Monoclonal antibodies exhibit high specificity for target molecules and for that reason have been successfully utilized as therapeutic and diagnostic agents. The sequence of amino acids comprising the primary structure of an antibody is largely responsible for its binding preference and efficacy. Therefore, antibody sequencing is a central requirement for the development of novel antibody therapies. We propose a method of performing antibody sequencing directly from the protein sequence, without requiring the source cell, which makes it practical for many lab and clinical settings. In addition, our proposed computational method is fully automated, and will increase throughput by dramatically reducing the time required for sequencing from weeks to hours. We plan to implement our method in both a stand-alone tool that may be run on a single desktop computer, or make use of the vast resources available in cloud computing. We will also provide an in-house sequencing service for users without access to the mass spectrometry equipment or computing resources.
Characterizing the sequence of an antibody is a prerequisite for the development of antibody based therapies and diagnostic methods, which represent a growing segment of the drug market. We propose a novel computational method of antibody sequencing based on mass spectrometry, which will dramatically increase the rate of antibody characterization, and reduce the time from development in the lab to treatment in the clinic.