increment of diversity (ID) method using protein sequence information for this prediction task. In this work, based on the concept of Chou's pseudo-amino acid composition [Chou, K.C., 2001. Prediction of protein cellular attributes using pseudo-amino acid composition. Proteins: Struct. Funct. Genet. (Erratum: Chou, K.C., 2001, vol. 44, 60) 43, 246-255, Chou, K.C., 2005. Using amphiphilic pseudo-amino acid composition to predict enzyme subfamily classes. Bioinformatics 21, 10-19], a different pseudo-amino acid composition by using the hydropathy distribution information is introduced. A novel ID_SVM algorithm combined ID with support vector machine (SVM) is proposed. This method is applied to three data sets (317 apoptosis proteins, 225 apoptosis proteins and 98 apoptosis proteins). The higher predictive success rates than the previous algorithms are obtained by the jackknife tests.

Comparative analysis of protein structure alignments

Background

Several methods are currently available for the comparison of protein structures. These methods have been analysed regarding the performance in the identification of structurally/evolutionary related proteins, but so far there has been less focus on the objective comparison between the alignments produced by different methods.

Results

We analysed and compared the structural alignments obtained by different methods using three sets of pairs of structurally related proteins. The first set corresponds to 355 pairs of remote homologous proteins according to the SCOP database (ASTRAL40 set). The second set was derived from the SISYPHUS database and includes 69 protein pairs (SISY set). The third set consists of 40 pairs that are challenging to align (RIPC set). The alignment of pairs of this set requires indels of considerable number and size and some of the proteins are related by circular permutations, show extensive conformational variability or include repetitions. Two standard methods (CE and DALI) were applied to align the proteins in the ASTRAL40 set. The extent of structural similarity identified by both methods is highly correlated and the alignments from the two methods agree on average in more than half of the aligned positions. CE, DALI, as well as four additional methods (FATCAT, MATRAS, C_α-match and SHEBA) were then compared using the SISY and RIPC sets. The accuracy of the alignments was assessed by comparison to reference alignments. The alignments generated by the different methods on average match more than half of the reference alignments in the SISY set. The alignments obtained in the more challenging RIPC set tend to differ considerably and match reference alignments less successfully than the SISY set alignments.

Conclusion

The alignments produced by different methods tend to agree to a considerable extent, but the agreement is lower for the more challenging pairs. The results for the comparison to reference alignments are encouraging, but also indicate that there is still room for improvement.

Homology modeling and molecular dynamics simulations of the glycine receptor ligand binding domain

We present a homology based model of the ligand binding domain (LBD) of the homopentameric alpha1 glycine receptor (GlyR). The model is based on multiple sequence alignment with other members of the nicotinicoid ligand gated ion channel superfamily and two homologous acetylcholine binding proteins (AChBP) from the freshwater (Lymnaea stagnalis) and saltwater (Aplysia californica) snails with known high resolution structure. Using two template proteins with known structure to model three dimensional structure of a target protein is especially advantageous for sequences with low homology as in the case presented in this paper. The final model was cross-validated by critical evaluation of experimental and published mutagenesis, functional and other biochemical studies. In addition, a complex structure with strychnine antagonist in the putative binding site is proposed based on docking simulation using Autodock program. Molecular dynamics (MD) simulations with simulated annealing protocol are reported on the proposed LBD of GlyR, which is stable in 5 ns simulation in water, as well as for a deformed LBD structure modeled on the corresponding domain determined in low-resolution cryomicroscopy structure of the alpha subunit of the full-length acetylcholine receptor (AChR). Our simulations demonstrate that the beta-sandwich central core of the protein monomer is fairly rigid in the simulations and resistant to deformations in water.

Comparison of sequence-based and structure-based phylogenetic trees of homologous proteins: Inferences on protein evolution

Several studies based on the known three-dimensional (3-D) structures of proteins show that two homologous proteins with insignificant sequence similarity could adopt a common fold and may perform same or similar biochemical functions. Hence, it is appropriate to use similarities in 3-D structure of proteins rather than the amino acid sequence similarities in modelling evolution of distantly related proteins. Here we present an assessment of using 3-D structures in modelling evolution of homologous proteins. Using a dataset of 108 protein domain families of known structures with at least 10 members per family we present a comparison of extent of structural and sequence dissimilarities among pairs of proteins which are inputs into the construction of phylogenetic trees. We find that correlation between the structure-based dissimilarity measures and the sequence-based dissimilarity measures is usually good if the sequence similarity among the homologues is about 30% or more. For protein families with low sequence similarity among the members, the correlation coefficient between the sequence-based and the structure-based dissimilarities are poor. In these cases the structure-based dendrogram clusters proteins with most similar biochemical functional properties better than the sequence-similarity based dendrogram. In multi-domain protein families and disulphide-rich protein families the correlation coefficient for the match of sequence-based and structure-based dissimilarity (SDM) measures can be poor though the sequence identity could be higher than 30%. Hence it is suggested that protein evolution is best modelled using 3-D structures if the sequence similarities (SSM) of the homologues are very low.

Prediction of the subcellular location of apoptosis proteins

Apoptosis proteins have a central role in the development and the homeostasis of an organism. These proteins are very important for understanding the mechanism of programmed cell death. The function of an apoptosis protein is closely related to its subcellular location. Based on the concept that the subcellular location of an apoptosis protein is mainly determined by its amino acid sequence, a new algorithm for prediction of the subcellular location of an apoptosis protein is proposed. By using of a distinctive set of information parameters derived from the primary sequence of 317 apoptosis proteins, the increment of diversity (ID), the sole prediction parameter, is calculated. The higher predictive success rates than the previous other algorithms is obtained by the jackknife tests using the expanded dataset. Our prediction results show that the local compositions of twin amino acids and hydropathy distribution are very useful to predict subcellular location of protein.

Periodic distributions of hydrophobic amino acids allows the definition of fundamental building blocks to align distantly related proteins

Several studies on large and small families of proteins proved in a general manner that hydrophobic amino acids are globally conserved even if they are subjected to high rate substitution. Statistical analysis of amino acids evolution within blocks of hydrophobic amino acids detected in sequences suggests their usage as a basic structural pattern to align pairs of proteins of less than 25% sequence identity, with no need of knowing their 3D structure. The authors present a new global alignment method and an automatic tool for Proteins with HYdrophobic Blocks ALignment (PHYBAL) based on the combinatorics of overlapping hydrophobic blocks. Two substitution matrices modeling a different selective pressure inside and outside hydrophobic blocks are constructed, the Inside Hydrophobic Blocks Matrix and the Outside Hydrophobic Blocks Matrix, and a 4D space of gap values is explored. PHYBAL performance is evaluated against Needleman and Wunsch algorithm run with Blosum 30, Blosum 45, Blosum 62, Gonnet, HSDM, PAM250, Johnson and Remote Homo matrices. PHYBAL behavior is analyzed on eight randomly selected pairs of proteins of >30% sequence identity that cover a large spectrum of structural properties. It is also validated on two large datasets, the 127 pairs of the Domingues dataset with >30% sequence identity, and 181 pairs issued from BAliBASE 2.0 and ranked by percentage of identity from 7 to 25%. Results confirm the importance of considering substitution matrices modeling hydrophobic contexts and a 4D space of gap values in aligning distantly related proteins. Two new notions of local and global stability are defined to assess the robustness of an alignment algorithm and the accuracy of PHYBAL. A new notion, the SAD-coefficient, to assess the difficulty of structural alignment is also introduced. PHYBAL has been compared with Hydrophobic Cluster Analysis and HMMSUM methods.

