In this research work, we propose a cooperative approach called simulated particle swarm optimization (SPSO) which is based on metaheuristics to find an approximate solution for the multiple sequence alignment (MSA) problem. The developed approach uses the particle swam optimization (PSO) algorithm to discover the search space globally and the simulated annealing (SA) technique to improve the population leader «gbest» quality in order to overcome local optimum problem. Simulation results on BaliBASE benchmarks have shown the potent of the proposed method to produce good quality alignments comparing to those given by other existing methods.