Michael Levitt is a South African-born American biophysicist at Stanford University who, together with Martin Karplus and Arieh Warshel, pioneered multiscale computational approaches to study complex chemical systems. Levitt developed some of the first practical methods for simulating protein structures computationally, including simplified representations of proteins and the first molecular dynamics simulation of a protein in water. His work established the principles of protein structure prediction and coarse-grained modeling, which remain central to modern structural bioinformatics. Levitt was among the first to use computers to understand how proteins fold into their functional three-dimensional shapes, a problem of enormous biological and medical significance. He shared the 2013 Nobel Prize in Chemistry with Karplus and Warshel. His methods have influenced the development of deep learning approaches to protein folding, including AlphaFold, and are foundational to drug discovery pipelines across the pharmaceutical industry.