Name
Abstract | ||
|---|---|---|
Designing a drug is the process of finding or creating a molecule which has a specific activity on a biological organism. Drug design is difficult since there are only few molecules that are both effective against a certain disease and exhibit other necessary physiological properties, such as absorption by the body and safety of use. The main problem of drug design is therefore how to explore the chemical space of many possible molecules to find the few suitable ones. Computational methods are increasingly being used for this purpose, among them evolutionary algorithms. This review will focus on the applications of evolutionary algorithms in drug design, in which evolutionary algorithms are used both to create new molecules and to construct methods for predicting the properties of real or yet unexisting molecules. We will also discuss the progress and problems of application of evolutionary algorithms in this field, as well as possible developments and future perspectives. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/s11047-004-5237-8 | Natural Computing |
Keywords | Field | DocType |
possible development,future perspective,biological organism,genetic algorithms,de novo design,computational method,ligand docking,quantitative structure-activity relationships,molecule superposition,evolutionary algorithm,conformational analysis,drug design,possible molecule,chemical space,library design,main problem,certain disease,evolutionary algo- rithms,evolutionary algorithms,genetic algorithm,specific activity,quantitative structure activity relationship | Interactive evolutionary computation,Evolutionary algorithm,Human-based evolutionary computation,Artificial intelligence,Chemical space,Evolutionary programming,Genetic algorithm,Mathematics,Machine learning,Organism | Journal |
Volume | Issue | Citations |
4 | 3 | 7 |
PageRank | References | Authors |
0.69 | 47 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Eric-Wubbo Lameijer | 1 | 37 | 5.84 |
| Thomas Bäck | 2 | 629 | 86.94 |
| Joost N. Kok | 3 | 1429 | 121.49 |
| Ad P. IJzerman | 4 | 33 | 2.81 |