1.
Pfam
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Pfam is a database of protein families that includes their annotations and multiple sequence alignments generated using hidden Markov models. The most recent version, Pfam 31.0, was released in March 2017, the general purpose of the Pfam database is to provide a complete and accurate classification of protein families and domains. Originally, the rationale behind creating the database was to have a method of curating information on known protein families to improve the efficiency of annotating genomes. The Pfam classification of families has been widely adopted by biologists because of its wide coverage of proteins. Early genome projects, such as human and fly used Pfam extensively for functional annotation of genomic data, the Pfam website allows users to submit protein or DNA sequences to search for matches to families in the database. If DNA is submitted, a translation is performed, then each frame is searched. Family is the class, which simply indicates that members are related. Domains are defined as a structural unit or reusable sequence unit that can be found in multiple protein contexts. Repeats are not usually stable in isolation, but rather are required to form tandem repeats in order to form a domain or extended structure. Motifs are usually shorter sequence units found outside of globular domains, the descriptions of Pfam families are managed by the general public using Wikipedia. As of release 29.0,76. 1% of protein sequences in UniprotKB matched to at least one Pfam domain, new families come from a range of sources, primarily the PDB and analysis of complete proteomes to find genes with no Pfam hit. For each family, a subset of sequences are aligned into a high-quality seed alignment. Sequences for the alignment are taken primarily from pfamseq with some supplementation from UniprotKB. This seed alignment is used to build a profile hidden Markov model using HMMER. This HMM is then searched against sequence databases, and all hits that reach a curated gathering threshold are classified as members of the protein family, the resulting collection of members is then aligned to the profile HMM to generate a full alignment. For each family, a curated gathering threshold is assigned that maximises the number of true matches to the family while excluding any false positive matches. False positives are estimated by observing overlaps between Pfam family hits that are not from the same clan and this threshold is used to assess whether a match to a family HMM should be included in the protein family. Upon each update of Pfam, gathering thresholds are reassessed to prevent overlaps between new and existing families, domains of Unknown Function represent a growing fraction of the Pfam database
2.
InterPro
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The contents of InterPro consist of diagnostic signatures and the proteins that they significantly match. The signatures consist of models which describe protein families, domains or sites, models are built from the amino acid sequences of known families or domains and they are subsequently used to search unknown sequences in order to classify them. Each of the databases of InterPro contribute towards a different niche, from very high-level. InterPros intention is to provide a one-stop-shop for protein classification, where all the signatures produced by the different member databases are placed into entries within the InterPro database. Signatures which represent equivalent domains, sites or families are put into the same entry, additional information such as a description, consistent names and Gene Ontology terms are associated with each entry, where possible. InterPro contains three main entities, proteins, signatures and entries, the proteins in UniProtKB are also the central protein entities in InterPro. Information regarding which signatures significantly match these proteins are calculated as the sequences are released by UniProtKB, only signatures deemed to be of sufficient quality are integrated into InterPro. InterPro also includes data for splice variants and the contained in the UniParc. The signatures from InterPro come from 11 member databases, which are listed below, cATH-Gene3D describes protein families and domain architectures in complete genomes. Protein families are formed using a Markov clustering algorithm, followed by multi-linkage clustering according to sequence identity, mapping of predicted structure and sequence domains is undertaken using hidden Markov models libraries representing CATH and Pfam domains. Functional annotation is provided to proteins from multiple resources, functional prediction and analysis of domain architectures is available from the Gene3D website. HAMAP stands for High-quality Automated and Manual Annotation of microbial Proteomes, HAMAP profiles are manually created by expert curators they identify proteins that are part of well-conserved bacterial, archaeal and plastid-encoded proteins families or subfamilies. PANTHER is a collection of protein families that have been subdivided into functionally related subfamilies. Hidden Markov models are built for each family and subfamily for classifying additional protein sequences, Pfam is a large collection of multiple sequence alignments and hidden Markov models covering many common protein domains and families. The primary PIRSF classification unit is the family, whose members are both homologous and homeomorphic. PRINTS is a compendium of protein fingerprints, a fingerprint is a group of conserved motifs used to characterise a protein family, its diagnostic power is refined by iterative scanning of UniProt. Usually the motifs do not overlap, but are separated along a sequence, ProDom domain database consists of an automatic compilation of homologous domains. Current versions of ProDom are built using a procedure based on recursive PSI-BLAST searches
3.
