Accurate Identification of Small Chemical Compounds’ Structure, Using Fragmented Ions (No. 0120)

 
<< Back to all technologies

Summary

A novel method that enables to accurately determine the chemical structure of a wide variety of small compounds.

The global mass spectrometry market was valued at USD 4.48 Billion in 2020 and is projected to reach USD 7.30 Billion by 2028, growing at a CAGR of 6.24% from 2021 to 2028.
Accurate chemical compound identification is of high importance for multiple purposes and industries including for drug testing and discovery, and food contamination detection. However, chemical compound analysis using existing methods, including Mass spectrometry (MS) and ion mobility spectrometry (IMS), still poses some obstacles, due to difficulties such as molecule cleavage site prediction, and low tested material quantities, resulting in a huge number of potential structures and hence molecule candidates. The novel algorithm-based method can allow for an accurate chemical compound identification.
 

 

Lead Researcher:
Eisuke Hayakawa

Evolutionary Neurobiology Unit

Applications

  • Environmental or forensic analysis
  • Pharmaceutical analysis
  • Drug development and drug screening

 

Advantages

  • High sensitivity and reliable structure identification
  • High throughput based on commonly used methods (MS/IMS)
  • Enables to identify compounds with an unknown reference structure

   

     Click on the images to enlarge

 

Technology's Essence

The present method combines MS/IMS, and a set of algorithms. It matches the results of the MS/IMS to a standard chemical library, for better compound identification. It consists of several methods that share common data structures and data processing techniques, based on data set formation and comparison. The methods do not depend on any compound class-specific characteristics or structural features, therefore enable to determine any class of small compounds. A specific algorithm uses additional methods to identify compounds that are not present “as is” in the database, by assessing their spectral similarity.

 

Media Coverage and Presentations

 

CONTACT FOR MORE INFORMATION

  Graham Garner
Technology Licensing Section

  tls@oist.jp
  +81(0)98-966-8937