Fleming Jennifer, Magana Paulyna, Nair Sreenath, Tsenkov Maxim, Bertoni Damian, Pidruchna Ivanna, Lima Afonso Marcelo Querino, Midlik Adam, Paramval Urmila, Žídek Augustin, Laydon Agata, Kovalevskiy Oleg, Pan Joshua, Cheng Jun, Avsec Žiga, Bycroft Clare, Wong Lai Hong, Last Meera, Mirdita Milot, Steinegger Martin, Kohli Pushmeet, Váradi Mihály, Velankar Sameer
European Molecular Biology Laboratory European Bioinformatics Institute Hinxton UK.
Google DeepMind London UK.
J Mol Biol. 2025 Aug 1;437(15):168967. doi: 10.1016/j.jmb.2025.168967. Epub 2025 Jan 29.
The AlphaFold Protein Structure Database (https://alphafold.ebi.ac.uk/) has made significant strides in enhancing its utility and accessibility for the life science research community. The recent integration of AlphaMissense predictions enables access to the pathogenicity of human protein missense variants, with an innovative and interactive heatmap and 3D visualisation that display variant data at the residue level. Users can now toggle between structure model quality (pLDDT) and average pathogenicity scores, providing insights into the implications of specific residue changes. The Foldseek integration offers a rapid and accurate method for protein structure searches and comparisons. Bulk data download options further facilitate comprehensive data analysis and integration with other computational tools. The 3D-Beacons framework (https://www.ebi.ac.uk/pdbe/pdbe-kb/3dbeacons/) has also been enhanced with detailed annotation endpoints (such as AlphaMissense data) and integrates LevyLab's dataset of homomeric AlphaFold 2 models. These advancements significantly improve the functionality and accessibility of these resources, enabling discoveries using structure data.
AlphaFold蛋白质结构数据库（https://alphafold.ebi.ac.uk/）在提升其对生命科学研究界的实用性和可访问性方面取得了重大进展。最近整合的AlphaMissense预测功能可让人了解人类蛋白质错义变体的致病性，并通过创新的交互式热图和3D可视化在残基水平显示变体数据。用户现在可以在结构模型质量（pLDDT）和平均致病性评分之间切换，从而深入了解特定残基变化的影响。Foldseek整合提供了一种快速准确的蛋白质结构搜索和比较方法。批量数据下载选项进一步便于进行全面的数据分析以及与其他计算工具的整合。3D-Beacons框架（https://www.ebi.ac.uk/pdbe/pdbe-kb/3dbeacons/）也通过详细的注释端点（如AlphaMissense数据）得到了增强，并整合了LevyLab的同聚体AlphaFold 2模型数据集。这些进展显著改善了这些资源的功能和可访问性，使利用结构数据进行发现成为可能。
