"We’re no longer limited to what nature gives us"
Earlier this month, we spoke to Dr Binuraj Menon, Senior Lecturer in Biotechnology, about his work in developing biocatalysts and chemo-enzymatic approaches. Read on to learn how these advancements are impacting the wider world.
What first drew you to biotechnology and enzymology as a research focus?
I’ve always been fascinated by how biological systems operate at the molecular level, and biotechnology stood out to me as a field that connects that curiosity to real-world applications. It offers a powerful way to translate molecular insights into solutions for healthcare, sustainability, and industry.
My interest in enzymology grew when I learned how enzymes, as a biological molecule, function as highly efficient and selective catalysts. I was particularly struck by their ability to drive complex reactions under mild conditions that would otherwise require harsh chemistry. Over time, I became more interested in the relationship between enzyme structure and function, and in how enzymes can be optimized or combined for specific applications. This blend of fundamental science and practical impact is what motivates my research focus today.
Can you tell us about the Menon Group and its aims?
My group focuses on developing innovative enzyme-based solutions by exploiting untapped enzymes. A central theme of our work is the engineering and designing of new enzymatic processes, particularly by exploiting biocatalysts derived from diverse natural product pathways. Our goal is to create new, efficient and environmentally friendly routes for producing valuable chemicals and drug precursors. To achieve this, we design and integrate synthetic and biosynthetic pathways, approaches that combine multiple enzymes and catalytic systems. We aim to bridge fundamental enzymology with real-world applications, enabling more sustainable and scalable strategies for chemical synthesis, drug development, and challenges such as plastic biodegradation and chemical pollution.
What intrigued you most about working with halogenase enzymes specifically?
Halogenase enzymes have a remarkable ability to perform highly selective halogenation reactions – reactions that insert chlorine, bromine or iodine into specific carbon atoms in various molecules. This is a chemically important reaction to prepare many highly useful pharmaceutical drugs, plastics and polymers. However, these reactions are often very challenging with traditional chemistry and need harsh chemicals and solvents- leading to chemical pollution in the industrial production of those materials. Halogenase enzymes on the other hand introduce halogen atoms into complex molecules under mild, environmentally friendly conditions with exceptional precision.
I’m particularly fascinated by how this selectivity opens opportunities to generate new or “non‑natural” compounds with improved biological, chemical or pharmacokinetics properties, especially for drug development. Thus, halogenases sit at an exciting intersection of fundamental enzymology and practical application, which is what makes working with them so compelling.
How important is interdisciplinary teamwork in your research?
The kinds of challenges we’re addressing, either designing new biocatalysts or building entirely new synthetic pathways, are too complex to be addressed using a single discipline strategy. We collaborate across fields, particularly those who work with natural product synthesis, organic chemistry, biophysics, machine learning as well as synthetic and structural biology. This allows us to combine different perspectives and expertise, which often leads to more creative and effective solutions. For that reason, interdisciplinary teamwork is central to our research.
Your work combines synthetic biology, chemistry, and machine learning. How do these disciplines come together in your research?
Our work sits at the intersection of these areas. Synthetic biology provides the framework to design and engineer biological systems and pathways. Chemistry helps us understand reaction mechanisms and enables the integration of chemo‑enzymatic steps to expand what biology alone can achieve. Machine learning is becoming increasingly important for analysing complex datasets, predicting enzyme behaviour, in understanding pathway flux and bottlenecks, and in guiding protein design or pathway optimisation. By bringing these disciplines together, we can move more efficiently from understanding enzyme function to designing and optimising systems that are novel and have real-world applications. That integration is what allows us to push the boundaries of what biocatalysis can do.
What is your approach to designing or improving enzymes through techniques like directed evolution?
Natural enzymes have evolved to work efficiently inside cells, which often means they’re relatively slow but highly specific for their natural substrates. That specificity and moderate speed are perfectly adequate for biology, but for industrial applications we need something different; faster reactions, the ability to accept a broader range of substrates, and robustness under harsh conditions like high temperatures or organic solvents.
To achieve that, I use different enzyme engineering tools, from site directed designs to random or directed evolution approaches as a way of accelerating or replicating natural selection in the lab. We introduce mutations to modify the enzyme, then screen for variants that perform better under these industrial conditions. By iterating this cycle, mutation, selection, and refinement, and increasingly guiding it with structural insights and machine learning, we can reshape natural enzymes into much more efficient and versatile industrial catalysts.
What are the most promising applications of biocatalysts in industry right now?
Biocatalysts are already widely used in the chemical industry, and over the next 10–20 years we’re likely to see many traditional chemical processes replaced by enzymes available almost “off the shelf.” A big reason for this shift is that we can now engineer enzymes to suit industrial needs rather than relying on what nature provides.
Halogenases are a particularly powerful example for this because they enable transformations that are otherwise difficult or inefficient to achieve using conventional methods. It replaces conventional chemistry and the harsh, energy-intensive, and difficult to control. Beyond that, there’s growing interest in late-stage functionalisation, where these enzymes modify complex molecules at the final steps of synthesis, making drug development faster and more flexible. We’re also seeing strong applications of halogenases and other enzymes in fine chemical and agrochemical industries, where both selectivity and sustainability are becoming critical.
How do you see your research area evolving in the coming years?
I see the field moving very quickly from discovery to true on-demand enzyme design. We’re no longer limited to what nature gives us, we’re getting better at reshaping enzymes and designing them to carry out completely new reactions under industrial conditions. In the next few years, advances in machine learning, artificial intelligence, structural biology, and high-throughput screening will make this process much faster and more predictable.
For enzymes like halogenases, I think we’ll see them become standard tools in synthesis, especially for pharmaceuticals and fine chemicals, where precise and selective modifications are critical. In future designing a biocatalyst will become almost routine to that of an ambition now, so rather than forcing chemical reactions to work under harsh conditions, we can instead tailor enzymes to carry out those reactions efficiently, sustainably, and at industrial scale.
What’s the most rewarding part of your work?
The most rewarding part is seeing something that started as a basic scientific idea turn into a real, working solution, taking an enzyme from barely functional to something genuinely useful. It’s also incredibly fulfilling to train and mentor the next generation of scientists, helping students develop the skills and curiosity to push this field forward themselves.
If time and resources were unlimited, what research project would you pursue?
If time and resources were unlimited, I’d be really interested in building adaptive or “evolving” enzymatic systems. Essentially, these are platforms where enzymes can continuously learn and improve in response to new substrates or reaction conditions. Rather than optimizing one enzyme at a time, the idea would be to create integrated systems that combine directed evolution, machine learning, and high‑throughput screening to rapidly explore entirely new areas of chemical space. This could allow us to develop biocatalysts for reactions that currently have no efficient biological or chemical solutions. I’d also be keen to apply this to tackling difficult, real-world problems, like breaking down persistent pollutants, plastics or converting complex waste streams into useful chemicals, where traditional approaches fall short.