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Pages in category "Protein folding"
The following 15 pages are in this category, out of 15 total. This list may not reflect recent changes (learn more).
|Wikimedia Commons has media related to Protein folding.|
The following 15 pages are in this category, out of 15 total. This list may not reflect recent changes (learn more).
1. Protein folding – It is the physical process by which a polypeptide folds into its characteristic and functional three-dimensional structure from random coil. Each protein exists as a polypeptide or random coil when translated from a sequence of mRNA to a linear chain of amino acids. This polypeptide lacks any stable three-dimensional structure, as the polypeptide chain is being synthesized by the ribosome, the linear chain begins to fold into its three dimensional structure. Folding begins to occur even during translation of the polypeptide chain, amino acids interact with each other to produce a well-defined three-dimensional structure, the folded protein, known as the native state. The resulting three-dimensional structure is determined by the amino acid sequence or primary structure, the energy landscape describes the folding pathways in which the unfolded protein is able to assume its native state. Experiments beginning in the 1980s indicate the codon for an acid can also influence protein structure. The correct three-dimensional structure is essential to function, although parts of functional proteins may remain unfolded. Failure to fold into native structure generally produces inactive proteins, several neurodegenerative and other diseases are believed to result from the accumulation of amyloid fibrils formed by misfolded proteins. Many allergies are caused by folding of some proteins, because the immune system does not produce antibodies for certain protein structures. The primary structure of a protein, its linear amino-acid sequence, the amino acid composition is not as important as the sequence. The essential fact of folding, however, remains that the amino acid sequence of protein contains the information that specifies both the native structure and the pathway to attain that state. This is not to say that nearly identical amino acid sequences always fold similarly, conformations differ based on environmental factors as well, similar proteins fold differently based on where they are found. Formation of a structure is the first step in the folding process that a protein takes to assume its native structure. Formation of intramolecular hydrogen bonds provides another important contribution to protein stability, alpha helices are formed by hydrogen bonding of the backbone to form a spiral shape. The beta pleated sheet is a structure forms with the backbone bending over itself to form the hydrogen bonds. The hydrogen bonds are between the hydrogen and carbonyl carbon of the peptide bond. The alpha helices and beta pleated sheets can be amphipathic in nature, or contain a hydrophilic portion, secondary structure hierarchically gives way to tertiary structure formation. Tertiary structure of a protein involves a single chain, however
2. Protein dynamics – Proteins are generally thought to adopt unique structures determined by their amino acid sequences, as outlined by Anfinsens dogma. However, proteins are not strictly static objects, but rather populate ensembles of conformations, transitions between these states occur on a variety of length scales and time scales, and have been linked to functionally relevant phenomena such as allosteric signaling and enzyme catalysis. The study of dynamics is most directly concerned with the transitions between these states, but can also involve the nature and equilibrium populations of the states themselves. Portions of protein structures often deviate from the equilibrium state, some such excursions are harmonic, such as stochastic fluctuations of chemical bonds and bond angles. Others are anharmonic, such as sidechains that jump between separate discrete energy minima, or rotamers, evidence for local flexibility is often obtained from NMR spectroscopy. Flexible and potentially disordered regions of a protein can be detected using the random coil index, flexibility in folded proteins can be identified by analyzing the spin relaxation of individual atoms in the protein. Many residues are in spatial proximity in protein structures. This is true for most residues that are contiguous in the primary sequence, because of this proximity, these residuess energy landscapes become coupled based on various biophysical phenomena such as hydrogen bonds, ionic bonds, and van der Waals interactions. Transitions between states for such sets of residues therefore become correlated and this is perhaps most obvious for surface-exposed loops, which often shift collectively to adopt different conformations in different crystal structures. However, coupled conformational heterogeneity is also evident in secondary structure. For example, consecutive residues and residues offset by 4 in the sequence often interact in α helices. When these coupled residues form pathways linking functionally important parts of a protein, the presence of multiple domains in proteins gives rise to a great deal of flexibility and mobility, leading to protein domain dynamics. Domain motions can be inferred by comparing different structures of a protein and they can also be suggested by sampling in extensive molecular dynamics trajectories and principal component analysis. The phosphoinositide domain swivels between two states in order to bring a group from the active site of the nucleotide binding domain to that of the phosphoenolpyruvate/pyruvate domain. The phosphate group is moved over a distance of 45 Å involving a domain motion of about 100 degrees around a single residue. In enzymes, the closure of one domain onto another captures a substrate by an induced fit, a detailed analysis by Gerstein led to the classification of two basic types of domain motion, hinge and shear. Only a relatively small portion of the chain, namely the inter-domain linker, a study by Hayward found that the termini of α-helices and β-sheets form hinges in a large number of cases. Many hinges were found to two secondary structure elements acting like hinges of a door, allowing an opening and closing motion to occur
