Early 1900s, London
The Industrial Revolution’s dynamic machines inspired scientists to ponder the mechanistic nature of life itself.
How do cells animate living things the way gears animate machines?
He guessed that special structures on cells help them detect and interpret signals.
Ehrlich called the structures “side chains.” Today, we know them as cellular receptors, the mediators of cellular communication.
1948 - 1965, the United States and the United Kingdom
In 1948, American pharmacologist Raymond P. Ahlquist defined two distinct cardiovascular receptors, alpha and beta. He believed the beta receptor controlled the heart’s response to adrenaline, a hormone that sometimes contributes to cases of elevated blood pressure, arrhythmias, and chest pain.
In the late 1950s, Sir James Black built on Ahlquist’s work by investigating the beta receptor as a therapeutic target for cardiovascular disease. He guessed blocking this influential receptor might also stop adrenaline from straining the heart.
Black invented the beta blocker propranolol in the mid 1960s. This drug, one of the first based on our understanding of cell receptors, still saves the lives of heart-disease patients today.
Present Day, Los Angeles, California
UCLA’s Institute for Quantitative and Computational Biosciences, led by Director Alexander Hoffmann, incorporates big data and computational modeling to understand cellular communication and how it affects genes and disease development.
“Big data and mathematical modeling give us the tools to understand disease as never before. In the past, the challenge in the biological sciences was to generate data,” Hoffmann says. “Now, the challenge is how to make sense of a tsunami of scientific data. The opportunities to develop accurate predictions are unprecedented.”
The human body contains an estimated 37.2 trillion cells. Understanding the precise mechanics that drive interactions between those trillions of cells will bolster our ability to treat nearly any disease affecting nearly any part of the body.