Improving Accuracy, Diversity, and Speed with Prime Macrocycle Conformational Sampling

A novel method for
exploring macrocycle conformational space, Prime
macrocycle conformational sampling (Prime-MCS), is introduced and
evaluated in the context of other available algorithms (Molecular
Dynamics, LowModeMD in MOE, and MacroModel Baseline Search). The algorithms
were benchmarked on a data set of 208 macrocycles which was curated
for diversity from the Cambridge Structural Database, the Protein
Data Bank, and the Biologically Interesting Molecule Reference Dictionary.
The algorithms were evaluated in terms of accuracy (ability to reproduce
the crystal structure), diversity (coverage of conformational space),
and computational speed. Prime-MCS most reliably reproduced crystallographic
structures for RMSD thresholds >1.0 Å, most often produced
the
most diverse conformational ensemble, and was most often the fastest
algorithm. Detailed analysis and examination of both typical and outlier
cases were performed to reveal characteristics, shortcomings, expected
performance, and complementarity of the methods.