A genetic algorithm has been developed for molecular mechanics calculations. It has been proved to be a robust and efficient structure optimization technique. Because it uses randomly generated starting structures and stochastic operators, the resulting structures are not subjected to the chemist's
Applications of genetic algorithms in molecular diversity
β Scribed by Lutz Weber
- Publisher
- Elsevier Science
- Year
- 1998
- Tongue
- English
- Weight
- 425 KB
- Volume
- 2
- Category
- Article
- ISSN
- 1367-5931
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β¦ Synopsis
The definition of molecular diversity and the development of measures for assessing the similarity or dissimilarity of molecules are central tasks for the design of novel biologically active compounds. Combinatorial chemistry allows the coupling of mathematical optimisation methods that do not require the a priori knowledge of structure-activity relationships with the synthesis of biologically active compounds. Genetic algorithms that computationally mimic Darwinian evolution have proven to be useful in solving multidimensional problems and are now being used successfully in various areas of combinatorial chemistry. Applications have been developed that help in the selection of diverse compound libraries and in the synthesis of biologically active molecules.
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Quantitative data analysis is an important step in the appli-where n(t) is assumed to be white Gaussian noise. F i (t) is specified as a function of the resonance frequency, n i , and cation of NMR spectroscopy. Despite an assortment of existing methods, difficulty still exists in accurate quantific