Evolutionary conservation of protein backbone flexibility

Internal protein dynamics is essential for biological function. During evolution, protein divergence is functionally constrained: properties more relevant for function vary more slowly than less important properties. Thus, if protein dynamics is relevant for function, it should be evolutionary conserved. In contrast with the well-studied evolution of protein structure, the evolutionary divergence of protein dynamics has not been addressed systematically before, apart from a few case studies. X-Ray diffraction analysis gives information not only on protein structure but also on B-factors, which characterize the flexibility that results from protein dynamics. Here we study the evolutionary divergence of protein backbone dynamics by comparing the C(alpha) flexibility (B-factor) profiles for a large dataset of homologous proteins classified into families and superfamilies. We show that C(alpha) flexibility profiles diverge slowly, so that they are conserved at family and superfamily levels, even for pairs of proteins with nonsignificant sequence similarity. We also analyze and discuss the correlations among the divergences of flexibility, sequence, and structure.

NdPASA: a novel pairwise protein sequence alignment algorithm that incorporates neighbor-dependent amino acid propensities

Sequence alignment has become one of the essential bioinformatics tools in biomedical research. Existing sequence alignment methods can produce reliable alignments for homologous proteins sharing a high percentage of sequence identity. The performance of these methods deteriorates sharply for the sequence pairs sharing less than 25% sequence identity. We report here a new method, NdPASA, for pairwise sequence alignment. This method employs neighbor-dependent propensities of amino acids as a unique parameter for alignment. The values of neighbor-dependent propensity measure the preference of an amino acid pair adopting a particular secondary structure conformation. NdPASA optimizes alignment by evaluating the likelihood of a residue pair in the query sequence matching against a corresponding residue pair adopting a particular secondary structure in the template sequence. Using superpositions of homologous proteins derived from the PSI-BLAST analysis and the Structural Classification of Proteins (SCOP) classification of a nonredundant Protein Data Bank (PDB) database as a gold standard, we show that NdPASA has improved pairwise alignment. Statistical analyses of the performance of NdPASA indicate that the introduction of sequence patterns of secondary structure derived from neighbor-dependent sequence analysis clearly improves alignment performance for sequence pairs sharing less than 20% sequence identity. For sequence pairs sharing 13-21% sequence identity, NdPASA improves the accuracy of alignment over the conventional global alignment (GA) algorithm using the BLOSUM62 by an average of 8.6%. NdPASA is most effective for aligning query sequences with template sequences whose structure is known. NdPASA can be accessed online at http://astro.temple.edu/feng/Servers/BioinformaticServers.htm.

Evolutionary plasticity of protein families: coupling between sequence and structure variation

In this work we examine how protein structural changes are coupled with sequence variation in the course of evolution of a family of homologs. The sequence-structure correlation analysis performed on 81 homologous protein families shows that the majority of them exhibit statistically significant linear correlation between the measures of sequence and structural similarity. We observed, however, that there are cases where structural variability cannot be mainly explained by sequence variation, such as protein families with a number of disulfide bonds. To understand whether structures from different families and/or folds evolve in the same manner, we compared the degrees of structural change per unit of sequence change ("the evolutionary plasticity of structure") between those families with a significant linear correlation. Using rigorous statistical procedures we find that, with a few exceptions, evolutionary plasticity does not show a statistically significant difference between protein families. Similar sequence-structure analysis performed for protein loop regions shows that evolutionary plasticity of loop regions is greater than for the protein core.

Divergent evolution within protein superfolds inferred from profile-based phylogenetics

Many dissimilar protein sequences fold into similar structures. A central and persistent challenge facing protein structural analysis is the discrimination between homology and convergence for structurally similar domains that lack significant sequence similarity. Classic examples are the OB-fold and SH3 domains, both small, modular beta-barrel protein superfolds. The similarities among these domains have variously been attributed to common descent or to convergent evolution. Using a sequence profile-based phylogenetic technique, we analyzed all structurally characterized OB-fold, SH3, and PDZ domains with less than 40% mutual sequence identity. An all-against-all, profile-versus-profile analysis of these domains revealed many previously undetectable significant interrelationships. The matrices of scores were used to infer phylogenies based on our derivation of the relationships between sequence similarity E-values and evolutionary distances. The resulting clades of domains correlate remarkably well with biological function, as opposed to structural similarity, indicating that the functionally distinct sub-families within these superfolds are homologous. This method extends phylogenetics into the challenging "twilight zone" of sequence similarity, providing the first objective resolution of deep evolutionary relationships among distant protein families.

A robust method to detect structural and functional remote homologues

With currently available sequence data, it is feasible to conduct extensive comparisons among large sets of protein sequences. It is still a much more challenging task to partition the protein space into structurally and functionally related families solely based on sequence comparisons. The ProtoNet system automatically generates a treelike classification of the whole protein space. It stands to reason that this classification reflects evolutionary relationships, both close and remote. In this article, we examine this hypothesis. We present a semiautomatic procedure that singles out certain inner nodes in the ProtoNet tree that should ideally correspond to structurally and functionally defined protein families. We compare the performance of this method against several expert systems. Some of the competing methods incorporate additional extraneous information on protein structure or on enzymatic activities. The ProtoNet-based method performs at least as well as any of the methods with which it was compared. This article illustrates the ProtoNet-based method on several evolutionarily diverse families. Using this new method, an evolutionary divergence scheme can be proposed for a large number of structural and functional related superfamilies.

Analysis of protein homology by assessing the (dis)similarity in protein loop regions

Two proteins are considered to have a similar fold if sufficiently many of their secondary structure elements are positioned similarly in space and are connected in the same order. Such a common structural scaffold may arise due to either divergent or convergent evolution. The intervening unaligned regions ("loops") between the superimposable helices and strands can exhibit a wide range of similarity and may offer clues to the structural evolution of folds. One might argue that more closely related proteins differ less in their nonconserved loop regions than distantly related proteins and, at the same time, the degree of variability in the loop regions in structurally similar but unrelated proteins is higher than in homologs. Here we introduce a new measure for structural (dis)similarity in loop regions that is based on the concept of the Hausdorff metric. This measure is used to gauge protein relatedness and is tested on a benchmark of homologous and analogous protein structures. It has been shown that the new measure can distinguish homologous from analogous proteins with the same or higher accuracy than the conventional measures that are based on comparing proteins in structurally aligned regions. We argue that this result can be attributed to the higher sensitivity of the Hausdorff (dis)similarity measure in detecting particularly evident dissimilarities in structures and draw some conclusions about evolutionary relatedness of proteins in the most populated protein folds.

