University of Washington

Amazon Technologies, Inc.

Vanessa Nguyen

David Baker

William H Sheffler

Jorge Fallas

George Ueda

Layne Christopher Price

Yen Ling Adelene Sim

Alexander Sewall Ford

Franziska Seeger

Described herein are polypeptides capable of self-assembling to form homo-oligomers, and methods for designing such polypeptides.

Computational design of self-assembling cyclic protein homo-oligomers

Techniques for predicting a protein sequence are described. An exemplary method includes receiving a request to predict a missing area of a protein's primary sequence and a corresponding three-dimensional position of the missing area; applying a machine learning model to backbone Cartesian coordinates of the protein's primary sequence and a protein vector of a representation of the protein's primary sequence including the missing area to predict a missing area of the protein primary sequence and a corresponding three-dimensional position for the missing area, wherein the machine learning model is selected from the group consisting of: an attention-based machine learning model, a bidirectional long short term memory-based model, and a convolutional neural network-based model; and outputting a result of the machine learning model.

Systems, methods, and apparatuses to predict protein sequence and structure

Growing community of inventors

Seattle, WA, United States of America

Vanessa Nguyen