Amelie Stein

Papers

Total Citations

216

H-Index

About

Amelie Stein is a leading computational structural biologist whose work has fundamentally advanced protein modeling and design. Her primary research focuses on developing and applying Rosetta-based methods to predict and engineer protein conformations, dynamics, and functions. Stein’s most impactful contribution is her pioneering work on robotics-inspired conformational sampling, detailed in her highly cited 2013 paper (216 citations), which dramatically improved the ability to navigate the rugged energy landscapes of proteins. By integrating fragment-based moves with kinematic closure, she enabled more accurate, atomic-level sampling of protein backbones, directly addressing the challenge of generating models close enough to native structures for reliable prediction. This breakthrough has become a cornerstone of modern Rosetta protocols, empowering researchers to model flexible loops, design novel enzymes, and understand allostery. Her work has not only yielded thousands of citations but also shaped the field’s approach to computational protein science, making her a key figure in bridging algorithm development with biological discovery.