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New Protein Analysis Kit Provides Sensitive, Reproducible and Fast Results

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A new tool for protein digestion is designed to substantially reduce preparation times and associated errors, facilitating fast and reliable analytical results for biopharmaceutical and protein research applications. 

Current protein digestion techniques are comprised of complex procedures that require the determination of protein concentration, followed by sample reduction and alkylation steps prior to digestion with trypsin. This multifaceted preparation protocol can take up to 24 hours and is prone to both irreproducibility and poor sensitivity. 

To improve upon this process, the Thermo Scientific SMART Digest kit uses a simple three-step, easy-to-implement process that can be automated. Its immobilized trypsin design is formulated for high-quality data with a significantly reduced sample preparation time compared to traditional in-solution digestion methods. 

The SMART Digest kit will be exhibited at the 42nd International HPLC Conference in Geneva, Switzerland, Booth 14, June 21-25. 

“Sample preparation that requires protein digestion can be a laborious and time-consuming task, particularly when performing high-throughput applications,” said Kevin Doolan, product line director, Chromatography Columns and Consumables, for Thermo Fisher Scientific. “Our new SMART Digest kit is designed to simplify this process, providing higher reproducible, sensitive analyses of protein digests in a fraction of the time, which is especially valuable for both biopharma and research labs.” 

The increased reproducibility of digestion possible with this kit should enable users to implement generic, fast and robust methods for high throughput processing of samples. Furthermore, the SMART Digest kit is designed to provide higher sequence coverage, while reducing both chemically induced post-translational modifications and the number of chemicals in the final sample. This design makes the SMART Digest kit accurate and sensitive, capable of generating high-quality data at high throughputs.