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Interactive function

The biasing function is applied to spread the range of configurations sampled such that the trajectory contains configurations appropriate to both the initial and final states. For the creation or deletion of atoms a softcore interaction function may be used. The standard Lennard-Jones (LJ) function used to model van der Waals interactions between atoms is strongly repulsive at short distances and contains a singularity at r = 0. This precludes two atoms from occupying the same position. A so-called softcore potential in contrast approaches a finite value at short distances. This removes the sin-... [Pg.154]

Allen JW, Shanker G, Tan KH, Aschner M. 2002. The consequences of methyhnercury exposure on interactive functions between astrocytes and neurons. Neurotoxicology 23 755-759. [Pg.166]

Thus the alternative approach is to create enhancements (add-ons) to an ERP system that do not have their own persistent database and provide additional interactive functions, visualization and algorithmic processing of enhanced model data. The add-ons create a temporary local data storage (LiveCache) to effectively process the enhanced data. However, all data is stored persistently exclusively in the ERP system. This allows for the local LiveCache to use a mapping of the ERP data model that is structured in a way that is more suitable for APS purposes. Additionally the... [Pg.274]

Fig. 8. Representation of the interaction functions O and R in terms of equivalent sphere radii and Rj respectively. Both interaction functions depend on the segment density but small solvent molecules can easier penetrate into a coil (left) than two of such coils penetrate into each other (right)... Fig. 8. Representation of the interaction functions O and R in terms of equivalent sphere radii and Rj respectively. Both interaction functions depend on the segment density but small solvent molecules can easier penetrate into a coil (left) than two of such coils penetrate into each other (right)...
Histone methyltransferases may associate or act cooperatively with either HATs or HDACs. In fission yeast the H3 Lys-14 deacetylase Clr3 interacts functionally with H3 Lys-9 methyltransferase Clr4. Clr4 methylates Lys-9 of H3, a process facilitated by Rikl, resulting in the recruitment of Swi6 and heterochromatin assembly [157,221]. In Drosophila SU(VAR)3-9 H3 Lys-9 methyltransferase is in complex with HDACl [222]. Thus, HDACl would deacetylate acetylated Lys-9 allowing methylation by SU(VAR)3-9 at this site to occur. CBP, a potent HAT, is associated with a histone methyltransferase that methylated H3 at Lys-9 and to a lesser extent Lys-4. H3 methylation at Lys-9 did not alter the HAT activity of CBP, and vice versa acetylation of H3 (predominantly Lys-14) did not affect the associated histone methyltransferase activity [223]. [Pg.226]

The Gordon-Kim interaction functions may be compared with empirical potential functions derived by energy- or net-force minimization methods using known crystal structures. The O—O Gordon-Kim potentials are more repulsive, as illustrated in Fig. 9.2. Spackman points out that the empirical potentials likely contain a significant attractive component because of the inadequate allowance for electrostatic interactions in their derivation. This attractive component is included in the electrostatic interaction in the density functional model. [Pg.205]

The described examples, where more than one carbohydrate is attached to a synthetic framework, foreshadow the advances that we should expect in research involving multivalent protein-carbohydrate interactions. Functionalization of multivalent... [Pg.353]

For many practically important interaction functions, the Fourier coefficients in Eq. (D.9) have finite analytic forms, for example, the Lennard-Jones potential, the Yukawa potential, the Morse potential, and functions that can be derived from those functions. For a power-law interaction... [Pg.355]

A base can be contacted by more than one amino acid residue. Furthermore, there are many examples of one amino acid residue, e.g. Arg, contacting two sequential bases. This type of interaction functions as a clip and maintains a spatially defined arrangement. [Pg.15]

There are four basic mechanisms underlying interactions functional, chemical, dispositional, and receptor. [Pg.15]

Thermodynamic descriptions of polymer systems are usually based on a rigid-lattice model published in 1941 independently by Staverman and Van Santen, Huggins and Flory where the symbol x(T) is used to express the binary interaction function [16]. Once the interaction parameter is known we can calculate the liquid liquid phase behaviour. [Pg.578]

In many production routes, and also during processing, polymer systems have to undergo pressure. Changes in the volume of a system by compression or expansion, however, cannot be dealt with in rigid-lattice-type models. Thus, non-combinatorial free volume ( equation of state ) contributions to AG have been advanced [23 - 29]. Detailed interaction functions have been suggested (but all of them are based on adjustable parameters, for blends, e.g., Mean-field lattice gas [30], SAFT [31], specific interactions [32]), and have been succesfully applied, for example, by Kennis et al. [33]. [Pg.579]

