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As shown in Algorithm 1, the proposed algorithm (FCPLDPA) is applied to the Lamarckian genetic algorithm (LGA) to solve the docking problem for the rigid protein and flexible drug molecules.
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This paper principally focuses on the search techniques for solving the docking problem.
As such, it is one of the efficient ways for solving the docking problem [ 8].
For example, local surfaces of proteins and ligands are often used for shape comparison in the docking problem.
This explains why many search methods for reducing the computation time have been presented to solve the docking problem [ 5].
This is known as the "docking problem".
Some algorithms have been shown to be very effective for solving the protein ligand docking problem, and some researchers have improved the power of these docking methods.
For the protein ligand docking problem, GA is real code, so real mutation is used as mutation operator.
On the one hand, a number of four metaheuristic techniques are analyzed within an extensive set of docking problems, looking for the best technique according to the quality of the binding energy solutions.
This paper illustrates a novel and robust optimization algorithm (CEPGA) for solving the protein ligand docking problems with an aim to overcome the above-mentioned drawback.
However, to develop an efficient and reliable search algorithm is still a challenge for docking problem.
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CEO of Professional Science Editing for Scientists @ prosciediting.com