Chemical-Biological Activities

TT-Electron materials, which are defined as those having extended Jt-electron clouds in the solid state, have various peculiar properties such as high electron mobility and chemical/biological activities. We have developed a set of techniques for synthesizing carbonaceous K-electron materials, especially crystalline graphite and carbon nanotubes, at temperatures below 1000°C. We have also revealed new types of physical or chemical interactions between Jt-electron materials and various other materials. The unique interactions found in various Jt-electron materials, especially carbon nanotubes, will lay the foundation for developing novel functional, electronic devices in the next generation. 

CBAC (Chemical-Biological Activities) from CAS 1965-present... 

Chemical Abstracts Service are also producing a similar rapid digest to act as a guide to the literature dealing with the biological action of organic compounds, known as Chemical-Biological Activities. Keyword-in-context, notation, molecular formula and author indexes are provided. 

Chemical-Biological Activities (CBAC), the first integrated system for both current awareness and retrospective searching, produced simultaneously in printed and computer-readable form... 

TOXLINE/TOXBACK are made up of component files that come from the major secondary literature sources, as well as specialized sources. The collection of bibliographic citations are obtained either through profiling certain files or selecting complete specialty files. The sources and extent of coverage of component files are Chemical-Biological Activities (CBAC)... 

The second application of the CFTI protocol is the evaluation of the free energy differences between four states of the linear form of the opioid peptide DPDPE in solution. Our primary result is the determination of the free energy differences between the representative stable structures j3c and Pe and the cyclic-like conformer Cyc of linear DPDPE in aqueous solution. These free energy differences, 4.0 kcal/mol between pc and Cyc, and 6.3 kcal/mol between pE and Cyc, reflect the cost of pre-organizing the linear peptide into a conformation conducive for disulfide bond formation. Such a conformational change is a pre-requisite for the chemical reaction of S-S bond formation to proceed. The predicted low population of the cyclic-like structure, which is presumably the biologically active conformer, agrees qualitatively with observed lower potency and different receptor specificity of the linear form relative to the cyclic peptide. 

The work by Hammett and Taft in the 1950s had been dedicated to the separation and quantification of steric and electronic influences on chemical reactivity. Building on this, from 1964 onwards Hansch started to quantify the steric, electrostatic, and hydrophobic effects and their influences on a variety of properties, not least on the biological activity of drugs. In 1964, the Free-Wilson analysis was introduced to relate biological activity to the presence or absence of certain substructures in a molecule. 

In chemoinformatics, chirality is taken into account by many structural representation schemes, in order that a specific enantiomer can be imambiguously specified. A challenging task is the automatic detection of chirality in a molecular structure, which was solved for the case of chiral atoms, but not for chirality arising from other stereogenic units. Beyond labeling, quantitative descriptors of molecular chirahty are required for the prediction of chiral properties such as biological activity or enantioselectivity in chemical reactions) from the molecular structure. These descriptors, and how chemoinformatics can be used to automatically detect, specify, and represent molecular chirality, are described in more detail in Chapter 8. 

For example, the objects may be chemical compounds. The individual components of a data vector are called features and may, for example, be molecular descriptors (see Chapter 8) specifying the chemical structure of an object. For statistical data analysis, these objects and features are represented by a matrix X which has a row for each object and a column for each feature. In addition, each object win have one or more properties that are to be investigated, e.g., a biological activity of the structure or a class membership. This property or properties are merged into a matrix Y Thus, the data matrix X contains the independent variables whereas the matrix Ycontains the dependent ones. Figure 9-3 shows a typical multivariate data matrix. 

Large data sets such as screening data or results obtained by combinatorial experiments are made up of a large number of data records. Hence a data record may represent a chemical reaction or substance, for example its corresponding variables will define the corresponding reaction conditions or biological activities. Depending on the dimensionality or data type of the information, one-, two-, multidimensional, or specific data types can be identified. 

The fundamental assumption of SAR and QSAR (Structure-Activity Relationships and Quantitative Structure-Activity Relationships) is that the activity of a compound is related to its structural and/or physicochemical properties. In a classic article Corwin Hansch formulated Eq. (15) as a linear frcc-cncrgy related model for the biological activity (e.g.. toxicity) of a group of congeneric chemicals [37, in which the inverse of C, the concentration effect of the toxicant, is related to a hy-drophobidty term, FI, an electronic term, a (the Hammett substituent constant). Stcric terms can be added to this equation (typically Taft s steric parameter, E,). 

As a conclusion one can say that the distinction of islands of specific activity from within a sea of baseline toxicity, with each island representing a local chemical biological mechanism domain, is still a challenge to be solved by scientists working both experimentally and computationally. 

J, P Willett and ] Bradshaw 1998. Identification Of Biological Activity Profiles Using Sub- tural Analysis And Genetic Algorithms. Journal of Chemical Information and Computer Science 55-179. 

Rusinko A III, M W Farmen, C G Lambert, P L Brown and S S Young 1999. Analysis of a Larj Structure/Biological Activity Data Set Using Recursive Partitioning. Journal of Chemic Information and Computer Science 39 1017-1026. 

PW91 (Perdew, Wang 1991) a gradient corrected DFT method QCI (quadratic conhguration interaction) a correlated ah initio method QMC (quantum Monte Carlo) an explicitly correlated ah initio method QM/MM a technique in which orbital-based calculations and molecular mechanics calculations are combined into one calculation QSAR (quantitative structure-activity relationship) a technique for computing chemical properties, particularly as applied to biological activity QSPR (quantitative structure-property relationship) a technique for computing chemical properties... 

Many biological processes involve an associa tion between two species in a step prior to some subsequent transformation This asso ciation can take many forms It can be a weak associ ation of the attractive van der Waals type or a stronger interaction such as a hydrogen bond It can be an electrostatic attraction between a positively charged atom of one molecule and a negatively charged atom of another Covalent bond formation between two species of complementary chemical re activity represents an extreme kind of association It often occurs in biological processes in which aide hydes or ketones react with amines via imine inter mediates... 

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