3. Proteopathy – In medicine, proteopathy refers to a class of diseases in which certain proteins become structurally abnormal, and thereby disrupt the function of cells, tissues and organs of the body. Often the proteins fail to fold into their normal configuration, in this misfolded state, the proteopathies include such diseases as Creutzfeldt–Jakob disease and other prion diseases, Alzheimers disease, Parkinsons disease, amyloidosis, and a wide range of other disorders. In 1859, Friedreich and Kekulé demonstrated that, rather consisting of cellulose. However, some proteinaceous lesions lack birefringence and contain few or no classical amyloid fibrils, in most, if not all proteopathies, a change in 3-dimensional folding increases the tendency of a specific protein to bind to itself. In this aggregated form, the protein is resistant to clearance, in some cases, misfolding of the protein results in a loss of its usual function. Because proteins share a structural feature known as the polypeptide backbone. However, only a small number of proteins are linked to proteopathic disorders. For example, proteins that are normally unfolded or relatively unstable as monomers are likely to misfold into an abnormal conformation. In nearly all instances, the molecular configuration involves an increase in beta-sheet secondary structure of the protein. They have been most thoroughly studied with regard to prion disease, the likelihood that proteopathy will develop is increased by certain risk factors that promote the self-assembly of a protein. Advancing age is a risk factor, as is traumatic brain injury. In the aging brain, multiple proteopathies can overlap, for example, in addition to tauopathy and Aβ-amyloidosis, many Alzheimer patients have concomitant synucleinopathy in the brain. It is hypothesized that chaperones and co-chaperones may antagonize proteotoxicity during aging, some proteins can be induced to form abnormal assemblies by exposure to the same protein that has folded into a disease-causing conformation, a process called seeding or permissive templating. In this way, the state can be brought about in a susceptible host by the introduction of diseased tissue extract from an afflicted donor. The best known form of such inducible proteopathy is prion disease, in all of these instances, an aberrant form of the protein itself appears to be the pathogenic agent. For example, AA amyloidosis can be stimulated in mice by such diverse macromolecules as silk, the yeast amyloid Sup35, and curli fibrils from the bacterium Escherichia coli. In addition, apolipoprotein AII amyloid can be induced in mice by a variety of β-sheet rich amyloid fibrils, there is also experimental evidence for cross-seeding between prion protein and Aβ. In general, such heterologous seeding is less efficient than is seeding by a form of the same protein
4. Phi value analysis – Phi value analysis is an experimental protein engineering method used to study the structure of the folding transition state in small protein domains that fold in a two-state manner. In phi-value analysis, the kinetics and conformational folding stability of the wild-type protein are compared with those of one or more point mutants. Typically, a fraction of the proteins residues are mutated one by one to identify clusters of residues that are well-ordered in the folded transition state. The interactions of these residues can be validated using double-mutant-cycle phi analysis, examples of proteins that have been studied by phi value analysis include chymotrypsin inhibitor, SH3 domains, individual domains of proteins L and G, ubiquitin, and barnase. Thus, the phi value represents the ratio of the energetic destabilization introduced by the mutation to the state versus that introduced to the native folded state. The phi value should range from 0 to 1, but also negative phi values can be observed and it is generally the case that conservative substitutions on the surface of a protein yield phi values near 1. Phi value analysis fundamentally assumes a close relationship between structure and energy, however, if the energy landscape is relatively flat or has many local minima, the relationship may not hold strongly enough for free energy destabilizations to provide useful structural information. The method also assumes that the pathway is not significantly altered. Also, it is assumed that the interactions that stabilize a folding transition state are native-like in nature. Many recent studies of folding, however, have suggested that stabilizing non-native interactions in a folding transition state may aid in folding. An elegant example of this is given in Zarrine-Afsar et al, PNAS, where authors have demonstrated that stabilizing non-native interaction in the Fyn SH3 domain actually accelerated the folding rate of this protein. Alan Fersht pioneered the phi value analysis method by first applying it to the bacterial protein barnase. Phi values were found to vary considerably with the location of the mutation, with regions of the protein yielding values near 0. Such variations in the folding rate within a protein present another challenge in interpreting phi values, folding and unfolding simulations, though computationally expensive, can provide valuable structural information that complements phi value results. ϕ -value analysis Other kinetic-perturbation techniques for analyzing the folding transition state have been developed in recent years, however, Fersht has illustrated some difficulties with this approach. ϕ -value analysis Experimental errors can be high in measuring equilibrium stability as well the folding/unfolding rates in water for the wild-type protein, the necessity of extrapolating phi values in pure water from measurements made in solutions containing denaturants adds uncertainty to the reported values. In addition, calculated phi values have been shown to depend strongly on the number of points collected. Chevron plot Denaturation midpoint Equilibrium unfolding
