Our research

Drug discovery: Engineering next-generation therapeutics for the heart and brain

Cardio-neurovascular disorders, including stroke, heart failure, and dementia, are among the most pressing health challenges of our time. Although many current therapies target GPCRs, these drugs often lack specificity, acting as blunt “on/off” switches that activate both therapeutic and harmful pathways. This lack of precision frequently leads to significant side effects that hinder their clinical effectiveness.

We take a smarter, more selective approach. We view GPCRs not as simple on/off switches, but as allosteric microprocessors capable of fine-tuning and integrating diverse signals. Using this framework, we develop two classes of precision therapeutics:

Allosteric modulators, which bind to topographically distinct sites from the endogenous (orthosteric) sites and act like “dimmer switches” to fine-tune receptor activity in a spatial and temporal manner. Allosteric modulation allows us to fine-tune the body’s natural signalling processes without overwhelming them.

Biased ligands, designed to selectively activate beneficial intracellular signaling pathways (e.g., cardioprotective or anti-inflammatory responses) while minimizing activation of pathways linked to side effects (e.g., bradycardia or neurotoxicity). Biased agonism allows us to harness the therapeutic potential of GPCRs with greater precision and fewer unwanted outcomes.

To accelerate this discovery pipeline, we’ve built an integrated platform powered by:

  • Structure-based virtual ligand screening (VLS) using X-ray, cryo-EM, or AI-predicted receptor structures.
  • PSICHIC, our in-house deep learning model for predicting ligand-GPCR interaction and affinity from SMILES and sequence.
  • High-throughput in vitro pharmacological assays to assess affinity, efficacy, selectivity, cooperativity, and bias factor.
  • Predictive AI models trained on multi-omic toxicity and pharmacology data
  • In vivo preclinical models to validate safety and therapeutic potential.

This AI-assisted “Smarter, Faster” drug discovery funnel enables us to screen millions of compounds and refine them down to a handful of candidates with optimised profiles, ready for stroke and neurodegenerative models.

Our mission is to engineer safer, smarter, faster, and more effective GPCR-targeted drugs that meet the urgent clinical needs.

Uncovering how plastic pollution hijacks GPCR signalling

Plastic pollution is no longer just an environmental issue - it’s a biological one. Micro- and nanoplastics (MNPs) and plastic-derived pollutants such as bisphenols and phthalates have now been detected in nearly every compartment of the human body: in blood, lungs, placenta, atherosclerotic plaques, and even the brain.

Mounting evidence links these contaminants to serious chronic diseases, including stroke, heart attacks, dementia, and neurodegeneration. But the molecular mechanisms behind this link remain poorly defined.

We are pioneering a new frontier of discovery to fill this critical gap. Our research is built on a bold hypothesis that plastic-associated pollutants act as unregulated, evolutionarily novel GPCR ligands - rogue molecules that mimic or disrupt endogenous signaling.

Rather than causing damage through generic toxicity, we propose that many of these compounds bind directly to GPCRs and subtly distort their signaling over time. These pollutants may act as agonists, antagonists, or allosteric modulators, perturbing tightly regulated pathways in the cardiovascular and neurovascular systems.

Supported by an ARC-funded research program, we are applying our full platform - molecular pharmacology, molecular modeling, high-throughput screening, and artificial intelligence - to define the ecopharmacological activity of MNPs and plastic-derived chemicals. Our current targets include the Adenosine A1 Receptor (A1R) and the G protein-coupled Estrogen Receptor (GPER), two key players in cardiovascular and endocrine health.

Our mission is to uncover how environmental chemicals hijack receptor function at the molecular level and use this knowledge to protect human health, guide public policy, and inspire the design of safer materials for the future.

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