KR20260028069A - 메소 스케일 조작된 펩티드 및 선택 방법 - Google Patents

메소 스케일 조작된 펩티드 및 선택 방법

Info

Publication number
KR20260028069A
KR20260028069A KR1020267002109A KR20267002109A KR20260028069A KR 20260028069 A KR20260028069 A KR 20260028069A KR 1020267002109 A KR1020267002109 A KR 1020267002109A KR 20267002109 A KR20267002109 A KR 20267002109A KR 20260028069 A KR20260028069 A KR 20260028069A
Authority
KR
South Korea
Prior art keywords
constraints
ser
reference target
derived
prt
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
KR1020267002109A
Other languages
English (en)
Korean (ko)
Inventor
매튜 피. 그레빙
케빈 에두아드 하우저
앤드류 모린
조던 알. 윌리스
Original Assignee
루브릭 테라퓨틱스 인코포레이티드
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 루브릭 테라퓨틱스 인코포레이티드 filed Critical 루브릭 테라퓨틱스 인코포레이티드
Publication of KR20260028069A publication Critical patent/KR20260028069A/ko
Pending legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B40/00—ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
    • G16B40/20—Supervised data analysis
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
    • G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
    • G16C20/70—Machine learning, data mining or chemometrics
    • C—CHEMISTRY; METALLURGY
    • C07—ORGANIC CHEMISTRY
    • C07K—PEPTIDES
    • C07K1/00—General methods for the preparation of peptides, i.e. processes for the organic chemical preparation of peptides or proteins of any length
    • C—CHEMISTRY; METALLURGY
    • C07—ORGANIC CHEMISTRY
    • C07K—PEPTIDES
    • C07K1/00—General methods for the preparation of peptides, i.e. processes for the organic chemical preparation of peptides or proteins of any length
    • C07K1/10—General methods for the preparation of peptides, i.e. processes for the organic chemical preparation of peptides or proteins of any length using coupling agents
    • C—CHEMISTRY; METALLURGY
    • C07—ORGANIC CHEMISTRY
    • C07K—PEPTIDES
    • C07K14/00—Peptides having more than 20 amino acids; Gastrins; Somatostatins; Melanotropins; Derivatives thereof
    • C—CHEMISTRY; METALLURGY
    • C07—ORGANIC CHEMISTRY
    • C07K—PEPTIDES
    • C07K14/00—Peptides having more than 20 amino acids; Gastrins; Somatostatins; Melanotropins; Derivatives thereof
    • C07K14/001—Peptides having more than 20 amino acids; Gastrins; Somatostatins; Melanotropins; Derivatives thereof by chemical synthesis
    • C—CHEMISTRY; METALLURGY
    • C07—ORGANIC CHEMISTRY
    • C07K—PEPTIDES
    • C07K16/00—Immunoglobulins [IG], e.g. monoclonal or polyclonal antibodies
    • C07K16/18—Immunoglobulins [IG], e.g. monoclonal or polyclonal antibodies against material from animals or humans
    • C07K16/22—Immunoglobulins [IG], e.g. monoclonal or polyclonal antibodies against material from animals or humans against growth factors ; against growth regulators
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6803—General methods of protein analysis not limited to specific proteins or families of proteins
    • G01N33/6845—Methods of identifying protein-protein interactions in protein mixtures
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G06N20/10—Machine learning using kernel methods, e.g. support vector machines [SVM]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G06N20/20—Ensemble learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/044—Recurrent networks, e.g. Hopfield networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/0464—Convolutional networks [CNN, ConvNet]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/0475—Generative networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/09—Supervised learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computing arrangements using knowledge-based models
    • G06N5/01—Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computing arrangements using knowledge-based models
    • G06N5/04—Inference or reasoning models
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B15/00—ICT specially adapted for analysing two-dimensional [2D] or three-dimensional [3D] molecular structures, e.g. structural or functional relations or structure alignment
    • G16B15/20—Protein or domain folding
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B15/00—ICT specially adapted for analysing two-dimensional [2D] or three-dimensional [3D] molecular structures, e.g. structural or functional relations or structure alignment
    • G16B15/30—Drug targeting using structural data; Docking or binding prediction
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B30/00—ICT specially adapted for sequence analysis involving nucleotides or amino acids
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B5/00—ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B5/00—ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
    • G16B5/30—Dynamic-time models
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
    • G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
    • G16C20/80—Data visualisation
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
    • G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
    • G16C20/90—Programming languages; Computing architectures; Database systems; Data warehousing
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Landscapes

