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Backbone-dependent Rotamer Library
In biochemistry, a backbone-dependent rotamer library provides the frequencies, mean dihedral angles, and standard deviations of the discrete conformations (known as rotamers) of the amino acid side chains in proteins as a function of the backbone dihedral angles φ and ψ of the Ramachandran map. By contrast, backbone-independent rotamer libraries express the frequencies and mean dihedral angles for all side chains in proteins, regardless of the backbone conformation of each residue type. Backbone-dependent rotamer libraries have been shown to have significant advantages over backbone-independent rotamer libraries, principally when used as an energy term, by speeding up search times of side-chain packing algorithms used in protein structure prediction and protein design. History The first backbone-dependent rotamer library was developed in 1993 by Roland Dunbrack and Martin Karplus to assist the prediction of the Cartesian coordinates of a protein's side chains given the expe ...
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Serine Backbone-dependent Chi1 Rotamer Populations
Serine (symbol Ser or S) is an α-amino acid that is used in the biosynthesis of proteins. It contains an α-amino group (which is in the protonated − form under biological conditions), a carboxyl group (which is in the deprotonated − form under biological conditions), and a side chain consisting of a hydroxymethyl group, classifying it as a polar amino acid. It can be synthesized in the human body under normal physiological circumstances, making it a nonessential amino acid. It is encoded by the codons UCU, UCC, UCA, UCG, AGU and AGC. Occurrence This compound is one of the naturally occurring proteinogenic amino acids. Only the L-stereoisomer appears naturally in proteins. It is not essential to the human diet, since it is synthesized in the body from other metabolites, including glycine. Serine was first obtained from silk protein, a particularly rich source, in 1865 by Emil Cramer. Its name is derived from the Latin for silk, ''sericum''. Serine's structure was establi ...
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Glycine
Glycine (symbol Gly or G; ) is an amino acid that has a single hydrogen atom as its side chain. It is the simplest stable amino acid (carbamic acid is unstable), with the chemical formula NH2‐ CH2‐ COOH. Glycine is one of the proteinogenic amino acids. It is encoded by all the codons starting with GG (GGU, GGC, GGA, GGG). Glycine is integral to the formation of alpha-helices in secondary protein structure due to its compact form. For the same reason, it is the most abundant amino acid in collagen triple-helices. Glycine is also an inhibitory neurotransmitter – interference with its release within the spinal cord (such as during a ''Clostridium tetani'' infection) can cause spastic paralysis due to uninhibited muscle contraction. It is the only achiral proteinogenic amino acid. It can fit into hydrophilic or hydrophobic environments, due to its minimal side chain of only one hydrogen atom. History and etymology Glycine was discovered in 1820 by the French chemist He ...
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Phenylalanine
Phenylalanine (symbol Phe or F) is an essential α-amino acid with the formula . It can be viewed as a benzyl group substituted for the methyl group of alanine, or a phenyl group in place of a terminal hydrogen of alanine. This essential amino acid is classified as neutral, and nonpolar because of the inert and hydrophobic nature of the benzyl side chain. The L-isomer is used to biochemically form proteins coded for by DNA. Phenylalanine is a precursor for tyrosine, the monoamine neurotransmitters dopamine, norepinephrine (noradrenaline), and epinephrine (adrenaline), and the skin pigment melanin. It is encoded by the codons UUU and UUC. Phenylalanine is found naturally in the milk of mammals. It is used in the manufacture of food and drink products and sold as a nutritional supplement for its analgesic and antidepressant effects. It is a direct precursor to the neuromodulator phenethylamine, a commonly used dietary supplement. As an essential amino acid, phenylalanine is n ...
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Aspartate
Aspartic acid (symbol Asp or D; the ionic form is known as aspartate), is an α-amino acid that is used in the biosynthesis of proteins. Like all other amino acids, it contains an amino group and a carboxylic acid. Its α-amino group is in the protonated –NH form under physiological conditions, while its α-carboxylic acid group is deprotonated −COO− under physiological conditions. Aspartic acid has an acidic side chain (CH2COOH) which reacts with other amino acids, enzymes and proteins in the body. Under physiological conditions (pH 7.4) in proteins the side chain usually occurs as the negatively charged aspartate form, −COO−. It is a non-essential amino acid in humans, meaning the body can synthesize it as needed. It is encoded by the codons GAU and GAC. D-Aspartate is one of two D-amino acids commonly found in mammals. .html" ;"title="/sup>">/sup> In proteins aspartate sidechains are often hydrogen bonded to form asx turns or asx motifs, which frequently occur at t ...
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Asparagine
Asparagine (symbol Asn or N) is an α-amino acid that is used in the biosynthesis of proteins. It contains an α-amino group (which is in the protonated −NH form under biological conditions), an α-carboxylic acid group (which is in the deprotonated −COO− form under biological conditions), and a side chain carboxamide, classifying it as a polar (at physiological pH), aliphatic amino acid. It is non-essential in humans, meaning the body can synthesize it. It is encoded by the codons AAU and AAC. History Asparagine was first isolated in 1806 in a crystalline form by French chemists Louis Nicolas Vauquelin and Pierre Jean Robiquet (then a young assistant). It was isolated from asparagus juice, in which it is abundant, hence the chosen name. It was the first amino acid to be isolated. Three years later, in 1809, Pierre Jean Robiquet identified a substance from liquorice root with properties which he qualified as very similar to those of asparagine, and which Plisson identi ...
