MitoMorphy: an alignment and annotation tool for human mitochondrial DNA polymorphisms

MitoMorphy uses a number of publicly available human mitochondrial DNA (mtDNA) sequences from different ethnic groups to compare and annotate the associated polymorphic data. It provides an integrated display of mtDNA sequence comparison, sequence variation, and annotation for 695 different mtDNA sequences from many different ethnic groups around the world.     

S curve, a graphic representation of protein secondary structure sequence and its applications

A secondary structure sequence is a symbolic string composed of three kinds of letters, indicating the helix, strand, and coil (including turns), respectively. A graphic representation for this abstract symbolic sequence is proposed here, called the S curve. The S curve is the unique representation for a given secondary structure sequence in the sense that the sequence and the S curve can be uniquely determined from the other. Therefore, the S curve contains all the information that the secondary structure sequence contains. Different geometrical properties of the S curve are studied in details, which reflect the basic characteristics of the secondary structure sequences. The S curves are used to display, analyze, and compare the secondary structure sequences. Detailed application examples are presented. One advantage of the S curve methodology is that the main patterns of a given secondary structure sequence can be grasped quickly in a perceivable form. This is particularly useful in the cases in which longer sequences are involved and structures of proteins are unknown.     

Virtual interaction profiles of proteins.

We have developed a new method for the prediction of peptide sequences that bind to a protein, given a three-dimensional structure of the protein in complex with a peptide. By applying a recently developed sequence prediction algorithm and a novel ensemble averaging calculation, we generate a diverse collection of peptide sequences that are predicted to have significant affinity for the protein. Using output from the simulations, we create position-specific scoring matrices, or virtual interaction profiles (VIPs). Comparison of VIPs for a collection of binding motifs to sequences determined experimentally indicates that the prediction algorithm is accurate and applicable to a diverse range of structures. With these VIPs, one can scan protein sequence databases rapidly to seek binding partners of potential biological significance. Overall, this method can significantly enhance the information contained within a protein- peptide crystal structure, and enrich the data obtained by experimental selection methods such as phage display.     

Use of tandem Biacore-mass spectrometry to identify platelet membrane targets of novel monoclonal antibodies

The monoclonal antibodies (mAbs) ALMA.17 and ALMA.7 recognize human platelet membrane proteins. ALMA.17 is directed against α_IIbβ₃ integrin, but the target of ALMA.7 was unknown previously. Tandem Biacore micropurification and mass spectrometry (MS) analysis of a platelet membrane lysate was used to identify the target of ALMA.7. Detergent lysates enriched in membrane proteins were perfused over immobilized ALMA.17 or ALMA.7 in a Biacore system. The captured proteins were eluted, concentrated on C3 magnetic beads, and digested with trypsin before nano liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. Critical adjustments needed to be made in (i) the detergent mixture to preserve protein antigenicity and sensor chip integrity and (ii) the method of trypsin digestion to concentrate the proteins and use elution buffers that do not interfere with MS. The target of ALMA.17 was confirmed to be α_IIbβ₃ integrin, whereas that of ALMA.7 was identified as CD226 (PTA-1, DNAM-1, TLiSa-1). This was confirmed by immunoassays comparing ALMA.7 with a commercial anti-CD226 mAb. Thus, a tandem Biacore and nano LC-MS/MS strategy allowed unambiguous identification of an unknown antigen in a complex medium such as a platelet membrane lysate. This strategy may be employed to identify any protein “capturable” on a sensor chip provided that one uses appropriate experimental conditions.     

Sampled ensemble neutrality as a feature to classify potential structured RNAs

Background

Structured RNAs have many biological functions ranging from catalysis of chemical reactions to gene regulation. Yet, many homologous structured RNAs display most of their conservation at the secondary or tertiary structure level. As a result, strategies for structured RNA discovery rely heavily on identification of sequences sharing a common stable secondary structure. However, correctly distinguishing structured RNAs from surrounding genomic sequence remains challenging, especially during de novo discovery. RNA also has a long history as a computational model for evolution due to the direct link between genotype (sequence) and phenotype (structure). From these studies it is clear that evolved RNA structures, like protein structures, can be considered robust to point mutations. In this context, an RNA sequence is considered robust if its neutrality (extent to which single mutant neighbors maintain the same secondary structure) is greater than that expected for an artificial sequence with the same minimum free energy structure.

