Exhaustive Conformational Sampling of Complex Fused Ring Macrocycles Using Inverse Kinematics

Natural product and
synthetic macrocycles are chemically and topologically
diverse. An efficient, accurate, and general method for generating
macrocycle conformations would enable structure-based design of macrocycle
drugs or host–guest complexes. Computational sampling also
provides insight into transiently populated states, complementing
crystallographic and NMR data. Here, we report a new algorithm, BRIKARD,
that addresses this challenge through computational algebraic geometry
and inverse kinematics together with local energy minimization. BRIKARD
is demonstrated on 67 diverse macrocycles with structural data, encompassing
various ring topologies. We find this approach enumerates diverse
structures with macrocyclic RMSD < 1.0 Å to the experimental
conformation for 85% of our data set in contrast to success rates
of 67–75% with other approaches, while for the subset of 21
more challenging compounds in the data set, these rates are 57% and
10–29%, respectively. Because the algorithm can be efficiently
run in parallel on many processors, exhaustive conformational sampling
of complex cycles can be obtained in minutes rather than hours: with
a 40 processor implementation protocol, BRIKARD samples the conformational
diversity of a potential energy landscape in a median of 1.3 minutes
of wallclock time, much faster than 3.1–10.3 hours necessary
with current programs. By rigorously testing BRIKARD on a broad range
of scaffolds with highly complex ring systems, we push the frontiers
of macrocycle sampling to encompass multiring compounds, including
those with more than 50 ring atoms and up to seven interlaced flexible
rings.