药物基因 (DrugGen):一个针对特定标蛋白的新生成分子结合剂的数据库
Hao Qian1, Jingyuan Zhou1, Shikui Tu1
1Department of Computer Science and Engineering, Shanghai Jiao Tong University, No. 800 Dong Chuan Road, Shanghai 200240, China.
Database : the journal of biological databases and curation
|December 27, 2023
概括
我们使用6个人工智能 (AI) 模型创建了一个3D连体数据库,用于新的分子生成. 这种资源通过为特定的蛋白质标设计的新分子提供帮助药物发现.
科学领域:
- 计算化学是一种计算化学.
- 药物发现 药物发现
- 生物信息学是一种生物信息学.
背景情况:
- De novo分子生成通过创建针对特定蛋白质的新分子来加速药物发现.
- 人工智能 (AI) 和机器学习 (ML) 对于从头开始设计分子越来越重要.
- 现有的计算工具需要有效的数据库来探索人工智能驱动的分子设计.
研究的目的:
- 开发使用人工智能生成的3D联体的用户友好数据库.
- 为选潜在药物化合物与疾病相关的标提供资源.
- 为了使不同的人工智能模型能够进行 de novo 分子生成的比较.
主要方法:
- 编制了来自6个AI模型的3D连体数据库,用于新的分子生成.
- 数据库中包括了20个与疾病相关的目标和1767个蛋白质目标.
- 为各种目标生成多达164,107个新设计的分子.
主要成果:
- 建立了一个包括1767个蛋白质标和164,107个新设计的分子的综合数据库.
- 该数据库有助于有效选潜在的候选药物.
- 为评估和比较分子生成中的AI模型性能提供了一个平台.
结论:
- 开发的数据库为药物发现专业人员提供了有价值的,可访问的资源.
- 它支持探索人工智能驱动的de novo分子生成用于治疗开发.
- 在https://cmach.sjtu.edu.cn/drug/上公开访问,促进研究和合作.
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