Computational platform for generating molecules

A method performed by one or more computers, the method comprising:

• receiving, from a user, a request to generate data identifying candidate molecules satisfying one or more molecular criteria, wherein the one or more molecular criteria include a criterion requiring that candidate molecules bind to a target binding site;
• generating a collection of candidate molecules based at least in part on the one or more molecular criteria, comprising:
• generating a network input to a generative neural network based on the one or more molecular criteria, wherein the network input comprises data characterizing a chemical structure of the target binding site for the candidate molecules;
• and
• processing the network input using the generative neural network to generate, as outputs of the generative neural network, the collection of candidate molecules;
• generating, for each candidate molecule in the collection of candidate molecules, one or more molecular scores that characterize one or more properties of the candidate molecule;
• filtering the collection of candidate molecules, based on the molecular scores, to remove a plurality of candidate molecules from the collection of candidate molecules;
• and
• after filtering the collection of candidate molecules based on the molecular scores, providing a representation of the collection of candidate molecules to the user.

A system comprising:

• one or more computers;
• and
• one or more storage devices communicatively coupled to the one or more computers, wherein the one or more storage devices store instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising:
• receiving, from a user, a request to generate data identifying candidate molecules satisfying one or more molecular criteria, wherein the one or more molecular criteria include a criterion requiring that candidate molecules bind to a target binding site;
• generating a collection of candidate molecules based at least in part on the one or more molecular criteria, comprising:
• generating a network input to a generative neural network based on the one or more molecular criteria, wherein the network input comprises data characterizing a chemical structure of the target binding site for the candidate molecules;
• and
• processing the network input using the generative neural network to generate, as outputs of the generative neural network, the collection of candidate molecules;
• generating, for each candidate molecule in the collection of candidate molecules, one or more molecular scores that characterize one or more properties of the candidate molecule;
• filtering the collection of candidate molecules, based on the molecular scores, to remove a plurality of candidate molecules from the collection of candidate molecules;
• and
• after filtering the collection of candidate molecules based on the molecular scores, providing a representation of the collection of candidate molecules to the user.

One or more non-transitory computer storage media storing instructions that when executed by one or more computers cause the one or more computers to perform operations comprising:

• receiving, from a user, a request to generate data identifying candidate molecules satisfying one or more molecular criteria, wherein the one or more molecular criteria include a criterion requiring that candidate molecules bind to a target binding site;
• generating a collection of candidate molecules based at least in part on the one or more molecular criteria, comprising:
• generating a network input to a generative neural network based on the one or more molecular criteria, wherein the network input comprises data characterizing a chemical structure of the target binding site for the candidate molecules;
• and
• processing the network input using the generative neural network to generate, as outputs of the generative neural network, the collection of candidate molecules;
• generating, for each candidate molecule in the collection of candidate molecules, one or more molecular scores that characterize one or more properties of the candidate molecule;
• filtering the collection of candidate molecules, based on the molecular scores, to remove a plurality of candidate molecules from the collection of candidate molecules;
• and
• after filtering the collection of candidate molecules based on the molecular scores, providing a representation of the collection of candidate molecules to the user.