GalaxySagittarius-AF: Predicting Targets for Drug-Like Compounds in the Extended Human 3D Proteome

IF 4.7 2区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Journal of Molecular Biology Pub Date : 2024-09-01 DOI:10.1016/j.jmb.2024.168617
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Abstract

In recent years, advancements in deep learning techniques have significantly expanded the structural coverage of the human proteome. GalaxySagittarius-AF translates these achievements in structure prediction into target prediction for druglike compounds by incorporating predicted structures. This web server searches the database of human protein structures using both similarity- and structure-based approaches, suggesting potential targets for a given druglike compound. In comparison to its predecessor, GalaxySagittarius, GalaxySagittarius-AF utilizes an enlarged structure database, incorporating curated AlphaFold model structures alongside their binding sites and ligands, predicted using an updated version of GalaxySite. GalaxySagittarius-AF covers a large human protein space compared to many other available computational target screening methods. The structure-based prediction method enhances the use of expanded structural information, differentiating it from other target prediction servers that rely on ligand-based methods. Additionally, the web server has undergone enhancements, operating two to three times faster than its predecessor. The updated report page provides comprehensive information on the sequence and structure of the predicted protein targets. GalaxySagittarius-AF is accessible at https://galaxy.seoklab.org/sagittarius_af without the need for registration.

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GalaxySagittarius-AF:在扩展的人类三维蛋白质组中预测类药物的靶点
近年来,深度学习技术的进步极大地扩展了人类蛋白质组的结构覆盖范围。GalaxySagittarius-AF 将这些结构预测方面的成就转化为类药物的靶点预测,将预测的结构纳入其中。该网络服务器使用相似性和基于结构的方法搜索人类蛋白质结构数据库,为给定的类药物化合物推荐潜在靶点。与它的前身 GalaxySagittarius 相比,GalaxySagittarius-AF 利用了更大的结构数据库,将经过策划的 AlphaFold 模型结构与利用 GalaxySite 更新版预测的结合位点和配体结合在一起。与许多其他可用的计算目标筛选方法相比,GalaxySagittarius-AF 覆盖了一个巨大的人类蛋白质空间。基于结构的预测方法加强了对扩展结构信息的利用,使其有别于其他依赖配体方法的靶标预测服务器。此外,网络服务器也进行了改进,运行速度比其前身快了两到三倍。更新后的报告页面提供了有关预测蛋白质靶标序列和结构的全面信息。GalaxySagittarius-AF 可通过 https://galaxy.seoklab.org/sagittarius_af 访问,无需注册。
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
Journal of Molecular Biology
Journal of Molecular Biology 生物-生化与分子生物学
CiteScore
11.30
自引率
1.80%
发文量
412
审稿时长
28 days
期刊介绍: Journal of Molecular Biology (JMB) provides high quality, comprehensive and broad coverage in all areas of molecular biology. The journal publishes original scientific research papers that provide mechanistic and functional insights and report a significant advance to the field. The journal encourages the submission of multidisciplinary studies that use complementary experimental and computational approaches to address challenging biological questions. Research areas include but are not limited to: Biomolecular interactions, signaling networks, systems biology; Cell cycle, cell growth, cell differentiation; Cell death, autophagy; Cell signaling and regulation; Chemical biology; Computational biology, in combination with experimental studies; DNA replication, repair, and recombination; Development, regenerative biology, mechanistic and functional studies of stem cells; Epigenetics, chromatin structure and function; Gene expression; Membrane processes, cell surface proteins and cell-cell interactions; Methodological advances, both experimental and theoretical, including databases; Microbiology, virology, and interactions with the host or environment; Microbiota mechanistic and functional studies; Nuclear organization; Post-translational modifications, proteomics; Processing and function of biologically important macromolecules and complexes; Molecular basis of disease; RNA processing, structure and functions of non-coding RNAs, transcription; Sorting, spatiotemporal organization, trafficking; Structural biology; Synthetic biology; Translation, protein folding, chaperones, protein degradation and quality control.
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