This research applies large language models to decode and design proteins by treating amino acid sequences as biological languages. By identifying hidden structural and functional patterns across massive protein datasets, the work enables creation of novel proteins for medicine, cancer therapy, carbon capture, and environmental remediation beyond naturally evolved biological systems.

This research focuses on the total synthesis of natural products, biologically important molecules produced by nature. Using pedrolide, an anticancer compound, as a case study, the work applies strategic molecular “deconstruction” to identify simple building blocks and develop laboratory methods for assembling complex natural molecules through innovative organic chemistry.

This research develops rigorous mathematical foundations for consensus-based optimization algorithms, where large groups of interacting particles collaboratively search for optimal solutions. Using mean-field theory and propagation of chaos, the work proves long-term stability and improves optimization methods for applications including robotics, aircraft design, and drug discovery under real-world constraints.

This research explores endophytes—fungi living symbiotically within plants—that produce bioactive compounds aiding plant defense and growth. These compounds have led to major medical breakthroughs like antibiotics and immunosuppressants. Studying endophytes in crops may uncover new drugs and agricultural benefits, highlighting nature’s vast, largely untapped biochemical potential.

This research develops a non-hormonal male contraceptive by blocking two sperm proteins, Catsper and SLO3, that enable hyperactivated “power swimming” required for fertilization. By designing molecules that inhibit these proteins, the project aims to create a safe, reversible contraceptive option that avoids hormonal side effects.

This research addresses antibiotic resistance by developing new compounds effective against Pseudomonas aeruginosa. Using engineered Streptomyces albus, it produces uridyl peptide antibiotics with a triple-target mechanism that reduces resistance risk. The work focuses on purification and chemical optimization to create more effective, clinically viable antibiotics for future infections.

Respiratory Syncytial Virus (RSV) hospitalises thousands of children each year, yet effective treatments remain unavailable. This research investigates a critical protein–protein interaction that enables RSV infection. By identifying and disrupting key molecular binding sites using AI, the work aims to support the development of targeted antiviral therapies for severe RSV.

Mental health disorders disrupt neural connections in the brain, yet most treatments only manage symptoms. This research explores psychedelic-inspired drugs that restore lost brain connections without hallucinogenic effects, using automated imaging tools to identify compounds that rebuild neural structure and offer lasting recovery.

This research uses a computational method called MELT to identify hidden allosteric pockets in shape-shifting proteins like BCR–ABL kinase. By targeting these pockets, drugs can stabilize inactive protein states, overcoming resistance caused by protein flexibility and enabling more effective, adaptable strategies for drug discovery.

This research tackles antibiotic resistance by developing nano-scale microfluidic cultures that isolate and study previously unculturable bacteria. By screening rare microbes and directly testing their antimicrobial activity, the platform accelerates discovery of new antibiotics, offering a powerful tool against drug-resistant superbugs.