Patent classifications
G16B15/20
BIOINFORMATIC PROCESSES FOR DETERMINATION OF PEPTIDE BINDING
This invention relates to the identification of peptide binding to ligands, and in particular to identification of epitopes expressed by microorganisms and by mammalian cells. The present invention provides polypeptides comprising the epitopes, and vaccines, antibodies and diagnostic products that utilize or are developed using the epitopes.
Evaluation and optimization of supramolecular therapeutics
The disclosure provides a process of designing and optimizing supramolecular therapeutics. The disclosure also provides a method for designing and optimizing antibody drug conjugates.
Evaluation and optimization of supramolecular therapeutics
The disclosure provides a process of designing and optimizing supramolecular therapeutics. The disclosure also provides a method for designing and optimizing antibody drug conjugates.
SYSTEM AND METHOD FOR PROTEIN SELECTION
The method for protein selection can include: characterizing a protein set, training a prediction model, determining target characteristic values, and determining a candidate protein set based on the target characteristic values.
SYSTEM AND METHOD FOR PROTEIN SELECTION
The method for protein selection can include: characterizing a protein set, training a prediction model, determining target characteristic values, and determining a candidate protein set based on the target characteristic values.
METHOD FOR PREDICTING PROTEIN-PROTEIN INTERACTION
Provided is a method for predicting protein-protein interaction. Also provided are an electronic device and a non-transitory computer readable storage medium.
METHOD FOR PREDICTING PROTEIN-PROTEIN INTERACTION
Provided is a method for predicting protein-protein interaction. Also provided are an electronic device and a non-transitory computer readable storage medium.
Branched heteropolymer lattice model for quantum optimization
Techniques regarding determining a three-dimensional structure of a heteropolymer are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise a polymer folding component that can generate a course-grained model to determine a three-dimensional structure of a heteropolymer based on a first qubit registry that encodes a conformation of the heteropolymer on a lattice and a second qubit registry that encodes an interaction distance between monomers comprised within the heteropolymer.
Protein Structure Prediction
The disclosure provides, inter alia, methods of determining the three-dimensional structure of a polypeptide, given a subject protein sequence, e.g., a primary amino acid sequence. The methods can efficiently determine structures, including those of de novo proteins for example, those without known homologues with pre-determined structures.
Protein Structure Prediction
The disclosure provides, inter alia, methods of determining the three-dimensional structure of a polypeptide, given a subject protein sequence, e.g., a primary amino acid sequence. The methods can efficiently determine structures, including those of de novo proteins for example, those without known homologues with pre-determined structures.