Conformational Sampling of Macrocycles in Both the Solid- and Solution-States" was presented by Paul Hawkins, PhD., Head of Scientific Solutions, on Wednesday, June 27, 2018 at 12pm EDT / 9am PDT (US).
Molecules containing large rings, or macrocycles, have become of greater and greater interest to the drug discovery community over the past decade. A key part of productively exploiting this class of molecules as therapeutics is understanding their conformational landscape, and there have been a number of different approaches to this problem presented recently.1,2 Here we will present a new approach to macrocycle conformation sampling based on distance geometry, OMIGEN. In the most extensive comparison performed to date in this area we evaluate OMIGEN against a wide variety of other algorithms in reproducing conformations found in the solid-state, the most popular approach to validating conformer generators. While conformations found in the solid-state are easy to validate against, and are relevant to a number of problems in macrocycle design, including pose prediction by docking and structure-guided lead optimization, generating conformations relevant to the solution state is also important. We will present preliminary data on the use of distance geometry to generate conformations consistent with experimental data from NMR experiments.
Sindikhara, D.; Spronk, S. A.; Day, T.; Borrelli, K.; Cheney, D. L.; Posy, S. L. Improving Accuracy, Diversity and Speed with Prime Macrocycle Conformational Sampling. Chem. Inf. Model. 2017, 57, 1881-1894.
Coutsias, E. A.; Lexa, K. W.; Wester, M. J.; Pollock, S. N.; Jacobsen, M. P. Exhaustive Conformational Sampling of Complex Fused Ring Macrocycles Using Inverse Kinematics. Chem. Theory Comput. 2016, 12, 4674-4687.