  • Engineering & Computer Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Chemical & Material Sciences (AREA)
  • Molecular Biology (AREA)
  • Software Systems (AREA)
  • General Health & Medical Sciences (AREA)
  • Biophysics (AREA)
  • Data Mining & Analysis (AREA)
  • Evolutionary Computation (AREA)
  • Artificial Intelligence (AREA)
  • General Physics & Mathematics (AREA)
  • Medical Informatics (AREA)
  • Computing Systems (AREA)
  • Mathematical Physics (AREA)
  • General Engineering & Computer Science (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Biotechnology (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Biomedical Technology (AREA)
  • Computational Linguistics (AREA)
  • Organic Chemistry (AREA)
  • Evolutionary Biology (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Medicinal Chemistry (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • Biochemistry (AREA)
  • Genetics & Genomics (AREA)
  • Immunology (AREA)
  • Hematology (AREA)
  • Urology & Nephrology (AREA)
  • Physiology (AREA)
  • Gastroenterology & Hepatology (AREA)
  • Analytical Chemistry (AREA)
  • Databases & Information Systems (AREA)
  • Epidemiology (AREA)
  • Public Health (AREA)
KR1020267002109A 2019-05-31 2020-05-13 메소 스케일 조작된 펩티드 및 선택 방법 Pending KR20260028069A (ko)

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
US201962855767P 2019-05-31 2019-05-31
US62/855,767 2019-05-31
KR1020217043265A KR20220041784A (ko) 2019-05-31 2020-05-13 메소 스케일 조작된 펩티드 및 선택 방법
PCT/US2020/032715 WO2020242765A1 (en) 2019-05-31 2020-05-13 Meso-scale engineered peptides and methods of selecting

Related Parent Applications (1)

Application Number Title Priority Date Filing Date
KR1020217043265A Division KR20220041784A (ko) 2019-05-31 2020-05-13 메소 스케일 조작된 펩티드 및 선택 방법

Publications (1)

Publication Number Publication Date
KR20260028069A true KR20260028069A (ko) 2026-03-03

Family

ID=73553528

Family Applications (3)

Application Number Title Priority Date Filing Date
KR1020267002109A Pending KR20260028069A (ko) 2019-05-31 2020-05-13 메소 스케일 조작된 펩티드 및 선택 방법
KR1020217043265A Ceased KR20220041784A (ko) 2019-05-31 2020-05-13 메소 스케일 조작된 펩티드 및 선택 방법
KR1020217043264A Pending KR20220039659A (ko) 2019-05-31 2020-05-13 메소 스케일 펩티드를 조작하기 위한 머신 러닝 기반 장치 및 이를 위한 방법 및 시스템

Family Applications After (2)

Application Number Title Priority Date Filing Date
KR1020217043265A Ceased KR20220041784A (ko) 2019-05-31 2020-05-13 메소 스케일 조작된 펩티드 및 선택 방법
KR1020217043264A Pending KR20220039659A (ko) 2019-05-31 2020-05-13 메소 스케일 펩티드를 조작하기 위한 머신 러닝 기반 장치 및 이를 위한 방법 및 시스템

Country Status (7)

Country Link
US (3) US11545238B2 (https=)
EP (2) EP3977117A4 (https=)
JP (4) JP7579812B2 (https=)
KR (3) KR20260028069A (https=)
CN (2) CN114585918A (https=)
CA (2) CA3142339A1 (https=)
WO (2) WO2020242765A1 (https=)

