… As a retrospective assessment of our new Adaptive BP-Dock approach, we analyze 5
different diverse sets of protein–ligand complexes and glycan–cyanovirin interaction from our …

… This work presents a new genetic algorithm to facilitate molecular evolution of small organic
molecules, in the context of a 3D protein-ligand binding site, over multiple generations. …

… Overall, in this work, we developed a machine learning approach for estimating protein–ligand
binding affinity changes upon single mutations trained on a data set of 796 \(\Delta \Delta {…

… algorithms to improve the docking performance in this study. Being stochastic algorithms,
evolutionary algorithms (… and robust solutions to solve protein-ligand docking problems. This …

… Compared with protein–ligand binding, ligand binding sites … tools have been developed for
protein–ligand binding, 72-75 the … The Monte Carlo (MC) 61, 66 and Genetic algorithms (GA) …

… protein–ligand binding predictions are a valuable help in drug discovery. Protein–ligand
docking … components: a scoring function and a search algorithm. It is of interest to evaluate the …

… improved compared with three other popular protein–ligand … functions used in protein–ligand
docking programs are not … , heuristic search algorithms such as genetic algorithms and …

… In this paper, we propose a novel optimization algorithm of pose search for protein-ligand
docking based on the FWA, namely, FWAVina, which is implemented in the framework of …

… affinity of a ligand to a target of interest, we need a description of the protein-ligand binding
site that allows the key protein-ligand interactions to be learned. Ideally, this representation …

… evolutionary algorithms. To address this problem, we propose a dual-population multi-objective
evolutionary algorithm … , thus improving the performance of the evolutionary algorithm. …