Accuracy of sequence alignment and fold assessment using reduced amino acid alphabets

Reduced or simplified amino acid alphabets group the 20 naturally occurring amino acids into a smaller number of representative protein residues. To date, several reduced amino acid alphabets have been proposed, which have been derived and optimized by a variety of methods. The resulting reduced amino acid alphabets have been applied to pattern recognition, generation of consensus sequences from multiple alignments, protein folding, and protein structure prediction. In this work, amino acid substitution matrices and statistical potentials were derived based on several reduced amino acid alphabets and their performance assessed in a large benchmark for the tasks of sequence alignment and fold assessment of protein structure models, using as a reference frame the standard alphabet of 20 amino acids. The results showed that a large reduction in the total number of residue types does not necessarily translate into a significant loss of discriminative power for sequence alignment and fold assessment. Therefore, some definitions of a few residue types are able to encode most of the relevant sequence/structure information that is present in the 20 standard amino acids. Based on these results, we suggest that the use of reduced amino acid alphabets may allow to increasing the accuracy of current substitution matrices and statistical potentials for the prediction of protein structure of remote homologs.     

基于进化信息改进蛋白质定点突变稳定性预测准确率

定点突变后蛋白质稳定性的增加还是降低,是分子生物学和蛋白质工程的核心问题之一,也是目前生物信息学研究的重要领域。基于蛋白质序列信息对蛋白质定点突变后的稳定性进行预测的方法,因其简易、适用面广而得到广泛的研究应用。通过对编码策略（coding schemes）的探索,发现不同编码策略对预测准确率有较大影响,并发现基于进化信息的BLOSUM打分矩阵可以用于蛋白质定点突变稳定性预测,具有较高的预测准确率。应用基于BLOSUM62打分矩阵的神经网络（ANN）和支持向量机（SVM）算法,可以改进蛋白质定点突变后稳定性的预测,而且ANN+ BLOSUM62在1623条序列的数据集上的实测结果优于目前国际通用的几款预测 软件。     

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.     

Widespread protein sequence similarities: origins of Escherichia coli genes.

To learn more about the evolutionary origins of Escherichia coli genes, we surveyed systematically for extended sequence similarities among the 1,264 amino acid sequences encoded by chromosomal genes of E. coli K-12 in SwissProt release 26 by using the FASTA program and imposing the following criteria: (i) alignment of segments at least 100 amino acids long and (ii) at least 20% amino acid identity. Altogether, 624 extended alignments meeting the two criteria were identified, corresponding to 577 protein sequences (45.6% of the 1,264 E. coli protein sequences) that had an extended alignment with at least one other E. coli protein sequence. To exclude alignments of questionable biological significance, we imposed a high threshold on the number of gaps allowed in each of the 624 extended alignments, giving us a subset of 464 proteins. The population of 464 alignments has the following characteristics expressed as median values of the group: 254 amino acids in the alignment, representing 86% of the length of the protein, 33% of the amino acids in the alignment being identical, and 1.1 gaps introduced per 100 amino acids of alignment. Where functions are known, nearly all pairs consist of functionally related proteins. This implies that the sequence similarity we detected has biological meaning and did not arise by chance. That a major fraction of E. coli proteins form extended alignments strongly suggests the predominance of duplication and divergence of ancestral genes in the evolution of E. coli genes. The range of degrees of similarity shows that some genes originated more recently than others. There is no evidence of genome doubling in the past, since map distances between genes of sequence-related proteins show no coherent pattern of favored separations.     

Cloning and sequence analysis reveal structural variation among related zein genes in maize

We have isolated a gene encoding one of the 19,000 dalton zein proteins from a maize genomic library constructed in Charon 4A. This gene occurs on a 7.7 kb Eco RI fragment, and based on Southern hybridization analysis, represents one of several homologous sequences present in the maize genome. The nucleotide sequence of the gene predicts a protein composed of 235 amino acids, including a signal peptide of 21 amino acids. There are no intervening sequences in the gene. By comparing the nucleotide sequence of this gene with that of a homologous cDNA clone, we have identified a basis for microheterogeneity within the gene family. The 5′ nucleotide sequences of the genomic and cDNA clones are identical, but they differ in the center of the protein, where repeated amino acid sequences occur. A nucleotide sequence encoding a conserved peptide of 20 amino acids is repeated nine times in the center of both of these clones.     

