Automatic assessment of alignment quality

Multiple sequence alignments play a central role in the annotation of novel genomes. Given the biological and computational complexity of this task, the automatic generation of high-quality alignments remains challenging. Since multiple alignments are usually employed at the very start of data analysis pipelines, it is crucial to ensure high alignment quality. We describe a simple, yet elegant, solution to assess the biological accuracy of alignments automatically. Our approach is based on the comparison of several alignments of the same sequences. We introduce two functions to compare alignments: the average overlap score and the multiple overlap score. The former identifies difficult alignment cases by expressing the similarity among several alignments, while the latter estimates the biological correctness of individual alignments. We implemented both functions in the MUMSA program and demonstrate the overall robustness and accuracy of both functions on three large benchmark sets.     

The structural alignment between two proteins: is there a unique answer?

Structurally similar but sequentially unrelated proteins have been discovered and rediscovered by many researchers, using a variety of structure comparison tools. For several pairs of such proteins, existing structural alignments obtained from the literature, as well as alignments prepared using several different similarity criteria, are compared with each other. It is shown that, in general, they differ from each other, with differences increasing with diminishing sequence similarity. Differences are particularly strong between alignments optimizing global similarity measures, such as RMS deviation between C alpha atoms, and alignments focusing on more local features, such as packing or interaction pattern similarity. Simply speaking, by putting emphasis on different aspects of structure, different structural alignments show the unquestionable similarity in a different way. With differences between various alignments extending to a point where they can differ at all positions, analysis of structural similarities leads to contradictory results reported by groups using different alignment techniques. The problem of uniqueness and stability of structural alignments is further studied with the help of visualization of the suboptimal alignments. It is shown that alignments are often degenerate and whole families of alignments can be generated with almost the same score as the "optimal alignment." However, for some similarity criteria, specially those based on side-chain positions, rather than C alpha positions, alignments in some areas of the protein are unique. This opens the question of how and if the structural alignments can be used as "standards of truth" for protein comparison.     

Improving the alignment quality of consistency based aligners with an evaluation function using synonymous protein words

Most sequence alignment tools can successfully align protein sequences with higher levels of sequence identity. The accuracy of corresponding structure alignment, however, decreases rapidly when considering distantly related sequences (<20% identity). In this range of identity, alignments optimized so as to maximize sequence similarity are often inaccurate from a structural point of view. Over the last two decades, most multiple protein aligners have been optimized for their capacity to reproduce structure-based alignments while using sequence information. Methods currently available differ essentially in the similarity measurement between aligned residues using substitution matrices, Fourier transform, sophisticated profile-profile functions, or consistency-based approaches, more recently.In this paper, we present a flexible similarity measure for residue pairs to improve the quality of protein sequence alignment. Our approach, called SymAlign, relies on the identification of conserved words found across a sizeable fraction of the considered dataset, and supported by evolutionary analysis. These words are then used to define a position specific substitution matrix that better reflects the biological significance of local similarity. The experiment results show that the SymAlign scoring scheme can be incorporated within T-Coffee to improve sequence alignment accuracy. We also demonstrate that SymAlign is less sensitive to the presence of structurally non-similar proteins. In the analysis of the relationship between sequence identity and structure similarity, SymAlign can better differentiate structurally similar proteins from non- similar proteins. We show that protein sequence alignments can be significantly improved using a similarity estimation based on weighted n-grams. In our analysis of the alignments thus produced, sequence conservation becomes a better indicator of structural similarity. SymAlign also provides alignment visualization that can display sub-optimal alignments on dot-matrices. The visualization makes it easy to identify well-supported alternative alignments that may not have been identified by dynamic programming. SymAlign is available at http://bio-cluster.iis.sinica.edu.tw/SymAlign/.     

Statistical potential-based amino acid similarity matrices for aligning distantly related protein sequences

Aligning distantly related protein sequences is a long-standing problem in bioinformatics, and a key for successful protein structure prediction. Its importance is increasing recently in the context of structural genomics projects because more and more experimentally solved structures are available as templates for protein structure modeling. Toward this end, recent structure prediction methods employ profile-profile alignments, and various ways of aligning two profiles have been developed. More fundamentally, a better amino acid similarity matrix can improve a profile itself; thereby resulting in more accurate profile-profile alignments. Here we have developed novel amino acid similarity matrices from knowledge-based amino acid contact potentials. Contact potentials are used because the contact propensity to the other amino acids would be one of the most conserved features of each position of a protein structure. The derived amino acid similarity matrices are tested on benchmark alignments at three different levels, namely, the family, the superfamily, and the fold level. Compared to BLOSUM45 and the other existing matrices, the contact potential-based matrices perform comparably in the family level alignments, but clearly outperform in the fold level alignments. The contact potential-based matrices perform even better when suboptimal alignments are considered. Comparing the matrices themselves with each other revealed that the contact potential-based matrices are very different from BLOSUM45 and the other matrices, indicating that they are located in a different basin in the amino acid similarity matrix space.     

