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相关概念视频

Structure-Activity Relationships and Drug Design01:28

Structure-Activity Relationships and Drug Design

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Drug design is a dynamic field that involves discovering and developing new medications based on specific biological targets. This process heavily relies on structure-activity relationships (SAR) and quantitative structure-activity relationships (QSAR) to guide the design and optimization of efficient drugs.
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence...
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Drug Discovery: Overview01:26

Drug Discovery: Overview

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Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...
7.9K
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
Ligand Binding Sites02:40

Ligand Binding Sites

12.8K
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...
12.8K
Small GTPases - Ras and Rho01:24

Small GTPases - Ras and Rho

3.9K
Ras and Rho are small monomeric GTPases that act downstream of receptor tyrosine kinase (RTK) and regulate various cellular processes. These GTPases switch between active and inactive states by binding to guanine nucleotides.
Three regulatory proteins control their activity:
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Conserved Binding Sites01:49

Conserved Binding Sites

4.2K
Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...
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相关实验视频

Updated: Jun 29, 2025

Development of Inhibitors of Protein-protein Interactions through REPLACE: Application to the Design and Development Non-ATP Competitive CDK Inhibitors
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关于使用DOCK用于KRAS的基于结构的药物发现的考虑.

Mayukh Chakrabarti1, Y Stanley Tan1, Trent E Balius2

  • 1NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, MD, USA.

Methods in molecular biology (Clifton, N.J.)
|April 3, 2024
PubMed
概括

本章详细介绍了使用UCSF DOCK进行分子对接的最佳实践,重点是优化用于针对KRAS蛋白的药物发现的虚拟选.

关键词:
计算机化药物发现.码头的码头是什么意思药物可的口袋 可以的口袋分子对接是分子对接.虚拟选是一个虚拟的选.

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Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
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科学领域:

  • 计算化学是一种计算化学.
  • 药物发现 药物发现
  • 结构生物学是结构生物学.

背景情况:

  • 分子对接是药物发现的关键计算方法.
  • 它预测小分子如何与蛋白质标结合.
  • 虚拟选利用对接来识别潜在的药物配体.

研究的目的:

  • 为使用UCSF DOCK.提供分子对接的最佳实践.
  • 用KRAS蛋白作为模型系统来说明这些方法.
  • 为了指导虚拟选协议的优化.

主要方法:

  • 详细讨论了分子对接的六个关键优化点.
  • 蛋白质结构的选择和活性部位 (口袋) 的识别.
  • 评分函数的改进,采样范围/程序的调整,化学空间的选择,以及击中优先级.

主要成果:

  • 本章介绍了一个全面的指南,以优化分子对接设置.
  • 它强调了有效的虚拟选的战略选择.
  • 针对KRAS蛋白质对接的具体考虑是突出显示的.

结论:

  • 坚持这些最佳实践可以提高分子对接的效率和准确性.
  • 优化的对接协议对于成功的虚拟选和连接体发现至关重要.
  • 这种方法有助于识别有前途的候选药物,例如KRAS.