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相关概念视频

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...
4.2K
The Equilibrium Binding Constant and Binding Strength02:18

The Equilibrium Binding Constant and Binding Strength

12.8K
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:
12.8K
Mismatch Repair01:20

Mismatch Repair

4.8K
Organisms are capable of detecting and fixing nucleotide mismatches that occur during DNA replication. This sophisticated process requires identifying the new strand and replacing the erroneous bases with correct nucleotides. Mismatch repair is coordinated by many proteins in both prokaryotes and eukaryotes.
The Mutator Protein Family Plays a Key Role in DNA Mismatch Repair
The human genome has more than 3 billion base pairs of DNA per cell. Prior to cell division, that vast amount of genetic...
4.8K
Covalently Linked Protein Regulators02:04

Covalently Linked Protein Regulators

6.8K
Proteins can undergo many types of post-translational modifications, often in response to changes in their environment. These modifications play an important role in the function and stability of these proteins. Covalently linked molecules include functional groups, such as methyl, acetyl, and phosphate groups, and also small proteins, such as ubiquitin. There are around 200 different types of covalent regulators that have been identified.
These groups modify specific amino acids in a protein....
6.8K
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
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

4.8K
Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence...
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Updated: Jun 13, 2025

Implementation of In Vitro Drug Resistance Assays: Maximizing the Potential for Uncovering Clinically Relevant Resistance Mechanisms
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ProBASS-一种具有序列和结构特征的语言模型,用于预测突变对结合亲和力的影响.

Sagara N S Gurusinghe1, Yibing Wu2, William DeGrado2

  • 1Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel.

Bioinformatics (Oxford, England)
|May 9, 2025
PubMed
概括

我们开发了ProBASS,一种使用蛋白质语言模型 (PLM) 的新方法,以准确预测突变如何影响蛋白质结合亲和力 (ΔΔGbind),帮助蛋白质工程.

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科学领域:

  • 计算生物学 计算生物学
  • 生物信息学是一种生物信息学.
  • 结构生物学 结构生物学

背景情况:

  • 蛋白与蛋白相互作用 (PPI) 对细胞功能至关重要.
  • PPI中的突变可能导致疾病.
  • 预测结合亲和力变化 (ΔΔGbind) 的现有方法往往缺乏精度.
  • 蛋白质语言模型 (PLM) 是有前途的,但需要优化 ΔΔGbind 预测.

研究的目的:

  • 开发一个精确和广泛适用的模型来预测突变对蛋白质结合亲和力 (ΔΔGbind) 的影响.
  • 利用先进的蛋白质语言模型 (PLMs) 来提高 ΔΔGbind 预测的准确性.

主要方法:

  • 开发了ProBASS (基于结构和序列的蛋白质结合亲和) 方法.
  • 使用两个先进的PLM (ESM2,ESM-IF1) 进行序列和结构数据.
  • 为PPI突变物生成嵌入物,并根据实验 ΔΔGbind 数据对模型进行微调.

主要成果:

  • 在同一PPI上,ProBASS与实验 ΔΔGbind 值 (0.83±0.05对于单个突变,0.69±0.04对于双重突变) 实现了高相关性.
  • 在2325个单一突变的大数据集上,ProBASS达到了0.81±0.02.2的相关性.
  • 在 ΔΔGbind. 的预测准确性方面显著超过其他 PLM.

结论:

  • 将预先训练的PLM与广泛的ΔΔG绑定数据集完善,可以提高预测的准确性.
  • 普罗巴斯提供了一个精确且广泛适用的工具,用于预测突变对结合亲和力的影响.
  • 该模型促进了未来的蛋白质工程和设计研究,并且可以通过更多的数据进一步改进.