Phenix-AlphaFold 网络服务：将 AlphaFold 预测用于 Phenix

IF 4.5 3区生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY

Protein Science Pub Date : 2024-04-22 DOI:10.1002/pro.4992

Billy K. Poon, Thomas C. Terwilliger, Paul D. Adams

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引用次数: 0

摘要

机器学习技术的进步使蛋白质结构预测足够准确，可用于利用晶体学和冷冻电镜数据确定大分子结构。Phenix 软件套件已将 AlphaFold 预测集成到一个自动管道中，该管道可以从氨基酸序列和数据开始，自动执行模型构建和完善，以返回与数据相匹配的蛋白质模型。由于高效运行 AlphaFold 需要很高的技术要求，我们已经实现了 Phenix-AlphaFold 网络服务，从 1.21 正式版开始，所有 Phenix 用户都可以通过 Phenix GUI 远程运行 AlphaFold 预测。我们将根据研究界的使用情况和 Phenix 的未来研究方向对该网络服务进行改进。

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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The Phenix‐AlphaFold webservice: Enabling AlphaFold predictions for use in Phenix

Advances in machine learning have enabled sufficiently accurate predictions of protein structure to be used in macromolecular structure determination with crystallography and cryo‐electron microscopy data. The Phenix software suite has AlphaFold predictions integrated into an automated pipeline that can start with an amino acid sequence and data, and automatically perform model‐building and refinement to return a protein model fitted into the data. Due to the steep technical requirements of running AlphaFold efficiently, we have implemented a Phenix‐AlphaFold webservice that enables all Phenix users to run AlphaFold predictions remotely from the Phenix GUI starting with the official 1.21 release. This webservice will be improved based on how it is used by the research community and the future research directions for Phenix.

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来源期刊

Protein Science 生物-生化与分子生物学

CiteScore

12.40

自引率

1.20%

发文量

246

审稿时长

1 months

期刊介绍： Protein Science, the flagship journal of The Protein Society, is a publication that focuses on advancing fundamental knowledge in the field of protein molecules. The journal welcomes original reports and review articles that contribute to our understanding of protein function, structure, folding, design, and evolution. Additionally, Protein Science encourages papers that explore the applications of protein science in various areas such as therapeutics, protein-based biomaterials, bionanotechnology, synthetic biology, and bioelectronics. The journal accepts manuscript submissions in any suitable format for review, with the requirement of converting the manuscript to journal-style format only upon acceptance for publication. Protein Science is indexed and abstracted in numerous databases, including the Agricultural & Environmental Science Database (ProQuest), Biological Science Database (ProQuest), CAS: Chemical Abstracts Service (ACS), Embase (Elsevier), Health & Medical Collection (ProQuest), Health Research Premium Collection (ProQuest), Materials Science & Engineering Database (ProQuest), MEDLINE/PubMed (NLM), Natural Science Collection (ProQuest), and SciTech Premium Collection (ProQuest).