Protein Data Bank
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The Protein Data Bank is a crystallographic database for the three-dimensional structural data of large biological molecules, such as proteins and nucleic acids. The PDB is overseen by a called the Worldwide Protein Data Bank. The PDB is a key resource in areas of structural biology, most major scientific journals, and some funding agencies, now require scientists to submit their structure data to the PDB. Many other databases use protein structures deposited in the PDB, for example, SCOP and CATH classify protein structures, while PDBsum provides a graphic overview of PDB entries using information from other sources, such as Gene ontology. By 1971, one of Meyers programs, SEARCH, enabled researchers to access information from the database to study protein structures offline. SEARCH was instrumental in enabling networking, thus marking the beginning of the PDB. Upon Hamiltons death in 1973, Tom Koeztle took over direction of the PDB for the subsequent 20 years, in January 1994, Joel Sussman of Israels Weizmann Institute of Science was appointed head of the PDB. In October 1998, the PDB was transferred to the Research Collaboratory for Structural Bioinformatics, the new director was Helen M. Berman of Rutgers University. In 2003, with the formation of the wwPDB, the PDB became an international organization, the founding members are PDBe, RCSB, and PDBj. Each of the four members of wwPDB can act as deposition, data processing, the data processing refers to the fact that wwPDB staff review and annotate each submitted entry. The data are automatically checked for plausibility. The PDB database is updated weekly, likewise, the PDB holdings list is also updated weekly. As of 14 March 2017, the breakdown of current holdings is as follows,103,514 structures in the PDB have a structure factor file,9,057 structures have an NMR restraint file. 2,826 structures in the PDB have a chemical shifts file, therefore, the final conformation of the protein is obtained, in the latter case, by solving a distance geometry problem. A few proteins are determined by cryo-electron microscopy, the significance of the structure factor files, mentioned above, is that, for PDB structures determined by X-ray diffraction that have a structure file, the electron density map may be viewed. The data of such structures is stored on the electron density server, however, since 2007, the rate of accumulation of new protein structures appears to have plateaued. The file format used by the PDB was called the PDB file format. This original format was restricted by the width of computer punch cards to 80 characters per line, around 1996, the macromolecular Crystallographic Information file format, mmCIF, which is an extension of the CIF format started to be phased in
4.
Neuraminidase
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Neuraminidase enzymes are glycoside hydrolase enzymes that cleave the glycosidic linkages of neuraminic acids. Neuraminidase enzymes are a family, found in a range of organisms. The best-known neuraminidase is the viral neuraminidase, a target for the prevention of the spread of influenza infection. The viral neuraminidases are frequently used as antigenic determinants found on the surface of the influenza virus, some variants of the influenza neuraminidase confer more virulence to the virus than others. Other homologues are found in cells, which have a range of functions. At least four mammalian sialidase homologues have been described in the human genome, sialidase activities include assistance in the mobility of virus particles through the respiratory tract mucus and in the elution of virion progeny from the infected cell. Swiss-Prot lists 137 types of neuraminidase from various species as of October 18,2006, nine subtypes of influenza neuraminidase are known, many occur only in various species of duck and chicken. Subtypes N1 and N2 have been linked to epidemics in man. It has a head consisting of four co-planar and roughly spherical subunits, and it comprises a single polypeptide chain that is oriented in the opposite direction to the hemagglutinin antigen. The composition of the polypeptide is a chain of six conserved polar amino acids, followed by hydrophilic. β-Sheets predominate as the level of protein conformation. The enzymatic mechanism of influenza virus sialidase has been studied by Taylor et al. shown in Figure 1, the enzyme catalysis process has four steps. The first step involves the distortion of the α-sialoside from a 2C5 chair conformation to a pseudoboat conformation when the sialoside binds to the sialidase, the second step leads to an oxocarbocation intermediate, the sialosyl cation. The third step is the formation of Neu5Ac initially as the α-anomer, there are two major proteins on the surface of influenza virus particles. One is the lectin haemagglutinin protein with three relatively shallow sialic acid-binding sites and the other is enzyme sialidase with the site in a pocket. After the X-ray crystal structures of several influenza virus sialidases were available, the unsaturated sialic acid derivative 2-deoxy-2, 3-didehydro-D-N-acetylneuraminic acid, a sialosyl cation transition-state analogue, is believed the most potent inhibitor core template. Structurally modified Neu5Ac2en derivatives may give more effective inhibitors, many Neu5Ac2en-based compounds have been synthesized and tested for their influenza virus sialidase inhibitory potential. A series of amide-linked C9 modified Neu5Ac2en have been reported by Megesh, glycoside hydrolase Neuraminidase inhibitors Neuraminidase at the US National Library of Medicine Medical Subject Headings Orthomyxoviruses, Robert B
5.
