一个易于使用的三维蛋白质结构预测在线平台"DPL3D",基于深度学习算法
Yunlong Gao1, He Wang1, Jiapeng Zhou2
1NewInsyght Biotech (Guangdong) Co., Ltd. DongGuan 523000, China.
Current research in structural biology
|January 27, 2025
概括
预测突变蛋白质结构对于了解疾病至关重要. DPL3D是一个新的平台,可视化这些3D蛋白质结构,帮助生物发现和临床应用.
科学领域:
- 结构生物学 结构生物学
- 计算生物学 计算生物学
- 基因组学就是基因组学.
背景情况:
- 蛋白质结构的变化,通常是由于错误的突变,可以导致疾病.
- 对突变蛋白质结构的准确预测受到数据可用性的限制.
- 评估突变影响的现有方法严重依赖于进化保护.
研究的目的:
- 开发一个用户友好的平台,用于预测和可视化突变蛋白质的3D结构.
- 集成先进的计算蛋白质结构预测工具.
- 为临床医生和研究人员提供可访问的结构生物学信息.
主要方法:
- 使用AlphaFold 2,RoseTTAFold,RoseTTAFold全原子和trRosettaX-Single进行结构预测.
- 编制了210,180个分子结构的数据库,包括52,248个人类蛋白质.
- 使用LiteMol实现了交互式2D和3D结构可视化.
主要成果:
- 开发了DPL3D平台 (http://nsbio.tech:3000) 用于突变蛋白质结构预测和可视化.
- 启用了蛋白质结构的自动和手动交互可视化.
- 提供了对蛋白质结构信息的大规模数据库的访问.
结论:
- DPL3D有助于临床医生和研究人员利用结构生物学信息.
- 该平台增强了研究突变对蛋白质结构和功能的影响的能力.
- 通过轻松获取大规模蛋白质结构数据,加速生物发现.
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