… It combines a Multi-Objective Genetic Algorithm with diverse … , peptide folding, and
protein-ligand docking. GaudiMM is available … to deal with protein-ligand docking problems have …

… This paper proposed a reinforcement learning approach to protein-ligand docking …
algorithm for protein-ligand docking has been, among others, is to use modified genetic algorithm…

… -based approach called DeepCSeqSite for ab initio protein-ligand binding residue prediction.
DeepCSeqSite includes a standard edition and an enhanced edition. The classifier of …

… We propose an evolutionary algorithm to search … algorithm RosettaEvolutionaryLigand
(REvoLd) explores the vast search space of combinatorial libraries for protein-ligand docking with …

… BFGS local search algorithm, PSOVina provides … improve the time efficiency while maintaining
the docking performance of PSOVina, in this investigation, we presents a novel algorithm …

… The latter three are more reliable methodologies for predicting protein–ligand binding energies
… there are three types of random algorithms, namely Monte Carlo (MC), Genetic Algorithm …

… Binding poses for a refined set of the protein–ligand complexes were generated by docking
calculations 40 . A 90% homology test was run on this set, which resulted in a small number …

… -objective evolutionary algorithm for molecular docking (… protein-ligand docking problem
in drug discovery. In: Proceedings of the 8th Annual Conference on Genetic and Evolutionary …

… The rapid and accurate in silico prediction of protein-ligand binding free energies or
binding … of protein-ligand binding affinities based on the structural information of protein-ligand …

… based on structural similarity for predicting protein-ligand binding sites. From the whole
scPDB (an annotated database of druggable binding sites extracted from the Protein DataBank) …