最好的:基本嵌入式搜索工具,增强新酶的发现
Yuxuan Wu1, Xiao Yi1, Yang Tan1
1School of Information Science and Engineering, East China University of Science and Technology, Shanghai, 200237, China.
Interdisciplinary sciences, computational life sciences
|August 11, 2025
概括
基本嵌入搜索工具 (BEST) 识别了具有增强灵敏度和速度的蛋白质同类. 这种新方法使用蛋白质语言模型来找到传统序列对齐工具所遗漏的远程同类.
科学领域:
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
- 结构生物学 结构生物学
背景情况:
- 鉴定蛋白质同质性对生物研究至关重要.
- 像序列对齐这样的传统方法难以检测远程同类.
- 需要更快,更灵敏的同源性搜索工具.
研究的目的:
- 开发一个新的工具,基本嵌入搜索工具 (BEST),用于快速和敏感的蛋白质同质识别.
- 利用蛋白质语言模型来改进远程同类的检测.
- 为了加速序列编码和矢量检索,以实现高效的数据库搜索.
主要方法:
- 利用蛋白质语言模型来生成包含进化和结构数据的序列嵌入.
- 实施了针对加速序列编码的细分蒸修剪技术.
- 开发了一种多层加速度结构,用于快速密集向量访问和检索.
- 在真实数据集上进行了广泛的实验,以评估BEST的性能.
主要成果:
- 与现有方法相比,BEST的灵敏度增加了20%以上,保持了高精度和回忆.
- 在密集的矢量访问和检索中实现了4290.86倍的加速.
- 它的运行速度是PSI-BLAST的23.41倍,是Foldseek的3.92倍.
- 成功识别了传统的同源性搜索工具错过的同源序列.
结论:
- 在蛋白质同质识别方面,BEST提供了显著的进步,在灵敏度和速度上都超过了传统方法.
- 该工具的远程同类检测能力及其效率使其对酶开采和更广泛的生物研究具有价值.
- 开放式访问的Web服务器和公开可用的代码促进了BEST在科学界的采用和应用.
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