Molecular Quantum Similarity in QSAR and Drug Design by Ramon Carbó-Dorca, David Robert, Lluís Amat, Xavier Gironés, PDF


By Ramon Carbó-Dorca, David Robert, Lluís Amat, Xavier Gironés, Emili Besalú (auth.)

ISBN-10: 3540675817

ISBN-13: 9783540675815

ISBN-10: 3642572731

ISBN-13: 9783642572739

The authors introduce the idea that of Molecular Quantum Similarity, constructed of their laboratory, in a didactic shape. the foundation of the concept that combines quantum theoretical calculations with molecular constitution and houses even for giant molecules. they offer definitions and techniques to compute similarities molecules and supply graphical instruments for visualisation of units of molecules as n-dimensional element charts.

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1. (continued). 302 No. 80E-03 7. 15 ~. ,. 30 ~. •• ~. 1. Isodensity contours of 2,4,6-trinitrophenol from an ab initio calculation with a 6-311 G basis set and titted with ASA. 30 au. Nevertheless, the final objective of the fitted densities in this work is the fast and accurate calculation of MQSM. Thus, what is really relevant to compare is the differences between the MQSM derived from ab initio and ASA densities. With respect to this question, in all the studied cases the differences between the ab initio and ASA MQSM were not higher than 2% [109, II 0].

Further, the design of agonists or antagonists for this receptor might be of a great importance for medicinal chemists. The indole activity is measured with pK j , Kj being the concentration necessary to produce 50% inhibition in an assay with bovine brain membrane. A previous study on this same data set by HadjipavlouLitina and Hansch [188], using classical descriptors, already existed. The results of these authors will be compared with the ones obtained with MQSM techniques. 1 gathers the general structure of the studied indole derivatives, together with the substituents and the activity data.

183). The computational algorithm encompasses two stages: first, a global search is carried out by means of a Monte Carlo procedure [184]. A random sequence of weights is generated, and the predictive model is constructed following the steps given in the previous section. The q2 value obtained is stored. Starting with this sequence, a Fibonacci succession [185] is applied to refine the search. This cycle is repeated until a satisfactory QSAR model is achieved. Another possible degree of freedom of the 49 model consists of the number of combined matrices.

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Molecular Quantum Similarity in QSAR and Drug Design by Ramon Carbó-Dorca, David Robert, Lluís Amat, Xavier Gironés, Emili Besalú (auth.)

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