The amount of chemical biological data accessible to medicinal chemists and modelers is skyrocketing. In fact, the continuous generation of experimental data points via high throughput/content screening along with the rise of fully automated chemical synthesis platforms will even accelerate the data revolution in drug discovery. As a result, the actual integration, visualization, and modeling of such <i>Big Chemical Data</i> represent increasingly complex tasks to accomplish, even for experts in cheminformatics. Meanwhile, medicinal chemists are demanding easy-to-use tools that give them a direct access and visual representation to critical information to guide the rational molecular design. In particular, needed are methods and software for representing structure-activity relationships (SAR) for chemical series tested in multi-dimensional experimental assays. <u>Herein</u>, we recapitulate several methods and associated software allowing the visualization of complex SAR data. Notably, we will discuss: (1) the use of ligand- and structure-based graphs to represent complex associations between targets, chemicals, and experimental activities; (2) the complementarity of 2D/3D/MD descriptors to build ligand-based radial plots and circular dendrograms to rapidly establish SAR and solve activity cliffs; (3) the emergence of web-based services such as ChemMaps.com to easily browse and navigate the chemical space of drugs and drug candidates; (4) 3D printing to physically print complex protein-ligand or protein-protein interfaces; and (5) the rapid rise of augmented/virtual reality to visualize SAR data in a fully immersive virtual environment. At last, we will discuss the future of SAR data visualization with some suggestions for next-generation methods and tools.

Cheminformatics-powered visualization methods of complex multidimensional SAR data

2019 Fall National Meeting

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