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相关概念视频

Mismatch Repair01:20

Mismatch Repair

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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...
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Mutagenicity and Carcinogenicity01:25

Mutagenicity and Carcinogenicity

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Mutagenicity and carcinogenicity refer to the ability of drugs to cause genetic defects and induce cancer, respectively. The International Agency for Research on Cancer (IARC) classifies agents into four groups based on their carcinogenic potential. Group 1 agents are known human carcinogens; group 2A agents are probably carcinogenic to humans; group 3 agents lack data to support their role in carcinogenesis; and group 4 includes agents for which data support that they are not likely to be...
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Mutations in Microorganisms01:18

Mutations in Microorganisms

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Mutations are heritable changes in an organism’s genome involving alterations in the base sequence of DNA or RNA. These changes can influence cellular processes and phenotypic traits, potentially transforming the unaltered wild type into a mutant form. Such changes, termed forward mutations, are pivotal in shaping the genetic diversity of organisms.RNA viruses exhibit the highest mutation rates due to the absence of robust proofreading mechanisms during genome replication. In contrast,...
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Spontaneous and Induced Mutations01:30

Spontaneous and Induced Mutations

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Spontaneous mutations arise infrequently during DNA replication due to errors in the process. A key factor behind these errors is tautomeric shifts in nitrogenous bases, where bases transition from keto to enol forms or amino to imino forms. This shift can alter base-pairing rules, leading to mutations. Additionally, reactive oxygen species (ROS) arising from aerobic metabolism can damage DNA, resulting in depurination (loss of a purine base) or depyrimidination (loss of a pyrimidine base).
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In-vitro Mutagenesis01:16

In-vitro Mutagenesis

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To learn more about the function of a gene, researchers can observe what happens when the gene is inactivated or “knocked out,” by creating genetically engineered knockout animals. Knockout mice have been particularly useful as models for human diseases such as cancer, Parkinson’s disease, and diabetes.
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Genetic Screens02:46

Genetic Screens

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Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which...
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相关实验视频

Updated: Jan 9, 2026

Implementation of In Vitro Drug Resistance Assays: Maximizing the Potential for Uncovering Clinically Relevant Resistance Mechanisms
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对进化药物设计的基准测试分子突变运营者.

Raúl Acosta Murillo1, Patricio Adrián Zapata-Morin1, José Carlos Ortiz-Bayliss2

  • 1Department of Microbiology and Immunology, School of Biological Sciences, Universidad Autónoma de Nuevo León, Pedro de Alba SN, San Nicolás de los Garza 66455, Nuevo Leon, Mexico.

International journal of molecular sciences
|December 11, 2025
PubMed
概括

选择正确的分子突变策略是人工智能驱动药物设计的关键. 基于图形的遗传算法提供了高的有效性和效率,而其他算法则以不同的方式影响分子复杂性和生物活性.

关键词:
计算机辅助药物设计基因操作员是基因操作员.分子突变是分子突变.分子的重组组合.

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科学领域:

  • 计算化学是一种计算化学.
  • 生物信息学是一种生物信息学.
  • 药物发现 药物发现

背景情况:

  • 遗传算法是药物设计的强大工具.
  • 分子突变操作者对于探索化学空间至关重要.
  • 优化这些运营商可以提高人工智能驱动的药物发现效率.

研究的目的:

  • 为了比较药物设计中的遗传算法中的五种分子突变策略.
  • 评估它们的计算效率,分子有效性和对复杂性的影响.
  • 评估它们对生物活性和结构性保护的影响.

主要方法:

  • 评估了基于图形的遗传算法,基于图形的生成模型,SmilesClickChem,SELFIES令牌和SMILES令牌突变.
  • 评估计算效率,分子有效性,复杂性和结构保护.
  • 分析了pIC50强度和生物活性中的突变诱导的变化.

主要成果:

  • 基于图形的遗传算法显示出最高的分子有效性 (96.5%) 和效率.
  • SmilesClickChem和基于图形的生成模型增加了分子复杂性.
  • 自拍标记显著改变了生物活性,特别是针对SRC向的分子.

结论:

  • 选择突变策略会影响药物设计结果,平衡有效性,多样性和成本.
  • 基于图形的遗传算法适用于快速发现药物.
  • 这些发现指导了分子生成和候选物选择的进化算法的改进.