Computational Molecular Science for the Nutritional Industry

Abstract

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.

Keywords

• Cheminformatics
• Computational molecular science
• In silico screening
• Molecular docking
• Molecular similarity