Unlocking the Mysteries of Aging: From Proteomic Enigma to AI-Driven Longevity
Addressing the reversal of aging can be considerably more complex than simply preventing this process because, in addition to reversing processes related to chronic inflammation, which is the main factor linked to cellular deterioration, we also need to recover crucial biological components that we've lost over time.
Proteins are a fundamental part of these components and have an intrinsic connection to the health and youthfulness of biological organs and tissues. Due to the complexity of their functioning and mysterious epigenetic mutations, these proteins play a much broader role than our biological maps have been able to unravel in recent decades.
It’s not hard to find new studies unveiling a single protein as if it were a newly discovered pirate treasure. However, in the academic realm, despite the excitement about these findings, there is also considerable apprehension due to the lack of comprehensive biological data about these powerful agents.
The scale of the human proteome is a subject of debate, with estimates in the literature ranging from 20,000 to several million proteins. This alone is enough to leave anyone, even if a scientist, perplexed by the discrepancy. Furthermore, our knowledge of the function of these proteins and the individual ability of the biological system to create new proteins through epigenetic modifications is quite limited.
Now, why does this become even more complex in the context of combating diseases and reversing aging?
The loss of just one protein can accelerate the formation of fibrous tissue in organs like the kidney, heart, and liver, and some proteins have a direct impact on overall longevity.
Restoring these proteins represents a significant challenge for both medicine and scientific research. From a less optimistic perspective, this means that we are dealing with a biological computer of extreme complexity, but we only partially understand its composition and functions.
On the other hand, the enigmatic nature of these challenges stimulates our brilliant minds to seek solutions, and the great turnaround in the study of the human proteome has already begun, with artificial intelligence not only accelerating the creation of a solid database for this field of study but also revolutionizing the understanding of the protein code.
AI can be the light at the end of the tunnel
By the end of 2020, the AI pioneer DeepMind achieved a 50-year breakthrough. By accurately predicting the shapes of proteins at the atomic level, its deep learning algorithm, AlphaFold, virtually solved one of biology's great challenges.
As of mid-2022, DeepMind announced that AlphaFold 2 predicted the structure of 200 million proteins - almost all known ones - and made them available in an open database.
However, the most fascinating aspect is the inventive capacity of artificial intelligence. More recent algorithms, from the same family as DALL-E and GPT-4 - the algorithm behind ChatGPT - have the ability to generate new proteins. This new tool proposes a new dimension to epigenetics.
Artificial intelligence is indeed proposing therapies through the implementation of proteins that our biological system has never encountered, emulating our biological ability to generate new proteins.
Imagine the implementation of proteins like Klotho, crucial for overall longevity. Or better yet, new proteins with specific functions to combat the biological triggers of aging. This is not just fantastic but revolutionary in extending human life.
Nevertheless, I still have many questions, such as how our natural epigenetics will react to the implementation of protein therapies. But I’m not alone; many involved and excited about these new advances can hardly wait to find out.
