中枢神经系统中关键GPCR家族的活动模型:多用途工具
Shayma El-Atawneh1, Amiram Goldblum1
1Molecular Modelling and Drug Design Lab, Institute for Drug Research and Fraunhofer Project Center for Drug Discovery and Delivery, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem 91905, Israel.
Journal of chemical information and modeling
|May 31, 2023
概括
这项研究引入了一种新的算法,用于预测与参与中枢神经系统疾病的G蛋白结合受体 (GPCR) 的药物相互作用. 该工具有助于设计更安全,更有效的中枢神经系统治疗方法.
科学领域:
- 药理学 药理学是指药理学的学科.
- 计算化学计算化学
- 神经科学是一个神经科学.
背景情况:
- G蛋白结合受体 (GPCR) 是关键的药物标,特别是在中枢神经系统 (CNS) 疾病中,约25%的药物向它们.
- 药物乱交,或与多个标结合,可能会影响治疗药物的有效性和安全性.
- 预测多药理学对于开发精确的中枢神经系统疗法至关重要,通过识别预期目标和非目标.
研究的目的:
- 开发和验证一种计算工具,用于对关键的中枢神经系统GPCRs进行化合物的多药理学预测.
- 评估与中枢神经系统药物-GPCR相互作用的现有方法相比,新算法的预测性能.
主要方法:
- 开发了一种内部算法,即"代随机淘汰" (ISE),以生成对抗和对抗的基于连接体的模型.
- 应用ISE模型来预测中枢神经系统 (中枢神经系统) 突出的家族 (血清素,多巴胺,组胺,肌肉素,阿片类,大麻素) 内31个GPCR的相互作用和活动.
- 对比ISE模型的预测与"相似组合方法"和报告的DrugBank分子活动.
主要成果:
- 该ISE算法实现了31个CNS GPCR的高质量联体基模型.
- 与相似组合方法 (33%) 相比,ISE模型对中枢神经系统药物-GPCR相互作用 (68%) 的预测准确度更高.
- 基于ISE的活动模型正确预测了DrugBank分子对这些中枢神经系统受体的56%报告的活动.
结论:
- 该ISE工具提供了一种可靠的方法,用于预测中枢神经系统中的GPCR多药学.
- 预测的相互作用和活动概况可以指导新型,精确的中枢神经系统治疗方法的设计和发现,包括单标,多标或重用药物.
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