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T33-ml35 - Designed Tetrahedral Protein Cage Using Machine Learning Algorithms

NIAID Data Ecosystem2026-05-02 收录

蛋白质笼设计

机器学习蛋白质设计

数据链接：

https://www.rcsb.org/structure/8UMP 数据链接链接失效反馈

官方服务：

资源简介：

T33-ml35 - Designed Tetrahedral Protein Cage Using Machine Learning Algorithms

应用场景：

创建时间：

2024-06-19

定向进化

机器学习蛋白质设计

Machine learning (ML) is becoming an attractive tool in mutagenesis-based protein engineering because of its ability to design a variant library containing proteins with a desired function. However, i

Figshare2021-11-19 更新20

T33-ml23 - Designed Tetrahedral Protein Cage Using Machine Learning Algorithms

蛋白质笼设计

计算生物学

T33-ml23 - Designed Tetrahedral Protein Cage Using Machine Learning Algorithms

NIAID Data Ecosystem00

T33-ml28 - Designed Tetrahedral Protein Cage Using Machine Learning Algorithms

蛋白质笼设计

机器学习辅助蛋白质设计

T33-ml28 - Designed Tetrahedral Protein Cage Using Machine Learning Algorithms Descriptor: T33-ml28-redesigned-CutA-fold, T33-ml28-redesigned-tandem-BMC-T-fold Authors: Castells-Graells, R, Meador, K,

Protein Data Bank Japan2024-06-19 更新00

Bimetallic dodecameric cage design 2 (BMC2) from cytochrome cb562

蛋白质笼设计

金属蛋白工程

Bimetallic dodecameric cage design 2 (BMC2) from cytochrome cb562

NIAID Data Ecosystem20

Structure of a 16 nm protein cage designed by fusing symmetric oligomeric domains, quadruple mutant, I222 form

蛋白质笼设计

结构生物学

Structure of a 16 nm protein cage designed by fusing symmetric oligomeric domains, quadruple mutant, I222 form

NIAID Data Ecosystem00