Successful Application of the QSAR Paradigm in Discovery Programs

Abstract

The Quantitative Structure-Activity Relationship (QSAR) approach, first described by Corwin Hansch and Toshio Fujita thirty years ago, remains central to pesticide design. The successful application of this paradigm in the discovery of new pesticides depends on two key elements: statistical experimental design and effective computational tools. These tools must be available to bench scientists in a form that they can readily apply in the course of their daily design efforts. This report will describe a system that laboratory scientists have used for over ten years in our laboratory. Key components of this system are: • Database tools to automatically integrate physicochemical parameters and biological data • Experimental design tools for application of statistical experimental designs • Analysis tools for pattern recognition and Free-Wilson and regression analysesThe report will illustrate the application of the approach to actual research programs. This will include application of cluster analysis, sequential simplex, and central composite designs to rapidly advance pesticide design projects.Thirty years ago Drs. Corwin Hansen and Toshio Fujita initiated a body of work that has evolved into the current QSAR paradigm 1 . This represented a dramatic shift from the way drugs and pesticides had been discovered; it moved from an intuitive evaluation of the effects of structure change on biological activity to a quantitative, scientifically verifiable evaluation based on accurately measured physical properties and sound statistical principles. Over the years that I have been involved in following and teaching the QSAR Paradigm, the question most asked has been: "Does QSAR really work?" It has become easier for me to answer the question as I see the many ways that QSAR can make Discovery programs more effective. Today I would list QSAR's success criteria as the following: 0097-6156/95/0606-0240$12.00/0

Future direction of agrochemical development for plant disease in China

“…QSAR was the earliest ligand-based design method that has been used in the discovery of new pesticides (Hansch & Fujita, 1995;Plummer, 1995). It is an important "ligandbased design" tool for optimizing and developing active agrochemical structures using the information derived from the models (Figure 3a).…”

“…It is an important "ligandbased design" tool for optimizing and developing active agrochemical structures using the information derived from the models (Figure 3a). Many active compounds have been obtained based on the information derived from CoMFA and CoMSIA models, which lay a good foundation for the further designing of drugs against pathogenic bacteria (including plant virus) (Plummer, 1995;Wu et al, 2017;Xu et al, 2012).…”

Binary Quantitative Structure−Activity Relationship (QSAR) Analysis of Estrogen Receptor Ligands

“…Quantitative structure−activity relationship (QSAR) analysis has been widely used to modify lead compounds, however identified, to optimize their biological activity, selectivity, and pharmacokinetic properties and to minimize the toxic effects . It is often applied as part of the drug discovery process to better understand the interaction mechanisms between chemical compounds and biological targets. − A variety of molecular descriptors and statistical techniques have been developed to achieve better correlation between chemical structures and biological activities. − The fundamental hypothesis of QSAR is that biological activity is a function of molecular structure.…”