Characterizing conserved structural contacts by pair-wise relative contacts and relative packing groups

To adequately deal with the inherent complexity of interactions between protein side-chains, we develop and describe here a novel method for characterizing protein packing within a fold family. Instead of approaching side-chain interactions absolutely from one residue to another, we instead consider the relative interactions of contacting residue pairs. The basic element, the pair-wise relative contact, is constructed from a sequence alignment and contact analysis of a set of structures and consists of a cluster of similarly oriented, interacting, side-chain pairs. To demonstrate this construct's usefulness in analyzing protein structure, we used the pair-wise relative contacts to analyze two sets of protein structures as defined by SCOP: the diverse globin-like superfamily (126 structures) and the more uniform heme binding globin family (a 94 structure subset of the globin-like superfamily). The superfamily structure set produced 1266 unique pair-wise relative contacts, whereas the family structure subset gave 1001 unique pair-wise relative contacts. For both sets, we show that these constructs can be used to accurately and automatically differentiate between fold classes. Furthermore, these pair-wise relative contacts correlate well with sequence identity and thus provide a direct relationship between changes in sequence and changes in structure. To capture the complexity of protein packing, these pair-wise relative contacts can be superimposed around a single residue to create a multi-body construct called a relative packing group. Construction of convex hulls around the individual packing groups provides a measure of the variation in packing around a residue and defines an approximate volume of space occupied by the groups interacting with a residue. We find that these relative packing groups are useful in understanding the structural quality of sequence or structure alignments. Moreover, they provide context to calculate a value for structural randomness, which is important in properly assessing the quality of a structural alignment. The results of this study provide the framework for future analysis for correlating sequence changes to specific structure changes.

Statistical evaluation of pairwise protein sequence comparison with the Bayesian bootstrap

MOTIVATION

Protein sequence comparison methods are routinely used to infer the intricate network of evolutionary relationships found within the rapidly growing library of protein sequences, and thereby to predict the structure and function of uncharacterized proteins. In the present study, we detail an improved statistical benchmark of pairwise protein sequence comparison algorithms. We use bootstrap resampling techniques to determine standard statistical errors and to estimate the confidence of our conclusions. We show that the underlying structure within benchmark databases causes Efron's standard, non-parametric bootstrap to be biased. Consequently, the standard bootstrap underpredicts average performance when used in the context of evaluating sequence comparison methods. We have developed, as an alternative, an unbiased statistical evaluation based on the Bayesian bootstrap, a resampling method operationally similar to the standard bootstrap.

RESULTS

We apply our analysis to the comparative study of amino acid substitution matrix families and find that using modern matrices results in a small, but statistically significant improvement in remote homology detection compared with the classic PAM and BLOSUM matrices.

AVAILABILITY

The sequence sets and code for performing these analyses are available from http://compbio.berkeley.edu/.

CONTACT

brenner@compbio.berkeley.edu.

Conformational dynamics of the ligand-binding domain of inward rectifier K channels as revealed by molecular dynamics simulations: toward an understanding of Kir channel gating

Inward rectifier (Kir) potassium channels are characterized by two transmembrane helices per subunit, plus an intracellular C-terminal domain that controls channel gating in response to changes in concentration of various ligands. Based on the crystal structure of the tetrameric C-terminal domain of Kir3.1, it is possible to build a homology model of the ATP-binding C-terminal domain of Kir6.2. Molecular dynamics simulations have been used to probe the dynamics of Kir C-terminal domains and to explore the relationship between their dynamics and possible mechanisms of channel gating. Multiple simulations, each of 10 ns duration, have been performed for Kir3.1 (crystal structure) and Kir6.2 (homology model), in both their monomeric and tetrameric forms. The Kir6.2 simulations were performed with and without bound ATP. The results of the simulations reveal comparable conformational stability for the crystal structure and the homology model. There is some decrease in conformational flexibility when comparing the monomers with the tetramers, corresponding mainly to the subunit interfaces in the tetramer. The beta-phosphate of ATP interacts with the side chain of K185 in the Kir6.2 model and simulations. The flexibility of the Kir6.2 tetramer is not changed greatly by the presence of bound ATP, other than in two loop regions. Principal components analysis of the simulated dynamics suggests loss of symmetry in both the Kir3.1 and Kir6.2 tetramers, consistent with "dimer-of-dimers" motion of subunits in C-terminal domains of the corresponding Kir channels. This is suggestive of a gating model in which a transition between exact tetrameric symmetry and dimer-of-dimers symmetry is associated with a change in transmembrane helix packing coupled to gating of the channel. Dimer-of-dimers motion of the C-terminal domain tetramer is also supported by coarse-grained (anisotropic network model) calculations. It is of interest that loss of exact rotational symmetry has also been suggested to play a role in gating in the bacterial Kir homolog, KirBac1.1, and in the nicotinic acetylcholine receptor channel.

Subunit rotation models activation of serotonin 5-HT3AB receptors by agonists

The N-terminal extracellular regions of heterooligomeric 3AB-type human 5-hydroxytryptamine receptors (5-HT3ABR) were modelled based on the crystal structure of snail acetylcholine binding protein AChBP. Stepwise rotation of subunit A by 5 degrees was performed between -10 degrees and 15 degrees to mimic agonist binding and receptor activation. Anticlockwise rotation reduced the size of the binding cavity in interface AB and reorganised the network of hydrogen bonds along the interface. AB subunit dimers with different rotations were applied for docking of ligands with different efficacies: 5-HT, m-chlorophenylbiguanide, SR 57227, quinolinyl piperazine and lerisetron derivatives. All ligands were docked into the dimer with -10 degrees rotation representing ligand-free, open binding cavities similarly, without pharmacological discrimination. Their ammonium ions were in hydrogen bonding distance to the backbone carbonyl of W183. Anticlockwise rotation and contraction of the binding cavity led to distinctive docking interactions of agonists with E129 and cation-pi interactions of their ammonium ions. Side chains of several further amino acids participating in docking (Y143, Y153, Y234 and E236) are in agreement with the effects of point mutations in the binding loops. Our model postulates that 5-HT binds to W183 in a hydrophobic cleft as well as to E236 in a hydrophilic vestibule. Then it elicits anticlockwise rotation to draw in loop C via pi-cation-pi interactions of its ammonium ion with W183 and Y234. Finally, closure of the binding cavity might end in rebinding of 5-HT to E129 in the hydrophilic vestibule.

