RESEARCH
RESEARCH
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As a chemical biologist, I use molecular tools and computational methods to investigate cellular function at its most fundamental level. My research focuses on nucleic acids, DNA and RNA, aiming to uncover how their structures are recognised and how this shapes their function in the cell. This work integrates chemistry, biology and AI/ML to solve complex biological problems.
Nucleic acid secondary structures and recognition
Beyond its well-known double helix, DNA can fold into intricate shapes like G-quadruplexes and Z-DNA that function as molecular switches inside cells. I design and develop chemical tools that specifically recognize these non-canonical structures, enabling me to investigate their roles in cellular processes. A primary focus is on mitochondrial DNA, and through comparative genomics and experimental validation, I investigate why DNA sequences that form these structures have increased over evolution, and what critical functions they perform inside the cell.
Why this matters: A deeper understanding of these unique DNA topologies is critical for revealing their fundamental roles in regulating mitochondrial and cellular function.
iScience 2026, 29, (7), 116425 116425
Trends in Biochemical Sciences. 2025, 50, (3), 267-279 – [Cover page]
Detecting Nucleic acid modification
DNA and RNA modifications are chemical alterations to nucleotides that play crucial roles in development, cellular function, and disease. I develop innovative detection methods that combine chemical probes, advanced DNA/RNA sequencing technologies, and machine learning algorithms to map these modifications.
Why this matters: By simplifying the detection process, we hope to advance our understanding of how RNA/DNA modifications contribute to disease development, paving the way for more efficient diagnostic tools and therapeutic strategies.
ACS Chemical Biology. 2022, 17 (10), 2704–2709 - [Highlighted by Oxford Nanopore Technologies]
Microbial secondary metabolites
My research focuses on discovering microbial-derived secondary metabolites with antimicrobial and anticancer properties. Our team has successfully identified and characterized novel compounds, including the potent anti-tuberculosis agent Chrysomycin A and the mTOR inhibitor Urdamycin E. To overcome the traditionally laborious process of natural product discovery, I integrate machine learning and genome mining into my work. This computational approach allows for a more efficient and targeted discovery of new bioactive molecules from complex biological sources.
Why this matters: With the rise of antibiotic-resistant bacteria and the ongoing need for novel cancer therapies, microbes represent a vast, untapped source of potential. By accelerating the discovery process, we can identify new drug candidates to address various disease.
Natural Product Reports. 2022, 39 (12), 2215–2230 - [Cover page]
ACS Chemical Biology. 2020, 15 (3), 780–788 - [Cover page] [Highlighted by Indiabioscience] [Introducing Our Authors]
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