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An Evolutionary Approach to Drug-Design Using Quantam Binary Particle Swarm Optimization Algorithm
The present work provides a new approach to evolve ligand structures which
represent possible drug to be docked to the active site of the target protein.
The structure is represented as a tree where each non-empty node represents a
functional group. It is assumed that the active site configuration of the
target protein is known with position of the essential residues. In this paper
the interaction energy of the ligands with the protein target is minimized.
Moreover, the size of the tree is difficult to obtain and it will be different
for different active sites. To overcome the difficulty, a variable tree size
configuration is used for designing ligands. The optimization is done using a
quantum discrete PSO. The result using fixed length and variable length
configuration are compared.Comment: 4 pages, 6 figures (Published in IEEE SCEECS 2012). arXiv admin note:
substantial text overlap with arXiv:1205.641
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