Functional analysis of a structural model of the ATP-binding site of the KATP channel Kir6.2 subunit

ATP-sensitive potassium (KATP) channels couple cell metabolism to electrical activity by regulating K+ flux across the plasma membrane. Channel closure is mediated by ATP, which binds to the pore-forming subunit (Kir6.2). Here we use homology modelling and ligand docking to construct a model of the Kir6.2 tetramer and identify the ATP-binding site. The model is consistent with a large amount of functional data and was further tested by mutagenesis. Ligand binding occurs at the interface between two subunits. The phosphate tail of ATP interacts with R201 and K185 in the C-terminus of one subunit, and with R50 in the N-terminus of another; the N6 atom of the adenine ring interacts with E179 and R301 in the same subunit. Mutation of residues lining the binding pocket reduced ATP-dependent channel inhibition. The model also suggests that interactions between the C-terminus of one subunit and the 'slide helix' of the adjacent subunit may be involved in ATP-dependent gating. Consistent with a role in gating, mutations in the slide helix bias the intrinsic channel conformation towards the open state.

A new method for identification of protein (sub)families in a set of proteins based on hydropathy distribution in proteins

Structural similarity among proteins is reflected in the distribution of hydropathicity along the amino acids in the protein sequence. Similarities in the hydropathy distributions are obvious for homologous proteins within a protein family. They also were observed for proteins with related structures, even when sequence similarities were undetectable. Here we present a novel method that employs the hydropathy distribution in proteins for identification of (sub)families in a set of (homologous) proteins. We represent proteins as points in a generalized hydropathy space, represented by vectors of specifically defined features. The features are derived from hydropathy of the individual amino acids. Projection of this space onto principal axes reveals groups of proteins with related hydropathy distributions. The groups identified correspond well to families of structurally and functionally related proteins. We found that this method accurately identifies protein families in a set of proteins, or subfamilies in a set of homologous proteins. Our results show that protein families can be identified by the analysis of hydropathy distribution, without the need for sequence alignment.

Generality of the Structurally Constrained Protein Evolution model: assessment on representatives of the four main fold classes

The Structurally Constrained Protein Evolution (SCPE) model simulates protein evolution by introducing random mutations into the evolving sequences and selecting them against too much structural perturbation. Given a single protein structure, the SCPE model can be used to obtain a whole set of site-dependent amino acid substitution matrices. The set of SCPE substitution matrices for a given protein family can be seen as an independent-sites model of evolution for that family. Thus, these matrices can be compared with other substitution-matrix-based models of evolution. So far, SCPE has been tested only on left-handed parallel beta helix (LbetaH) proteins. Here, we address the question of generality by assessing the SCPE model on representatives of the four main classes of folds: alpha, beta, alpha+beta, and alpha/beta. We compare with other models using the likelihood ratio test with parametric bootstrapping. We show that SCPE performs better than the popular JTT model for all cases considered. Furthermore, by considering the relative contributions of mutation and selection, we found that the key to the success of the SCPE model is the selection step.

4SCOPmap: automated assignment of protein structures to evolutionary superfamilies

Background

Inference of remote homology between proteins is very challenging and remains a prerogative of an expert. Thus a significant drawback to the use of evolutionary-based protein structure classifications is the difficulty in assigning new proteins to unique positions in the classification scheme with automatic methods. To address this issue, we have developed an algorithm to map protein domains to an existing structural classification scheme and have applied it to the SCOP database.

Results

The general strategy employed by this algorithm is to combine the results of several existing sequence and structure comparison tools applied to a query protein of known structure in order to find the homologs already classified in SCOP database and thus determine classification assignments. The algorithm is able to map domains within newly solved structures to the appropriate SCOP superfamily level with ~95% accuracy. Examples of correctly mapped remote homologs are discussed. The algorithm is also capable of identifying potential evolutionary relationships not specified in the SCOP database, thus helping to make it better. The strategy of the mapping algorithm is not limited to SCOP and can be applied to any other evolutionary-based classification scheme as well. SCOPmap is available for download.

Conclusion

The SCOPmap program is useful for assigning domains in newly solved structures to appropriate superfamilies and for identifying evolutionary links between different superfamilies.

Sensitivity and selectivity in protein structure comparison

Seven protein structure comparison methods and two sequence comparison programs were evaluated on their ability to detect either protein homologs or domains with the same topology (fold) as defined by the CATH structure database. The structure alignment programs Dali, Structal, Combinatorial Extension (CE), VAST, and Matras were tested along with SGM and PRIDE, which calculate a structural distance between two domains without aligning them. We also tested two sequence alignment programs, SSEARCH and PSI-BLAST. Depending upon the level of selectivity and error model, structure alignment programs can detect roughly twice as many homologous domains in CATH as sequence alignment programs. Dali finds the most homologs, 321-533 of 1120 possible true positives (28.7%-45.7%), at an error rate of 0.1 errors per query (EPQ), whereas PSI-BLAST finds 365 true positives (32.6%), regardless of the error model. At an EPQ of 1.0, Dali finds 42%-70% of possible homologs, whereas Matras finds 49%-57%; PSI-BLAST finds 36.9%. However, Dali achieves >84% coverage before the first error for half of the families tested. Dali and PSI-BLAST find 9.2% and 5.2%, respectively, of the 7056 possible topology pairs at an EPQ of 0.1 and 19.5, and 5.9% at an EPQ of 1.0. Most statistical significance estimates reported by the structural alignment programs overestimate the significance of an alignment by orders of magnitude when compared with the actual distribution of errors. These results help quantify the statistical distinction between analogous and homologous structures, and provide a benchmark for structure comparison statistics.

The structurally constrained protein evolution model accounts for sequence patterns of the LbetaH superfamily

Background

Structure conservation constrains evolutionary sequence divergence, resulting in observable sequence patterns. Most current models of protein evolution do not take structure into account explicitly, being unsuitable for investigating the effects of structure conservation on sequence divergence. To this end, we recently developed the Structurally Constrained Protein Evolution (SCPE) model. The model starts with the coding sequence of a protein with known three-dimensional structure. At each evolutionary time-step of an SCPE simulation, a trial sequence is generated by introducing a random point mutation in the current coding DNA sequence. Then, a "score" for the trial sequence is calculated and the mutation is accepted only if its score is under a given cutoff, λ. The SCPE score measures the distance between the trial sequence and a given reference sequence, given the structure. In our first brief report we used a "global score", in which the same reference sequence, the ancestral one, was used at each evolutionary step. Here, we introduce a new scoring function, the "local score", in which the sequence accepted at the previous evolutionary time-step is used as the reference. We assess the model on the UDP-N-acetylglucosamine acyltransferase (LPXA) family, as in our previous report, and we extend this study to all other members of the left-handed parallel beta helix fold (LβH) superfamily whose structure has been determined.

Results

We studied site-dependent entropies, amino acid probability distributions, and substitution matrices predicted by SCPE and compared with experimental data for several members of the LβH superfamily. We also evaluated structure conservation during simulations. Overall, SCPE outperforms JTT in the description of sequence patterns observed in structurally constrained sites. Maximum Likelihood calculations show that the local-score and global-score SCPE substitution matrices obtained for LPXA outperform the JTT model for the LPXA family and for the structurally constrained sites of class i of other members within the LβH superfamily.

