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Molecular space

FIGURE 9.16 Cortisone acetate, a molecule similar in size to many pharmaceuticals [Pg.229]

The value 1063 demonstrates that the number of possible molecules that may be considered as drugs is seemingly infinite. As of 2011, the number of organic and inorganic substances in the Chemical Abstract Services (CAS) Registry was approximately [Pg.229]

6 X 107.14 The CAS Registry includes substances that have been published in the literature and patents. Therefore, the number of molecules that have been reported in the chemical literature is miniscule relative to the possible number of drug-sized molecules (1063). Furthermore, if each of the 1063 molecules has an average molecular weight of 400, just one molecule of each member of the entire collection would have a mass of [Pg.229]

7 X 1038 kg. That value far exceeds the collective mass of all the objects in our solar system ( 2 X 103° kg). [Pg.229]

FIGURE 9.17 Pockets of activity against a target within a defined molecular space [Pg.229]


The UHE wave function can also apply to singlet molecules. Usually, the results are the same as for the faster RHEmethod. That is, electrons prefer to pair, with an alpha electron sharing a molecular space orbital with a beta electron. Use the UHE method for singlet states only to avoid potential energy discontinuities when a covalent bond is broken and electrons can unpair (see Bond Breaking on page 46). [Pg.37]

Compared with most other crystalline polymers the permeability of P4MP1 is rather high. This is no doubt due to the ability of gas molecules to pass through the open crystal structure with the large molecular spacing. [Pg.271]

A five-membered heterocyclic ring packs a relatively large number of polarized bonds into a relatively small molecular space. This provides a convenient framework to which to attach necessary side chains. In some cases, the framework itself is believed to be part of the pharmacophore. [Pg.127]

The variable selection methods have been also adopted for region selection in the area of 3D QSAR. For example, GOLPE [31] was developed with chemometric principles and q2-GRS [32] was developed based on independent CoMFA analyses of small areas of near-molecular space to address the issue of optimal region selection in CoMFA analysis. Both of these methods have been shown to improve the QSAR models compared to original CoMFA technique. [Pg.313]

In Fig.26, the energy correlation is schematically presented. The potential-controlled modulation of the molecular-interfaced enzymes may be interpreted by Fig.26. The enzyme and its substrate molecule have their intrinsic redox potentials. The redox potentials of oxidases and dehydrogenases are determined by an electron transferring molecule, i.e. a cofactor such as FAD, which is located at the active site of the enzyme. Due to potential gradient, an electron can be transferred from the substrate molecule to the active site of the enzyme, if the substrate molecule is accepted by the molecular space of the enzyme active site. However, the electron transfer between the active site of the enzyme and the electrode is regulated by the electrode potential, even if the molecule wire could be completed. It should be reasonable that the enzyme activity is electrically modulated at a threshold of the redox potential of the enzyme. [Pg.356]

The Bonding Evolution Theory, briefly presented in Appendix B, provides a description of the bonding features of a system, along with their evolution accompanying a reaction path. It relies on the variation of the ELF topological profile as a function of nuclear coordinates. The ELF makes a partition of the molecular space into open sets having a... [Pg.348]

PLS is related to principal components analysis (PCA) (20), This is a method used to project the matrix of the X-block, with the aim of obtaining a general survey of the distribution of the objects in the molecular space. PCA is recommended as an initial step to other multivariate analyses techniques, to help identify outliers and delineate classes. The data are randomly divided into a training set and a test set. Once the principal components model has been calculated on the training set, the test set may be applied to check the validity of the model. PCA differs most obviously from PLS in that it is optimized with respect to the variance of the descriptors. [Pg.104]

Anyone who has seen the well-formed crystals of minerals in our museums must have been impressed by the great variety of shapes exhibited cubes and octahedra, prisms of various kinds, pyramids and double pyramids, flat plates of various shapes, rhombohedra and other less symmetrical parallelepipeda, and many other shapes less easy to describe in a word or two. These crystal shapes are extremely fascinating in themselves artists (notably Durer) have used crystal shapes for formal or symbolic purposes, while many a natural philosopher has been drawn to the attempt to understand first of all the geometry of crystal shapes considered simply as solid figures, and then the manner in which these shapes are formed by the anisotropic growth of atomic and molecular space-patterns. [Pg.9]

But this book has a practical object, as its title proclaims. Our purpose in this chapter is to inquire to what extent crystal shapes can be criteria for identification, and how much they tell us about the atomic and molecular space-patterns within them. [Pg.9]

This is one reason for studying crystal shapes. Another and more weighty reason is that crystal shapes tell us a great deal about the relative dimensions and the symmetries of the atomic and molecular space-patterns constituting the crystalline material. [Pg.10]

If one analyses the gradient of p (r) not only at the point p but also at other points in molecular space, then the gradient vector field of p (r) will be obtained81. The gradient vector p (r) always points in the direction of a maximum increase in p (r). Thus, each such vector is directed toward some neighbouring point. By calculating Vp (r) at a continuous succession of points, a trajectory of Vp (r), the path traced out by the gradient vector of p (r), is obtained. [Pg.375]

The molecular space is divided into core and valence basins, the latter being classified according to their connectivity to the core basins as monosynaptic basins, associated with electron pairs, or dissynaptic basins, associated with covalent bonds. Moreover, an integration of the electronic population over each basin gives the number of electrons in each of them and the fluctuation between basins is related to the electronic delocalisation [39]. [Pg.278]

Certain areas of molecular space, such as regions containing privileged structures, are rich in hits. The inverse argument—molecular space regions without privileged structures... [Pg.230]

To match the incredible diversity of molecular space, pharmaceutical companies often rely on combinatorial chemistry. Combinatorial chemistry, or less formally combi chem or even just combi, is a technique for synthesizing large numbers of different molecules... [Pg.231]


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Body-fixed frame, molecular internal space

Carbon-molecular oxygen reaction spaces

Chemical space representation molecular similarity

Chemical spaces molecular similarity

Closely spaced molecular orbitals

Conformational search space, molecular

Conformational search space, molecular contacts

Coordinate-based chemical spaces, molecular

Corey-Pauling-Koltun space filling molecular

Corey-Pauling-Koltun space filling molecular models

Developmental path in parameter space a molecular basis for the ontogenesis of cAMP oscillations

Direct molecular dynamics, complete active space self-consistent field

Interaction space, molecular

Introduction to Molecular Similarity and Chemical Space

Kinematics, molecular internal space

Lead discovery molecular space

Molecular Configurations over Space

Molecular Modeling - Mapping Biochemical State Space

Molecular Phase Space Nonstatistical Effects in Reaction Dynamics

Molecular databases and chemical space

Molecular descriptors and chemical spaces

Molecular geometry coordinate space

Molecular internal space

Molecular internal space applications

Molecular internal space effects

Molecular internal space mechanism

Molecular models space-filling

Molecular orbital theory complete active space self-consistent field

Molecular phase space

Molecular similarity analysis chemical space representation

Molecular similarity and chemical spaces

Molecular similarity spaces

Molecular space lattice

Molecular structure space-filling mode)

Molecular weight distribution time-volume space

Other molecular spaces

Porosity molecular space

Potential energy surfaces molecular internal space

Principal component analysis molecular similarity, chemical space

Protein molecular evolution searching space

Protein molecular evolution space

Simulated Annealing by Molecular Dynamics Simulation in Cartesian Space

Space Limitations and Molecular Sieving

The Molecular Phase Space

Time-volume space, molecular

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