How does the Needleman-Wunsch algorithm compare two biological sequences?

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Computer-generated model of anthrax toxin showing seven differently colored protein units, with a small gold molecule representing a drug bound to the protein structure. — bioinformatics This computerized image of anthrax shows the various structural relationships of seven units within the protein and demonstrates the interaction of a drug (shown in yellow) bound to the protein to block the so-called lethal factor unit. Bioinformatics plays an important role in enabling scientists to predict where a drug molecule will bind within a protein, given the individual structures of the molecules.

The Needleman-Wunsch algorithm is a method used in bioinformatics to compare two biological sequences by determining their optimal global alignment. It utilizes a technique known as dynamic programming, which breaks down the complex task of aligning full sequences into a series of smaller, manageable problems involving short sequence segments. By solving these smaller components, the algorithm constructs an optimal solution for the entire sequence pair.1

During the alignment process, the algorithm scores similarities between the sequences within a matrix. A key feature of this approach is its ability to account for and detect gaps in the sequence alignment, which is essential for identifying evolutionary or functional relationships between DNA or amino acid sequences. While the Needleman-Wunsch algorithm is highly effective at finding the optimal alignment, it is computationally intensive and generally considered too slow for searching through vast sequence databases, leading researchers to use faster alternatives like BLAST for large-scale data retrieval.1