Restriction site placement in virus genomes using Particle Swarm Optimization

The Presence of unique restriction sites (URSs) within a sequence is very important so that the sequence may be cut unambiguously in exactly one place with a restriction enzyme. Restriction site manipulation in virus genome may produce virus variants to serve as potential vaccines. Therefore, a number of applications are invented for the manipulation of viral genomes to produce attenuated viruses. Recently, automatic generation of URSs in the sequence has been investigated through different approaches (e.g., Greedy, Weighted Bipartite and Max-Min Gap) and found effective. The aim of this study is to investigate URS enhancement in a given virus genome considering it as an optimization task. URS placement (URSP) is a kind of pattern matching problem; therefore, formulation of existing optimization approach(s) to solve it efficiently is very important timely research so that working with large sized genomes becomes easy. In this study, Particle Swarm Optimization (PSO), the popular method of optimization, has been modified and formulated to solve URSP problem. The proposed URSP-PSO method has been tested on a set of benchmark virus genome sequences and found to increase URSs in a large number. The method is also found better than existing methods for large sized genome sequences.