摘要:

The flow of information in combinatorial chemistry is much like that which medicinal chemists have traditionally faced; however, the speed and quantity of that flow is much greater. In traditional chemistry, computational tools have been applied essentially as a replacement for Dreiding models; with combi-chem, the use of computational tools now becomes compelling. In our environment, the primary focus is less on the use of combi-chem in the development of universal libraries for screening, and more on its use in the development of targeted libraries. Hence, the four primary challenges we face are: (1) gaining an understanding of the structure-activity relationship (SAR), (2) using that understanding in the iterative design of new targeted libraries, (3) incorporating any structural data into that iterative design process, and (4) registering the compounds produced by combi-chem into a database. For computational tools to be effective, they must address these challenges more quickly and more accurately than the combi-chemist is able to achieve independently, i.e. high-quality answers must be developed in less than a few days. We describe how the first challenge may be addressed by pharmacophore recognition tools (Catalyst, DANTE), how the second and third may be addressed by 3D database searching, and how the fourth may be addressed by ‘virtual chemistry’ using databases of compounds and tables of reactions which may be applied to those compounds.

ISSN:1062-936X    

DOI:10.1080/10629369808039146

出版商:Taylor & Francis Group    

年代:1998

数据来源: Taylor

摘要:

Compounds containing a specific pharmacophore - the minimum structural features necessary for enzyme binding - can be retrieved from a database such as the National Cancer Institute repository by means of three-dimensional (3D) searching, which allows the retrieval of all compounds possessing a specified set of atoms with a given 3D geometry. The ways in which pharmacophores can be found and characterized and the details of the 3D searching methods are described. Elaboration of compounds found in such searches and their subsequent development as lead drugs is also discussed.

ISSN:1062-936X    

DOI:10.1080/10629369808039147

出版商:Taylor & Francis Group    

年代:1998

数据来源: Taylor

摘要:

Virtual reality tightly coupled to high performance computing and communications ushers in a new era for the study of molecular recognition and the rational design of pharmaceutical compounds. We have created a combined virtual reality and molecular dynamics method, which consists of (1) massively parallel computing to simulate the physical and chemical properties of a molecular system, (2) the Cave Automatic Virtual Environment (CAVE) for immersive display and interaction with the molecular system, and (3) a high-speed network interface to exchange data between the simulation and the CAVE. This system enables molecular scientists to have a visual, auditory, and haptic experience with a chemical system. while simultaneously manipulating its physical properties by steering, in real-time, a simulation executed on a supercomputer.

ISSN:1062-936X    

DOI:10.1080/10629369808039148

出版商:Taylor & Francis Group    

年代:1998

数据来源: Taylor

摘要:

The paper describes the program CLEW, which utilizes learning and geometrical fitting to discover pharmacophores from a set of active and inactive compounds. The program first divides the compounds into similar classes. It then utilizes machine learning to derive a set of rules that relate structure to activity for each class. Then it finds the common features among all classes. These common features are used by a geometrical fitting program that tries to a 3D fit between these features between minimized conformations for every active molecule in every class. Such a fit is used to infer a pharmacophore.

ISSN:1062-936X    

DOI:10.1080/10629369808039149

出版商:Taylor & Francis Group    

年代:1998

数据来源: Taylor

摘要:

Noticeable progress has been achieved in the determination ofdynamic topochromatic variablesfor the structural representation of compounds and their situation in a given population. These independent structural variables can be further combined into more complex variables. Their contributions to the evolution of an associated property can therefore be evaluated with certainty. The risk of having correlated variables is avoided while the structural description remains exhaustive. In order to enhance the interpretative ability of the QSAR model, one or several physicochemical properties can be taken with these structural parameters as explanatory variables. Typically, partition coefficients, 3-D and quantum mechanical data are used for this purpose. The structural aspects not taken into account by the physicochemical parameters are reflected in the remaining topochromatic variables. The use of these new concepts is presented in a study of carbazole mutagenicity. The model explains 99% of the total variance with one external property and four additional topochromatic variables. The modulation of the heat of formation of an intermediate by two topochromatic variables suggests a much more precise interpretation than a simple combination of the usual external variables.

ISSN:1062-936X    

DOI:10.1080/10629369808039150

出版商:Taylor & Francis Group    

年代:1998

数据来源: Taylor

摘要:

This is a scanned image of the original Editorial Board page(s) for this issue.

ISSN:1062-936X    

DOI:10.1080/10629369808039145

出版商:Taylor & Francis Group    

年代:1998

数据来源: Taylor