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相关概念视频

The Significance of Membrane Transport01:44

The Significance of Membrane Transport

19.9K
The transport of solutes across the cell membrane is essential for metabolic processes, like maintaining cell size and volume, generating the action potential, exchanging nutrients and gases, etc. Membrane transport can be either passive or active. It can be simple diffusion, facilitated, or mediated transport aided by transport proteins such as transporters and channels.
Transporters facilitate either an active or passive movement of solutes. They can allow a single-molecule transport down its...
19.9K
Ligand Binding Sites02:40

Ligand Binding Sites

12.6K
Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...
12.6K
Primary Active Transport01:29

Primary Active Transport

9.4K
In contrast to passive transport, active transport involves a substance being moved through membranes in a direction against its concentration or electrochemical gradient. There are two types of active transport: primary active transport and secondary active transport. Primary active transport utilizes chemical energy from ATP to drive protein pumps embedded in the cell membrane. With energy from ATP, the pumps transport ions against their electrochemical gradients—a direction they would...
9.4K
Protein-protein Interfaces02:04

Protein-protein Interfaces

12.4K
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...
12.4K
Protein Networks02:26

Protein Networks

3.9K
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,...
3.9K
Membrane Transporters01:31

Membrane Transporters

9.9K
Transporters are essential membrane transport proteins with functions related to cell nutrition, homeostasis, communication, etc. Approximately 7% of all genes in the human genome code for transporters or transporter-related proteins.
Transporters are mainly composed of alpha-helices, built from bundles of ten or more helices traversing the plasma membrane. The solute-binding sites are located midway, where some of the helices are broken or distorted, making space for the binding site through...
9.9K

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Updated: May 9, 2025

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
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Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA

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DeepMolecules:一个用于预测酶和传送器-小分子相互作用的Web服务器.

Alexander Kroll1, Yvan Rousset1, Thomas Spitzlei1

  • 1Heinrich-Heine-University, Institute for Computer Science and Department of Biology, Universitätsstraße 1, 40225 Düsseldorf, Germany.

Nucleic acids research
|April 29, 2025
PubMed
概括

DeepMolecules使用先进的深度学习模型预测蛋白质-小分子相互作用. 这个网络服务器通过识别基质和预测酶动力学来帮助药物发现和生物催化剂优化.

科学领域:

  • 生物化学 生物化学
  • 计算生物学 计算生物学
  • 药物发现 药物发现 药物发现

背景情况:

  • 了解蛋白质和小分子相互作用对于各种生物过程和药物开发至关重要.
  • 精确预测酶动力学 (kcat,KM) 和基质识别对于优化生物催化剂和药物疗效至关重要.

研究的目的:

  • 开发并提供可访问的Web服务器DeepMolecules,用于预测蛋白质-小分子相互作用和酶动态参数.
  • 将多个最先进的预测模型集成到一个用户友好的平台中.

主要方法:

  • 利用深度学习对蛋白质和小分子的数值表示.
  • 采用渐变增强的决策树模型进行交互和动力预测.
  • 开发了一个支持各种输入格式 (SMILES,InChI,KEGG ID) 和提交类型 (单个,批量) 的Web界面.

主要成果:

  • 在酶基质识别,输送基质识别,酶周转数 (kcat) 和迈凯利斯常数 (KM) 中实现了高预测性能.
  • 综合实验数据,全面了解蛋白质和小分子之间的关系.

结论:

  • DeepMolecules为代谢工程,药物发现和生物催化剂研究人员提供了一个强大的,免费可访问的工具.

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  • 服务器有助于识别潜在的基板和量化它们的催化性能,加速研发.