Related Research Articles
In bioinformatics, a sequence alignment is a way of arranging the sequences of DNA, RNA, or protein to identify regions of similarity that may be a consequence of functional, structural, or evolutionary relationships between the sequences. Aligned sequences of nucleotide or amino acid residues are typically represented as rows within a matrix. Gaps are inserted between the residues so that identical or similar characters are aligned in successive columns. Sequence alignments are also used for non-biological sequences such as calculating the distance cost between strings in a natural language, or to display financial data.
In bioinformatics, sequence analysis is the process of subjecting a DNA, RNA or peptide sequence to any of a wide range of analytical methods to understand its features, function, structure, or evolution. It can be performed on the entire genome, transcriptome or proteome of an organism, and can also involve only selected segments or regions, like tandem repeats and transposable elements. Methodologies used include sequence alignment, searches against biological databases, and others.
Protein structure prediction is the inference of the three-dimensional structure of a protein from its amino acid sequence—that is, the prediction of its secondary and tertiary structure from primary structure. Structure prediction is different from the inverse problem of protein design. Protein structure prediction is one of the most important goals pursued by computational biology; it is important in medicine and biotechnology.
In bioinformatics and evolutionary biology, a substitution matrix describes the frequency at which a character in a nucleotide sequence or a protein sequence changes to other character states over evolutionary time. The information is often in the form of log odds of finding two specific character states aligned and depends on the assumed number of evolutionary changes or sequence dissimilarity between compared sequences. It is an application of a stochastic matrix. Substitution matrices are usually seen in the context of amino acid or DNA sequence alignments, where they are used to calculate similarity scores between the aligned sequences.
In bioinformatics, sequence clustering algorithms attempt to group biological sequences that are somehow related. The sequences can be either of genomic, "transcriptomic" (ESTs) or protein origin. For proteins, homologous sequences are typically grouped into families. For EST data, clustering is important to group sequences originating from the same gene before the ESTs are assembled to reconstruct the original mRNA.
Structural alignment attempts to establish homology between two or more polymer structures based on their shape and three-dimensional conformation. This process is usually applied to protein tertiary structures but can also be used for large RNA molecules. In contrast to simple structural superposition, where at least some equivalent residues of the two structures are known, structural alignment requires no a priori knowledge of equivalent positions. Structural alignment is a valuable tool for the comparison of proteins with low sequence similarity, where evolutionary relationships between proteins cannot be easily detected by standard sequence alignment techniques. Structural alignment can therefore be used to imply evolutionary relationships between proteins that share very little common sequence. However, caution should be used in using the results as evidence for shared evolutionary ancestry because of the possible confounding effects of convergent evolution by which multiple unrelated amino acid sequences converge on a common tertiary structure.
Structural bioinformatics is the branch of bioinformatics that is related to the analysis and prediction of the three-dimensional structure of biological macromolecules such as proteins, RNA, and DNA. It deals with generalizations about macromolecular 3D structures such as comparisons of overall folds and local motifs, principles of molecular folding, evolution, binding interactions, and structure/function relationships, working both from experimentally solved structures and from computational models. The term structural has the same meaning as in structural biology, and structural bioinformatics can be seen as a part of computational structural biology. The main objective of structural bioinformatics is the creation of new methods of analysing and manipulating biological macromolecular data in order to solve problems in biology and generate new knowledge.
The Structural Classification of Proteins (SCOP) database is a largely manual classification of protein structural domains based on similarities of their structures and amino acid sequences. A motivation for this classification is to determine the evolutionary relationship between proteins. Proteins with the same shapes but having little sequence or functional similarity are placed in different superfamilies, and are assumed to have only a very distant common ancestor. Proteins having the same shape and some similarity of sequence and/or function are placed in "families", and are assumed to have a closer common ancestor.
A sequence profiling tool in bioinformatics is a type of software that presents information related to a genetic sequence, gene name, or keyword input. Such tools generally take a query such as a DNA, RNA, or protein sequence or ‘keyword’ and search one or more databases for information related to that sequence. Summaries and aggregate results are provided in standardized format describing the information that would otherwise have required visits to many smaller sites or direct literature searches to compile. Many sequence profiling tools are software portals or gateways that simplify the process of finding information about a query in the large and growing number of bioinformatics databases. The access to these kinds of tools is either web based or locally downloadable executables.
In molecular biology, protein threading, also known as fold recognition, is a method of protein modeling which is used to model those proteins which have the same fold as proteins of known structures, but do not have homologous proteins with known structure. It differs from the homology modeling method of structure prediction as it is used for proteins which do not have their homologous protein structures deposited in the Protein Data Bank (PDB), whereas homology modeling is used for those proteins which do. Threading works by using statistical knowledge of the relationship between the structures deposited in the PDB and the sequence of the protein which one wishes to model.
Pfam is a database of protein families that includes their annotations and multiple sequence alignments generated using hidden Markov models. Last version of Pfam, 36.0, was released in September 2023 and contains 20,795 families. It is currently provided through InterPro database.
