Computational Molecular Science for the Nutritional Industry

The implementation of quantitative models of real phenomena that are evolved on computational devices has become a common practice in science and engineering in the last 50 years. The major advantage of this technology is the possibility to process large amounts of data in relatively short...

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Main Author: Martin G. Grigorov
Format: Article
Language:deu
Published: Swiss Chemical Society 2005-07-01
Series:CHIMIA
Subjects:
Online Access:https://chimia.ch/chimia/article/view/4030
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author Martin G. Grigorov
author_facet Martin G. Grigorov
author_sort Martin G. Grigorov
collection DOAJ
description The implementation of quantitative models of real phenomena that are evolved on computational devices has become a common practice in science and engineering in the last 50 years. The major advantage of this technology is the possibility to process large amounts of data in relatively short times. In this review the major techniques of computational molecular science as applied in the industry of life sciences are reviewed. Further these techniques are discussed in view of their documented impact on the research and development workflow, with real illustrative examples taken from the nutrition and food industry. Computational molecular sciences have now come of age and, when deployed knowledgably, are shown to be able to generate intelligent hypotheses for project advancement, to lower attrition rate and to ultimately reduce research and development costs and to shorten the time-to-market cycle. The documented successes are however episodic and therefore efforts should be directed towards the development of standard reproducible protocols to use this technology.
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spelling doaj.art-6b29335cdd6f48d9bf3007ca4bece02a2022-12-22T04:16:27ZdeuSwiss Chemical SocietyCHIMIA0009-42932673-24242005-07-01597-810.2533/000942905777676100Computational Molecular Science for the Nutritional IndustryMartin G. Grigorov The implementation of quantitative models of real phenomena that are evolved on computational devices has become a common practice in science and engineering in the last 50 years. The major advantage of this technology is the possibility to process large amounts of data in relatively short times. In this review the major techniques of computational molecular science as applied in the industry of life sciences are reviewed. Further these techniques are discussed in view of their documented impact on the research and development workflow, with real illustrative examples taken from the nutrition and food industry. Computational molecular sciences have now come of age and, when deployed knowledgably, are shown to be able to generate intelligent hypotheses for project advancement, to lower attrition rate and to ultimately reduce research and development costs and to shorten the time-to-market cycle. The documented successes are however episodic and therefore efforts should be directed towards the development of standard reproducible protocols to use this technology. https://chimia.ch/chimia/article/view/4030CheminformaticsComputational molecular scienceIn silico screeningMolecular dockingMolecular similarity
spellingShingle Martin G. Grigorov
Computational Molecular Science for the Nutritional Industry
CHIMIA
Cheminformatics
Computational molecular science
In silico screening
Molecular docking
Molecular similarity
title Computational Molecular Science for the Nutritional Industry
title_full Computational Molecular Science for the Nutritional Industry
title_fullStr Computational Molecular Science for the Nutritional Industry
title_full_unstemmed Computational Molecular Science for the Nutritional Industry
title_short Computational Molecular Science for the Nutritional Industry
title_sort computational molecular science for the nutritional industry
topic Cheminformatics
Computational molecular science
In silico screening
Molecular docking
Molecular similarity
url https://chimia.ch/chimia/article/view/4030
work_keys_str_mv AT martinggrigorov computationalmolecularscienceforthenutritionalindustry