Structural alignment of ferredoxin and flavodoxin based on electrostatic potentials: implications for their interactions with photosystem I and ferredoxin-NADP reductase

The two proteins ferredoxin and flavodoxin can replace each other in the photosynthetic electron transfer chain of cyanobacteria and algae. However, structure, size, and composition of ferredoxin and flavodoxin are completely different. Ferredoxin is a small iron-sulfur protein (approximately 100 amino acids), whereas flavodoxin is a flavin-containing protein (approximately 170 amino acids). The crystal structure of both proteins from the cyanobacteria Anabeana PCC 7120 is known. We used these two protein structures to investigate the structural basis of their functional equivalence. We apply the Hodgkin index to quantify the similarity of their electrostatic potentials. The technique has been applied successfully in indirect drug design for the alignment of small molecule and bioisosterism elucidation. It requires no predefined atom-atom correspondences. As is known from experiments, electrostatic interactions are most important for the association of ferredoxin and flavodoxin with their reaction partners photosystem I and ferredoxin-NADP reductase. Therefore, use of electrostatic potentials for the structural alignment is well justified. Our extensive search of the alignment space reveals two alignments with a high degree of similarity in the electrostatic potential. In both alignments, ferredoxin overlaps completely with flavodoxin. The active sites of ferredoxin and flavodoxin rather than their centers of mass coincide in both alignments. This is in agreement with electron microscopy investigations on photosystem I cross-linked to ferredoxin or flavodoxin. We identify residues that may have the same function in both proteins and relate our results to previous experimental data.     

An alternative view of protein fold space

Comparing and subsequently classifying protein structures information has received significant attention concurrent with the increase in the number of experimentally derived 3-dimensional structures. Classification schemes have focused on biological function found within protein domains and on structure classification based on topology. Here an alternative view is presented that groups substructures. Substructures are long (50-150 residue) highly repetitive near-contiguous pieces of polypeptide chain that occur frequently in a set of proteins from the PDB defined as structurally non-redundant over the complete polypeptide chain. The substructure classification is based on a previously reported Combinatorial Extension (CE) algorithm that provides a significantly different set of structure alignments than those previously described, having, for example, only a 40% overlap with FSSP. Qualitatively the algorithm provides longer contiguous aligned segments at the price of a slightly higher root-mean-square deviation (rmsd). Clustering these alignments gives a discreet and highly repetitive set of substructures not detectable by sequence similarity alone. In some cases different substructures represent all or different parts of well known folds indicative of the Russian doll effect--the continuity of protein fold space. In other cases they fall into different structure and functional classifications. It is too early to determine whether these newly classified substructures represent new insights into the evolution of a structural framework important to many proteins. What is apparent from on-going work is that these substructures have the potential to be useful probes in finding remote sequence homology and in structure prediction studies. The characteristics of the complete all-by-all comparison of the polypeptide chains present in the PDB and details of the filtering procedure by pair-wise structure alignment that led to the emergent substructure gallery are discussed. Substructure classification, alignments, and tools to analyze them are available at http://cl.sdsc.edu/ce.html.     

Within the twilight zone: a sensitive profile-profile comparison tool based on information theory

This paper presents a novel approach to profile-profile comparison. The method compares two input profiles (like those that are generated by PSI-BLAST) and assigns a similarity score to assess their statistical similarity. Our profile-profile comparison tool, which allows for gaps, can be used to detect weak similarities between protein families. It has also been optimized to produce alignments that are in very good agreement with structural alignments. Tests show that the profile-profile alignments are indeed highly correlated with similarities between secondary structure elements and tertiary structure. Exhaustive evaluations show that our method is significantly more sensitive in detecting distant homologies than the popular profile-based search programs PSI-BLAST and IMPALA. The relative improvement is the same order of magnitude as the improvement of PSI-BLAST relative to BLAST. Our new tool often detects similarities that fall within the twilight zone of sequence similarity.     

