@article{DonatiFackeldeyWeber2023, author = {Donati, Luca and Fackeldey, Konstantin and Weber, Marcus}, title = {Augmented ant colony algorithm for virtual drug discovery}, series = {Journal of Mathematical Chemistry}, volume = {62}, journal = {Journal of Mathematical Chemistry}, doi = {10.1007/s10910-023-01549-6}, pages = {367 -- 385}, year = {2023}, abstract = {Docking is a fundamental problem in computational biology and drug discovery that seeks to predict a ligand's binding mode and affinity to a target protein. However, the large search space size and the complexity of the underlying physical interactions make docking a challenging task. Here, we review a docking method, based on the ant colony optimization algorithm, that ranks a set of candidate ligands by solving a minimization problem for each ligand individually. In addition, we propose an augmented version that takes into account all energy functions collectively, allowing only one minimization problem to be solved. The results show that our modification outperforms in accuracy and efficiency.}, language = {en} }