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相关概念视频

Proteomics01:33

Proteomics

7.3K
A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
7.3K
Protein Networks02:26

Protein Networks

4.0K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.0K
Protein-protein Interfaces02:04

Protein-protein Interfaces

12.5K
Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
12.5K

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相关实验视频

Updated: Jul 2, 2025

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web
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Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Published on: July 16, 2017

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发现和比较三维蛋白质模式的并行算法.

Alejandro Valdes-Jimenez, Miguel Reyes-Parada, Gabriel Nunez-Vivanco

    IEEE/ACM transactions on computational biology and bioinformatics
    |February 26, 2024
    PubMed
    概括
    此摘要是机器生成的。

    这项研究引入了Geomfinder算法的并行版本,以加快识别类似蛋白质结构的速度. 这些增强版本显著提高了药物设计和结构生物学研究的计算性能.

    更多相关视频

    A Protocol for Computer-Based Protein Structure and Function Prediction
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    A Protocol for Computer-Based Protein Structure and Function Prediction

    Published on: November 3, 2011

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    Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
    07:08

    Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

    Published on: July 14, 2015

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    相关实验视频

    Last Updated: Jul 2, 2025

    Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web
    09:51

    Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

    Published on: July 16, 2017

    15.4K
    A Protocol for Computer-Based Protein Structure and Function Prediction
    16:41

    A Protocol for Computer-Based Protein Structure and Function Prediction

    Published on: November 3, 2011

    68.7K
    Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
    07:08

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    科学领域:

    • 计算生物学是一种计算生物学.
    • 结构生物信息学 结构生物信息学
    • 药物发现 药物发现

    背景情况:

    • 识别保存的3D蛋白质模式有助于多药学药物设计.
    • 现有的工具具有局限性,只关注已知的结合点或图案.
    • 这些工具无法比较所有潜在的 Orthosteric 和 Allosteric 结合位点.

    研究的目的:

    • 为了提高Geomfinder算法的性能,进行大规模的蛋白质结构比较.
    • 为各种计算架构开发 Geomfinder 的并行版本.
    • 为了能够有效地识别所有潜在的绑定站点之间的结构相似性.

    主要方法:

    • 开发了Geomfinder算法的并行版本.
    • 为对称多处理 (SMP) 系统实施了优化.
    • 适应分布式内存系统,混合架构和基于GPU的系统的Geomfinder.

    主要成果:

    • 与原来的Geomfinder相比,实现了显著的性能改进.
    • 对于平均大小的蛋白质来说,已经证明了高达24.5倍的加速度.
    • 对于较大的蛋白质数据集,报告的加速度高达95.4倍.

    结论:

    • 平行化Geomfinder版本提供了相当大的计算收益.
    • 改进的算法克服了以前对大型蛋白质分析的性能限制.
    • 这一进步为合理的药物设计提供了更全面的结构比较.