Polymer systems containing copolymers call for a further extension of the thermodynamic model. The interaction function for statistical copolymers was originally derived by Simha and Branson [34], discussed by Stockmayer [35] et al., and experimentally verified by Glbckner and Lohmann [36]. [Pg.579]

The miscibility gap will be described more accurately when a meanfield lattice gas approach is choosen [30], The mathematical form of the interaction function in all the above models may bring about a negative value for the effective interaction parameter, g, while all binary interactions by themselves are positive. The complexity of copolymer phase behaviour can be attributed to this peculiarity, like the miscibility-windows in mixtures of a copolymer with another homopolymer [37], or with a second copolymer [38,39]. [Pg.579]

Summary. The electron density model of substituent-ring interactions functions better than the MO model, which is not surprising since the electron density covers all MO effects while any MO model will simplify orbital interactions by selecting just a few important... [Pg.95]

Metabolic chemistry is characterized by functionality. Each reaction is important because of its participation in a sequence of reactions, and each sequence interacts functionally with other sequences. [Pg.240]


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See also in sourсe #XX -- [ Pg.40 , Pg.42 ]




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Aluminum interaction with functional groups

Apolipoproteins, functions receptor interactions

Basis functions interaction terms between

Basis functions, interaction site fluids

Bessel function interaction

Biomolecule-functionalized nanoparticles interaction with

Cation interaction with phosphine oxide functionalized

Chemical Interactions to the Adhesion Between Evaporated Metals and Functional Croups of Different Types at Polymer Surfaces

Chemical functionalities, interaction

Complementary functional/interactional

Complementary functional/interactional groups

Configuration Interaction wave function

Configuration interactions state functions

Density functional approaches interactions

Density functional theory interaction prediction

Density functional theory interactions

Density functional theory intermolecular interactions, electron

Density functional theory protein-ligand interactions

Density functionals covalent interactions

Density functionals noncovalent interactions

Description of Scoring Functions for Receptor-Ligand Interactions

Drug-receptor interactions functional group contributions

Electronic wave functions electrostatic interactions

Electrostatic potential, molecular interactive electronic density function

Energy Relations for Functional Groups and Their Interactions

Energy derivatives interaction wave functions

Full configuration interaction wave functions

Function interaction with antibodies

Functional Interaction of the Calcium Channel Subunits

Functional Interactions of PARP-1 with

Functional Interactions of PARP-1 with p53 and Genomic Integrity

Functional Interactions of PARP-1 with p53 in Apoptotic Cells

Functional Materials via Multiple Noncovalent Interactions

Functional groups dipole interactions

Functional groups drug-receptor interactions

Functional groups electrostatic interactions

Functional groups hydrophobic interactions

Functional groups inductive interactions

Functional groups interacting, local shapes

Functional groups interaction

Functional groups steric interactions

Functional interactions

Functional interactions

Functional monomer-template interactions

Functional monomers interactions

Functionalization and Solubilization of BN Nanotubes by Interaction with

General Interaction Properties Function descriptors

General Interaction Properties Function procedure

General interaction properties function

General interaction properties function GIPF)

Ground-state wave function interactions

Induction/dispersion interactions functional

Induction/dispersion interactions functionals

Interaction Potential and Partition Function

Interaction energy functions, poly

Interaction energy functions, poly(vinyl

Interaction function

Interaction of functional groups

Interaction potential wave functions

Interaction site fluids pair correlation functions

Interactions between Functional Elements

Interactions of Functional Dyes

Interactions transfer function

Interactive Functions and Algorithms

Interactive difference function

Ligand-receptor interaction-induced functional effects

Lymphocyte function-associated interactions

Multireference configuration interaction wave functions

Neutron-nucleus interaction function

Opioid-chemokine receptor interaction function

Pair correlation function, interaction site

Pair correlation function, interaction-induced

Pair interactions sequence-structure-function prediction

Partition functions intermolecular interaction, perturbative

Polar functional group interaction

Polarization functions interactions

Potential energy functions interactions)

Potential functions harmonic interaction

Potential functions nonbonded interactions

Purchasing interaction with other functions

Response equations interaction wave functions

Selectin-ligand interactions in lymphocyte function

Self-interaction-correction functional

Self-interaction-free functionals

Side Chain Functionalization Using Coulombic Interactions

Solvent-protein interactions functional roles

Steroid Molecular Structure, Protein Interaction and Biological Function

Structure, Function, and Interactions

The Interaction Function

The Role of Functional Groups in Drug-Receptor Interactions

The Strengths of Functional Group Contributions to Drug-Receptor Interactions

The scaling functions for purely electromagnetic interactions

Time-dependent density functional interacting electrons

Vibrational wave function interaction with rotation

Water interaction with functional groups

Wave-function based methods configuration interactions

Weak interactions. Generalized product functions

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