CN114585918A - 中尺度工程化肽和选择方法 - Google Patents

中尺度工程化肽和选择方法 Download PDF

Info

Publication number
CN114585918A
CN114585918A CN202080050892.XA CN202080050892A CN114585918A CN 114585918 A CN114585918 A CN 114585918A CN 202080050892 A CN202080050892 A CN 202080050892A CN 114585918 A CN114585918 A CN 114585918A
Authority
CN
China
Prior art keywords
constraints
derived
reference target
engineered peptide
peptide
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
CN202080050892.XA
Other languages
English (en)
Chinese (zh)
Inventor
M·P·格雷文
K·E·豪瑟
A·莫里
J·R·威利斯
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Yibio Co
Original Assignee
Rubik Therapy Co ltd
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 Rubik Therapy Co ltd filed Critical Rubik Therapy Co ltd
Publication of CN114585918A publication Critical patent/CN114585918A/zh
Pending legal-status Critical Current

Links

Images

Classifications

    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B40/00ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
    • G16B40/20Supervised data analysis
    • CCHEMISTRY; METALLURGY
    • C07ORGANIC CHEMISTRY
    • C07KPEPTIDES
    • C07K1/00General methods for the preparation of peptides, i.e. processes for the organic chemical preparation of peptides or proteins of any length
    • C07K1/10General methods for the preparation of peptides, i.e. processes for the organic chemical preparation of peptides or proteins of any length using coupling agents
    • CCHEMISTRY; METALLURGY
    • C07ORGANIC CHEMISTRY
    • C07KPEPTIDES
    • C07K14/00Peptides having more than 20 amino acids; Gastrins; Somatostatins; Melanotropins; Derivatives thereof
    • CCHEMISTRY; METALLURGY
    • C07ORGANIC CHEMISTRY
    • C07KPEPTIDES
    • C07K14/00Peptides having more than 20 amino acids; Gastrins; Somatostatins; Melanotropins; Derivatives thereof
    • C07K14/001Peptides having more than 20 amino acids; Gastrins; Somatostatins; Melanotropins; Derivatives thereof by chemical synthesis
    • 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 groups G01N1/00 - G01N31/00
    • G01N33/48Biological 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
    • G01N33/6803General methods of protein analysis not limited to specific proteins or families of proteins
    • G01N33/6845Methods of identifying protein-protein interactions in protein mixtures
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00Machine learning
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00Machine learning
    • G06N20/10Machine learning using kernel methods, e.g. support vector machines [SVM]
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00Machine learning
    • G06N20/20Ensemble learning
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/04Architecture, e.g. interconnection topology
    • G06N3/0464Convolutional networks [CNN, ConvNet]
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/04Architecture, e.g. interconnection topology
    • G06N3/0475Generative networks
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/08Learning methods
    • G06N3/09Supervised learning
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computing arrangements using knowledge-based models
    • G06N5/01Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computing arrangements using knowledge-based models
    • G06N5/04Inference or reasoning models
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B15/00ICT specially adapted for analysing two-dimensional [2D] or three-dimensional [3D] molecular structures, e.g. structural or functional relations or structure alignment
    • G16B15/20Protein or domain folding
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B5/00ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B5/00ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
    • G16B5/30Dynamic-time models
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/04Architecture, e.g. interconnection topology
    • G06N3/044Recurrent networks, e.g. Hopfield networks
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/04Architecture, e.g. interconnection topology
    • G06N3/045Combinations of networks
    • YGENERAL 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
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02ATECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/10Information 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)
CN202080050892.XA 2019-05-31 2020-05-13 中尺度工程化肽和选择方法 Pending CN114585918A (zh)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US201962855767P 2019-05-31 2019-05-31
US62/855,767 2019-05-31
PCT/US2020/032715 WO2020242765A1 (en) 2019-05-31 2020-05-13 Meso-scale engineered peptides and methods of selecting

Publications (1)

