Parallel multi-swarm cooperative particle swarm optimization for protein–ligand docking and virtual screening

• DOI: 10.1186/s12859-022-04711-0
• Publication Date: 2022-05-30T11:03:54Z
• Authors: Chao Li; Jinxing Li; Jun Sun; Li Mao; Vasile Palade; Bilal Ahmad
• Keywords: Docking (animal); Protein–ligand docking; Robustness; AutoDock

A high-quality docking method tends to yield multifold gains with half pains for the new drug development. Over past few decades, great efforts have been made development of novel programs efficiency and intriguing accuracy. AutoDock Vina (Vina) is one these achievements improved speed accuracy compared AutoDock4. Since it was proposed, some its variants, such as PSOVina GWOVina, also developed. However, all programs, there still large room performance improvement.In this work, we propose a parallel multi-swarm cooperative particle swarm model, in which master several slave swarms mutually cooperate co-evolve. Our experiments show that possess better robustness than PSOVina. Moreover, program based on random drift PSO can achieve best highest protein-ligand docking, an outstanding enrichment effect drug-like activate compounds, second AUC screening among but less computation consumption most other programs.The proposed model algorithmic modeling suitable virtual screening. Owing existing coevolution between swarms, generates remarkable performance. The source code be freely downloaded from https://github.com/li-jin-xing/MPSOVina .