The structural complexity and chemical diversity of macrocycles provide an important breadth of bioactive chemical space for hit identification and target exploration. One of the primary challenges for designing macrocyclic therapeutics is optimizing their pharmacokinetic properties. Another challenge is the frequent failure of standard techniques to generate conformations that correctly predict the native structure of large, complex macrocycles. As a consequence, structure-based drug design approaches cannot be reliably implemented. To address these challenges, we have developed a new sampling method based on kinematic loop sampling. We evaluate conformational diversity and sampling accuracy for a diverse set of complex macrocycles that have potential as chemical probes or therapeutic leads in infectious disease, autoimmune disease, and cancer. Comparison to experimental structures highlights the utility of our method for generating conformations relevant for both permeation and binding. We prospectively predict passive permeability for both a synthetic cyclic peptide-polyketide library and a set of natural products, finding good correlation in both cases. We demonstrate the outcome of macrocycle docking studies against several targets, and we discuss methods for identifying binders and discriminating amongst a set of analogues.

Predicting permeability and target binding of complex macrocycles

249th National Meeting (2015)

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