图形注意点预测 (GrASP):使用图形神经网络以注意力识别可吸毒结合点
Zachary Smith1,2, Michael Strobel3, Bodhi P Vani1
1Institute for Physical Science and Technology, University of Maryland, College Park 20742, USA.
bioRxiv : the preprint server for biology
|August 7, 2023
概括
我们开发了一种新的计算方法,即图形注意力位置预测 (GrASP),用于识别药物发现的蛋白质结合点. 格拉斯普提高了预测潜在药物点的准确性和效率.
科学领域:
- 计算化学是一种计算化学.
- 结构生物学是结构生物学.
- 药物发现 药物发现
背景情况:
- 识别可使用药物的蛋白质结合部位对于计算机辅助药物发现至关重要.
- 当前的方法通常依赖于实验数据,从而限制了效率.
- 通过计算预测绑定站点仍然是一个重大挑战.
结论:
- 格拉斯普显著推进了计算药物发现领域.
- 该方法提供了一个精确而有效的工具,用于识别可用药的蛋白质标.
- 这种方法有可能加速药物发现管道.
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