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Conformational analysis systematic

Whereas many scientists shared Mulliken s initial skepticism regarding the practical role of theory in solving problems in chemistry and physics, the work of London (6) on dispersion forces in 1930 and Hbckel s 7t-electron theory in 1931 (7) continued to attract the interest of many, including a young scientist named Frank Westheimer who, drawing on the physics of internal motions as detailed by Pitzer (8), first applied the basic concepts of what is now called molecular mechanics to compute the rates of the racemization of ortho-dibromobiphenyls. The 1946 publication (9) of these results would lay the foundation for Westheimer s own systematic conformational analysis studies (10) as well as for many others, eg, Hendrickson s (11) and Allinger s (12). These scientists would utilize basic Newtonian mechanics coupled with concepts from spectroscopy (13,14) to develop nonquantum mechanical models of structures, energies, and reactivity. [Pg.157]

D-QSAR. Since compounds are active in three dimensions and their shape and surface properties are major determinants of their activity, the attractiveness of 3D-QSAR methods is intuitively clear. Here conformations of active molecules must be generated and their features captured by use of conformation-dependent descriptors. Despite its conceptual attractiveness, 3D-QSAR faces two major challenges. First, since bioactive conformations are in many cases not known from experiment, they must be predicted. This is often done by systematic conformational analysis and identification of preferred low energy conformations, which presents one of the major uncertainties in 3D-QSAR analysis. In fact, to date there is no computational method available to reliably and routinely predict bioactive molecular conformations. Thus, conformational analysis often only generates a crude approximation of active conformations. In order to at least partly compensate for these difficulties, information from active sites in target proteins is taken into account, if available (receptor-dependent QSAR). Second, once conformations are modeled, they must be correctly aligned in three dimensions, which is another major source of errors in the system set-up for 3D-QSAR studies. [Pg.33]

Dolata and Carter [17] and Leach and Prout [18] developed two programs, WIZARD and COBRA, for the systematic conformational analysis using symbolical logic and techniques of artificial intelligence (AI). The basic idea of this approach is to develop a set of rules for the construction of molecular models derived from the method of a human expert who recognizes conformational units with well-known optimum geo-... [Pg.163]

P. J. De Clerq, Tetrahedron, 19, 3717 (1984). Systematic Conformational Analysis A Microcomputer Method for the Semi-quantitative Evaluation of Polycyclic Systems containing Five-, Six- and Seven-Membered Rings. 1. Program Characteristics. [Pg.50]

What has the Eschenmoser group achieved so far to bridge the g between the simplest organic molecules readily formed under prebiotic conditions and the self-constituted building blocks necessary to make up informational macromolecules Firstly, it has solved the ribose problem, secondly it has set up the basis for a systematic conformational analysis of nucleic acids, and, thirdly, it has synthesized a candidate for RNA precursor. [Pg.465]

ChemDBS-3D uses rule-based systematic conformational analysis (single = 3, alpha 4, double/conjugated = 2 points) or random rule-based (max. time 2 min), or flexifit (no VDW bump check) ISIS/3D and UNITY use torsional minimization (conformationally flexible searching and directed tweak, respectively. [Pg.84]

AI = artificial intelligence AIMB = analogy and intelligence in model building DG = distance geometry KB = knowledge base QM = quantum mechanical SCA = systematic conformational analysis SSSR = smallest set of smallest rings. [Pg.2976]


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See also in sourсe #XX -- [ Pg.18 , Pg.163 , Pg.187 ]

See also in sourсe #XX -- [ Pg.15 ]




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