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

Fluctuation corrections on thermodynamic functions: Finite size effect

The explicit thermodynamic functions, in particular, the specific heat of a spin system interacting with a spin bath which exerts finite dissipation on the system are determined. We show that the specific heat is a sum of the products of a thermal equilibration factor that carries the temperature dependence and a dynamical correction factor, characteristic of the dissipative energy flow under steady state from the system. The variation of specific heat with temperature is accompanied by an abrupt transition that depends on these dynamical factors characteristic of the finite system size.Comment: 18 pages, 3 figures, Presented as poster in Theoretical Chemistry Symposium, 2012 held at IIT Guwahati, Indi