Structure alignment based on coding of local geometric measures

Background  

A structure alignment method based on a local geometric property is presented and its performance is tested in pairwise and multiple structure alignments. In this approach, the writhing number, a quantity originating from integral formulas of Vassiliev knot invariants, is used as a local geometric measure. This measure is used in a sliding window to calculate the local writhe down the length of the protein chain. By encoding the distribution of writhing numbers across all the structures in the protein databank (PDB), protein geometries are represented in a 20-letter alphabet. This encoding transforms the structure alignment problem into a sequence alignment problem and allows the well-established algorithms of sequence alignment to be employed. Such geometric alignments offer distinct advantages over structural alignments in Cartesian coordinates as it better handles structural subtleties associated with slight twists and bends that distort one structure relative to another.     

Empirical models for substitution in ribosomal RNA

Empirical models of substitution are often used in protein sequence analysis because the large alphabet of amino acids requires that many parameters be estimated in all but the simplest parametric models. When information about structure is used in the analysis of substitutions in structured RNA, a similar situation occurs. The number of parameters necessary to adequately describe the substitution process increases in order to model the substitution of paired bases. We have developed a method to obtain substitution rate matrices empirically from RNA alignments that include structural information in the form of base pairs. Our data consisted of alignments from the European Ribosomal RNA Database of Bacterial and Eukaryotic Small Subunit and Large Subunit Ribosomal RNA ( Wuyts et al. 2001. Nucleic Acids Res. 29:175-177; Wuyts et al. 2002. Nucleic Acids Res. 30:183-185). Using secondary structural information, we converted each sequence in the alignments into a sequence over a 20-symbol code: one symbol for each of the four individual bases, and one symbol for each of the 16 ordered pairs. Substitutions in the coded sequences are defined in the natural way, as observed changes between two sequences at any particular site. For given ranges (windows) of sequence divergence, we obtained substitution frequency matrices for the coded sequences. Using a technique originally developed for modeling amino acid substitutions ( Veerassamy, Smith, and Tillier. 2003. J. Comput. Biol. 10:997-1010), we were able to estimate the actual evolutionary distance for each window. The actual evolutionary distances were used to derive instantaneous rate matrices, and from these we selected a universal rate matrix. The universal rate matrices were incorporated into the Phylip Software package ( Felsenstein 2002. http://evolution.genetics.washington.edu/phylip.html), and we analyzed the ribosomal RNA alignments using both distance and maximum likelihood methods. The empirical substitution models performed well on simulated data, and produced reasonable evolutionary trees for 16S ribosomal RNA sequences from sequenced Bacterial genomes. Empirical models have the advantage of being easily implemented, and the fact that the code consists of 20 symbols makes the models easily incorporated into existing programs for protein sequence analysis. In addition, the models are useful for simulating the evolution of RNA sequence and structure simultaneously.     

Scoring profile-to-profile sequence alignments

Sequence alignment profiles have been shown to be very powerful in creating accurate sequence alignments. Profiles are often used to search a sequence database with a local alignment algorithm. More accurate and longer alignments have been obtained with profile-to-profile comparison. There are several steps that must be performed in creating profile-profile alignments, and each involves choices in parameters and algorithms. These steps include (1) what sequences to include in a multiple alignment used to build each profile, (2) how to weight similar sequences in the multiple alignment and how to determine amino acid frequencies from the weighted alignment, (3) how to score a column from one profile aligned to a column of the other profile, (4) how to score gaps in the profile-profile alignment, and (5) how to include structural information. Large-scale benchmarks consisting of pairs of homologous proteins with structurally determined sequence alignments are necessary for evaluating the efficacy of each scoring scheme. With such a benchmark, we have investigated the properties of profile-profile alignments and found that (1) with optimized gap penalties, most column-column scoring functions behave similarly to one another in alignment accuracy; (2) some functions, however, have much higher search sensitivity and specificity; (3) position-specific weighting schemes in determining amino acid counts in columns of multiple sequence alignments are better than sequence-specific schemes; (4) removing positions in the profile with gaps in the query sequence results in better alignments; and (5) adding predicted and known secondary structure information improves alignments.     

