The article introduces MUSCLE, a multiple sequence alignment (MSA) method designed to improve both biological accuracy and computational complexity. MUSCLE is an extension of the progressive alignment method, which builds a multiple alignment by first estimating a phylogenetic tree and then constructing a multiple alignment for each node in the tree. The article details the three stages of the MUSCLE algorithm: draft progressive, improved progressive, and refinement. It also describes several techniques to enhance the algorithm's performance, such as using k-mer counting for similarity measures, position-specific gap penalties, and e-strings for efficient alignment path representation. The results show that MUSCLE outperforms other popular alignment programs like CLUSTALW and MAFFT in terms of speed and accuracy, achieving alignment accuracy comparable to CLUSTALW with significantly reduced computation time. Additionally, MUSCLE introduces a new option, MUSCLE-fast, optimized for high-throughput applications, and a method for evaluating objective functions for profile-profile alignment.The article introduces MUSCLE, a multiple sequence alignment (MSA) method designed to improve both biological accuracy and computational complexity. MUSCLE is an extension of the progressive alignment method, which builds a multiple alignment by first estimating a phylogenetic tree and then constructing a multiple alignment for each node in the tree. The article details the three stages of the MUSCLE algorithm: draft progressive, improved progressive, and refinement. It also describes several techniques to enhance the algorithm's performance, such as using k-mer counting for similarity measures, position-specific gap penalties, and e-strings for efficient alignment path representation. The results show that MUSCLE outperforms other popular alignment programs like CLUSTALW and MAFFT in terms of speed and accuracy, achieving alignment accuracy comparable to CLUSTALW with significantly reduced computation time. Additionally, MUSCLE introduces a new option, MUSCLE-fast, optimized for high-throughput applications, and a method for evaluating objective functions for profile-profile alignment.