Conclusion

We extended the SCPE model by introducing a new scoring function, the local score. We performed a thorough assessment of the SCPE model on the LPXA family and extended it to all other members of known structure of the LβH superfamily.

Phylogenomics and bioinformatics of SARS-CoV

Tracing the history of molecular changes in coronaviruses using phylogenetic methods can provide powerful insights into the patterns of modification to sequences that underlie alteration to selective pressure and molecular function in the SARS-CoV (severe acute respiratory syndrome coronavirus) genome. The topology and branch lengths of the phylogenetic relationships among the family Coronaviridae, including SARS-CoV, have been estimated using the replicase polyprotein. The spike protein fragments S1 (involved in receptor-binding) and S2 (involved in membrane fusion) have been found to have different mutation rates. Fragment S1 can be further divided into two regions (S1A, which comprises approximately the first 400 nucleotides, and S1B, comprising the next 280) that also show different rates of mutation. The phylogeny presented on the basis of S1B shows that SARS-CoV is closely related to MHV (murine hepatitis virus), which is known to bind the murine receptor CEACAM1. The predicted structure, accessibility and mutation rate of the S1B region is also presented. Because anti-SARS drugs based on S2 heptads have short half-lives and are difficult to manufacture, our findings suggest that the S1B region might be of interest for anti-SARS drug discovery.

FoldMiner: structural motif discovery using an improved superposition algorithm

We report an unsupervised structural motif discovery algorithm, FoldMiner, which is able to detect global and local motifs in a database of proteins without the need for multiple structure or sequence alignments and without relying on prior classification of proteins into families. Motifs, which are discovered from pairwise superpositions of a query structure to a database of targets, are described probabilistically in terms of the conservation of each secondary structure element's position and are used to improve detection of distant structural relationships. During each iteration of the algorithm, the motif is defined from the current set of homologs and is used both to recruit additional homologous structures and to discard false positives. FoldMiner thus achieves high specificity and sensitivity by distinguishing between homologous and nonhomologous structures by the regions of the query to which they align. We find that when two proteins of the same fold are aligned, highly conserved secondary structure elements in one protein tend to align to highly conserved elements in the second protein, suggesting that FoldMiner consistently identifies the same motif in members of a fold. Structural alignments are performed by an improved superposition algorithm, LOCK 2, which detects distant structural relationships by placing increased emphasis on the alignment of secondary structure elements. LOCK 2 obeys several properties essential in automated analysis of protein structure: It is symmetric, its alignments of secondary structure elements are transitive, its alignments of residues display a high degree of transitivity, and its scoring system is empirically found to behave as a metric.

Alpha-kinases: analysis of the family and comparison with conventional protein kinases

Alpha-kinases are a recently discovered family of protein kinases that have no detectable sequence homology to conventional protein kinases (CPKs). They include elongation factor 2 kinase, Dictyostelium myosin heavy chain kinases and many other protein kinases from diverse organisms, as revealed by various genome sequencing projects. Mammals have six alpha-kinases, including two channel-kinases-novel signaling molecules that contain an alpha-kinase domain fused to an ion-channel. Analysis of all known alpha-kinase sequences reveals the presence of several highly conserved motifs. Despite the fact that alpha-kinases have no detectable sequence identity with CPKs, the recently determined three-dimensional structure of the channel-kinase TRPM7/ChaK1 kinase domain reveals that alpha-kinases have a fold very similar to CPKs. Using the structural alignment of channel-kinase TRPM7/ChaK1 with cyclic-AMP dependent kinase, the consensus motifs of alpha-kinases and CPKs were aligned and compared. Remarkably, the majority of structural elements, sequence motifs, and the position of key amino acid residues important for catalysis appear to be very similar in alpha-kinases and CPKs. Differences between alpha-kinases and CPKs, and their possible impact on substrate recognition are discussed.

Serine 171, a conserved residue in the gamma-aminobutyric acid type A (GABAA) receptor gamma2 subunit, mediates subunit interaction and cell surface localization

Serine 171 in the GABA(A) receptor gamma2 subunit is highly conserved in the ligand-gated ion channel superfamily. In this paper, we report that mutating serine 171 within gamma2 to glycine or cysteine prevents the interaction of gamma2 with alpha2 and beta1 when these subunits are co-expressed in human embryo kidney 293 cells, resulting in intracellular retention of gamma2. Structure analysis based on a three-dimensional homology model of gamma2 (Ernst, M., Brauchart, D., Boresch, S., and Sieghart, W. (2003) Neuroscience 119, 933-943) reveals that serine 171 may play a critical role in the formation and stabilization of an exposed turn structure that is part of the subunit interaction site. Mutation of serine 171 in the gamma2 subunit could therefore result in alteration of the structure of the subunit interaction site, preventing correct subunit assembly.

ArchDB: automated protein loop classification as a tool for structural genomics

The annotation of protein function has become a crucial problem with the advent of sequence and structural genomics initiatives. A large body of evidence suggests that protein structural information is frequently encoded in local sequences, and that folds are mainly made up of a number of simple local units of super-secondary structural motifs, consisting of a few secondary structures and their connecting loops. Moreover, protein loops play an important role in protein function. Here we present ArchDB, a classification database of structural motifs, consisting of one loop plus its bracing secondary structures. ArchDB currently contains 12,665 super-secondary elements classified into 1496 motif subclasses. The database provides an easy way to retrieve functional information from protein structures sharing a common motif, to search motifs found in a given SCOP family, superfamily or fold, or to search by keywords on proteins with classified loops. The ArchDB database of loops is located at http://sbi.imim.es/archdb.

The relationship between sequence and interaction divergence in proteins

There is currently a gap in knowledge between complexes of known three-dimensional structure and those known from other experimental methods such as affinity purifications or the two-hybrid system. This gap can sometimes be bridged by methods that extrapolate interaction information from one complex structure to homologues of the interacting proteins. To do this, it is important to know if and when proteins of the same type (e.g. family, superfamily or fold) interact in the same way. Here, we study interactions of known structure to address this question. We found all instances within the structural classification of proteins database of the same domain pairs interacting in different complexes, and then compared them with a simple measure (interaction RMSD). When plotted against sequence similarity we find that close homologues (30-40% or higher sequence identity) almost invariably interact the same way. Conversely, similarity only in fold (i.e. without additional evidence for a common ancestor) is only rarely associated with a similarity in interaction. The results suggest that there is a twilight zone of sequence similarity where it is not possible to say whether or not domains will interact similarly. We also discuss the rare instances of fold similarities interacting the same way, and those where obviously homologous proteins interact differently.

