New research proves cellular proteins identify and communicate with one another using molecular “add-ons”. Scientists liken the protein add-ons to web browser plug-ins.
Slowly, researchers beginning to understand how proteins develop to perform specific functions. While, proteins have an interface region where they connect with other proteins. However, it’s clear exactly how key proteins find each other within a crowded cellular environment.
Now, researchers report that it’s the add-ons that enable proteins to connect exclusively with the right dedicated partner.
Florian Busch, a postdoctoral researcher at Ohio State, called the existence of protein add-ons “a previously unknown fundamental driving principle” to ensure that proteins interact in specific ways.
Scientists analyzed proteins among 15,000 bacterial genomes, sorting different proteins into family tree-like groupings based on their genetic sequences. The analysis revealed interface structures present on some proteins, but not on others. Researchers realized the add-ons could explain the diversity of protein functionality.
While, scientists identified around 1,000 known protein geometries in nature. Some proteins can form complexes that perform hundreds of thousands of very specific functions.
Study analyzing how proteins interact with each other, and what the interfaces look like, how they are constructed, and how they evolved, researchers said.
Researchers manipulated molecular add-ons to see how their absence might affect bacterial colonies. They found the deletion of one add-on hampered the growth of Bacillus subtilis. They used native mass spectrometry to detect how the presence and absence of add-ons influenced the ability of proteins to interact with each other.
Researchers said, the native mass spectrometry technology could help identify the role of these interface ‘add-ons’. A way for a protein to find its critical partner protein even in a crowded cellular environment with similar structures present.
One of the exciting things about the study is researchers use “big data” in this case, entire protein and genome databases.
More information: [PNAS]