Global Optimization of Large Molecular Systems Using Rigid-Body Chain Stochastic Surface Walking

The global potential energy surface (PES) search of large molecular systems remains a significant challenge in chemistry due to "the curse of dimensionality". To address this, here we develop a rigid-body chain method in the framework of a stochastic surface walking (SSW) global optimization method, termed rigid-body chain SSW (RC-SSW). Based on the angle-axis representation for a single rigid body, our algorithm realizes the cooperative motion of connected rigid bodies and achieves the coupling between rigid-body chain movement and lattice variation in the generalized coordinate. By exploiting the numerical energy second derivative information on rigid bodies, RC-SSW can optimize the global PES of large molecular systems with an unprecedentedly high efficiency. We show that RC-SSW is more than 10 times faster in locating the model protein global minimum while revealing many more low energy conformations than molecular dynamics and can identify low energy phases of molecular crystals up to 172 atoms missed in the sixth CCDC blind test.