Vorolign--fast structural alignment using Voronoi contacts

Vorolign, a fast and flexible structural alignment method for two or more protein structures is introduced. The method aligns protein structures using double dynamic programming and measures the similarity of two residues based on the evolutionary conservation of their corresponding Voronoi-contacts in the protein structure. This similarity function allows aligning protein structures even in cases where structural flexibilities exist. Multiple structural alignments are generated from a set of pairwise alignments using a consistency-based, progressive multiple alignment strategy. RESULTS: The performance of Vorolign is evaluated for different applications of protein structure comparison, including automatic family detection as well as pairwise and multiple structure alignment. Vorolign accurately detects the correct family, superfamily or fold of a protein with respect to the SCOP classification on a set of difficult target structures. A scan against a database of >4000 proteins takes on average 1 min per target. The performance of Vorolign in calculating pairwise and multiple alignments is found to be comparable with other pairwise and multiple protein structure alignment methods. AVAILABILITY: Vorolign is freely available for academic users as a web server at http://www.bio.ifi.lmu.de/Vorolign     

Protein sequence threading: Averaging over structures

Multiple sequence alignments are a routine tool in protein fold recognition, but multiple structure alignments are computationally less cooperative. This work describes a method for protein sequence threading and sequence-to-structure alignments that uses multiple aligned structures, the aim being to improve models from protein threading calculations. Sequences are aligned into a field due to corresponding sites in homologous proteins. On the basis of a test set of more than 570 protein pairs, the procedure does improve alignment quality, although no more than averaging over sequences. For the force field tested, the benefit of structure averaging is smaller than that of adding sequence similarity terms or a contribution from secondary structure predictions. Although there is a significant improvement in the quality of sequence-to-structure alignments, this does not directly translate to an immediate improvement in fold recognition capability.     

Consistency analysis of similarity between multiple alignments: prediction of protein function and fold structure from analysis of local sequence motifs

A new method to analyze the similarity between multiply aligned protein motifs (blocks) was developed. It identifies sets of consistently aligned blocks. These are found to be protein regions of similar function and structure that appear in different contexts. For example, the Rossmann fold ligand-binding region is found similar to TIM barrel and methylase regions, various protein families are predicted to have a TIM-barrel fold and the structural relation between the ClpP protease and crotonase folds is identified from their sequence. Besides identifying local structure features, sequence similarity across short sequence-regions (less than 20 amino acid regions) also predicts structure similarity of whole domains (folds) a few hundred amino acid residues long. Most of these relations could not be identified by other advanced sequence-to-sequence or sequence-to-multiple alignments comparisons. We describe the method (termed CYRCA), present examples of our findings, and discuss their implications.     

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.     

Multiple protein sequence alignment from tertiary structure comparison: assignment of global and residue confidence levels.

An algorithm is presented for the accurate and rapid generation of multiple protein sequence alignments from tertiary structure comparisons. A preliminary multiple sequence alignment is performed using sequence information, which then determines an initial superposition of the structures. A structure comparison algorithm is applied to all pairs of proteins in the superimposed set and a similarity tree calculated. Multiple sequence alignments are then generated by following the tree from the branches to the root. At each branchpoint of the tree, a structure-based sequence alignment and coordinate transformations are output, with the multiple alignment of all structures output at the root. The algorithm encoded in STAMP (STructural Alignment of Multiple Proteins) is shown to give alignments in good agreement with published structural accounts within the dehydrogenase fold domains, globins, and serine proteinases. In order to reduce the need for visual verification, two similarity indices are introduced to determine the quality of each generated structural alignment. Sc quantifies the global structural similarity between pairs or groups of proteins, whereas Pij' provides a normalized measure of the confidence in the alignment of each residue. STAMP alignments have the quality of each alignment characterized by Sc and Pij' values and thus provide a reproducible resource for studies of residue conservation within structural motifs.     

Codep: maximizing co-evolutionary interdependencies to discover interacting proteins

Approaches for the determination of interacting partners from different protein families (such as ligands and their receptors) have made use of the property that interacting proteins follow similar patterns and relative rates of evolution. Interacting protein partners can then be predicted from the similarity of their phylogenetic trees or evolutionary distances matrices. We present a novel method called Codep, for the determination of interacting protein partners by maximizing co-evolutionary signals. The order of sequences in the multiple sequence alignments from two protein families is determined in such a manner as to maximize the similarity of substitution patterns at amino acid sites in the two alignments and, thus, phylogenetic congruency. This is achieved by maximizing the total number of interdependencies of amino acids sites between the alignments. Once ordered, the corresponding sequences in the two alignments indicate the predicted interacting partners. We demonstrate the efficacy of this approach with computer simulations and in analyses of several protein families. A program implementing our method, Codep, is freely available to academic users from our website: http://www.uhnresearch.ca/labs/tillier/.     