Isolation and sequencing of a cDNA encoding for a ribonuclease from the insect Ceratitis capitata

Two overlapping clones encoding for a ribonuclease from six-day-old larvae of the insect Ceratitis capitata (Cc-RNase) have been isolated by immunoscreening a cDNA library and by 5' RACE. The sequence of the Cc-RNase cDNA contains an open reading frame of 414 nucleotides encoding for a precursor protein of 138 amino acids long with a putative signal peptide consisting of 19 amino acids. The calculated M(r) of the mature protein was found to be 13.7 kDa. Multiple alignments of the deduced amino acid Cc-RNase sequence with other ribonucleases revealed an approximate 25% average identity. Despite the low percentage of identity, histidine and lysine residues which are essential for its catalytic activity, were found to be completely conserved. Furthermore, expression of the clone in E. coli resulted in the production of a recombinant product that showed strong immunoreactivity with anti-RNase specific antibodies. These results support the hypothesis that the identified clone encodes for a protein which is a new member of the RNase superfamily.     

Modeling amino acid substitution patterns in orthologous and paralogous genes

We study to what degree patterns of amino acid substitution vary between genes using two models of protein-coding gene evolution. The first divides the amino acids into groups, with one substitution rate for pairs of residues in the same group and a second for those in differing groups. Unlike previous applications of this model, the groups themselves are estimated from data by simulated annealing. The second model makes substitution rates a function of the physical and chemical similarity between two residues. Because we model the evolution of coding DNA sequences as opposed to protein sequences, artifacts arising from the differing numbers of nucleotide substitutions required to bring about various amino acid substitutions are avoided. Using 10 alignments of related sequences (five of orthologous genes and five gene families), we do find differences in substitution patterns. We also find that, although patterns of amino acid substitution vary temporally within the history of a gene, variation is not greater in paralogous than in orthologous genes. Improved understanding of such gene-specific variation in substitution patterns may have implications for applications such as sequence alignment and phylogenetic inference.     

Reduction of protein sequence complexity by residue grouping

It is well known that there are some similarities among various naturally occurring amino acids. Thus, the complexity in protein systems could be reduced by sorting these amino acids with similarities into groups and then protein sequences can be simplified by reduced alphabets. This paper discusses how to group similar amino acids and whether there is a minimal amino acid alphabet by which proteins can be folded. Various reduced alphabets are obtained by reserving the maximal information for the simplified protein sequence compared with the parent sequence using global sequence alignment. With these reduced alphabets and simplified similarity matrices, we achieve recognition of the protein fold based on the similarity score of the sequence alignment. The coverage in dataset SCOP40 for various levels of reduction on the amino acid types is obtained, which is the number of homologous pairs detected by program BLAST to the number marked by SCOP40. For the reduced alphabets containing 10 types of amino acids, the ability to detect distantly related folds remains almost at the same level as that by the alphabet of 20 types of amino acids, which implies that 10 types of amino acids may be the degree of freedom for characterizing the complexity in proteins.     

RevTrans: Multiple alignment of coding DNA from aligned amino acid sequences

The simple fact that proteins are built from 20 amino acids while DNA only contains four different bases, means that the 'signal-to-noise ratio' in protein sequence alignments is much better than in alignments of DNA. Besides this information-theoretical advantage, protein alignments also benefit from the information that is implicit in empirical substitution matrices such as BLOSUM-62. Taken together with the generally higher rate of synonymous mutations over non-synonymous ones, this means that the phylogenetic signal disappears much more rapidly from DNA sequences than from the encoded proteins. It is therefore preferable to align coding DNA at the amino acid level and it is for this purpose we have constructed the program RevTrans. RevTrans constructs a multiple DNA alignment by: (i) translating the DNA; (ii) aligning the resulting peptide sequences; and (iii) building a multiple DNA alignment by 'reverse translation' of the aligned protein sequences. In the resulting DNA alignment, gaps occur in groups of three corresponding to entire codons, and analogous codon positions are therefore always lined up. These features are useful when constructing multiple DNA alignments for phylogenetic analysis. RevTrans also accepts user-provided protein alignments for greater control of the alignment process. The RevTrans web server is freely available at http://www.cbs.dtu.dk/services/RevTrans/.     

Penicillin-binding protein 4 of Escherichia coli shows a novel type of primary structure among penicillin-interacting proteins

The nucleotide sequence of a 1884 bp DNA fragment of E. coli, carrying the gene dacB, was determined. The DNA codes for penicillin-binding protein 4 (PBP4), an enzyme of 477 amino acids, being involved as a DD-carboxypeptidase-endopeptidase in murein metabolism. The enzyme is translated with a cleavable signal peptide of 20 amino acids, which was verified by sequencing the amino-terminus of the isolated protein. The characteristic active-site fingerprints SXXK, SXN and KTG of class A beta-lactamases and penicillin-binding proteins were located in the sequence. On the basis of amino acid alignments we propose, that PBP4 and class A beta-lactamases share a common evolutionary origin but PBP4 has acquired an additional domain of 188 amino acids in the region between the SXXK and SXN elements.     

