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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...
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Ligand Binding Sites02:40

Ligand Binding Sites

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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...
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Conserved Binding Sites01:49

Conserved Binding Sites

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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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Protein Organization01:24

Protein Organization

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Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
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Protein-protein Interfaces

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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...
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相关实验视频

Updated: Jul 4, 2025

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

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使用预测模型实现基于结构的药物发现

Edward B Miller1, Howook Hwang1, Mee Shelley2

  • 1Schrödinger New York, 1540 Broadway, 24th Floor, New York, NY 10036, USA.

Cell
|February 2, 2024
PubMed
概括
此摘要是机器生成的。

高质量的预测蛋白质结构,与自由能量扰动 (FEP) 计算相结合,可以可靠地指导药物设计. 这种方法使用基于结构的hERG抑制模型来证明药物发现.

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相关实验视频

Last Updated: Jul 4, 2025

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A Protocol for Computer-Based Protein Structure and Function Prediction

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科学领域:

  • 计算化学
  • 结构生物学
  • 药物发现

背景情况:

  • 精确的蛋白质结构对于基于结构的药物设计至关重要.
  • 现有方法在可靠利用预测结构方面面临挑战.

研究的目的:

  • 用预测的蛋白质结构来证明自由能量扰动 (FEP) 的实用性.
  • 通过计算建模验证FEP在实现药物设计目标方面的能力.

主要方法:

  • 使用预测的蛋白质结构作为分子建模的输入.
  • 应用自由能量扰动 (FEP) 计算以评估结合亲和力.
  • 专注于基于结构的hERG通道抑制模型.

主要成果:

  • 高质量的预测结构可以在药物设计中使用FEP.
  • FEP成功引导了基于结构的hERG抑制模型.
  • 在药物发现计划中展示了FEP的价值.

结论:

  • 自由能量扰动 (FEP) 提高了药物发现中预测结构的价值.
  • 基于结构的建模与FEP相结合,为实现药物设计目标提供了可靠的方法.
  • 这种方法支持在药物研究中扩大计算方法的使用.