Sickle cell disease turns red blood cells into stiff, clog-prone crescents that can kill if untreated, but doctors lack the tools to predict exactly how much drug or blood transfusion a patient needs. This fellowship builds computer simulations that connect the behaviour of individual molecules to the way whole tissues function, aiming to solve that problem. The same framework will also tackle bacterial biofilms—the slimy communities responsible for an estimated 700,000 deaths each year from antimicrobial resistance—and help design better nanobody and antibiotic treatments. A third strand focuses on biomolecular condensates, the liquid-like droplets inside cells whose malfunction is linked to neurodegenerative diseases and cancer. Rather than studying each system from scratch, the researcher uses the underlying physics they share to make predictions about one system feed into the others. If successful, the work could guide personalised dosing for sickle cell patients, prioritise which genetic therapies to develop, and identify complications before they appear clinically—all without waiting for expensive trial-and-error in the clinic.
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Recent successes of gene-therapy treatments have demonstrated the power of perturbing protein sequences to cure genetic diseases. However, current challenges to genetic treatment include prohibitive costs, a lack of understanding of risk, and heterogeneity in clinical responses. More traditional treatments are able to target cellular properties; for example, drug treatments and blood transfusions that reduce the stiffness of red blood cells in sickle cell disease. However, many of these approaches suffer from a lack of quantitative understanding to enable precision judgements, such as how much drug to administer or blood to transfuse. To continue driving progress forward so that we can treat a range of diseases effectively, and make such treatments more widely available, we need to better understand how molecular and cellular properties translate to emergent function in tissues and organisms. In this fellowship, I will apply my recently developed theoretical framework that uses discrete and continuum simulations to capture how macroscopic biological functions emerge from the properties of mesoscopic structures formed by interacting microscopic biomolecules. The overall aim is to predict optimal changes to molecules and cells to control emergent properties and biological functions in soft biological matter. I will meet the following objectives: 1) To predict optimal perturbations to molecular interactions in human proteins to control macroscopic functions such as chemical reactions in cells. A recent paradigm shift in biology has revealed that many human proteins and RNA can condense or aggregate to form liquid-, gel- or solid-like structures under cellular conditions. Biomolecular condensates, a physiological example of this process, have been implicated in diseases including neurodegenerative diseases, infectious diseases and cancer. However, it is largely unknown how physiological and pathological molecular interactions contribute to condensate functions in health and disease. 2) To predict optimal nanobody and antibiotic treatments for bacterial biofilms. Bacterial biofilms are a leading cause of antimicrobial resistance, which is thought to cause 700,000 deaths each year globally, with a cumulative cost of $100 trillion by 2050 if no action is taken. Recent evidence suggests that viral phages expressed by various bacteria may have important effects on antibiotic resistance, but to contribute to improved treatments for the many diseases associated with such bacterial infections, we need to understand and combat the mechanisms that confer phage-expressing bacteria with these benefits. 3) To predict optimal drug, genetic and transfusion treatments for sickle cell disease. Pathological biophysical dynamics of red blood cells are a hallmark of diseases of the blood that affect millions of people worldwide, including sickle cell disease (SCD). In SCD, blood increases in viscosity and may clog in deoxygenated conditions, causing death if left untreated. There is an ongoing clinical effort to develop genetic and pharmacological treatments for SCD, but we lack tools to prioritise specific treatment strategies or to clinically monitor patients and identify complications before they manifest physiologically. By leveraging the underlying physical connections between these biological systems, I will bypass the effort to study each system in isolation and ensure that advances in each system create added value for the others. The theoretical framework will be applicable to a broad range of related systems in which molecular and cellular interactions generate emergent biological functions. The results in this fellowship will generate long-term impacts on human health by guiding treatments to molecular diseases and bacterial infections that affect millions of people worldwide.
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