Biology Personal Statementfor Oxford & Cambridge

Reading about AlphaFold2's performance in CASP14 in 2020 made me think differently about proteins. A polypeptide starts as a linear sequence, yet folds into a structure precise enough to determine binding and catalysis. What interested me was not just that a system could predict that structure, but what the prediction implied biologically: if folding is so constrained by sequence, why can one substitution leave a protein looking almost unchanged while still altering its function? That question sent me back to tertiary structure and enzyme action. I began to look beyond textbook diagrams of hydrogen bonds, ionic interactions and disulfide bridges and think about the balance they create: proteins have to be stable enough to work, but flexible enough to change and interact. That is what makes biology worth studying at degree level for me. I want to study molecular biology in more depth, especially where sequence, structure and regulation produce behaviour that is patterned but not simple.

My studies have given that interest a more precise direction. In A-level biology, the induced-fit model made me think about enzymes as dynamic rather than rigid. Catalysis depends on geometry, but also on movement, charge and environment, which helped me connect protein structure to function more carefully. Because I kept returning to the gap between tidy molecular explanations and messy biological behaviour, I used my EPQ to investigate how pH and temperature affect catalase activity in potato extract. I prepared the extract, reacted it with hydrogen peroxide under buffered conditions, collected oxygen with a gas syringe and used the earliest part of each run to calculate initial reaction rates in Excel. My first results looked suspiciously neat. Repeating the trials showed why: small differences in preparation changed the apparent enzyme concentration enough to distort the pattern. Standardising the extraction volume, keeping samples on ice between runs and focusing on the initial rate improved the reliability of the data, but the project mattered most because it made the limits of simple explanations visible. That process made me more careful about what counts as evidence in biology.

Outside formal education, I tried to follow the same questions further. Reading Jumper et al.'s 2021 Nature paper on AlphaFold showed me that the achievement was not only the reported accuracy, but the way the system used patterns across evolutionarily related sequences. It made proteins seem less like isolated objects and more like records of selection, while also making a limit clearer to me: predicting a fold is not the same as explaining a cell. That led me to Siddhartha Mukherjee's The Gene, which challenged my earlier habit of thinking of biology too neatly, as though DNA simply moved towards an outcome. His discussion of regulation and expression made me more interested in how biological information is filtered from transcription to folding to cellular response. Taking part in the British Biology Olympiad reinforced that interest because the questions rarely rewarded recall alone. I found the unfamiliar data on genetics and physiology more useful than straightforward syllabus questions because they forced me to build explanations from patterns and competing possibilities rather than search for a memorised fact. Working part-time in a supermarket has also made me calmer when routines change and more attentive to people who explain the same problem differently, which helped when I was mentoring younger students in our school biology society. Those experiences have made me more patient with uncertainty and more willing to revise an explanation when the evidence does not fit it.