Exhaustive Conformational Sampling of Complex Fused Ring Macrocycles Using Inverse Kinematics

Abstract

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.

RMSD and Symmetry

“…Among the trimers, KCR has cyclic symmetry of order 3, while the others (BIX, CD4, CRP) have full dihedral symmetry of order 3, and may be aligned “upside down,” giving a total of six possible alignments. They are reproduced from Coutsias et al Invariably, we found that a lower RMSD was possible for some alignment other than the original, and in a few cases a much lower RMSD was found. This is of course expected, as including all alternative alignments effectively multiplies the ensemble size by a factor equal to the order of symmetry of a given compound.…”

Solution Conformations Explain the Chameleonic Behaviour of Macrocyclic Drugs

“…The results were validated within 10 % using standard methods, that is, by the addition of random noise (max 10 %) to the experimental data, by the random removal of individual restraints (10 %), and by comparison of the experimentally observed and back‐calculated distances. Macrocycle core conformations were classified as different if their heavy atom root‐mean‐square deviation (RMSD) was >0.5 Å, while a >0.75 Å heavy atom cut off was used for the overall macrocycle including side chains. All conformations for each macrocycle in the two solvents, with the corresponding molar fractions, are given in the Supporting Information, Section 6.…”

D3R grand challenge 4: blind prediction of protein–ligand poses, affinity rankings, and relative binding free energies

“…Our experience shows that multiple docking/cheminformatics software tools produced submissions of comparable accuracy. These software packages include docking software such as Glide [62,63], ICM [64], Corina [65], Gold [66], Cactvs[67], Rosetta [68], and EFindSite [69], and ligand preparation software such as Brikard [70]. In addition, almost all submissions in Table 1 used more than one type of software package in their workflow, preferring rather to combine multiple docking software packages.…”