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相关概念视频

Protein Families02:47

Protein Families

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Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism.   Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members.   If these new proteins contain similar amino acids in key...
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Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

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Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...
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Signal Sequences and Sorting Receptors01:41

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Signal sequences are short amino acid sequences that guide newly synthesized proteins to their proper location within the cell. Classical signal sequences are fifteen to sixty amino acids long and present at the N-terminus of a polypeptide chain. Each signal sequence has a conserved segment of basic residues towards their N terminus, a hydrophobic core, and a C-terminus rich in polar residues. The C-terminus also contains a signal cleavage site and features a -3 -1 sequence motif. The -3-1...
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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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An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
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Proteins are polymers of amino acids linked together by peptide bonds. Proteins and polypeptides are interchangeably used to refer to long chains of amino acids. However, polypeptides have a molecular weight of fewer than 10,000 daltons, while proteins have greater molecular weight.  Polypeptides with less than 20 amino acids are called oligopeptides or simply peptides. Interactions among the constituent amino acid side chains of proteins help them fold into a stable 3-dimensional...
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三重EP-CPP:用于预测序列属性的算法.

Maria Serebrennikova1,2, Ekaterina Grafskaia1, Dmitriy Maltsev3,4,5

  • 1Laboratory of Genetic Engineering, Lopukhin Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, Moscow 119435, Russia.

International journal of molecular sciences
|July 13, 2024
PubMed
概括

机器学习加速了用于药物输送的细胞透 (CPPs) 的发现. 这项研究发现了一种来自水母毒的新型低毒性CPP,增强了针对性的治疗应用.

关键词:
细胞透 (CPP) 是一种细胞透.功能性活动预测预测.细胞内输送是细胞内输送.机器学习是机器学习.蛋白质-脂质相互作用它具有结构动态特性,具有结构动态特性.

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科学领域:

  • 生物化学 生物化学
  • 药理学 药理学是指药理学的学科.
  • 生物信息学是一种生物信息学.

背景情况:

  • 药物输送系统旨在增加细胞内药物度,以提高疗效和降低毒性.
  • 细胞透 (CPP) 是促进分子进入细胞的有前途的工具.
  • 传统的CPP开发方法耗时且昂贵.

研究的目的:

  • 开发一种基于机器学习的预测算法,用于识别新的CPP序列.
  • 选潜在的CPP细胞毒性和细胞透能力.
  • 从自然来源发现新的CPP,特别是Rhilema esculentum毒素蛋白质.

主要方法:

  • 利用机器学习模型,包括k-最近邻居,梯度增强和随机森林算法.
  • 使用分子描述器来训练用于CPP序列识别的预测算法.
  • 对预测的CPP进行实验验证,评估细胞毒性和细胞透.

主要成果:

  • 成功创建了一个用于新型CPP识别的预测算法.
  • 确定并评估了几位潜在的CPP候选人.
  • 从Rhilema esculentum毒素蛋白中发现了一种新型的低毒性CPP.

结论:

  • 机器学习显著提高了效率,并降低了发现新CPP的成本.
  • 从水母毒中发现的CPP表明了安全有效的细胞内药物输送的潜力.
  • 这种方法为加速开发向治疗剂铺平了道路.