Patents by Inventor Nikolaos G. Sgourakis

Nikolaos G. Sgourakis has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 11814420
    Abstract: Compositions that include stable peptide deficient MHC class I/chaperone complexes and methods of making and using such complexes are provided. In particular embodiments, such peptide deficient MHC class I/chaperone complexes are used to form peptide MHC class I (pMHC-I) multimers useful for high throughput applications, such as, for the detection of antigen specific T cells and characterization of T cell profiles in subjects.
    Type: Grant
    Filed: July 3, 2019
    Date of Patent: November 14, 2023
    Assignee: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA
    Inventor: Nikolaos G. Sgourakis
  • Publication number: 20230059548
    Abstract: Provided herein are novels systems and methods for the identification of peptides that bind to MHC-I molecules using peptide receptive MHC-I complexes.
    Type: Application
    Filed: January 4, 2021
    Publication date: February 23, 2023
    Inventors: Nikolaos G. SGOURAKIS, Gioro MOROZOV
  • Publication number: 20210371498
    Abstract: Compositions are provided that comprise peptide receptive MHC class I complexes (peptide receptive MHC-I complexes) that are formed after treatment with a catalytic amount of chaperone (i.e. a ratio of chaperone to MHC-I of less than 1:1). In particular, these peptide receptive MHC class I complexes can be used to form peptide-MHC class I (pMHC-I) multimers that can be used in high throughput applications such as detection of antigen specific T cells and characterization of T cell profiles in subjects.
    Type: Application
    Filed: January 4, 2021
    Publication date: December 2, 2021
    Inventor: Nikolaos G. Sgourakis
  • Publication number: 20210371499
    Abstract: Compositions that include peptide receptive MEW class I complexes and methods of making and using such complexes are provided. In particular embodiments, such peptide receptive MHC class I complexes are used to form peptide MHC class I (pMHC-I) multimers useful for high throughput applications, such as, for the detection of antigen specific T cells and characterization of T cell profiles in subjects.
    Type: Application
    Filed: April 16, 2021
    Publication date: December 2, 2021
    Inventor: Nikolaos G. SGOURAKIS
  • Publication number: 20210269503
    Abstract: Compositions that include stable peptide deficient MHC class I/chaperone complexes and methods of making and using such complexes are provided. In particular embodiments, such peptide deficient MHC class I/chaperone complexes are used to form peptide MHC class I (pMHC-I) multimers useful for high throughput applications, such as, for the detection of antigen specific T cells and characterization of T cell profiles in subjects.
    Type: Application
    Filed: July 3, 2019
    Publication date: September 2, 2021
    Inventor: Nikolaos G. Sgourakis
  • Publication number: 20210155670
    Abstract: Disclosed herein are novel glycosylated peptide receptive MHC-I complexes that allow for efficient production of glycosylated MHC-I multimers. Such glycosylated peptide receptive MHC-I complexes include a single-chain MHC-I construct and are produced in mammalian expression systems (e.g., CHO and HEK cells) that allow for the glycosylation of the complexes at one or more native positions. Multimers (e.g., tetramers) produced from the glycosylated peptide receptive MHC-I complexes provided herein advantageously allow for the identification of high-affinity T cell and natural killer cell receptors previously unidentified using traditional unglycosylated MHC tetramers.
    Type: Application
    Filed: September 11, 2020
    Publication date: May 27, 2021
    Inventors: Nikolaos G. Sgourakis, Sara O'Rourke
  • Patent number: 10871459
    Abstract: Computing systems and methods for characterizing a protein are provided. Each residue in a subset of the protein is in an amino acid type set and is represented by a vertex in a graph G formed from an atomic model of the protein. NMR data, acquired with some of the residues of the protein isotopically labeled, is used to form a graph H with each vertex representing a different residue of the protein and assigned one or more amino types. Placements of H onto G are formed, each including mappings assigning vertices in H to vertices in G subject to the constraints that vertices in H mapped to vertices in G cannot be of different amino acid types and edges between pairs of vertices in H must map to corresponding edges in G. For each vertex in H, the number of different valid mappings to G is determined by polling the placements as a constraint satisfaction problem and is deemed assigned when only a single unique assignment is identified.
    Type: Grant
    Filed: February 17, 2018
    Date of Patent: December 22, 2020
    Assignee: The Regents of the University of California
    Inventors: Demetrios Achlioptas, Nikolaos G. Sgourakis
  • Publication number: 20190391093
    Abstract: Computing systems and methods for characterizing a protein are provided. Each residue in a subset of the protein is in an amino acid type set and is represented by a vertex in a graph G formed from an atomic model of the protein. NMR data, acquired with some of the residues of the protein isotopically labeled, is used to form a graph H with each vertex representing a different residue of the protein and assigned one or more amino types. Placements of H onto G are formed, each including mappings assigning vertices in H to vertices in G subject to the constraints that vertices in H mapped to vertices in G cannot be of different amino acid types and edges between pairs of vertices in H must map to corresponding edges in G. For each vertex in H, the number of different valid mappings to G is determined by polling the placements as a constraint satisfaction problem and is deemed assigned when only a single unique assignment is identified.
    Type: Application
    Filed: February 17, 2017
    Publication date: December 26, 2019
    Inventors: Demetrios Achlioptas, Nikolaos G. Sgourakis