5. Foldit – Foldit is an online puzzle video game about protein folding. It is part of a research project developed by the University of Washington, Center for Game Science. The objective of Foldit is to fold the structures of selected proteins as well as possible, the highest scoring solutions are analyzed by researchers, who determine whether or not there is a native structural configuration that can be applied to relevant proteins in the real world. Scientists can then use these solutions to target and eradicate diseases, a 2010 paper in the science journal Nature credited Foldits 57,000 players with providing useful results that matched or outperformed algorithmically computed solutions. Prof. David Baker, a research scientist at the University of Washington. Seth Cooper was the game designer. Its results were sent to a server for verification. Some Rosetta@home users became frustrated when they saw ways to solve protein structures, many of the same people who created Rosetta@home worked on Foldit. The public beta version was released in May 2008 and has 240,000 registered players, since 2008, Foldit has participated in Critical Assessment of Techniques for Protein Structure Prediction experiments, submitting its best solutions to targets based on unknown protein structures. CASP is a program to assess methods of protein structure prediction. Protein structure prediction is important in fields of science, including bioinformatics, molecular biology. Identifying natural proteins structural configurations enables scientists to understand them better and this can lead to creating novel proteins by design, advances in treating disease, and solutions for other real-world problems such as invasive species, waste, and pollution. The process by which living beings create the structure of proteins, protein biosynthesis, is reasonably well understood. However, determining how a given proteins primary structure becomes a functioning three-dimensional structure, the general process is understood, but predicting a proteins eventual, functioning structure is computationally demanding. Similarly to Rosetta@home, Foldit is a means to discover native protein structures faster through distributed computing, however, Foldit has a greater emphasis on community collaboration through its forums, where users can collaborate on certain folds. Furthermore, Foldits crowdsourced approach places an emphasis on the user. Foldits virtual interaction and gamification create a unique and innovative environment with the potential to greatly advance protein folding research, Foldit attempts to apply the human brains three-dimensional pattern matching and spatial reasoning abilities to help solve the problem of protein structure prediction. Current puzzles are based on well-understood proteins, by analysing how humans intuitively approach these puzzles, researchers hope to improve the algorithms used by protein-folding software
6. Proteostasis – Therefore, adapting proteostasis should enable the restoration of proteostasis once its loss leads to pathology. Cellular proteostasis is key to ensuring successful development, healthy aging, resistance to environmental stresses, mechanisms by which proteostasis is ensured include regulated protein translation, chaperone assisted protein folding and protein degradation pathways. Adjusting each of these mechanisms to the demand for proteins is essential to all cellular functions relying on a correctly folded proteome. One of the first points of regulation for proteostasis is during translation and this is accomplished via the structure of the ribosome, a complex central to translation. These two characteristics shape the way the protein folds and influences the proteins future interactions. The synthesis of a new peptide chain using the ribosome is very slow and the ribosome can even be stalled when it encounters a rare codon and these pauses provide an opportunity for an individual protein domain to have the necessary time to become folded before the production of following domains. This facilitates the correct folding of multi-domain proteins, the newly synthesized peptide chain exits the ribosome into the cellular environment through the narrow ribosome exit channel. Due to space restriction in the channel the nascent chain already forms secondary. For example, a helix is one such structural property that is commonly induced in this exit channel. At the same time the channel also prevents premature folding by impeding large scale interactions within the peptide chain which would require more space. In order to maintain protein homeostasis post-translationally, the cell makes use of molecular chaperones and/or chaperonins, chaperones begin to assist in protein folding as soon as a nascent chain longer than 60 amino acids emerges from the ribosome exit channel. One of the most studied ribosome binding chaperones is trigger factor, trigger Factor works to stabilize the peptide, promotes its folding, prevents aggregation, and promotes refolding of denatured model substrates. Trigger factor not only works to properly fold the protein but also recruits other chaperones to the ribosome. Hsp70 surrounds an unfolded peptide chain, thereby preventing aggregation and promoting folding, chaperonins are a special class of chaperones that promote native state folding by cyclically encapsulating the peptide chain. Chaperonins are divided into two groups, Group 1 chaperonins are commonly found in bacteria, chloroplasts, and mitochondria. Group 2 chaperonins are found in both the cytosol of cells as well as in archaea. Group 2 chaperonins also contain an additional component which acts as a lid for the cylindrical protein chamber. All chaperonins exhibit two states, between which they can cycle, the third component of the proteostasis network is the protein degradation machinery