Daniel J. Mandell

University of California, San Francisco, QB3

Papers

Total Citations

598

H-Index

About

Daniel J. Mandell is a leading computational structural biologist whose work bridges robotics and protein engineering to solve fundamental challenges in molecular design. His research focuses on developing algorithms for high-accuracy protein modeling, particularly in loop reconstruction and backbone flexibility—critical areas for understanding protein function and designing novel therapeutics. Mandell’s most influential contribution, the 2009 paper "Sub-angstrom accuracy in protein loop reconstruction by robotics-inspired conformational sampling," has garnered 487 citations, demonstrating its transformative impact on the field. This work introduced innovative sampling methods that achieve near-experimental precision, enabling more reliable predictions of protein structure. His subsequent study on "Backbone flexibility in computational protein design" (111 citations) further advanced the field by incorporating dynamic conformational changes into design algorithms, expanding the scope of computational protein engineering. Mandell’s robotics-inspired approach has opened new avenues for designing functional proteins with enhanced stability and activity, with applications ranging from enzyme engineering to drug discovery. His work exemplifies how interdisciplinary methods can push the boundaries of computational biology, making him a pivotal figure in modern protein design.