Patent ID: 11923044
Assignee: AMAZON TECHNOLOGIES, INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A computer-implemented method comprising:
receiving, at a protein sequence predictor comprising one or more processors, a request to predict a missing area of a protein primary sequence and a corresponding three-dimensional position of the missing area, the request including a representation of the protein primary sequence, backbone Cartesian coordinates for the protein primary sequence, and an indication of ablations in the protein primary sequence;
conditioning the protein primary sequence and the backbone Cartesian coordinates for the protein primary sequence by:
passing the representation of the protein primary sequence as input to an attention-based machine learning model of the protein sequence predictor and applying an embedding of the attention-based machine learning model to the representation of the protein primary sequence,
obtaining output of a protein vector from the attention-based machine learning model,
passing the backbone Cartesian coordinates as input to the protein sequence predictor to capture features in sequence space, and
obtaining output of processed backbone Cartesian coordinates from the protein sequence predictor;

combining the processed backbone Cartesian coordinates and the protein vector to generate a combined coordinate vector and protein vector;
passing the combined coordinate vector and protein vector as input to the attention-based machine learning model;
obtaining output of a prediction of the missing area of the protein primary sequence and the corresponding three-dimensional position of the missing area from the attention-based machine learning model;
and
generating a three-dimensional representation of the protein based on the output of the prediction of the missing area of the protein primary sequence and the corresponding three-dimensional position of the missing area.