ISSN 1662-4009 (online)

ey0019.15-15 | Basic Science and Genetics | ESPEYB19

15.15. Accurate prediction of protein structures and interactions using a three-track neural network

M Baek , F DiMaio , I Anishchenko , J Dauparas , S Ovchinnikov , GR Lee , J Wang , Q Cong , LN Kinch , RD Schaeffer , C Millan , H Park , C Adams , CR Glassman , A DeGiovanni , JH Pereira , AV Rodrigues , Dijk AA van , AC Ebrecht , DJ Opperman , T Sagmeister , C Buhlheller , T Pavkov-Keller , MK Rathinaswamy , U Dalwadi , CK Yip , JE Burke , KC Garcia , NV Grishin , PD Adams , RJ Read , D Baker

Science. 2021;373(6557):871-6. doi: 10.1126/science.abj8754 PubMed ID: 34282049Brief summary: This study reveals a Deep Learning method, ‘RoseTTA fold’, based on DeepMind’s Alphafold2 framework, to predict 3-dimensional protein structures from 1-dimensional sequence information and generate models of protein–protein complexes with high accuracy.Previ...