Unlocking Evolution: How Protein Shapes Illuminate Ancient Biological Connections

New YorkA groundbreaking study published in Nature Communications reveals that understanding the three-dimensional shapes of proteins can help researchers uncover ancient evolutionary links. Led by Dr. Cedric Notredame and Dr. Leila Mansouri from the Centre for Genomic Regulation, the study demonstrates that protein structures offer a more reliable method for constructing evolutionary trees than DNA sequences alone.

Traditional evolutionary trees rely on comparing DNA or protein sequences to identify relationships between species. Over long periods, these sequences can change significantly, making it difficult to trace back to common ancestors. This issue, known as sequence saturation, often leads to inaccurate evolutionary trees. The study shows that protein structures remain more consistent over time, providing a more stable foundation for understanding evolutionary history.

Here's what makes this approach significant:

• Uses protein shapes to trace evolutionary history.
• Combines protein structures with genetic sequences for better accuracy.
• Less affected by changes over time compared to genetic data alone.
• Potential to improve understanding of human kinases, vital for drug development.
• Helps pinpoint evolutionary relationships even from a billion years ago.

By focusing on the physical shape of proteins, researchers measured intra-molecular distances (IMDs) to map out evolutionary histories. They discovered that trees made from structural data matched closely with those built from genomic sequences, but with fewer discrepancies. This combined approach allows scientists to distinguish between accurate and inaccurate relationships more effectively.

This discovery could majorly impact many fields, including biotechnology and disease research. It can improve our understanding of how diseases evolve, aiding in the development of new vaccines and treatments. By examining the relationships of proteins like kinases, which play a crucial role in cellular functions, scientists can better develop targeted therapies for diseases such as cancer. The study opens up opportunities to explore protein evolution on an unprecedented scale, potentially benefiting numerous areas of science and medicine.

Overcoming Evolutionary Saturation

The challenge of evolutionary saturation is a significant issue in understanding the distant past of life's history. Over very long periods, DNA sequences can become heavily altered, making it hard to trace back to their original forms. This complicates constructing accurate evolutionary trees, which scientists rely on to understand relationships between species and genes.

To tackle this problem, researchers are now turning to protein shapes. These three-dimensional structures are more stable over time compared to their sequences. They adapt slowly, preserving ancient features that might be lost in sequences. In this groundbreaking approach, researchers measured the distances between specific parts of protein structures—known as intra-molecular distances. Here's why this method is impactful:

• It reveals evolutionary connections more reliably when DNA sequences fail.
• Combining structural and genomic data enhances the accuracy of evolutionary trees.
• It opens new possibilities for studying ancient relationships among protein families.

This new method doesn't require proteins to have experimentally determined shapes. This is important given the massive volume of structural data predicted by tools like AlphaFold 2. Millions of protein sequences exist, with many more expected as projects like the EarthBioGenome project progress.

Understanding these connections is essential for more than just historical curiosity. For example, protein kinases are crucial in many cellular functions and are key targets in cancer therapies. By creating a more accurate kinase evolutionary tree, researchers can better understand how these proteins work, their interactions with drugs, and possibly improve treatments. The implications extend beyond human health, aiding in vaccine development and understanding disease evolution, among other applications. The study of protein structures can offer unique insights where genetic data alone falls short, helping us to piece together the puzzle of life's ancient history.

Implications for Medicine

The recent study on protein shapes has significant implications for medicine. Protein structures offer new ways to understand diseases and improve treatments. Here are some potential medical benefits:

• Enhancing drug design: Understanding protein shapes can lead to more effective drugs. By knowing how proteins interact at a structural level, scientists can design drugs that fit better and work more efficiently.
• Improving cancer treatment: Many cancer therapies target specific proteins like kinases. With clearer evolutionary trees of these proteins, we can develop more precise cancer treatments.
• Boosting vaccine development: Insights into protein evolution can help us understand pathogens better. This knowledge aids in creating vaccines that target vulnerabilities in viruses and bacteria.
• Tracing disease evolution: By examining protein structures, we gain clues about how diseases have changed over time. This understanding helps in predicting future changes and preparing new treatments.
• Advancing biotechnology: Protein engineering in biotechnology could benefit from this research, leading to new enzymes and bio-products.

Combining protein structures with genetic data offers a fuller picture of how life has evolved. This dual approach reduces errors that come from relying only on genetic sequences, which can change over long periods. It allows us to see connections that were previously hidden.

In medicine, this means more reliable models of how proteins, and by extension, diseases, have developed. Take kinases, for instance—they are critical in many cellular processes and are targeted by numerous drugs. Understanding their evolution helps refine these treatments, potentially improving outcomes for patients.

Furthermore, improved evolutionary trees can guide research beyond kinases. They can assist in tracing proteins linked to genetic disorders, leading to better diagnostics or therapies. With a deeper understanding of protein evolution, researchers can tailor treatments to an individual's genetic makeup or anticipate how diseases might respond to new drugs.

The integration of protein structures into medical research represents a promising frontier. It opens new avenues for exploring complex traits and disease mechanisms, ultimately leading to advancements in healthcare.