This article provides a general solution for the problem of Multiple Sequence Alignment of biological sequences by dividing the sequences into many sub sequences and then applying Genetic Algorithms to each sub sequences. The main objective of this research work is to maximize the similarity between the sequences by adding and shuffling gaps and then calculating the score of each column of the alignment so as to get reliable multiple sequence alignment. The experimental results show that the proposed method is able to generate better alignments for the benchmark data sets (Balibase ref. 2) than other most commonly used methods, such as the CLUSTAL X, PRRP, DIALI, RBT-GA and PILEUP8. Computational results demonstrate the superiority of the proposed approach for many sequences with different length and identity when compared with methods stated above. The new approach is more robust and obtains better mathematical and biological quality. © 2015, International Journal of Pharmacy and Technology. All rights Reserved.