识别和评估CXCR4通过网络建模和通过合体竞争性和的网站识别预测CXCR4的假定合体位点和调节器
Tugce Inan1, Robin Flinko2, George K Lewis2
1Department of Chemical Engineering, Istanbul Technical University, Istanbul 34469, Turkey.
The journal of physical chemistry. B
|April 22, 2024
概括
这项研究使用计算方法在化学因子受体CXCR4 (CXCR4) 中确定了新型全性药物位点. 它揭示了癌症和HIV-1的潜在候选药物,推进了全性药物设计.
科学领域:
- 生物化学和分子生物学
- 药理学 药理学是指药理学的学科.
- 计算生物学 计算生物学
背景情况:
- 化基因受体CXCR4是治疗癌症和HIV-1感染的关键标.
- 现有的药物向细胞外或膜外区域,但膜内全位仍未得到充分探索.
- 识别新的全位可能会导致新的治疗策略.
研究的目的:
- 为了研究CXCR4的内膜区域作为所有菌结合点的潜力.
- 通过计算方法识别CXCR4的新型全调节剂.
- 开发一条计算机辅助药物设计的管道,用于所有菌性药物.
主要方法:
- 高斯网络模型 (GNM) 和残留物相互作用网络 (RIN) 分析,以确定功能性重要残留物和全性传播途径.
- 通过结体竞争和 (SILCS) 进行位点识别,以预测可药物治疗的全位点.
- 虚拟选使用Glide和SILCS-蒙特卡洛对接与FDA批准的药物.
主要成果:
- 在单体CXCR4上确定了两个假设的全位,在二极体CXCR4上确定了三个.
- 查结果显示了20种潜在的药物化合物,包括抗真菌,抗癌,HIV蛋白酶抑制剂和抗疟疾药物.
- 在体外测试证实了某些化合物的阳性和负性全调制.
结论:
- 这项研究提出了一个新的计算管道,将网络动态和SILCS结合起来,用于全位点识别.
- 这种方法成功地确定了CXCR4的潜在全位和候选药物.
- 这些发现为计算机辅助药物设计提供了新的视角,以向全位点为目标.
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