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相关概念视频

Noncovalent Attractions in Biomolecules02:35

Noncovalent Attractions in Biomolecules

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Noncovalent attractions are associations within and between molecules that influence the shape and structural stability of complexes. These interactions differ from covalent bonding in that they do not involve sharing of electrons.
Four types of noncovalent interactions are hydrogen bonds, van der Waals forces, ionic bonds, and hydrophobic interactions.
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The equilibrium binding constant (Kb) quantifies the strength of a protein-ligand interaction. Kb can be calculated as follows when the reaction is at equilibrium:
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Bond energy is the energy required to break a bond homolytically. These values are usually expressed in units of kcal/mol or kJ/mol and are referred to as bond dissociation energies when given for specific bonds or average bond energies when indicated for a given type of bond over many compounds. Firstly, the bond dissociation energy for a single bond is weaker than that of a double bond, which in turn is weaker than that of a triple bond. Secondly, hydrogen forms relatively strong bonds with...
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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.
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一个相对有约束力的自由能量框架,用于结构不同分子.

Hsu-Chun Tsai1, Shi Zhang2, Tai-Sung Lee2

  • 1TandemAI, New York, New York 10036, United States.

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此摘要是机器生成的。

核心跳转结合自由能量 (CBFE) 计算提供了一种有效的方法来预测药物的效力. 这种新方法准确地确定了具有多种结构的分子的相对结合自由能量,提高了药物发现效率.

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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
  • 分子建模分子建模

背景情况:

  • 相对结合自由能量 (RBFE) 的计算对于药物发现至关重要,但仅限于具有相似结构的分子.
  • 传统的RBFE方法与缺乏共同核心或结合模式的多种小分子作斗争.
  • 绝对结合的自由能量 (ABFE) 方法可以处理各种分子,但在计算上昂贵,并缓慢地融合.

研究的目的:

  • 引入一个计算效率高的框架,核心跳跃绑定自由能量 (CBFE) 计算,用于确定相对绑定自由能量.
  • 为了能够准确地预测具有不同核心和结合模式的小分子,克服传统RBFE的局限性.
  • 提供一个实用的工具,以挑战涉及各种化学结构的药物发现活动.

主要方法:

  • 开发了一个新的CBFE框架,利用化学增强采样 (ACES) 优化转换路径和灵活的λ间隔.
  • 嵌入了依赖于 λ 的博雷什限制装置,以提高采样和准确性.
  • 在使用GPU加速AMBER (pmemd.cuda) 的56个小分子的4个蛋白质系统中实施和基准CBFE.

主要成果:

  • CBFE结果显示与RBFE对同源配体的一致性.
  • 与ABFE相比,CBFE在各种小分子的计算成本和精度上提供了显著的改进.
  • 该方法在确定不同分子支架和结合模式的相对结合自由能量方面表现出精度和效率.

结论:

  • CBFE计算提供了一种准确且计算效率高的方法,用于确定具有不同核心的小分子之间的相对结合自由能量.
  • 这种方法扩大了结合性自由能量计算的适用性,使其在药物发现中适用于更广泛的分子.
  • 该CBFE框架在AMBER中完全实现,使其易于研究人员使用.