Families Citing this family (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3880698A4 (en) 2018-11-14 2022-11-30 RubrYc Therapeutics, Inc. MANIPULATED CD25 POLYPEPTIDES AND USES THEREOF
WO2022243940A1 (en) * 2021-05-21 2022-11-24 Peptone, Ltd. Spacio-temporal determination of polypeptide structure
CN114065620B (zh) * 2021-11-11 2022-06-03 四川大学 基于像素图表征和cnn的可解释性分子动力学轨迹分析方法
US20250299780A1 (en) * 2022-05-06 2025-09-25 Dyno Therapeutics, Inc. System and methods for predicting features of biological sequences
CN115512763B (zh) * 2022-09-06 2023-10-24 北京百度网讯科技有限公司 多肽序列的生成方法、多肽生成模型的训练方法和装置
CN116343922B (zh) * 2022-12-31 2026-01-09 浙江大学杭州国际科创中心 一种基于机器学习对多肽进行预测的方法
CN115881220B (zh) * 2023-02-15 2023-06-06 北京深势科技有限公司 一种抗体结构预测的处理方法和装置
US12587274B2 (en) 2023-03-28 2026-03-24 Quantum Generative Materials Llc Satellite optimization management system based on natural language input and artificial intelligence
CN116467894B (zh) * 2023-05-16 2024-08-20 郑州大学 一种基于机器学习分子动力学的辐照损伤仿真系统及方法
TWI860054B (zh) * 2023-08-22 2024-10-21 國立清華大學 訓練機器學習模型的方法、裝置和電腦程式產品
CN116913395B (zh) * 2023-09-13 2023-11-28 青岛虹竹生物科技有限公司 一种构建小分子肽数据库的数字化方法
WO2025057424A1 (ja) * 2023-09-15 2025-03-20 富士通株式会社 情報処理プログラム，情報処理装置および情報処理方法
US12603701B2 (en) 2023-12-27 2026-04-14 Quantum Generative Materials Llc Distributed satellite constellation management and control system
US12368503B2 (en) 2023-12-27 2025-07-22 Quantum Generative Materials Llc Intent-based satellite transmit management based on preexisting historical location and machine learning

Family Cites Families (21)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
AUPP660698A0 (en) * 1998-10-21 1998-11-12 University Of Queensland, The A method of protein engineering
JP2002536301A (ja) 1999-01-27 2002-10-29 ザ スクリプス リサーチ インスティテュート タンパク質モデリングツール
IL147031A0 (en) * 1999-08-02 2002-08-14 Synt Em Sa Computational design methods for making molecular mimetics
ATE385811T1 (de) * 2000-12-19 2008-03-15 Palatin Technologies Inc Identifizierung zielgerichteter faltungsstellen in peptiden und proteinen
EP1503321A3 (en) * 2001-08-10 2006-08-30 Xencor, Inc. Protein design automation for protein libraries
US20060020396A1 (en) * 2002-09-09 2006-01-26 Rene Gantier Rational directed protein evolution using two-dimensional rational mutagenesis scanning
US20070192033A1 (en) 2006-02-16 2007-08-16 Microsoft Corporation Molecular interaction predictors
US8050870B2 (en) 2007-01-12 2011-11-01 Microsoft Corporation Identifying associations using graphical models
US8374828B1 (en) * 2007-12-24 2013-02-12 The University Of North Carolina At Charlotte Computer implemented system for protein and drug target design utilizing quantified stability and flexibility relationships to control function
JP2010113473A (ja) 2008-11-05 2010-05-20 Saitama Univ ペプチドとタンパク質の結合部位を予測する方法、装置、およびプログラム
JP2013541528A (ja) * 2010-09-21 2013-11-14 マサチューセッツ インスティテュート オブ テクノロジー ヒト適応ｈａポリペプチド、ワクチン、およびインフルエンザの処置
US20130090265A1 (en) 2011-10-11 2013-04-11 Biolauncher Ltd. Systems and methods for generation of context-specific, molecular field-based amino acid substitution matrices
US10431325B2 (en) 2012-08-03 2019-10-01 Novartis Ag Methods to identify amino acid residues involved in macromolecular binding and uses therefor
EP3417874B1 (en) * 2012-11-28 2024-09-11 BioNTech SE Individualized vaccines for cancer
US10665324B2 (en) * 2014-07-07 2020-05-26 Yeda Research And Development Co. Ltd. Method of computational protein design
RS61907B1 (sr) * 2015-04-06 2021-06-30 Subdomain Llc Polipeptidi koji sadrže de novo vezujući domen i njihova primena
US20180068054A1 (en) * 2016-09-06 2018-03-08 University Of Washington Hyperstable Constrained Peptides and Their Design
WO2018132752A1 (en) 2017-01-13 2018-07-19 Massachusetts Institute Of Technology Machine learning based antibody design
WO2018201020A1 (en) * 2017-04-28 2018-11-01 University Of Washington Folded and protease-resistant polypeptides
EP3880698A4 (en) * 2018-11-14 2022-11-30 RubrYc Therapeutics, Inc. MANIPULATED CD25 POLYPEPTIDES AND USES THEREOF
KR20240091046A (ko) 2018-12-21 2024-06-21 바이오엔테크 유에스 인크. Hla 클래스 ii-특이적 에피토프 예측 및 cd4+ t 세포 특징화를 위한 방법 및 시스템