Results

In this work, we bring concepts from evolutionary biology to bear on the structured RNA de novo discovery process. We hypothesize that alignments corresponding to structured RNAs should consist of neutral sequences. We evaluate several measures of neutrality for their ability to distinguish between alignments of structured RNA sequences drawn from Rfam and various decoy alignments. We also introduce a new measure of RNA structural neutrality, the structure ensemble neutrality (SEN). SEN seeks to increase the biological relevance of existing neutrality measures in two ways. First, it uses information from an alignment of homologous sequences to identify a conserved biologically relevant structure for comparison. Second, it only counts base-pairs of the original structure that are absent in the comparison structure and does not penalize the formation of additional base-pairs.

Conclusion

We find that several measures of neutrality are effective at separating structured RNAs from decoy sequences, including both shuffled alignments and flanking genomic sequence. Furthermore, as an independent feature classifier to identify structured RNAs, SEN yields comparable performance to current approaches that consider a variety of features including stability and sequence identity. Finally, SEN outperforms other measures of neutrality at detecting mutational robustness in bacterial regulatory RNA structures.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-014-1203-8) contains supplementary material, which is available to authorized users.     

Alignment editing and identification of consensus secondary structures for nucleic acid sequences: interactive use of dot matrix representations.

We present a computer-aided approach for identifying and aligning consensus secondary structure within a set of functionally related oligonucleotide sequences aligned by sequence. The method relies on visualization of secondary structure using a generalization of the dot matrix representation appropriate for consensus sequence data sets. An interactive computer program implementing such a visualization of consensus structure has been developed. The program allows for alignment editing, data and display filtering and various modes of base pair representation, including co-variation. The utility of this approach is demonstrated with four sample data sets derived from in vitro selection experiments and one data set comprising tRNA sequences.     

Predicting RNA secondary structure by the comparative approach: how to select the homologous sequences

Background  

The secondary structure of an RNA must be known before the relationship between its structure and function can be determined. One way to predict the secondary structure of an RNA is to identify covarying residues that maintain the pairings (Watson-Crick, Wobble and non-canonical pairings). This "comparative approach" consists of identifying mutations from homologous sequence alignments. The sequences must covary enough for compensatory mutations to be revealed, but comparison is difficult if they are too different. Thus the choice of homologous sequences is critical. While many possible combinations of homologous sequences may be used for prediction, only a few will give good structure predictions. This can be due to poor quality alignment in stems or to the variability of certain sequences. This problem of sequence selection is currently unsolved.     

Distance analysis helps to establish characteristic motifs in intron sequences

Computer-assisted sequence analysis was applied to detect the most apparent nonrandom sequence motifs in eukaryotic introns. We describe in detail a method, which we call distance analysis, that we applied to the extensive study of 405 eukaryotic intron sequences. We observed very strong two-base periodicities for almost all tetranucleotides that are tandem repeats of nonhomopolymeric dinucleotides (the exception was GCGC and CGCG). We also observed, by using a fixed-point alignment method, that these periodic sequence motifs belong to large clusters of dinucleotides repeated tandemly as many as 15–35 times, which corresponds to the cluster lengths of 30–70 bases. We did not observe two-base periodicity of tetranucleotides in the collections of either 262 spliced eukaryotic exons or 107 bacterial genes. Instead, these sequences displayed strong three-base periodicity of some other tetranucleotides. These findings suggest that introns and exons display distinct sequence properties that can be used for mapping purposes.     

Plant defensins: Common fold,multiple functions

Plant defensins represent a large class of structurally similar peptides found throughout the plant kingdom. Despite a conserved cysteine spacing pattern and three-dimensional structure, their sequences are highly divergent and they display a range of activities including antifungal and antibacterial activities, enzyme inhibitory activities as well as roles in heavy metal tolerance and development. The vast number of sequences along with their diverse range of activities makes it impossible to test the activity and assign function to all plant defensins. However, as the number of characterized defensins increases, in depth sequence analysis may allow us to predict the function of newly identified peptides. In this review, we analyze the sequences of defensins whose activities have been described and group these based on similarity using a maximum-likelihood phylogenetic tree. We also compare the amino acids that have been described as essential for the activity of various plant defensins between these groups. While many more plant defensins will need to be characterized before we can develop rules to predict the activity of novel sequences, this approach may prove useful in identifying structure–function relationships.     