TOUCHSTONE: A unified approach to protein structure prediction

We have applied the TOUCHSTONE structure prediction algorithm that spans the range from homology modeling to ab initio folding to all protein targets in CASP5. Using our threading algorithm PROSPECTOR that does not utilize input from metaservers, one threads against a representative set of PDB templates. If a template is significantly hit, Generalized Comparative Modeling designed to span the range from closely to distantly related proteins from the template is done. This involves freezing the aligned regions and relaxing the remaining structure to accommodate insertions or deletions with respect to the template. For all targets, consensus predicted side chain contacts from at least weakly threading templates are pooled and incorporated into ab initio folding. Often, TOUCHSTONE performs well in the CM to FR categories, with PROSPECTOR showing significant ability to identify analogous templates. When ab initio folding is done, frequently the best models are closer to the native state than the initial template. Among the particularly good predictions are T0130 in the CM/FR category, T0138 in the FR(H) category, T0135 in the FR(A) category, T0170 in the FR/NF category and T0181 in the NF category. Improvements in the approach are needed in the FR/NF and NF categories. Nevertheless, TOUCHSTONE was one of the best performing algorithms over all categories in CASP5.

Relationship between protein structures and disulfide-bonding patterns

We found that that disulfide-bonding patterns can be used to discriminate structure similarity. Our method, based on the hierarchical clustering scheme, is applicable to proteins with two or more disulfide bonds and is able to detect the structural similarities of proteins of low sequence identities (<25%). Our results show the surprisingly close relationship between disulfide-bonding patterns and proteins structures. Our findings should be useful in protein structure modeling.

Comparative modeling of GABA(A) receptors: limits, insights, future developments

GABA(A) receptors are chloride ion channels that mediate fast synaptic transmission and belong to a superfamily of pentameric ligand-gated ion channels. The recently published crystal structure of the acetylcholine binding protein can be used as a template for comparative modeling of the extracellular domain of GABA(A) receptors. In this commentary, difficulties with comparative modeling at low sequence identity are discussed, the degree of structural conservation to be expected within the superfamily is analyzed and numerical estimates of model uncertainties in functional regions are provided. Topography of the binding sites at subunit-interfaces is examined and possible targets for rational mutagenesis studies are suggested. Allosteric motions are considered and a mechanism for mediation of positive cooperativity at the benzodiazepine site is proposed.

Binding Interactions of Antagonists with 5‐Hydroxytryptamine3AReceptor Models

Homology modeling was performed on the N-terminal extracellular regions of human, mouse, and guinea pig 5-hydroxytryptamine type 3A receptors (5-HT3R) based on the 24% sequence homology with and on the crystal structure of the snail acetylcholine binding protein (AChBP). Docking of 5-HT3 antagonists granisetron, tropisetron, ondansetron, dolasetron ('setrons), and (+)-tubocurarine suggests an aromatic binding cleft behind a hydrophilic vestibule. Several intra- and interface interactions, H-bonds, and salt bridges stabilize the pentameric structure and the binding cleft. The planar rings of antagonists are intercalated between aromatic side-chains (W183-Y234, Y143-Y153). S227 donates H-bonds to the carbonyl groups of 'setrons. The tertiary ammonium ions interact with E236, N128 or E129, and/or W90 (cation-pi interaction). This offers a molecular explanation of the pharmacophore models of 5-HT3R antagonists. Docking artifacts suggest some ambiguities in the binding loops A and C of the 5-HT3AR models. Lower potencies of (+)-tubocurarine for human, and those of tropisetron for guinea pig 5-HT3ARs can be attributed to steric differences of I/S230 in the binding cleft and to distinct binding interactions with E229 and S227, respectively. Ligand binding interferes with crucial intra- and interface interactions along the binding cleft.

Identification of residues contributing to the ATP binding site of Kir6.2

The ATP-sensitive potassium (K(ATP)) channel links cell metabolism to membrane excitability. Intracellular ATP inhibits channel activity by binding to the Kir6.2 subunit of the channel, but the ATP binding site is unknown. Using cysteine-scanning mutagenesis and charged thiol-modifying reagents, we identified two amino acids in Kir6.2 that appear to interact directly with ATP: R50 in the N-terminus, and K185 in the C-terminus. The ATP sensitivity of the R50C and K185C mutant channels was increased by a positively charged thiol reagent (MTSEA), and was reduced by the negatively charged reagent MTSES. Comparison of the inhibitory effects of ATP, ADP and AMP after thiol modification suggests that K185 interacts primarily with the beta-phosphate, and R50 with the gamma-phosphate, of ATP. A molecular model of the C-terminus of Kir6.2 (based on the crystal structure of Kir3.1) was constructed and automated docking was used to identify residues interacting with ATP. These results support the idea that K185 interacts with the beta-phosphate of ATP. Thus both N- and C-termini may contribute to the ATP binding site.

The Tudor domain 'Royal Family': Tudor, plant Agenet, Chromo, PWWP and MBT domains

We have identified a family of 'Agenet' domains that are plant-specific homologs of Tudor domains. This finding has been extended, using a combination of sequence- and structure-dependent approaches, to show that the three beta-stranded core regions of Tudor, PWWP, chromatin-binding (Chromo) and MBT domains are homologous because they originate from a common ancestor. In addition, we have revealed pairs of tandem repeats in the fragile X mental retardation protein (FMRP) family that are also members of this Tudor domain 'Royal Family'.

Analysis of protein sequence/structure similarity relationships

Current analyses of protein sequence/structure relationships have focused on expected similarity relationships for structurally similar proteins. To survey and explore the basis of these relationships, we present a general sequence/structure map that covers all combinations of similarity/dissimilarity relationships and provide novel energetic analyses of these relationships. To aid our analysis, we divide protein relationships into four categories: expected/unexpected similarity (S and S(?)) and expected/unexpected dissimilarity (D and D(?)) relationships. In the expected similarity region S, we show that trends in the sequence/structure relation can be derived based on the requirement of protein stability and the energetics of sequence and structural changes. Specifically, we derive a formula relating sequence and structural deviations to a parameter characterizing protein stiffness; the formula fits the data reasonably well. We suggest that the absence of data in region S(?) (high structural but low sequence similarity) is due to unfavorable energetics. In contrast to region S, region D(?) (high sequence but low structural similarity) is well-represented by proteins that can accommodate large structural changes. Our analyses indicate that there are several categories of similarity relationships and that protein energetics provide a basis for understanding these relationships.

Sequence variations within protein families are linearly related to structural variations

It is commonly believed that similarities between the sequences of two proteins infer similarities between their structures. Sequence alignments reliably recognize pairs of protein of similar structures provided that the percentage sequence identity between their two sequences is sufficiently high. This distinction, however, is statistically less reliable when the percentage sequence identity is lower than 30% and little is known then about the detailed relationship between the two measures of similarity. Here, we investigate the inverse correlation between structural similarity and sequence similarity on 12 protein structure families. We define the structure similarity between two proteins as the cRMS distance between their structures. The sequence similarity for a pair of proteins is measured as the mean distance between the sequences in the subsets of sequence space compatible with their structures. We obtain an approximation of the sequence space compatible with a protein by designing a collection of protein sequences both stable and specific to the structure of that protein. Using these measures of sequence and structure similarities, we find that structural changes within a protein family are linearly related to changes in sequence similarity.

