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相关概念视频

Diffusion01:12

Diffusion

202.1K
Diffusion is the passive movement of substances down their concentration gradients—requiring no expenditure of cellular energy. Substances, such as molecules or ions, diffuse from an area of high concentration to an area of low concentration in the cytosol or across membranes. Eventually, the concentration will even out, with the substance moving randomly but causing no net change in concentration. Such a state is called dynamic equilibrium, which is essential for maintaining overall...
202.1K
Passive Diffusion: Overview and Kinetics01:17

Passive Diffusion: Overview and Kinetics

785
Passive diffusion is a critical process that allows small lipophilic drugs to cross the cell membrane along a concentration gradient. This mechanism's efficiency depends on four primary factors: the membrane's surface area, the drug's lipid-water partition coefficient, the concentration gradient, and the membrane's thickness.
When administered orally, drugs establish a substantial concentration gradient between the gastrointestinal (GI) lumen and the bloodstream, expediting...
785

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Correction to "AstraMEV (AI-Guided Structural Assembly of Multi-Epitope Vaccines) Against Infectious Bronchitis Virus".

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MolPy: A Large Language Model-Friendly Toolkit for Reactive Topology Editing in Polymer Simulations.

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相关实验视频

Updated: Sep 19, 2025

Generation of Heterogeneous Drug Gradients Across Cancer Populations on a Microfluidic Evolution Accelerator for Real-Time Observation
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Generation of Heterogeneous Drug Gradients Across Cancer Populations on a Microfluidic Evolution Accelerator for Real-Time Observation

Published on: September 19, 2019

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均衡差异:为高质量分子生成提供平衡扩散网络.

Yulong Wu1, Jin Xie1, Jing Nie2,3

  • 1School of Big Data and Software Engineering, Chongqing University, Chongqing 400044, China.

Journal of chemical information and modeling
|June 18, 2025
PubMed
概括
此摘要是机器生成的。

这项研究引入了新的深度学习方法,以提高药物发现效率. 通过平衡样本偏差和结合生化原理,该方法产生更高质量的候选药物,提高可预测性.

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A Simple, Robust, and High Throughput Single Molecule Flow Stretching Assay Implementation for Studying Transport of Molecules Along DNA
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A Simple, Robust, and High Throughput Single Molecule Flow Stretching Assay Implementation for Studying Transport of Molecules Along DNA

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Single-Molecule Diffusion and Assembly on Polymer-Crowded Lipid Membranes
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Single-Molecule Diffusion and Assembly on Polymer-Crowded Lipid Membranes

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相关实验视频

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Generation of Heterogeneous Drug Gradients Across Cancer Populations on a Microfluidic Evolution Accelerator for Real-Time Observation
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Generation of Heterogeneous Drug Gradients Across Cancer Populations on a Microfluidic Evolution Accelerator for Real-Time Observation

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A Simple, Robust, and High Throughput Single Molecule Flow Stretching Assay Implementation for Studying Transport of Molecules Along DNA
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A Simple, Robust, and High Throughput Single Molecule Flow Stretching Assay Implementation for Studying Transport of Molecules Along DNA

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Single-Molecule Diffusion and Assembly on Polymer-Crowded Lipid Membranes
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Single-Molecule Diffusion and Assembly on Polymer-Crowded Lipid Membranes

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科学领域:

  • 计算化学是一种计算化学.
  • 人工智能在药物发现中的作用
  • 分子建模分子建模

背景情况:

  • 传统的药物发现是昂贵而缓慢的.
  • 深度学习 (DL) 提供了效率,但与样本偏差和生化原理扎.
  • 现有的DL方法往往忽略了空间安排和ADME属性.

研究的目的:

  • 开发一个DL框架,用于高效和高质量的分子生成.
  • 解决药物发现中现有的DL方法的局限性.
  • 为了提高产生的分子的可靠性和适用性.

主要方法:

  • 建议平衡损失以减轻样本偏差.
  • 引入了一个基于KAN的平衡特征过 (KBFF) 模块,集成分子特征和空间数据.
  • 开发了一个QikProp模块,用于预测ADME属性以过分子.

主要成果:

  • 余额损失有效地解决了样本偏差.
  • KBFF模块通过平衡化学特性和空间安排来提高分子质量.
  • QikProp模块通过基于ADME属性的过来增强分子选择.
  • 对CrossDocked2020数据集的实验显示出卓越的性能.

结论:

  • 拟议的方法显著提高了分子生成质量和效率.
  • 整合生化原理和属性预测可以改善类似药物的特性.
  • 这种方法为药物发现提供了更可靠,更实用的DL解决方案.