Nothing Special   »   [go: up one dir, main page]

Dilsook, 2023 - Google Patents

ETD: In silico redesign and de novo design of anti-MUC1 monoclonal antibodies

Dilsook, 2023

View PDF
Document ID
7078790367541388121
Author
Dilsook K
Publication year

External Links

Snippet

Abstract Mucin 1 (MUC1) is a cellular membrane-tethered protein which is abnormally glycosylated and overexpressed in several epithelial cancers. This abnormal glycosylation is hypothesized to participate in the hyper-activation of signaling pathways which promote …
Continue reading at open.uct.ac.za (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/16Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for molecular structure, e.g. structure alignment, structural or functional relations, protein folding, domain topologies, drug targeting using structure data, involving two-dimensional or three-dimensional structures
    • CCHEMISTRY; METALLURGY
    • C07ORGANIC CHEMISTRY
    • C07KPEPTIDES
    • C07K16/00Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies
    • C07K16/18Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies against material from animals or humans
    • C07K16/28Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/18Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for functional genomics or proteomics, e.g. genotype-phenotype associations, linkage disequilibrium, population genetics, binding site identification, mutagenesis, genotyping or genome annotation, protein-protein interactions or protein-nucleic acid interactions
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/28Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for programming tools or database systems, e.g. ontologies, heterogeneous data integration, data warehousing or computing architectures
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/22Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for sequence comparison involving nucleotides or amino acids, e.g. homology search, motif or SNP [Single-Nucleotide Polymorphism] discovery or sequence alignment
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/12Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for modelling or simulation in systems biology, e.g. probabilistic or dynamic models, gene-regulatory networks, protein interaction networks or metabolic networks
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00Investigating or analysing materials by specific methods not covered by the preceding groups
    • G01N33/48Investigating or analysing materials by specific methods not covered by the preceding groups biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • CCHEMISTRY; METALLURGY
    • C07ORGANIC CHEMISTRY
    • C07KPEPTIDES
    • C07K2317/00Immunoglobulins specific features
    • C07K2317/20Immunoglobulins specific features characterized by taxonomic origin
    • C07K2317/24Immunoglobulins specific features characterized by taxonomic origin containing regions, domains or residues from different species, e.g. chimeric, humanized or veneered
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/70Chemoinformatics, i.e. data processing methods or systems for the retrieval, analysis, visualisation, or storage of physicochemical or structural data of chemical compounds
    • G06F19/706Chemoinformatics, i.e. data processing methods or systems for the retrieval, analysis, visualisation, or storage of physicochemical or structural data of chemical compounds for drug design with the emphasis on a therapeutic agent, e.g. ligand-biological target interactions, pharmacophore generation
    • CCHEMISTRY; METALLURGY
    • C07ORGANIC CHEMISTRY
    • C07KPEPTIDES
    • C07K16/00Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies
    • C07K16/46Hybrid immunoglobulins
    • C07K16/461Igs containing Ig-regions, -domains or -residues form different species
    • C07K16/464Igs containing CDR-residues from one specie grafted between FR-residues from another
    • CCHEMISTRY; METALLURGY
    • C07ORGANIC CHEMISTRY
    • C07KPEPTIDES
    • C07K16/00Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies
    • C07K16/44Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies against material not provided for elsewhere, e.g. haptens, metals, DNA, RNA, amino acids
    • CCHEMISTRY; METALLURGY
    • C07ORGANIC CHEMISTRY
    • C07KPEPTIDES
    • C07K2317/00Immunoglobulins specific features
    • C07K2317/50Immunoglobulins specific features characterized by immunoglobulin fragments
    • C07K2317/55Fab or Fab'
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
    • G06F19/3437Medical simulation or modelling, e.g. simulating the evolution of medical disorders
    • CCHEMISTRY; METALLURGY
    • C07ORGANIC CHEMISTRY
    • C07KPEPTIDES
    • C07K2317/00Immunoglobulins specific features
    • C07K2317/90Immunoglobulins specific features characterized by (pharmaco)kinetic aspects or by stability of the immunoglobulin

Similar Documents

Publication Publication Date Title
Adolf-Bryfogle et al. RosettaAntibodyDesign (RAbD): A general framework for computational antibody design
Baran et al. Principles for computational design of binding antibodies
US20220415436A1 (en) Computer assisted antibody re-epitoping
Shirai et al. Antibody informatics for drug discovery
Townsend et al. Augmented binary substitution: single-pass CDR germ-lining and stabilization of therapeutic antibodies
Steinbrecher et al. Free energy perturbation calculations of the thermodynamics of protein side-chain mutations
Kuroda et al. Antibody affinity maturation by computational design
Sulea et al. Assessment of solvated interaction energy function for ranking antibody–antigen binding affinities
Qu et al. Analysis of binding modes of antigen–antibody complexes by molecular mechanics calculation
Sevy et al. Antibodies: Computer‐aided prediction of structure and design of function
Bai et al. Accelerating antibody discovery and design with artificial intelligence: Recent advances and prospects
Licari et al. Embedding dynamics in intrinsic physicochemical profiles of market-stage antibody-based biotherapeutics
Mignon et al. Computational design of the Tiam1 PDZ domain and its ligand binding
Sefid et al. In silico engineering towards enhancement of bap–VHH monoclonal antibody binding affinity
US20160125124A1 (en) Obtaining an Improved Therapeutic Ligand
Dilsook ETD: In silico redesign and de novo design of anti-MUC1 monoclonal antibodies
Choong et al. Computer-aided antibody design: An overview
Faruk et al. Challenges and advantages of accounting for backbone flexibility in prediction of protein–protein complexes
Okazaki et al. Molecular dynamics-based design and biophysical evaluation of thermostable single-chain Fv antibody mutants derived from pharmaceutical antibodies
Opuni et al. In silico epitope mapping of glucose-6-phosphate isomerase: A Rheumatoid arthritis autoantigen
Kaur et al. Deciphering evolution of immune recognition in antibodies
WO2023078420A1 (en) Methods for antibody optimization
Schneider Deep learning algorithms for predicting association between antibody sequence, structure, and antibody properties
Ferraz et al. Design of nanobody targeting SARS-CoV-2 spike glycoprotein using CDR-grafting assisted by molecular simulation and machine learning
Rios Zertuche Establishment and Evaluation of a Computational Workflow for the Design and Optimization of Nanobodies