Quantum-Si. has been granted a patent for methods and compositions that identify and sequence proteins and amino acids. The invention includes amino acid recognition molecules with enhanced photostability, featuring polypeptides that combine multiple binding proteins linked by a short amino acid sequence. GlobalData’s report on Quantum-Si gives a 360-degree view of the company including its patenting strategy. Buy the report here.

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According to GlobalData’s company profile on Quantum-Si, Optoelectronic biosensors was a key innovation area identified from patents. Quantum-Si's grant share as of July 2024 was 20%. Grant share is based on the ratio of number of grants to total number of patents.

Amino acid recognition molecules for protein sequencing

Source: United States Patent and Trademark Office (USPTO). Credit: Quantum-Si Inc

The granted patent US12065466B2 describes an innovative amino acid recognition molecule characterized by a polypeptide that includes two distinct amino acid binding proteins connected by a linker of at least two amino acids. The polypeptide must exhibit at least 90% sequence identity to specific sequences listed in SEQ ID NOs 249-271. The binding proteins can be selected from a group that includes ClpS proteins, Gid proteins, UBR-box proteins, and p62 proteins, among others. Notably, the first and second binding proteins can be identical, with claims specifying instances where both are ClpS proteins or UBR proteins.

Further claims detail the structural components of the polypeptide, including the potential for the linker to comprise up to 100 amino acids, with an optimal range of 5 to 50 amino acids. The patent also allows for the inclusion of a tag sequence, which may consist of purification tags, cleavage sites, or biotinylation sequences, and can feature tandem biotin ligase recognition sequences. Additionally, the polypeptide may be labeled with a luminescent marker. The claims emphasize the importance of sequence identity, with specific thresholds set at 90% and 95% for various components, ensuring a high degree of similarity to the referenced sequences.

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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.