For example, scientists at Imperial College have been investigating how certain “pirate phages” – those fascinating viruses that hijack other viruses – can hack into bacteria. Understanding these mechanisms could open up completely modern ways of combating drug-resistant infections, which of course constitutes a huge global health challenge.
What the co-scientist brought to this work was the ability to quickly analyze decades of published research and independently develop a hypothesis about the mechanisms of gene transfer in bacteria that is consistent with what the Imperial team has spent years developing and testing experimentally.
In fact, we see that the system can dramatically shorten the hypothesis generation phase – enabling the rapid synthesis of extensive amounts of literature – while human researchers continue to design experiments and understand what their findings actually mean for patients.
Looking ahead to the next five years, beyond proteins and materials, what is the “unsolved problem” that keeps you up at night that these tools can lend a hand solve?
What really excites me is understanding how cells function as complete systems, and deciphering the genome is fundamental to this.
DNA is a book with recipes for life, proteins are its ingredients. If we truly understand what makes us genetically unique and what happens when our DNA changes, we will unlock extraordinary modern possibilities. Not only personalized medicine, but also the potential design of modern enzymes to fight climate change and other applications far beyond healthcare.
That said, simulating the entire cell is one of the main goals of biology, but it’s still a long way off. First, we need to understand the cell’s deepest structure, its nucleus: precisely where each part of the genetic code is read, how the signaling molecules that ultimately lead to the assembly of proteins are created. Once we have examined the nucleus, we can start from the inside. We are working on it, but it will take a few more years.
If we could reliably simulate cells, we could transform medicine and biology. We could computationally test drug candidates before synthesis, understand disease mechanisms at a fundamental level, and design personalized treatments. This is really the bridge between biological simulation and the clinical reality you’re asking about – moving from computational predictions to actual therapies that lend a hand patients.
This story originally appeared on WIRED Italy and was translated from Italian.