Publication Number Publication Date
CN114585918A true CN114585918A (zh) 2022-06-03

Family

ID=73553528

Family Applications (2)

Application Number Title Priority Date Filing Date
CN202080050892.XA Pending CN114585918A (zh) 2019-05-31 2020-05-13 中尺度工程化肽和选择方法
CN202080050301.9A Active CN114401734B (zh) 2019-05-31 2020-05-13 用于工程化中尺度肽的基于机器学习的设备及其方法和系统

Family Applications After (1)

Application Number Title Priority Date Filing Date
CN202080050301.9A Active CN114401734B (zh) 2019-05-31 2020-05-13 用于工程化中尺度肽的基于机器学习的设备及其方法和系统

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

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1206494B1 (en) * 1999-08-02 2004-11-03 Synt:Em S.A. Computational design methods for making molecular mimetics
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
CN113646330A (zh) * 2018-11-14 2021-11-12 鲁比克治疗股份有限公司 工程化cd25多肽及其用途

Family Cites Families (18)

* 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
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
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
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

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1206494B1 (en) * 1999-08-02 2004-11-03 Synt:Em S.A. Computational design methods for making molecular mimetics
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
CN113646330A (zh) * 2018-11-14 2021-11-12 鲁比克治疗股份有限公司 工程化cd25多肽及其用途

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
YI LIU等: "RosettaDesign server for protein design", 《NUCLEIC ACIDS RESEARCH》, vol. 34, 31 December 2006 (2006-12-31), pages 235 *

Also Published As

Publication number Publication date
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
KR20260028069A (ko) 2026-03-03
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
CN114585918A (zh) 中尺度工程化肽和选择方法
Adolf-Bryfogle et al. RosettaAntibodyDesign (RAbD): A general framework for computational antibody design
CN116434844A (zh) 用于生成蛋白质的氨基酸序列的方法和系统
JP2025026923A (ja) 操作されたcd25ポリペプチドおよびその使用
JP2022535511A5 (https=)
US11749377B2 (en) Method and electronic system for predicting at least one fitness value of a protein, related computer program product
CN115094523A (zh) 用于治疗性抗体表征的基于阵列的肽文库
Vögele et al. Is the functional response of a receptor determined by the thermodynamics of ligand binding?
Goverde et al. Computational design of soluble analogues of integral membrane protein structures
Li et al. RareFold: Structure prediction and design of proteins with noncanonical amino acids
Wang et al. A generative foundation model for antibody design
Wu et al. De novo design of epitope-specific antibodies via a structure-driven computational workflow
WO2023220758A2 (en) Systems and methods for protein design using deep generative modeling
Kabir et al. Antigen Binding Reshapes Antibody Energy Landscape and Conformation Dynamics
Ali et al. Disulphide and sequence-encoded conformational priors guide nanobody structure prediction
JP7611464B1 (ja) 情報処理システム、情報処理方法、情報処理プログラム、および分子化合物の製造方法
Vlachakis Antibody Clustering and 3D Modeling for Neurodegenerative Diseases
Adler et al. Conformational Rank Conditioned Committees for Machine Learning-Assisted Directed Evolution
HK40063514A (en) Engineered cd25 polypeptides and uses thereof
CN113874395A (zh) 鉴定表位和互补位的方法
Zhang AlphaFold Beyond Folding: Protein Property Prediction and Drug Discovery
Sang AI-Guided Computational Tools for Nanobody Discovery and Bioengineering
Li et al. AI-Driven De Novo Binder Design: From Structure Prediction to Closed-Loop Optimization
Team et al. Latent-Y: A Lab-Validated Autonomous Agent for De Novo Drug Design
Leem Development of computational methodologies for antibody design

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
TA01 Transfer of patent application right

Effective date of registration: 20230217

Address after: Texas, USA

Applicant after: Yibio Co.

Address before: California, USA

Applicant before: Rubik therapy Co.,Ltd.

TA01 Transfer of patent application right