Editing Protein engineering (section)

===Multiple sequence alignment===
Without structural information about a protein, sequence analysis is often useful in elucidating information about the protein. These techniques involve alignment of target protein sequences with other related protein sequences. This alignment can show which amino acids are conserved between species and are important for the function of the protein. These analyses can help to identify hot spot amino acids that can serve as the target sites for mutations. [[Multiple sequence alignment]] utilizes data bases such as PREFAB, SABMARK, OXBENCH, IRMBASE, and BALIBASE in order to cross reference target protein sequences with known sequences. Multiple sequence alignment techniques are listed below.<ref name=PoluriBook>{{cite book|last1=Poluri|first1=Krishna Mohan|last2=Gulati|first2=Khushboo|title=Protein Engineering Techniques|date=2017|publisher=Springer|language=en|doi=10.1007/978-981-10-2732-1|series=SpringerBriefs in Applied Sciences and Technology|isbn=978-981-10-2731-4}}</ref>{{page needed|date=May 2017}}

This method begins by performing pair wise alignment of sequences using [[k-tuple]] or [[Needleman–Wunsch algorithm|Needleman–Wunsch]] methods. These methods calculate a matrix that depicts the pair wise similarity among the sequence pairs. Similarity scores are then transformed into distance scores that are used to produce a guide tree using the neighbor joining method. This guide tree is then employed to yield a multiple sequence alignment.<ref name=PoluriBook/>{{page needed|date=May 2017}}

====Clustal omega====
This method is capable of aligning up to 190,000 sequences by utilizing the k-tuple method. Next sequences are clustered using the mBed and [[k-means clustering|''k''-means]] methods. A guide tree is then constructed using the [[UPGMA]] method that is used by the HH align package. This guide tree is used to generate multiple sequence alignments.<ref name=PoluriBook/>{{page needed|date=May 2017}}

====MAFFT====
This method utilizes fast Fourier transform (FFT) that converts amino acid sequences into a sequence composed of volume and polarity values for each amino acid residue. This new sequence is used to find homologous regions.<ref name=PoluriBook/>{{page needed|date=May 2017}}

====K-Align====
This method utilizes the Wu-Manber approximate string matching algorithm to generate multiple sequence alignments.<ref name=PoluriBook/>{{page needed|date=May 2017}}

====Multiple sequence comparison by log expectation (MUSCLE)====
This method utilizes Kmer and Kimura distances to generate multiple sequence alignments.<ref name=PoluriBook/>{{page needed|date=May 2017}}

====T-Coffee====
This method utilizes tree based consistency objective functions for alignment evolution. This method has been shown to be 5–10% more accurate than Clustal W.<ref name=PoluriBook/>{{page needed|date=May 2017}}