Protein recognition methods for diagnostics and therapy.

Ryne Montoya, Peter Deckerman, Mustafa O Guler
Author Information
  1. Ryne Montoya: The Pritzker School of Molecular Engineering, The University of Chicago, 5640 S Ellis Ave Chicago, IL 60637 USA.
  2. Peter Deckerman: The Pritzker School of Molecular Engineering, The University of Chicago, 5640 S Ellis Ave Chicago, IL 60637 USA.
  3. Mustafa O Guler: The Pritzker School of Molecular Engineering, The University of Chicago, 5640 S Ellis Ave Chicago, IL 60637 USA.

Abstract

The fundamental biological processes involving highly specific interactions between proteins and other biological motifs are the pillars of protein recognition mechanisms. These interactions are crucial for biological systems, often having significant implications within diagnostics and therapy development. Protein recognition and specificity are reliant on structural compatibility, dynamic conformational changes, and biochemical interactions-all of which are grounded in fundamental molecular forces like hydrogen bonding, ionic interactions, and van der Waals forces. Advanced characterization tools have improved our understanding of protein interactions, revealing the kinetics and thermodynamics of these recognition mechanisms. In parallel, new computing methods, including artificial intelligence, molecular docking, and dynamical simulations, have increased prediction accuracy for molecular interactions, leading to well-defined interaction sites and binding kinetics information. Protein recognition is pivotal in diagnostic methods including ELISAs and biosensors, which are crucial within disease detection applications. In therapeutics, protein recognition plays an important role in drug development, enabling the design of small molecules, peptides, and monoclonal antibodies. Despite recent progress, there are many challenges remaining to fully understand protein recognition, particularly within the complex cell environment. These challenges require future work in protein recognition studies to enhance diagnostic and therapeutic applications. The researchers are using improved detection and screening methods to identify, assess, and optimize interactions for clinical translation.

Keywords

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