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Orbital Hybridisation
In chemistry, orbital hybridisation (or hybridization) is the concept of mixing atomic orbitals to form new ''hybrid orbitals'' (with different energies, shapes, etc., than the component atomic orbitals) suitable for the pairing of electrons to form chemical bonds in valence bond theory. For example, in a carbon atom which forms four single bonds the valence-shell s orbital combines with three valence-shell p orbitals to form four equivalent sp3 mixtures in a tetrahedral arrangement around the carbon to bond to four different atoms. Hybrid orbitals are useful in the explanation of molecular geometry and atomic bonding properties and are symmetrically disposed in space. Usually hybrid orbitals are formed by mixing atomic orbitals of comparable energies. History and uses Chemist Linus Pauling first developed the hybridisation theory in 1931 to explain the structure of simple molecules such as methane (CH4) using atomic orbitals. Pauling pointed out that a carbon atom forms four ...
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Mathematical Optimization
Mathematical optimization (alternatively spelled ''optimisation'') or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives. It is generally divided into two subfields: discrete optimization and continuous optimization. Optimization problems of sorts arise in all quantitative disciplines from computer science and engineering to operations research and economics, and the development of solution methods has been of interest in mathematics for centuries. In the more general approach, an optimization problem consists of maxima and minima, maximizing or minimizing a Function of a real variable, real function by systematically choosing Argument of a function, input values from within an allowed set and computing the Value (mathematics), value of the function. The generalization of optimization theory and techniques to other formulations constitutes a large area of applied mathematics. More generally, opti ...
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Rosetta@Home
Rosetta@home is a volunteer computing project researching protein structure prediction on the Berkeley Open Infrastructure for Network Computing (BOINC) platform, run by the Baker laboratory at the University of Washington. Rosetta@home aims to predict protein–protein docking and design new proteins with the help of about fifty-five thousand active volunteered computers processing at over 487,946 GigaFLOPS on average as of September 19, 2020. Foldit, a Rosetta@home videogame, aims to reach these goals with a crowdsourcing approach. Though much of the project is oriented toward basic research to improve the accuracy and robustness of proteomics methods, Rosetta@home also does applied research on malaria, Alzheimer's disease, and other pathologies. Like all BOINC projects, Rosetta@home uses idle computer processing resources from volunteers' computers to perform calculations on individual workunits. Completed results are sent to a central project server where they are validate ...
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Phenylalanine Backbone-dependent Chi1 Rotamer Populations
Phenylalanine (symbol Phe or F) is an essential α-amino acid with the formula . It can be viewed as a benzyl group substituted for the methyl group of alanine, or a phenyl group in place of a terminal hydrogen of alanine. This essential amino acid is classified as neutral, and nonpolar because of the inert and hydrophobic nature of the benzyl side chain. The L-isomer is used to biochemically form proteins coded for by DNA. Phenylalanine is a precursor for tyrosine, the monoamine neurotransmitters dopamine, norepinephrine (noradrenaline), and epinephrine (adrenaline), and the skin pigment melanin. It is encoded by the codons UUU and UUC. Phenylalanine is found naturally in the milk of mammals. It is used in the manufacture of food and drink products and sold as a nutritional supplement for its analgesic and antidepressant effects. It is a direct precursor to the neuromodulator phenethylamine, a commonly used dietary supplement. As an essential amino acid, phenylalanine is not sy ...
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Directional Statistics
Directional statistics (also circular statistics or spherical statistics) is the subdiscipline of statistics that deals with directions (unit vectors in Euclidean space, R''n''), axes (lines through the origin in R''n'') or rotations in R''n''. More generally, directional statistics deals with observations on compact Riemannian manifolds including the Stiefel manifold. The fact that 0 degrees and 360 degrees are identical angles, so that for example 180 degrees is not a sensible mean of 2 degrees and 358 degrees, provides one illustration that special statistical methods are required for the analysis of some types of data (in this case, angular data). Other examples of data that may be regarded as directional include statistics involving temporal periods (e.g. time of day, week, month, year, etc.), compass directions, dihedral angles in molecules, orientations, rotations and so on. Circular distributions Any probability density function (pdf) \ p(x) on the line can be "wrappe ...
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Von Mises Distribution
In probability theory and directional statistics, the von Mises distribution (also known as the circular normal distribution or Tikhonov distribution) is a continuous probability distribution on the circle. It is a close approximation to the wrapped normal distribution, which is the circular analogue of the normal distribution. A freely diffusing angle \theta on a circle is a wrapped normally distributed random variable with an unwrapped variance that grows linearly in time. On the other hand, the von Mises distribution is the stationary distribution of a drift and diffusion process on the circle in a harmonic potential, i.e. with a preferred orientation. The von Mises distribution is the maximum entropy distribution for circular data when the real and imaginary parts of the first circular moment are specified. The von Mises distribution is a special case of the von Mises–Fisher distribution on the ''N''-dimensional sphere. Definition The von Mises probability density funct ...
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Bayesian Statistics
Bayesian statistics is a theory in the field of statistics based on the Bayesian interpretation of probability where probability expresses a ''degree of belief'' in an event. The degree of belief may be based on prior knowledge about the event, such as the results of previous experiments, or on personal beliefs about the event. This differs from a number of other interpretations of probability, such as the frequentist interpretation that views probability as the limit of the relative frequency of an event after many trials. Bayesian statistical methods use Bayes' theorem to compute and update probabilities after obtaining new data. Bayes' theorem describes the conditional probability of an event based on data as well as prior information or beliefs about the event or conditions related to the event. For example, in Bayesian inference, Bayes' theorem can be used to estimate the parameters of a probability distribution or statistical model. Since Bayesian statistics treats probabi ...
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