Skip to main content

Table 5 Overall pose prediction performance of AutoDock Vina, PSOVina, PSOVina\(^{{\mathrm{2LS}}}\), chaos-embedded PSOVina\(^{{\mathrm{2LS}}}\) methods

From: Chaos-embedded particle swarm optimization approach for protein-ligand docking and virtual screening

  Best-scoring pose RMSD (Å) Best-scoring pose success rate (%) Run time (s)
AutoDock Vina 2.50 (0.40) 65.68 (4.17) 17.56 (5.24)
PSOVina 2.27 (0.33) 68.56 (3.86) 9.40 (2.31)
PSOVina\(^{{\mathrm{2LS}}}\) 2.11 (0.37) 70.89 (3.79) 2.96 (0.36)
Chaos-embedded PSOVina\(^{2LS}\)
 Logistic map 2.08 (0.36) 72.72 (4.57) 3.21 (0.41)
 Singer map 2.06 (0.37) 73.21 (3.06) 3.26 (0.35)
 Sinusoidal map 1.96 (0.34) 74.62 (4.08) 3.33 (0.35)
 Tent map 2.01 (0.31) 71.85 (4.67) 3.08 (0.37)
 Zaslavskii map 2.08 (0.41) 72.48 (5.21) 3.09 (0.47)
  1. Best results are shown in italics