Long-term overlap of social and genetic structure in free-ranging house mice reveals dynamic seasonal and group size effects

Associating with relatives in social groups can bring benefits such as reduced risk of aggression and increased likelihood of cooperation.Competition among relatives over limited resources,on the other hand,can induce individuals to alter their patterns of association.Population density might further affect the costs and benefits of associating with relatives by altering resource competition or by changing the structure of social groups;preventing easy association with relatives.Consequently,the overlap between genetic and social structure is expected to decrease with increasing population size,as well as during times of increased breeding activity.Here,we use multi-layer network techniques to quantify the similarity between long-term,high resolution genetic,and behavioral data from a large population of free-ranging house mice(Mus musculus domesticus),studied over 10years.We infer how the benefit of associating with genetically similar individuals might fluctuate in relation to breeding behavior and environmental conditions.We found a clear seasonal effect,with decreased overlap between social and genetic structure during summer months,characterized by high temperatures and high breeding activity.Though the effect of overall population size was relatively weak,we found a clear decrease in the overlap between genetic similarity and social associations within larger groups.As well as longer-term within-group changes,these results reveal population-wide short-term shifts in how individuals associate with relatives.Our study suggests that resource competition modifies the trade-off between the costs and benefits of interacting with relatives.     

Structure-derived substitution matrices for alignment of distantly related sequences

Sequence alignment is a standard method to infer evolutionary, structural, and functional relationships among sequences. The quality of alignments depends on the substitution matrix used. Here we derive matrices based on superimpositions from protein pairs of similar structure, but of low or no sequence similarity. In a performance test the matrices are compared with 12 other previously published matrices. It is found that the structure-derived matrices are applicable for comparisons of distantly related sequences. We investigate the influence of evolutionary relationships of protein pairs on the alignment accuracy.     

Use of a database of structural alignments and phylogenetic trees in investigating the relationship between sequence and structural variability among homologous proteins

The database PALI (Phylogeny and ALIgnment of homologous protein structures) consists of families of protein domains of known three-dimensional (3D) structure. In a PALI family, every member has been structurally aligned with every other member (pairwise) and also simultaneous superposition (multiple) of all the members has been performed. The database also contains 3D structure-based and structure-dependent sequence similarity-based phylogenetic dendrograms for all the families. The PALI release used in the present analysis comprises 225 families derived largely from the HOMSTRAD and SCOP databases. The quality of the multiple rigid-body structural alignments in PALI was compared with that obtained from COMPARER, which encodes a procedure based on properties and relationships. The alignments from the two procedures agreed very well and variations are seen only in the low sequence similarity cases often in the loop regions. A validation of Direct Pairwise Alignment (DPA) between two proteins is provided by comparing it with Pairwise alignment extracted from Multiple Alignment of all the members in the family (PMA). In general, DPA and PMA are found to vary rarely. The ready availability of pairwise alignments allows the analysis of variations in structural distances as a function of sequence similarities and number of topologically equivalent Calpha atoms. The structural distance metric used in the analysis combines root mean square deviation (r.m.s.d.) and number of equivalences, and is shown to vary similarly to r.m.s.d. The correlation between sequence similarity and structural similarity is poor in pairs with low sequence similarities. A comparison of sequence and 3D structure-based phylogenies for all the families suggests that only a few families have a radical difference in the two kinds of dendrograms. The difference could occur when the sequence similarity among the homologues is low or when the structures are subjected to evolutionary pressure for the retention of function. The PALI database is expected to be useful in furthering our understanding of the relationship between sequences and structures of homologous proteins and their evolution.     

The calculation of molecular similarity: alternative formulas,data manipulation and graphical display

The use of electrostatic potential comparisons between molecules for the elucidation of structure activity relationships is now a well-established modeling technique. The Carbo and Hodgkin similarity indices are used extensively to make quantitative comparisons of this nature; yet their roots are found in the overlap of electron density distribution, with both formulas utilizing a product-based numerator.Two new similarity indices are suggested that calculate the electrostatic potential similarity using a difference-based numerator. The form of the new indices allows the creation of additional software functions that enhance the flexibility of similarity calculations and permit the creation of similarity maps.The general properties of these software functions and all indices are discussed and applied to a series of dopamine D2 receptor agonists.     

The p32K Structural Protein of the Atadenovirus Might Have Bacterial Relatives

Abstract The primary structure of a novel adenoviral protein referred to as p32K and found exclusively in members of the proposed new genus Atadenovirus was analyzed. The p32K gene sequence was determined from two bovine and one snake adenovirus types. Altogether five different p32K sequences were examined, two of them were obtained from the Gene Bank. The C-terminal part of the protein is conserved and shares similarity with certain bacterial small acid soluble proteins (SASPs). The sequence similarity seems coupled with functional relatedness, i.e. both protein groups are found in structures where the genome of the “dormant” organism is packaged in tight nucleoprotein complexes. In these complexes the DNA is protected against harmful environmental effects until the new reproductive cycle is started with specific protease cleavage of the packaging proteins. Although there is no experimental clue about the role of the p32K proteins, we hypothesize phylogenetic relationship between the two protein groups based on the sequence similarity and the supposed functional similarity. The alignments of these protein groups shows that the conserved part of the p32Ks probably is the result of the duplication of a shorter sequence similar to the SASPs of the Bacilli.