新しいデータベースがタンパク質-脂質研究に革命を起こす(New Database Revolutionizes Protein-Lipid Research)

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2024-12-18 ジョージア工科大学

ジョージア工科大学の研究者たちは、タンパク質と脂質の相互作用を詳細に記録した新しいデータベース「BioDolphin」を開発しました。このデータベースは、膜タンパク質に限定されず、127,000以上の相互作用を網羅的に収集・注釈しています。無料で公開されており、研究者が分子構造や結合親和性を分析しやすく、疾患治療やバイオ医薬品開発に役立てられます。また、教育ツールとしても利用が期待されています。

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脂質-タンパク質結合相互作用の包括的データベースとしてのBioDolphin BioDolphin as a comprehensive database of lipid–protein binding interactions

Li-Yen Yang,Kaike Ping,Yunan Luo & Andrew C. McShan
Communications Chemistry  Published:04 December 2024
DOI:https://doi.org/10.1038/s42004-024-01384-z

新しいデータベースがタンパク質-脂質研究に革命を起こす(New Database Revolutionizes Protein-Lipid Research)

Abstract

Lipid-protein interactions are crucial for virtually all biological processes in living cells. However, existing structural databases focusing on these interactions are limited to integral membrane proteins. A systematic understanding of diverse lipid-protein interactions also encompassing lipid-anchored, peripheral membrane and soluble lipid binding proteins remains to be elucidated. To address this gap and facilitate the research of universal lipid-protein assemblies, we developed BioDolphin – a curated database with over 127,000 lipid-protein interactions. BioDolphin provides comprehensive annotations, including protein functions, protein families, lipid classifications, lipid-protein binding affinities, membrane association type, and atomic structures. Accessible via a publicly available web server (www.biodolphin.chemistry.gatech.edu), users can efficiently search for lipid-protein interactions using a wide range of options and download datasets of interest. Additionally, BioDolphin features interactive 3D visualization of each lipid-protein complex, facilitating the exploration of structure-function relationships. BioDolphin also includes detailed information on atomic-level intermolecular interactions between lipids and proteins that enable large scale analysis of both paired complexes and larger assemblies. As an open-source resource, BioDolphin enables global analysis of lipid-protein interactions and supports data-driven approaches for developing predictive machine learning algorithms for lipid-protein binding affinity and structures.

有機化学・薬学
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