可执行文件
计算机科学
注释
螺旋线圈
鉴定(生物学)
Web服务器
可视化
人工智能
上传
任务(项目管理)
模式识别(心理学)
数据挖掘
程序设计语言
生物
互联网
操作系统
生物化学
植物
管理
经济
作者
Matteo Manfredi,Castrense Savojardo,Pier Luigi Martelli,Rita Casadio
出处
期刊:Bio-protocol
[Bio-Protocol]
日期:2024-01-01
卷期号:14 (4)
标识
DOI:10.21769/bioprotoc.4935
摘要
Coiled-coil domains (CCDs) are structural motifs observed in proteins in all organisms that perform several crucial functions. The computational identification of CCD segments over a protein sequence is of great importance for its functional characterization. This task can essentially be divided into three separate steps: the detection of segment boundaries, the annotation of the heptad repeat pattern along the segment, and the classification of its oligomerization state. Several methods have been proposed over the years addressing one or more of these predictive steps. In this protocol, we illustrate how to make use of CoCoNat, a novel approach based on protein language models, to characterize CCDs. CoCoNat is, at its release (August 2023), the state of the art for CCD detection. The web server allows users to submit input protein sequences and visualize the predicted domains after a few minutes. Optionally, precomputed segments can be provided to the model, which will predict the oligomerization state for each of them. CoCoNat can be easily integrated into biological pipelines by downloading the standalone version, which provides a single executable script to produce the output. Key features • Web server for the prediction of coiled-coil segments from a protein sequence. • Three different predictions from a single tool (segment position, heptad repeat annotation, oligomerization state). • Possibility to visualize the results online or to download the predictions in different formats for further processing. • Easy integration in automated pipelines with the local version of the tool.
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