… Our results show that the adaptive strategy provides a significant improvement in fitness …
adaptive approach for automating mutations we broaden the capabilities of genetic algorithm …

… Our plan to extend this work includes implementing genetic algorithm between nearby
points to maximize the benefit of shared wisdom of threads, in addition to making a self-fine-…

… However, the constraint is not as strict as in protein-ligand docking, where the lock-…
Evolutionary algorithms are metaheuristic algorithms that mimic natural evolution. These algorithms …

… of potent agonists by docking different molecules … improve docking performance on a
specific target is to incorporate into the docking algorithm previous knowledge of key protein–ligand …

… docking algorithms have been developed for protein–ligand interactions, only a few docking
… AutoDock utilizes a Lamarckian Genetic Algorithm to search the conformational space and …

… residence time, high binding efficiency and strong selectivity. … molecular docking for
modeling of covalent protein–ligand … , an efficient docking algorithm for covalent protein–ligand …

… docking workflows. Specifically, we first benchmark the method on blind protein–ligand docking
… and the ligand coordinates are predicted without any binding-site constraint. As detailed (…

… We compared our method (called CurPocket) with state-of-the-art protein–ligand binding
site prediction methods using the benchmark set of COACH [23], which is one of the best …

… binding affinity (scoring power). Here, we focus on the latter: accurately predicting protein–ligand
binding affinity … (10) These algorithms, commonly posed as a regression problems for …

… docking has been significantly adapted from protein–ligand … the defined box through a
genetic algorithm. During the random … of genetic algorithms are used to search the ligand-binding …