In bioinformatics, the BLOSUM matrix is a substitution matrix used for sequence alignment of proteins. BLOSUM matrices are used to score alignments between evolutionarily divergent protein sequences. They are based on local alignments. BLOSUM matrices were first introduced in a paper by Steven Henikoff and Jorja Henikoff. They scanned the BLOCKS database for very conserved regions of protein families and then counted the relative frequencies of amino acids and their substitution probabilities. Then, they calculated a log-odds score for each of the 210 possible substitution pairs of the 20 standard amino acids. All BLOSUM matrices are based on observed alignments; they are not extrapolated from comparisons of closely related proteins like the PAM Matrices.
Homology modeling, also known as comparative modeling of protein, refers to constructing an atomic-resolution model of the "target" protein from its amino acid sequence and an experimental three-dimensional structure of a related homologous protein. Homology modeling relies on the identification of one or more known protein structures likely to resemble the structure of the query sequence, and on the production of an alignment that maps residues in the query sequence to residues in the template sequence. It has been seen that protein structures are more conserved than protein sequences amongst homologues, but sequences falling below a 20% sequence identity can have very different structure.
In molecular biology, a protein domain is a region of a protein's polypeptide chain that is self-stabilizing and that folds independently from the rest. Each domain forms a compact folded three-dimensional structure. Many proteins consist of several domains, and a domain may appear in a variety of different proteins. Molecular evolution uses domains as building blocks and these may be recombined in different arrangements to create proteins with different functions. In general, domains vary in length from between about 50 amino acids up to 250 amino acids in length. The shortest domains, such as zinc fingers, are stabilized by metal ions or disulfide bridges. Domains often form functional units, such as the calcium-binding EF hand domain of calmodulin. Because they are independently stable, domains can be "swapped" by genetic engineering between one protein and another to make chimeric proteins.
RAPTOR is protein threading software used for protein structure prediction. It has been replaced by RaptorX, which is much more accurate than RAPTOR.
CS-BLAST (Context-Specific BLAST) is a tool that searches a protein sequence that extends BLAST, using context-specific mutation probabilities. More specifically, CS-BLAST derives context-specific amino-acid similarities on each query sequence from short windows on the query sequences. Using CS-BLAST doubles sensitivity and significantly improves alignment quality without a loss of speed in comparison to BLAST. CSI-BLAST is the context-specific analog of PSI-BLAST, which computes the mutation profile with substitution probabilities and mixes it with the query profile. CSI-BLAST is the context specific analog of PSI-BLAST. Both of these programs are available as web-server and are available for free download.
SUPERFAMILY is a database and search platform of structural and functional annotation for all proteins and genomes. It classifies amino acid sequences into known structural domains, especially into SCOP superfamilies. Domains are functional, structural, and evolutionary units that form proteins. Domains of common Ancestry are grouped into superfamilies. The domains and domain superfamilies are defined and described in SCOP. Superfamilies are groups of proteins which have structural evidence to support a common evolutionary ancestor but may not have detectable sequence homology.
The sequential structure alignment program (SSAP) in chemistry, physics, and biology is a method that uses double dynamic programming to produce a structural alignment based on atom-to-atom vectors in structure space. Instead of the alpha carbons typically used in structural alignment, SSAP constructs its vectors from the beta carbons for all residues except glycine, a method which thus takes into account the rotameric state of each residue as well as its location along the backbone. SSAP works by first constructing a series of inter-residue distance vectors between each residue and its nearest non-contiguous neighbors on each protein. A series of matrices are then constructed containing the vector differences between neighbors for each pair of residues for which vectors were constructed. Dynamic programming applied to each resulting matrix determines a series of optimal local alignments which are then summed into a "summary" matrix to which dynamic programming is applied again to determine the overall structural alignment.
The HH-suite is an open-source software package for sensitive protein sequence searching. It contains programs that can search for similar protein sequences in protein sequence databases. Sequence searches are a standard tool in modern biology with which the function of unknown proteins can be inferred from the functions of proteins with similar sequences. HHsearch and HHblits are two main programs in the package and the entry point to its search function, the latter being a faster iteration. HHpred is an online server for protein structure prediction that uses homology information from HH-suite.
A protein superfamily is the largest grouping (clade) of proteins for which common ancestry can be inferred. Usually this common ancestry is inferred from structural alignment and mechanistic similarity, even if no sequence similarity is evident. Sequence homology can then be deduced even if not apparent. Superfamilies typically contain several protein families which show sequence similarity within each family. The term protein clan is commonly used for protease and glycosyl hydrolases superfamilies based on the MEROPS and CAZy classification systems.
References
- ↑ Holm L, Ouzounis C, Sander C, Tuparev G, Vriend G (1992). "A database of protein structure families with common folding motifs". Protein Science. 1 (12): 1691–1698. doi:10.1002/pro.5560011217. PMC 2142138 . PMID 1304898.