Plant defensins: Common fold,multiple functions

Plant defensins represent a large class of structurally similar peptides found throughout the plant kingdom. Despite a conserved cysteine spacing pattern and three-dimensional structure, their sequences are highly divergent and they display a range of activities including antifungal and antibacterial activities, enzyme inhibitory activities as well as roles in heavy metal tolerance and development. The vast number of sequences along with their diverse range of activities makes it impossible to test the activity and assign function to all plant defensins. However, as the number of characterized defensins increases, in depth sequence analysis may allow us to predict the function of newly identified peptides. In this review, we analyze the sequences of defensins whose activities have been described and group these based on similarity using a maximum-likelihood phylogenetic tree. We also compare the amino acids that have been described as essential for the activity of various plant defensins between these groups. While many more plant defensins will need to be characterized before we can develop rules to predict the activity of novel sequences, this approach may prove useful in identifying structure–function relationships.     

TM-MOTIF: an alignment viewer to annotate predicted transmembrane helices and conserved motifs in aligned set of sequences

Multiple sequence alignments become biologically meaningful only if conserved and functionally important residues and secondary structural elements preserved can be identified at equivalent positions. This is particularly important for transmembrane proteins like G-protein coupled receptors (GPCRs) with seven transmembrane helices. TM-MOTIF is a software package and an effective alignment viewer to identify and display conserved motifs and amino acid substitutions (AAS) at each position of the aligned set of homologous sequences of GPCRs. The key feature of the package is to display the predicted membrane topology for seven transmembrane helices in seven colours (VIBGYOR colouring scheme) and to map the identified motifs on its respective helices /loop regions. It is an interactive package which provides options to the user to submit query or pre-aligned set of GPCR sequences to align with a reference sequence, like rhodopsin, whose structure has been solved experimentally. It also provides the possibility to identify the nearest homologue from the available inbuilt GPCR or Olfactory Receptor cluster dataset whose association is already known for its receptor type. AVAILABILITY: The database is available for free at mini@ncbs.res.in.     

Visualizing bacterial tRNA identity determinants and antideterminants using function logos and inverse function logos

Sequence logos are stacked bar graphs that generalize the notion of consensus sequence. They employ entropy statistics very effectively to display variation in a structural alignment of sequences of a common function, while emphasizing its over-represented features. Yet sequence logos cannot display features that distinguish functional subclasses within a structurally related superfamily nor do they display under-represented features. We introduce two extensions to address these needs: function logos and inverse logos. Function logos display subfunctions that are over-represented among sequences carrying a specific feature. Inverse logos generalize both sequence logos and function logos by displaying under-represented, rather than over-represented, features or functions in structural alignments. To make inverse logos, a compositional inverse is applied to the feature or function frequency distributions before logo construction, where a compositional inverse is a mathematical transform that makes common features or functions rare and vice versa. We applied these methods to a database of structurally aligned bacterial tDNAs to create highly condensed, birds-eye views of potentially all so-called identity determinants and antideterminants that confer specific amino acid charging or initiator function on tRNAs in bacteria. We recovered both known and a few potentially novel identity elements. Function logos and inverse logos are useful tools for exploratory bioinformatic analysis of structure-function relationships in sequence families and superfamilies.     

Fast assignment of protein structures to sequences using the intermediate sequence library PDB-ISL

MOTIVATION: For large-scale structural assignment to sequences, as in computational structural genomics, a fast yet sensitive sequence search procedure is essential. A new approach using intermediate sequences was tested as a shortcut to iterative multiple sequence search methods such as PSI-BLAST. RESULTS: A library containing potential intermediate sequences for proteins of known structure (PDB-ISL) was constructed. The sequences in the library were collected from a large sequence database using the sequences of the domains of proteins of known structure as the query sequences and the program PSI-BLAST. Sequences of proteins of unknown structure can be matched to distantly related proteins of known structure by using pairwise sequence comparison methods to find homologues in PDB-ISL. Searches of PDB-ISL were calibrated, and the number of correct matches found at a given error rate was the same as that found by PSI-BLAST. The advantage of this library is that it uses pairwise sequence comparison methods, such as FASTA or BLAST2, and can, therefore, be searched easily and, in many cases, much more quickly than an iterative multiple sequence comparison method. The procedure is roughly 20 times faster than PSI-BLAST for small genomes and several hundred times for large genomes. AVAILABILITY: Sequences can be submitted to the PDB-ISL servers at http://stash.mrc-lmb.cam.ac.uk/PDB_ISL/ or http://cyrah.ebi.ac.uk:1111/Serv/PDB_ISL/ and can be downloaded from ftp://ftp.ebi.ac.uk/pub/contrib/jong/PDB_+ ++ISL/ CONTACT: sat@mrc-lmb.cam.ac.uk and jong@ebi.ac.uk     