Enzyme
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Enzymes /ˈɛnzaɪmz/ are macromolecular biological catalysts. Enzymes accelerate, or catalyze, chemical reactions, the molecules at the beginning of the process upon which enzymes may act are called substrates and the enzyme converts these into different molecules, called products. Almost all metabolic processes in the cell need enzymes in order to occur at rates fast enough to sustain life, the set of enzymes made in a cell determines which metabolic pathways occur in that cell. The study of enzymes is called enzymology, enzymes are known to catalyze more than 5,000 biochemical reaction types. Most enzymes are proteins, although a few are catalytic RNA molecules, enzymes specificity comes from their unique three-dimensional structures. Like all catalysts, enzymes increase the rate of a reaction by lowering its activation energy, some enzymes can make their conversion of substrate to product occur many millions of times faster. An extreme example is orotidine 5-phosphate decarboxylase, which allows a reaction that would take millions of years to occur in milliseconds. Chemically, enzymes are like any catalyst and are not consumed in chemical reactions, enzymes differ from most other catalysts by being much more specific. Enzyme activity can be affected by other molecules, inhibitors are molecules that decrease enzyme activity, many drugs and poisons are enzyme inhibitors. An enzymes activity decreases markedly outside its optimal temperature and pH, some enzymes are used commercially, for example, in the synthesis of antibiotics. French chemist Anselme Payen was the first to discover an enzyme, diastase and he wrote that alcoholic fermentation is an act correlated with the life and organization of the yeast cells, not with the death or putrefaction of the cells. In 1877, German physiologist Wilhelm Kühne first used the term enzyme, the word enzyme was used later to refer to nonliving substances such as pepsin, and the word ferment was used to refer to chemical activity produced by living organisms. Eduard Buchner submitted his first paper on the study of yeast extracts in 1897, in a series of experiments at the University of Berlin, he found that sugar was fermented by yeast extracts even when there were no living yeast cells in the mixture. He named the enzyme that brought about the fermentation of sucrose zymase, in 1907, he received the Nobel Prize in Chemistry for his discovery of cell-free fermentation. Following Buchners example, enzymes are usually named according to the reaction they carry out, the biochemical identity of enzymes was still unknown in the early 1900s. Sumner showed that the enzyme urease was a protein and crystallized it. These three scientists were awarded the 1946 Nobel Prize in Chemistry, the discovery that enzymes could be crystallized eventually allowed their structures to be solved by x-ray crystallography. This high-resolution structure of lysozyme marked the beginning of the field of structural biology, an enzymes name is often derived from its substrate or the chemical reaction it catalyzes, with the word ending in -ase
6.
Sialic acid
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Sialic acid is a generic term for the N- or O-substituted derivatives of neuraminic acid, a monosaccharide with a nine-carbon backbone. It is also the name for the most common member of this group, Sialic acids are found widely distributed in animal tissues and to a lesser extent in other organisms, ranging from plants and fungi to yeasts and bacteria, mostly in glycoproteins and gangliosides. That is because it seems to have appeared late in evolution, however, it has been observed in Drosophila embryos and other insects and in the capsular polysaccharides of certain strains of bacteria. In humans the brain has the highest sialic acid concentration, where these acids play an important role in neural transmission, in general, the amino group bears either an acetyl or a glycolyl group, but other modifications have been described. The hydroxyl substituents may vary considerably, acetyl, lactyl, methyl, sulfate, the term sialic acid was first introduced by Swedish biochemist Gunnar Blix in 1952. The sialic acid family includes 43 derivatives of the nine-carbon sugar neuraminic acid, the numbering of the sialic acid structure begins at the carboxylate carbon and continues around the chain. The configuration that places the carboxylate in the position is the alpha-anomer. The alpha-anomer is the form that is found when sialic acid is bound to glycans, however, in solution, it is mainly in the beta-anomeric form. Sialic acid is synthesized by glucosamine 6 phosphate and acetyl CoA through a transferase and this becomes N-acetylmannosamine-6-P through epimerization, which reacts with phosphoenolpyruvate producing N-acetylneuraminic-9-P. This compound is synthesized in the nucleus of the animal cell, in bacterial systems, sialic acids are biosynthesized by an aldolase enzyme. The enzyme uses a derivative as a substrate, inserting three carbons from pyruvate into the resulting sialic acid structure. These enzymes can be used for synthesis of sialic acid derivatives. Sialic acid-rich glycoproteins bind selectin in humans and other organisms, metastatic cancer cells often express a high density of sialic acid-rich glycoproteins. This overexpression of sialic acid on surfaces creates a charge on cell membranes. This creates repulsion between cells and helps these late-stage cancer cells enter the blood stream, many bacteria also use sialic acid in their biology, although this is usually limited to bacteria that live in association with higher animals. Many of these incorporate sialic acid into cell surface features like their lipopolysaccharide and capsule, other bacteria simply use sialic acid as a good nutrient source, as it contains both carbon and nitrogen and can be converted to fructose-6-phosphate, which can then enter central metabolism. Sialic acid-rich oligosaccharides on the glycoconjugates found on surface membranes help keep water at the surface of cells, the sialic acid-rich regions contribute to creating a negative charge on the cells surfaces. Since water is a molecule with partial positive charges on both hydrogen atoms, it is attracted to cell surfaces and membranes
. PMID 18321971.
