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在FPGA平台上进行高吞吐量分子对接的新优化混合化方法

Amin Jarrah¹, Jawad Lababneh¹

¹Department of Computer Engineering, Hijjawi Faculty for Engineering Technology, Yarmouk University, Irbid, 21163, Jordan.

Current computer-aided drug design

|October 13, 2023

概括

一种新的混合方法 (hABCDE) 通过增强分子对接算法,显著加速了in silico药物设计. 这种方法提高了药物发现的计算效率和解决方案质量.

科学领域:

计算化学和药物发现.
生物信息学和分子建模.
为生命科学提供高性能计算.

背景情况:

在形药物设计加速了新疗法的发现.
分子对接对于识别稳定的药物受体复合体至关重要.
有效的搜索算法对于快速准确的分子对接至关重要.

研究的目的:

引入一种新的混合方法, hABCDE,用于分子对接.
将布里斯托尔大学对接引擎 (BUDE) 中现有的搜索组件替换为 hABCDE.
提高药物受体复合体识别解决方案的速度和质量.

主要方法:

人工蜂群 (ABC) 和差异进化 (DE) 算法的杂交.
在BUDE对接算法中实现 hABCDE方法.
在现场可编程门阵列 (FPGA) 平行平台上使用 Vivado 高级合成工具 (HLST) 进行部署.
使用NDM-1蛋白作为模型受体的验证.

主要成果:

采用 hABCDE 方法,执行时间显著改善.
与 hABCDE 集成的 BUDE 算法显示速度增加了 9,236 倍.
在分子对接模拟中观察到提高效率和溶液质量.

结论:

新的 hABCDE 方法有效地提高了像 BUDE 这样的对接算法的性能.
这种方法为in silico药物设计的计算效率提供了显著的改进.
这些发现有助于加速药物发现和开发管道.

关键词:

布德 (Bude) 是一个人.在FPGA中,FPGA是指FPGA.分子对接是分子对接.人工蜂群算法的人工蜂群算法不同进化算法差异进化算法优化的优化优化优化.平行处理是平行处理.维瓦多 HLS 在线

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