The Methods for Detecting Amino Acid Sequences

The amino acid sequence is the basic unit of proteins in organisms and is of great significance for studying the structure, function, and interaction of proteins. Therefore, the development of efficient and accurate methods for detecting amino acid sequences is of great importance for drug development in the field of biotechnology. This article will introduce several commonly used methods for detecting amino acid sequences.

 

Sanger Sequencing

Sanger sequencing is a classic sequencing method. It terminates DNA synthesis by adding dideoxynucleotide (ddNTP) during the process of DNA polymerase synthesizing DNA chains, so as to obtain a series of DNA fragments of different lengths. These fragments can determine the sequence of DNA after being separated by electrophoresis. The application of Sanger sequencing in the detection of amino acid sequences is realized by transcribing DNA into RNA, and then translating it into proteins after transcription.

 

Mass Spectrometry

Mass spectrometry is an analysis method based on the mass-to-charge ratio (m/z), which can be used to detect the amino acid sequence of proteins. Common mass spectrometry methods include mass spectrography and tandem mass spectrometry (MS/MS). Mass spectrography decomposes proteins into peptide segments, and then measures the mass of peptide segments by a mass spectrometer to infer the amino acid sequence. MS/MS, on the other hand, obtains more amino acid sequence information through fragmentation chemical reactions on the basis of mass spectrography.

 

High-Throughput Sequencing

High-throughput sequencing is a rapidly developing sequencing technology in recent years. It can efficiently obtain a large amount of amino acid sequence information by parallel sequencing of a large number of DNA or RNA molecules. Common high-throughput sequencing technologies include Illumina sequencing, Ion Torrent sequencing, and PacBio sequencing. The development of these technologies has made the detection of amino acid sequences faster, more accurate, and more economical.

 

Computational Methods

In addition to laboratory sequencing methods, there are also some computational methods that can predict the amino acid sequence of proteins. These methods, based on the structure and function of proteins, simulate and predict amino acid sequences through algorithms. Common computational methods include alignment algorithms, machine learning algorithms, and deep learning algorithms.

 

The detection of amino acid sequences is an important step in drug development in the field of biotechnology, and different detection methods have their advantages and disadvantages. Sanger sequencing is a classic sequencing method, mass spectrometry can obtain amino acid sequence information through mass spectrography and MS/MS, high-throughput sequencing can efficiently obtain a large amount of sequence information, and computational methods can predict the amino acid sequence of proteins. The comprehensive application of these methods can provide more sequence information for drug development in the field of biotechnology, promoting the progress of drug development.