INTERALIGN: interactive alignment editor for distantly related protein sequences

SUMMARY: Improving and ascertaining the quality of a multiple sequence alignment is a very challenging step in protein sequence analysis. This is particularly the case when dealing with sequences in the 'twilight zone', i.e. sharing < 30% identity. Here we describe INTERALIGN, a dedicated user-friendly alignment editor including a view of secondary structures and a synchronized display of carbon alpha traces of corresponding protein structures. Profile alignment, using CLUSTALW, is implemented to improve the alignment of a sequence of unknown structure with the visually optimized structural alignment as compared with a standard multiple sequence alignment. Tree-based ordering further helps in identifying the structure closest to a given sequence.     

Protein simple sequence conservation

Protein simple sequences, a subset of low-complexity sequences, are regions of sequence highly enriched in one or a few residue types. Simple sequences are exceedingly common, the average being more than one per protein sequence. Despite being so common, such sequences are not well-studied. The simple sequences that have been subjected to detailed study are often found to possess important functions. Here we present a survey of protein simple sequences, generally enriched in a single residue type, with the aim of studying their conservation. We find that the majority of such simple sequences are not conserved. However, conserved protein simple sequences are relatively common, with approximately 11% of the surveyed protein families possessing a conserved simple sequence. The data obtained in this study support the idea that simple sequences are conserved for functional reasons. Such functions can range from substrate binding, to mediating protein-protein interactions, to structural integrity. A perhaps surprising finding is that the residue enriching a conserved simple sequence is itself not necessarily conserved. Neither is the length of many of the highly conserved simple sequences. In the few cases where structural and functional data is available it is found that the conserved simple sequences are consistent with both local structure and function. The data presented support the idea that protein simple sequences can be conserved and have important roles in protein structure and function.     

The primary structure of the alpha subunit of human elongation factor 1. Structural aspects of guanine-nucleotide-binding sites

The primary structure of the alpha subunit of elongation factor 1 (EF-1 alpha) from human MOLT 4 cells was determined by cDNA sequencing. The data show that the conservation of the amino acid sequence is more than 80% when compared with yeast and Artemia EF-1 alpha. An inventory of amino acid sequences around the guanine-nucleotide-binding site in elongation factor Tu from Escherichia coli and homologous amino acid sequences in G proteins, initiation and elongation factors and proteins from the RAS family shows two regions containing conserved sequence elements. Region I has the sequence apolar-Xaa-Xaa-Xaa-Gly-Xaa-Xaa-Yaa-Xaa-Gly-LYs-Thr(Ser)- -Xaa-Xaa-Xaa-Xaa-X-apolar. Except for RAS proteins, Yaa is always an acidic amino acid residue. Region II is characterized by the invariant sequence apolar-apolar-Xaa-Xaa-Asn-Lys-Xaa-Asp. In order to facilitate sequence comparison we have used a graphic display, which is based on the hydrophilicity values of individual amino acids in a sequence.     

High-throughput analysis of the protein sequence-stability landscape using a quantitative yeast surface two-hybrid system and fragment reconstitution

Stability evaluation of many mutants can lead to a better understanding of the sequence determinants of a structural motif and of factors governing protein stability and protein evolution. The traditional biophysical analysis of protein stability is low throughput, limiting our ability to widely explore sequence space in a quantitative manner. In this study, we have developed a high-throughput library screening method for quantifying stability changes, which is based on protein fragment reconstitution and yeast surface display. Our method exploits the thermodynamic linkage between protein stability and fragment reconstitution and the ability of the yeast surface display technique to quantitatively evaluate protein-protein interactions. The method was applied to a fibronectin type III (FN3) domain. Characterization of fragment reconstitution was facilitated by the co-expression of two FN3 fragments, thus establishing a yeast surface two-hybrid method. Importantly, our method does not rely on competition between clones and thus eliminates a common limitation of high-throughput selection methods in which the most stable variants are recovered predominantly. Thus, it allows for the isolation of sequences that exhibit a desired level of stability. We identified more than 100 unique sequences for a β-bulge motif, which was significantly more informative than natural sequences of the FN3 family in revealing the sequence determinants for the β-bulge. Our method provides a powerful means for the rapid assessment of the stability of many variants, for the systematic assessment of the contribution of different factors to protein stability, and for enhancement of the protein stability.