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Updated: Jun 5, 2026

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
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Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

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混合计算框架集成集体学习,分子对接和动力学,用于预测疟疾盒组合物的抗疟疾有效性

Martín Moreno1, Sebastián A Cuesta1,2, José R Mora1

  • 1Grupo de Química Computacional y Teórica (QCT-USFQ), Departamento de Ingeniería Química, Universidad San Francisco de Quito USFQ, Diego de Robles y Vía Interoceánica, Quito 170901, Ecuador.

International journal of molecular sciences
|February 27, 2026
PubMed
概括

这项研究开发了一个计算框架来预测抗疟疾药物的活性. 该方法通过整合机器学习,对接和对疟疾药物发现的模拟成功识别了有希望的化合物.

关键词:
这是分类分类的分类.药物设计 药物设计总的来说,一个团队就是一个团队.机器学习是机器学习.疟疾 疟疾 是一种疾病.分子动力学分子动力学预测模型的预测模型.这是一个回归回归的回归.

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