End-to-End Differentiable Learning of Protein Structure

• Published in: Cell systems Vol. 8; no. 4; pp. 292 - 301.e3
• Main Author: AlQuraishi, Mohammed
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 24.04.2019
• Subjects: biophysics; co-evolution; deep learning; geometric deep learning; homology modeling; machine learning; protein design; protein folding; protein structure prediction; structural biology; deep learning; homology modeling; geometric deep learning; protein folding; structural biology; machine learning; protein structure prediction; biophysics; protein design; co-evolution

Predicting protein structure from sequence is a central challenge of biochemistry. Co-evolution methods show promise, but an explicit sequence-to-structure map remains elusive. Advances in deep learning that replace complex, human-designed pipelines with differentiable models optimized end to end su...