The boundaries of synthetic chemistry are being pushed to their limits, prompting researchers to look toward biology for solutions. With the rise of synthetic biology and artificial intelligence (AI), scientists are unlocking novel possibilities for drug discovery, such as designing and producing rare and new-to-nature molecules. By harnessing these tools, researchers are developing new approaches to synthesizing complex molecules, optimizing production pathways, and engineering biological systems for pharmaceutical innovation. To gain insight into this rapidly evolving field, we spoke with Graham Hudson, Ph.D., a synthetic biology and microbiology specialist, and Nathan Lanclos, an expert in AI-driven protein design. Learn more about how CAS is tackling these challenges.
CAS: Is synthetic biology a necessary next step for drug development innovation beyond synthetic chemistry?
CAS: What recent breakthroughs are helping scientists engineer microbes to be “living drug factories”?
CAS: What were the most difficult aspects of adapting plant-derived biosynthetic pathways for microbial production?
CAS: In what other areas are you leveraging AI to accelerate discovery?
CAS: What are some of the biggest data-related bottlenecks you have experienced in your work?
CAS: Is collaboration between researchers from different backgrounds becoming essential?
CAS: If you had a magic wand to change anything in the drug discovery process, what would you change?
Graham Hudson, Ph.D., earned a B.S. in Biochemistry from Saint Louis University, where he researched RNA base pair thermodynamics to support therapeutic design. He completed a Ph.D. at the University of Illinois at Urbana-Champaign with Douglas A. Mitchell, focusing on RiPP natural products—reconstituting thiopeptide biosynthesis, discovering two novel classes (ranthipeptides and pyritides) and uncovering the enzymatic basis of thioamidation. Currently a postdoctoral researcher at UC Berkeley in Jay D. Keasling’s lab, he studies the enzymology and biosynthesis of saponin natural products. He has also consulted for the industry on natural product research.
Nathan Lanclos holds a B.S. in Molecular Biology and a B.A. in Economics from the University of South Florida, where he researched protein function in cancer with Vladimir Uversky and engineered C1 metabolism in bacteria with Ramon Gonzalez. He is currently a Ph.D. student in the UCSF/UC Berkeley Joint Bioengineering Program. In 2022, he founded a consulting firm supporting biotech startups with marketing strategy and data modeling. His research focuses on machine learning for protein design and high-throughput protein engineering, with an emphasis on multi-domain complexes like polyketide synthases (PKSs) for chemical and therapeutic production.