The Need: Metabolite identification is a critical challenge in the fields of biochemistry, pharmaceuticals, and life sciences. Researchers often deal with complex mixtures of metabolites, making it difficult to accurately identify and analyze specific compounds. Existing web servers for metabolite identification through NMR (Nuclear Magnetic Resonance) spectra struggle with samples of high complexity, leading to inaccuracies and false positives. There is a pressing need for an advanced solution that can handle complex mixture analysis and improve metabolite identification accuracy.

The Technology: Ohio State presents the Complex Mixture Analysis by NMR (COLMAR) 13C–1H HSQC database, a cutting-edge technology that addresses the limitations of existing web servers. This new database offers an interactive, user-friendly web interface at http://spin.ccic.ohio-state.edu/index.php/hsqc/index. COLMAR 13C–1H HSQC database takes a groundbreaking approach by separately treating slowly exchanging isomers belonging to the same metabolite. This unique feature significantly enhances query performance, especially for lowly populated isomers that fall below the HSQC detection limit. Researchers can now achieve rapid and accurate identification of metabolites from 13C–1H HSQC spectra at natural abundance, an invaluable tool in their analytical arsenal.

Commercial Applications:

• Metabolite Identification: Rapidly and accurately identify metabolites from complex mixtures in biochemistry and life sciences research.
• Pharmaceutical Analysis: Facilitate drug discovery and development by analyzing NMR spectra of complex pharmaceutical compounds.
• Environmental Studies: Study metabolite mixtures in environmental samples for monitoring and assessing ecosystem health.

Benefits/Advantages:

• Enhanced Query Performance: Separate treatment of slowly exchanging isomers allows for improved query accuracy even for lowly populated isomers, overcoming HSQC detection limits.
• Superior Accuracy: Compared to existing web servers, Ohio State's COLMAR database demonstrates a remarkable 37% higher true positive rate and an 82% lower false positive rate for samples of high complexity, ensuring reliable results.
• User-Friendly Interface: The interactive web interface offers ease of use, enabling researchers to access and analyze data efficiently.

With Ohio State's COLMAR 13C–1H HSQC database, researchers can now embark on a journey of accurate metabolite identification, pushing the boundaries of scientific discovery and unlocking new opportunities in various industries. Discover the power of COLMAR and revolutionize your NMR-based analysis today!