One fold with many functions: the evolutionary relationships between TIM barrel families based on their sequences, structures and functions

The eightfold (betaalpha) barrel structure, first observed in triose-phosphate isomerase, occurs ubiquitously in nature. It is nearly always an enzyme and most often involved in molecular or energy metabolism within the cell. In this review we bring together data on the sequence, structure and function of the proteins known to adopt this fold. We highlight the sequence and functional diversity in the 21 homologous superfamilies, which include 76 different sequence families. In many structures, the barrels are "mixed and matched" with other domains generating additional variety. Global and local structure-based alignments are used to explore the distribution of the associated functional residues on this common structural scaffold. Many of the substrates/co-factors include a phosphate moiety, which is usually but not always bound towards the C-terminal end of the sequence. Some, but not all, of these structures, exhibit a structurally conserved "phosphate binding motif". In contrast metal-ligating residues and catalytic residues are distributed along the sequence. However, we also found striking structural superposition of some of these residues. Lastly we consider the possible evolutionary relationships between these proteins, whose sequences are so diverse that even the most powerful approaches find few relationships, yet whose active sites all cluster at one end of the barrel. This extreme example of the "one fold-many functions" paradigm illustrates the difficulty of assigning function through a structural genomics approach for some folds.

The natural history of protein domains

Genome sequencing and structural genomics projects are providing new insights into the evolutionary history ofprote in domains. As methods for sequence and structure comparison improve, more distantly related domains are shown to be homologous. Thus there is a need for domain families to be classified within a hierarchy similar to Linnaeus' Systema Naturae, the classification of species. With such a hierarchy in mind, we discuss the evolution of domains, their combination into proteins, and evidence as to the likely origin of protein domains. We also discuss when and how analysis of domains can be used to understand details of protein function. Unconventional features of domain evolution such as intragenomic competition, domain insertion, horizontal gene transfer, and convergent evolution are seen as analogs of organismal evolutionary events. These parallels illustrate how the concept of domains can be applied to provide insights into evolutionary biology.

Folding mechanism of indole-3-glycerol phosphate synthase from Sulfolobus solfataricus: a test of the conservation of folding mechanisms hypothesis in (beta(alpha))(8) barrels

As a test of the hypothesis that folding mechanisms are better conserved than sequences in TIM barrels, the equilibrium and kinetic folding mechanisms of indole-3-glycerol phosphate synthase (sIGPS) from the thermoacidophilic archaebacterium Sulfolobus solfataricus were compared to the well-characterized models of the alpha subunit of tryptophan synthase (alphaTS) from Escherichia coli. A multifaceted approach combining urea denaturation and far-UV circular dichroism, tyrosine fluorescence total intensity, and tyrosine fluorescence anisotropy was employed. Despite a sequence identity of only 13%, a stable intermediate (I) in sIGPS was found to be similar to a stable intermediate in alphaTS in terms of its thermodynamic properties and secondary structure. Kinetic experiments revealed that the fastest detectable folding event for sIGPS involves a burst-phase (<5ms) reaction that leads directly to the stable intermediate. The slower of two subsequent phases reflects the formation/disruption of an off-pathway dimeric form of I. The faster phase reflects the conversion of I to the native state and is limited by folding under marginally stable conditions and by isomerization or rearrangement under strongly folding conditions. By contrast, alphaTS is thought to fold via an off-pathway burst-phase intermediate whose unfolding controls access to a set of four on-pathway intermediates that comprise the stable equilibrium intermediate. At least three proline isomerization reactions are known to limit their interconversions and lead to a parallel channel mechanism. The simple sequential mechanism deduced for sIGPS reflects the dominance of the on-pathway burst-phase intermediate and the absence of prolyl residues that partition the stable intermediate into kinetically distinguishable species. Comparison of the results for sIGPS and alphaTS demonstrates that the thermodynamic properties and the final steps of the folding reaction are better conserved than the early events. The initial events in folding appear to be more sensitive to the sequence differences between the two TIM barrel proteins.

Structural similarity to link sequence space: new potential superfamilies and implications for structural genomics

The current pace of structural biology now means that protein three-dimensional structure can be known before protein function, making methods for assigning homology via structure comparison of growing importance. Previous research has suggested that sequence similarity after structure-based alignment is one of the best discriminators of homology and often functional similarity. Here, we exploit this observation, together with a merger of protein structure and sequence databases, to predict distant homologous relationships. We use the Structural Classification of Proteins (SCOP) database to link sequence alignments from the SMART and Pfam databases. We thus provide new alignments that could not be constructed easily in the absence of known three-dimensional structures. We then extend the method of Murzin (1993b) to assign statistical significance to sequence identities found after structural alignment and thus suggest the best link between diverse sequence families. We find that several distantly related protein sequence families can be linked with confidence, showing the approach to be a means for inferring homologous relationships and thus possible functions when proteins are of known structure but of unknown function. The analysis also finds several new potential superfamilies, where inspection of the associated alignments and superimpositions reveals conservation of unusual structural features or co-location of conserved amino acids and bound substrates. We discuss implications for Structural Genomics initiatives and for improvements to sequence comparison methods.

Evolutionary relationship between the bacterial HPr kinase and the ubiquitous PEP-carboxykinase: expanding the P-loop nucleotidyl transferase superfamily

Similarities between protein three-dimensional structures can reveal evolutionary and functional relationships not apparent from sequence comparison alone. Here we report such a similarity between the metabolic enzymes histidine phosphocarrier protein kinase (HPrK) and phosphoenolpyruvate carboxykinase (PCK), suggesting that they are evolutionarily related. Current structure classifications place PCK and other P-loop containing nucleotidyl-transferases into different folds. Our comparison of both HPrK and PCK to other P-loop containing proteins reveals that all share a common structural motif consisting of an alphabeta segment containing the P-loop flanked by an additional beta-strand that is adjacent in space, but far apart along the sequence. Analysis also shows that HPrK/PCK differ from other P-loop containing structures no more than they differ from each other. We thus suggest that HPrK and PCK should be classified with other P-loop containing proteins, and that all probably share a common ancestor that probably contained a simple P-loop motif with different protein segments being added or lost over the course of evolution. We used the structure-based sequence alignment containing residues specific to HPrK/PCK to identify additional members of this P-loop containing family.

