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Three Reasons Biomolecular Interactions are Important for Disease Treatment

studying biomolecular interactions

Almost all biological processes can be described as a sequence of interactions between small molecules. One of the best ways to monitor these biomolecular interactions is microscale thermophoresis (MST), a widely used analysis technique that quantifies biomolecular interactions based on unique physical principles of thermophoresis. Not only can analysis of these interactions give us fundamental insight into the molecular biology of the cell, but it also leads the way towards improved disease treatment.

Understanding Protein Structure and Function
Proteins are molecules that play a crucial role in our cells, and their dysfunctions are known to cause the development of different pathological conditions and diseases. From a biological point of view, enzymes and receptors are the most important proteins as they are involved in an almost endless variety of functions.

For the majority of proteins, we observe strong correlations between the polymeric structure and functional dynamics. (1) We can determine a protein’s function and how a disease affects its behavior or structure by the way it interacts with other proteins under normal conditions. For instance, the malaria-causing microorganism Plasmodium falciparum invades red blood cells through multiple receptor-ligand interactions. In these types of infectious diseases, host cell invasion is an important factor that involves specific protein-protein interactions.

Disease treatment drugs are most commonly composed of a small organic molecule that activates or inhibits the function of a biomolecule, such as a protein- which in turn results in a therapeutic benefit to the patient. Thus, being able to observe and understanding how these proteins behave sets the basis for how treatment therapies will be developed.

Predicting Protein Function and Behavior
The structure of a protein determines several functional features including cellular location, overall fold, active site residues and their conformation in enzymes, and interactions with ligands and other proteins. Because proteins with similar structures carry out similar functions, we are able to predict the way a protein will respond and behave in the presence of disease. For this reason, anticipating the binding affinity from structural models has been a matter of active research for more than 40 years. There are still many unknown proteins whose behavior can be predicted based on similarities in structure. The goal of new technologies like MST to determine these unknown functionalities.

Understanding Protein Pathways
Proteins do not function in isolation. They are constantly interacting with other biomolecules to form cellular networks or maps. These metabolic interaction networks provide a detailed description of protein binding events, which play a central role in all fields of life science, from molecular physiology and pathology to diagnostics and pharmacology.

Thousands of protein networks for many species have been outlined in detail, allowing us to predict the outcome of each map under normal healthy conditions. As diseases are introduced to different protein networks, we are able to see the effect that each disease has on the map’s outcome. These protein interaction networks can also be used to suggest functions for previously uncharacteristic proteins by uncovering their role in pathways or protein complexes. (2) Pathological alterations of these signal transduction networks have to be clarified in order to gain a better understanding of disease etiology.

Disease treatment requires a complex balance of many moving parts, and the first piece of the puzzle is understanding the biomolecular interactions involved. New technologies will continue to enhance our understanding of this dynamic, which will in turn better our treatment of diseases.

1. Wilson C, Kreychman J, Gerstein M. Assessing annotation transfer for genomics: Quantifying the relations between protein sequence, structure and function through traditional and probabilistic scores. J Mol Biol. 2000;297:233–249
2. Pazos F, Ranea JA, Juan D, Sternberg MJ (2005) Assessing protein co-evolution in the context of the tree of life assists in the prediction of the interactome. J Mol Biol 352: 1002–1015.

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