Abstract
Background: Study of folded structure of proteins provides insights into their biological functions, conformational dynamics and molecular evolution. Current methods of elucidating folded structure of proteins are laborious, low-throughput, and constrained by various limitations. Arising from these methods is the need for a sensitive, quantitative, rapid and high-throughput method not only analysing the folded structure of proteins, but also to monitor dynamic changes under physiological or experimental conditions.
Objectives: In this focused review, we outline the foundation and limitations of current protein structure-determination methods prior to discussing the advantages of an emerging antibody epitope analysis for applications in structural, conformational and evolutionary studies of proteins.
Methods: We discuss the application of this method using representative examples in monitoring allosteric conformation of regulatory proteins and the determination of the evolutionary lineage of related proteins and protein isoforms.
Results: The versatility of the method described herein is validated by the ability to modulate a variety of assay parameters to meet the needs of the user in order to monitor protein conformation. Furthermore, the assay has been used to clarify the lineage of troponin isoforms beyond what has been depicted by sequence homology alone, demonstrating the nonlinear evolutionary relationship between primary structure and tertiary structure of proteins.
Conclusion: The antibody epitope analysis method is a highly adaptable technique of protein conformation elucidation, which can be easily applied without the need for specialized equipment or technical expertise. When applied in a systematic and strategic manner, this method has the potential to reveal novel and biomedically meaningful information for structure-function relationship and evolutionary lineage of proteins.
Keywords: Protein conformation, epitope analysis, monoclonal antibody, molecular evolution, ELISA, evolutionary lineage.
Graphical Abstract