Systems and methods for artificial intelligence-guided biomolecule design and assessment

A system for designing a custom biologic structure for binding to a target via an artificial intelligence (AI)-powered scaffold docker module, the system comprising:

• a processor of a computing device;
• and
• a memory having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to:
• (a) generate a candidate scaffold model, wherein the candidate scaffold model is a representation of at least a portion of a candidate peptide backbone, wherein the candidate peptide backbone is a prospective backbone of the custom biologic structure being designed and wherein the candidate scaffold model (i) comprises representations of peptide backbone atoms identifying types and locations of peptide backbone atoms, but (ii) excluding side chains;
• (b) generate, for the candidate scaffold model, a plurality of prospective scaffold-target complex models, each representing at least a portion of a complex comprising the target and the candidate peptide backbone at a particular pose with respect to the target;
• (c) for each of the plurality of prospective scaffold-target complex models, determine a scaffold pose score, wherein determining the scaffold pose score for each particular one of the plurality of prospective scaffold-target complex models comprises:
• generating, based on the particular scaffold-target complex model, a corresponding representation;
• and
• using the corresponding representation as input to a machine learning model that determines, as output, the scaffold pose score for the particular scaffold-target complex model, said machine learning model having been trained using representations of native scaffold-target complex models, each representing a peptide backbone of a particular protein and/or peptide, as oriented at a particular pose with respect to a target, in an existing native protein-protein and/or protein-peptide example complex, and wherein the scaffold pose score is a likelihood that the particular scaffold-target complex model represents a native complex;
• (d) select a subset of the plurality of prospective scaffold-target complex models using the determined scaffold pose scores;
• and
• (e) provide the selected subset of prospective scaffold-target complex models for use in designing the custom biologic structure for binding to the target.