Amino acid substitution matrices from an artificial neural network model

An amino acid substitution matrix specifies probabilities of substitutions for each pair of the 20 amino acids. Log-odds scores transformed from the values in substitution matrices are widely used to construct protein sequence alignments. Any given substitution matrix is suited to matching sequences diverged by a specific evolutionary distance. However, for a given set of sequences, it is not always clear what matrix should be used. We used an artificial neural network model to predict probabilities of amino acid substitutions with alignment samples of different evolutionary distances. From this internal description, substitution matrices suitable for detecting relationships at any chosen evolutionary distance can be instantly generated. By using the additional information of evolutionary distances, the average cross entropy error of our neural network model is lower than that of a series of BLOSUM and PET matrices over all testing sets. Our model is more accurate on the prediction of amino acid substitution probabilities.

Models of the extracellular domain of the nicotinic receptors and of agonist- and Ca2+-binding sites

We constructed a three-dimensional model of the amino-terminal extracellular domain of three major types of nicotinic acetylcholine receptor, (alpha7)5, (alpha4)2(beta2)3, and (alpha1)2beta1gammadelta, on the basis of the recent x-ray structure determination of the molluscan acetylcholine-binding protein. Comparative analysis of the three models reveals that the agonist-binding pocket is much more conserved than the overall structure. Differences exist, however, in the side chains of several residues. In particular, a phenylalanine residue, present in beta2 but not in alpha7, is proposed to contribute to the high affinity for agonists in receptors containing the beta2 subunit. The semiautomatic docking of agonists in the ligand-binding pocket of (alpha7)5 led to positions consistent with labeling and mutagenesis experiments. Accordingly, the quaternary ammonium head group of nicotine makes a pi-cation interaction with W148 (alpha7 numbering), whereas the pyridine ring is close to both the cysteine pair 189-190 and the complementary component of the binding site. The intrinsic affinities inferred from docking give a rank order epibatidine > nicotine > acetylcholine, in agreement with experimental values. Finally, our models offer a structural basis for potentiation by external Ca2+.

The 2.0-A crystal structure of tachylectin 5A provides evidence for the common origin of the innate immunity and the blood coagulation systems

Because invertebrates lack an adaptive immune system, they had to evolve effective intrinsic defense strategies against a variety of microbial pathogens. This ancient form of host defense, the innate immunity, is present in all multicellular organisms including humans. The innate immune system of the Japanese horseshoe crab Tachypleus tridentatus, serving as a model organism, includes a hemolymph coagulation system, which participates both in defense against microbes and in hemostasis. Early work on the evolution of vertebrate fibrinogen suggested a common origin of the arthropod hemolymph coagulation and the vertebrate blood coagulation systems. However, this conjecture could not be verified by comparing the structures of coagulogen, the clotting protein of the horseshoe crab, and of mammalian fibrinogen. Here we report the crystal structure of tachylectin 5A (TL5A), a nonself-recognizing lectin from the hemolymph plasma of T. tridentatus. TL5A shares not only a common fold but also related functional sites with the gamma fragment of mammalian fibrinogen. Our observations provide the first structural evidence of a common ancestor for the innate immunity and the blood coagulation systems.

Annotation transfer for genomics: measuring functional divergence in multi-domain proteins

Annotation transfer is a principal process in genome annotation. It involves "transferring" structural and functional annotation to uncharacterized open reading frames (ORFs) in a newly completed genome from experimentally characterized proteins similar in sequence. To prevent errors in genome annotation, it is important that this process be robust and statistically well-characterized, especially with regard to how it depends on the degree of sequence similarity. Previously, we and others have analyzed annotation transfer in single-domain proteins. Multi-domain proteins, which make up the bulk of the ORFs in eukaryotic genomes, present more complex issues in functional conservation. Here we present a large-scale survey of annotation transfer in these proteins, using scop superfamilies to define domain folds and a thesaurus based on SWISS-PROT keywords to define functional categories. Our survey reveals that multi-domain proteins have significantly less functional conservation than single-domain ones, except when they share the exact same combination of domain folds. In particular, we find that for multi-domain proteins, approximate function can be accurately transferred with only 35% certainty for pairs of proteins sharing one structural superfamily. In contrast, this value is 67% for pairs of single-domain proteins sharing the same structural superfamily. On the other hand, if two multi-domain proteins contain the same combination of two structural superfamilies the probability of their sharing the same function increases to 80% in the case of complete coverage along the full length of both proteins, this value increases further to > 90%. Moreover, we found that only 70 of the current total of 455 structural superfamilies are found in both single and multi-domain proteins and only 14 of these were associated with the same function in both categories of proteins. We also investigated the degree to which function could be transferred between pairs of multi-domain proteins with respect to the degree of sequence similarity between them, finding that functional divergence at a given amount of sequence similarity is always about two-fold greater for pairs of multi-domain proteins (sharing similarity over a single domain) in comparison to pairs of single-domain ones, though the overall shape of the relationship is quite similar. Further information is available at http://partslist.org/func or http://bioinfo.mbb.yale.edu/partslist/func.

Review: what can structural classifications reveal about protein evolution?

In this article we present a review of the methods used for comparing and classifying protein structures. We discuss the hierarchies and populations of fold groups and evolutionary families in some of the major classifications and we consider some of the problems confronting any general analyses of structural evolution in protein families. We also review some more recent analyses that have expanded these classifications by identifying sequence relatives in the genomes and thereby reveal interesting trends in fold usage and recurrence.

On the evolution of protein folds: are similar motifs in different protein folds the result of convergence, insertion, or relics of an ancient peptide world?

This paper presents and discusses evidence suggesting how the diversity of domain folds in existence today might have evolved from peptide ancestors. We apply a structure similarity detection method to detect instances where localized regions of different protein folds contain highly similar sequences and structures. Results of performing an all-on-all comparison of known structures are described and compared with other recently published findings. The numerous instances of local sequence and structure similarities within different protein folds, together with evidence from proteins containing sequence and structure repeats, argues in favor of the evolution of modern single polypeptide domains from ancient short peptide ancestors (antecedent domain segments (ADSs)). In this model, ancient protein structures were formed by self-assembling aggregates of short polypeptides. Subsequently, and perhaps concomitantly with the evolution of higher fidelity DNA replication and repair systems, single polypeptide domains arose from the fusion of ADSs genes. Thus modern protein domains may have a polyphyletic origin.

Classification of protein disulphide-bridge topologies

The preferential occurrence of certain disulphide-bridge topologies in proteins has prompted us to design a method and a program, KNOT-MATCH, for their classification. The program has been applied to a database of proteins with less than 65% homology and more than two disulphide bridges. We have investigated whether there are topological preferences that can be used to group proteins and if these can be applied to gain insight into the structural or functional relationships among them. The classification has been performed by Density Search and Hierarchical Clustering Techniques, yielding thirteen main protein classes from the superimposition and clustering process. It is noteworthy that besides the disulphide bridges, regular secondary structures and loops frequently become correctly aligned. Although the lack of significant sequence similarity among some clustered proteins precludes the easy establishment of evolutionary relationships, the program permits us to find out important structural or functional residues upon the superimposition of two protein structures apparently unrelated. The derived classification can be very useful for finding relationships among proteins which would escape detection by current sequence or topology-based analytical algorithms.