TripleBind: a generalizable deep learning framework for protein-nucleic acid and protein-ligand binding sites prediction based on pre-trained protein language models.

IF 4.3 2区化学 Q2 CHEMISTRY, APPLIED

Molecular Diversity Pub Date : 2026-10-01 Epub Date: 2026-04-21 DOI:10.1007/s11030-026-11557-8

Zhiwei Liu, Ruisheng Zhang

引用次数: 0

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TripleBind：基于预训练的蛋白质语言模型的蛋白质-核酸和蛋白质-配体结合位点预测的可推广的深度学习框架。

蛋白质-核酸和蛋白质-配体相互作用在调节细胞过程中起着重要作用，是药物发现和设计的基础。虽然现有的实验分析可以产生高度精确的测量，但它们通常是劳动密集型的，昂贵的，并且不足以满足快速增长的大规模蛋白质序列注释的需求。因此，开发一种能够准确识别蛋白质-核酸和蛋白质-配体结合残基的高效可靠的计算框架变得至关重要。在这项研究中，我们提出了TripleBind，这是一种新的深度学习架构，可以仅使用序列信息预测蛋白质-核酸和蛋白质-配体结合位点。TripleBind集成了三个基于transformer的预训练蛋白质语言模型和一个专门设计的多分支卷积网络（MBCN）模块。在蛋白质核酸基准数据集上的实验结果表明，我们的方法在独立的蛋白质- dna测试集上的MCC得分为0.392和0.512，在独立的蛋白质- rna测试集上的MCC得分为0.46，与现有的基于序列的方法相比，性能有所提高。此外，TripleBind可以作为蛋白质-配体相互作用的一般预测因子，并在不同的任务中表现出强大的性能。最后，我们提供可解释性分析来阐明我们模型的行为并总结其总体贡献。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Molecular Diversity 化学-化学综合

CiteScore

7.30

自引率

7.90%

发文量

219

审稿时长

2.7 months

期刊介绍： Molecular Diversity is a new publication forum for the rapid publication of refereed papers dedicated to describing the development, application and theory of molecular diversity and combinatorial chemistry in basic and applied research and drug discovery. The journal publishes both short and full papers, perspectives, news and reviews dealing with all aspects of the generation of molecular diversity, application of diversity for screening against alternative targets of all types (biological, biophysical, technological), analysis of results obtained and their application in various scientific disciplines/approaches including: combinatorial chemistry and parallel synthesis; small molecule libraries; microwave synthesis; flow synthesis; fluorous synthesis; diversity oriented synthesis (DOS); nanoreactors; click chemistry; multiplex technologies; fragment- and ligand-based design; structure/function/SAR; computational chemistry and molecular design; chemoinformatics; screening techniques and screening interfaces; analytical and purification methods; robotics, automation and miniaturization; targeted libraries; display libraries; peptides and peptoids; proteins; oligonucleotides; carbohydrates; natural diversity; new methods of library formulation and deconvolution; directed evolution, origin of life and recombination; search techniques, landscapes, random chemistry and more;