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Lattice database

Raising Pevoi plays the role of skewing the database composition toward stronger binders (Fig. 14.1b). In the limit of pevoi 0, the lattice database will consist of randomly selected ligands. It is assumed that a sufficient number of ligands have been added and the evolution process is continued long enough until equilibrium is reached. By this, it is meant that the statistical distributions of contacts in this database are not altered by the inclusion of additional complexes. [Pg.330]

It is important to emphasize that this lattice database is highly idealized compared to real databases. Unlike the lattice database, real databases cannot be treated as thermodynamic ensembles of protein-ligand complexes equilibrated at room temperature [33,34]. Two of the more straightforward reasons are mentioned here. First, real databases are inherently biased toward strong binders (K < 10 pM), because weak binders are difficult to crystallize and of lesser interest. Second, as mentioned above, real databases are not composed of a representative selection of proteins and ligands, and their compositions are biased toward peptide and peptidomimetic inhibitors and certain protein superfamilies. In contrast, because only one protein and four ligand types are used, the lattice database should have representative ligand compositions. [Pg.330]

With this database in hand, a simple question is asked [29] How different is a knowledge-based potential derived from this lattice database compared to the actual energy function used to construct the database If statistical errors are negligible and the knowledge-based method is perfect, the answer is expected to be They are exactly the same. ... [Pg.330]

A database of lattice protein-ligand complexes is now constructed with the following steps ... [Pg.329]

The effect of this expansion process is illustrated in Figure 4.4, in which all points in the sample database are drawn from a donut-shaped object. The outline of that object is quickly reproduced, with increasing fidelity as the number of units increases. It is notable that fewer units lie in the interior of the object once the map is complete than was the case when the SOM was trained on a set of points that defined a conical flask. This is a consequence of the flexibility of the geometry of the lattice in which the GCS grows. [Pg.105]

A similar exercise can be made with other anions and cations, producing a list of relative values of standard enthalpies of formation, anchored on Af77°(H+, ao) = 0. This database is rather useful, because it allows the enthalpies of formation (equation 2.53) and the lattice enthalpies (equation 2.47) of many crystalline ionic salts to be predicted, since their solution enthalpies are usually easy to measure. [Pg.30]

Find the unit cell of layer material in the fully relaxed (i.e. bulk) condition from materials databases. For alloys of more than one material, Vegard s law is applied to the lattice parameters, Poisson ratios and stmcture factors. Find the susceptibility of the layers (the extremely small change in susceptibility when a layer is strained may be ignored). [Pg.115]

Database search identifies complementary molecules. These are joined on an irregular lattice... [Pg.120]

What is lacking at this point in theories relating lattice restraints and chemical reactivity is the identification of specific steric interactions which alter reactivity and an estimation of their magnitude. This requires an extensive database of structure-reactivity information for a series of closely related compounds. This we have from our studies on the solid state photochemistry and X-ray crystallography of a large number of variously substituted bicyclic dienones of general structure L (5). In this series, we recently observed a photorearrangement... [Pg.244]

Notes "Lattice spacing (in angstroms), probe atom type (sp3-C or proton), bThe entire database. [Pg.204]

Experimental structures are often the basis for computational studies they are used as input structures for structure optimizations and conformational searches, for the parameterization and validation of force fields and for analyzing the effects of crystal lattices. More than 200,000 experimental structures have been reported, and the majority are found in the Cambridge Structural Data Base (CSD, small molecular structures which include carbon atoms) the Inorganic Crystals Structure Database (ICSD) and the Protein Data Base (PDB this database includes X-ray as well as optimized structures based on NMR data). [Pg.15]

FJ clusters (in FJ units, or as a model for specified rare-gas atom clusters) continue to be used as a benchmark system for verification and tuning in method development. With the work of Romero et al. [52], there are now proposed global minimum structures and energies available on the internet [53], up to n=309. This considerably extends the Cambridge cluster database [54], but the main body of data comes from EA work that used the known FJ lattices (icosahedral, decahedral, and face-centered cubic) as the input. This is obviously dangerous,... [Pg.39]

Solubility is extremely difficult to calculate. Dozens of methods exist, but none is reliable enough to be used in the entire chemical diversity space populated by infinite drug candidates. Experimental solubility errors are relatively high and frequent. Moreover, solubility can change dramatically with the purity of the compounds, stability, and time. Solubility of liquid substances differs from that of solid phase compounds. Solubility is thermodynamically affected by crystal packing, influencing the process of crystal lattice disruption and hence polymorphism, amorphous solid compounds lead to imprecise experimental measures. Finally, publically available databases of solubility values contain a lot of errors. [Pg.180]

Sample preparation for XRD is rapid and data is acquired by a computer which also controls the sample changer. A typical acquisition time would be a few hours. For routine operations, such as determining zeolite lattice parameters, it is also possible to process data automatically. Phase identification, aided by a JCPDS database search software, takes a few tens of minutes. [Pg.205]


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