Evolutionary computation: toward a new philosophy of machine intelligence
Evolutionary computation: toward a new philosophy of machine intelligence
Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Optical Coating Designs Using the Family Competition Evolutionary Algorithm
Evolutionary Computation
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We have developed an evolutionary approach for the flexible docking that is now an important component of a rational drug design. This automatic docking tool, referred to as the GEMDOCK (Generic Evolutionary Method for DOCKing molecules), combines both global and local search strategies search mechanisms. GEMDOCKused a simple scoring function to recognize compounds by minimizing the energy of molecular interactions. The interactive types of atoms between ligands and proteins of our linear scoring function consist only hydrogen-bonding and steric terms. GEMDOCK has been tested on a diverse dataset of 100 protein-ligand complexes from Protein Data Bank. In total 76% of these complexes, it obtained docked ligand conformations with root mean square derivations (RMSD) to the crystal ligand structures less than 2.0 Å when the ligand was docked back into the binding site. Experiments shows that the scoring function is simple and efficiently discriminates between native and non-native docked conformations. This study suggests that GEMDOCK is a useful tool for molecular recognition and is a potential docking tool for protein structure variations.