A word-oriented approach to alignment validation

MOTIVATION: Multiple sequence alignment at the level of whole proteomes requires a high degree of automation, precluding the use of traditional validation methods such as manual curation. Since evolutionary models are too general to describe the history of each residue in a protein family, there is no single algorithm/model combination that can yield a biologically or evolutionarily optimal alignment. We propose a 'shotgun' strategy where many different algorithms are used to align the same family, and the best of these alignments is then chosen with a reliable objective function. We present WOOF, a novel 'word-oriented' objective function that relies on the identification and scoring of conserved amino acid patterns (words) between pairs of sequences. RESULTS: Tests on a subset of reference protein alignments from BAliBASE showed that WOOF tended to rank the (manually curated) reference alignment highest among 1060 alternative (automatically generated) alignments for a majority of protein families. Among the automated alignments, there was a strong positive relationship between the WOOF score and similarity to the reference alignment. The speed of WOOF and its independence from explicit considerations of three-dimensional structure make it an excellent tool for analyzing large numbers of protein families. AVAILABILITY: On request from the authors.     

Grouping of amino acid types and extraction of amino acid properties from multiple sequence alignments using variance maximization

Understanding of amino acid type co-occurrence in trusted multiple sequence alignments is a prerequisite for improved sequence alignment and remote homology detection algorithms. Two objective approaches were used to investigate co-occurrence, both based on variance maximization of the weighted residue frequencies in columns taken from a large alignment database. The first approach discretely grouped amino acid types, and the second approach extracted orthogonal properties of amino acids using principal components analysis. The grouping results corresponded to amino acid physical properties such as side chain hydrophobicity, size, or backbone flexibility, and an optimal arrangement of approximately eight groups was observed. However, interpretation of the orthogonal properties was more complex. Although the principal components accounting for the largest variances exhibited modest correlations with hydrophobicity and conservation of glycine, in general principal components did not correspond to physical properties of amino acids. Although not intuitive, these amino acid mathematical properties were demonstrated to be robust and to improve local pairwise alignment accuracy, relative to 20 amino acid frequencies alone, for a simple test case.     

Evaluation performance of substitution matrices,based on contacts between residue terminal groups

Sequence alignment is a standard method for the estimation of the evolutionary, structural, and functional relationships among amino acid sequences. The quality of alignments depends on the used similarity matrix. Statistical contact potentials (CPs) contain information on contact propensities among residues in native protein structures. Substitution matrices (SMs) based on CPs are applicable for the comparison of distantly related sequences. Here, contact between amino acids was estimated on the basis of the evaluation of the distances between side-chain terminal groups (SCTGs), which are defined as the group of the side-chain heavy atoms with fixed distances between them. In this paper, two new types of CPs and similarity matrices have been constructed: one based on fixed cutoff distance obtained from geometric characteristics of the SCTGs (TGC1), while the other is distance-dependent potential (TGC2). These matrices are compared with other popular SMs. The performance of the matrices was evaluated by comparing sequence with structural alignments. The obtained results show that TGC2 has the best performance among contact-based matrices, but on the whole, contact-based matrices have slightly lower performance than other SMs except fold-level similarity.     

Evaluation performance of substitution matrices, based on contacts between residue terminal groups

Sequence alignment is a standard method for the estimation of the evolutionary, structural, and functional relationships among amino acid sequences. The quality of alignments depends on the used similarity matrix. Statistical contact potentials (CPs) contain information on contact propensities among residues in native protein structures. Substitution matrices (SMs) based on CPs are applicable for the comparison of distantly related sequences. Here, contact between amino acids was estimated on the basis of the evaluation of the distances between side-chain terminal groups (SCTGs), which are defined as the group of the side-chain heavy atoms with fixed distances between them. In this paper, two new types of CPs and similarity matrices have been constructed: one based on fixed cutoff distance obtained from geometric characteristics of the SCTGs (TGC1), while the other is distance-dependent potential (TGC2). These matrices are compared with other popular SMs. The performance of the matrices was evaluated by comparing sequence with structural alignments. The obtained results show that TGC2 has the best performance among contact-based matrices, but on the whole, contact-based matrices have slightly lower performance than other SMs except fold-level similarity.