4 - Computational Analysis of Structure–Activity Relationships

Abstract

Publisher Summary In drug and agrochemical discovery it is of crucial importance to understand the relationship between chemical structure and biological activity. The abbreviation SAR (structure–activity relationship) is in general used for a qualitative description of this relationship. To describe this relationship quantitatively in computational chemistry, QSAR (quantitative structure–activity relationship) model is applied. The chapter discusses different aspects of QSAR modelling. The chapter discusses the importance of a good dataset, elaborates various descriptors and modelling methods currently in use, and focuses on what needs to be considered when applying models. While not as accurate as QSAR models, several published rules and guidelines have had a dramatic impact on pharmaceutical research. The chapter reviews recent contributions in this field.. The chapter gives an overview of several methods that are developed by medicinal chemists to support the SAR analysis. The success of using QSAR models for SAR analysis critically depends on the interpretability and type of descriptors. The chapter discusses recent developments that may shape the field in the future. The future of QSAR is exciting, especially because pharmaceutical companies are building up databases of hundreds of thousands of measurements of different compounds on the same biological.