Also Published As

Publication number Publication date
CN114585918A (zh) 2022-06-03
US20230095685A1 (en) 2023-03-30
WO2020242765A1 (en) 2020-12-03
JP2025118804A (ja) 2025-08-13
KR20220039659A (ko) 2022-03-29
CN114401734A (zh) 2022-04-26
JP2022535769A (ja) 2022-08-10
US20210166788A1 (en) 2021-06-03
JP7579812B2 (ja) 2024-11-08
US11545238B2 (en) 2023-01-03
CA3142227A1 (en) 2020-12-03
JP2022535511A (ja) 2022-08-09
KR20220041784A (ko) 2022-04-01
CN114401734B (zh) 2025-06-03
JP2025016594A (ja) 2025-02-04
EP3976083A4 (en) 2023-07-12
EP3977117A4 (en) 2023-08-16
EP3977117A1 (en) 2022-04-06
US20220081472A1 (en) 2022-03-17
CA3142339A1 (en) 2020-12-03
WO2020242766A1 (en) 2020-12-03
EP3976083A1 (en) 2022-04-06

Similar Documents

Publication Publication Date Title
KR20260028069A (ko) 메소 스케일 조작된 펩티드 및 선택 방법
AU2022202958B2 (en) Generation of protein sequences using machine learning techniques
JP7695881B2 (ja) 操作されたｃｄ２５ポリペプチドおよびその使用
Steichen et al. A generalized HIV vaccine design strategy for priming of broadly neutralizing antibody responses
JP6889328B2 (ja) 三次元構造に基づくヒト化方法
Chen et al. Synthetic antibodies and peptides recognizing progressive multifocal leukoencephalopathy-specific point mutations in polyomavirus JC capsid viral protein 1
Youkharibache Protodomains: symmetry-related supersecondary structures in proteins and self-complementarity
Zhang et al. Computational identification of epitopes in the glycoproteins of novel bunyavirus (SFTS virus) recognized by a human monoclonal antibody (MAb 4-5)
US20060263787A1 (en) Immunoglobulin-like variable chain binding polypeptides and methods of use
Kabir et al. Antigen Binding Reshapes Antibody Energy Landscape and Conformation Dynamics
HK40063514A (en) Engineered cd25 polypeptides and uses thereof
JP2022516445A (ja) エピトープおよびパラトープを同定する方法
Motmaen Structure-Based Prediction and Design of Adaptive Immune Receptors Targeting Peptide–MHC Complexes
Motmaen Deep Learning Methods for Structure Prediction and De Novo Design of T and B Cell Receptors Targeting Peptide-MHC Neoantigens
WO2026037609A1 (en) The generative design of peptide mhc (pmhc) binders
Leem Development of computational methodologies for antibody design
HK40070051A (en) Generation of protein sequences using machine learning techniques
HK40070051B (en) Generation of protein sequences using machine learning techniques
HK40063170A (en) Methods for identifying epitopes and paratopes
HK40023878B (zh) 基於三维结构的人源化方法

Legal Events

Date Code Title Description
A16 Divisional, continuation or continuation in part application filed

Free format text: ST27 STATUS EVENT CODE: A-0-1-A10-A16-DIV-PA0104 (AS PROVIDED BY THE NATIONAL OFFICE)

PA0104 Divisional application for international application

St.27 status event code: A-0-1-A10-A16-div-PA0104

PG1501 Laying open of application

St.27 status event code: A-1-1-Q10-Q12-nap-PG1501

Q12 Application published

Free format text: ST27 STATUS EVENT CODE: A-1-1-Q10-Q12-NAP-PG1501 (AS PROVIDED BY THE NATIONAL OFFICE)