Docking is a fundamental problem in computational biology that seeks to predict a ligand's binding mode and affinity to a target protein. The accurate prediction of protein-ligand interactions is crucial for drug discovery and design. However, the large search space size and the complexity of the underlying physical interactions make docking a challenging task requiring advanced computational techniques. Here, we review the PLANTS method, based on the ant colony optimization algorithm, that determines the optimal pose and ranks a set of molecules based on their binding affinity. PLANTS analyzes each ligand individually, then for each candidate, it solves a minimization problem. As an alternative, we propose PLANTS+, which considers all energy functions collectively and solves one single minimization problem. Our benchmark test results indicate that PLANTS+ outperforms PLANTS in accuracy and efficiency.