在弥合蛋白质结构预测和功能解释之间的差距方面存在挑战
Mihaly Varadi1, Maxim Tsenkov1, Sameer Velankar1
1Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, UK.
Proteins
|October 18, 2023
概括
蛋白质结构预测工具提供了前所未有的结构数据访问,加速研究. 然而,动态,多链预测和质量评估方面的挑战需要进一步的跨学科合作和开放的数据共享,以获得更深入的生物学见解.
科学领域:
- 结构生物学 结构生物学
- 计算生物学 计算生物学
- 生物信息学是一种生物信息学.
背景情况:
- 蛋白质结构预测工具的进步使得大量蛋白质结构数据的访问得到了民主化.
- 预测的蛋白质模型具有显著的潜力,可以加速各种生物学科的基础和翻译研究.
研究的目的:
- 突出蛋白质结构预测对科学研究的变革性影响.
- 确定持续存在的挑战,并为该领域的未来进步提出战略.
- 强调跨学科合作和 FAIR 数据访问的重要性.
主要方法:
- 审查当前的蛋白质结构预测工具及其能力.
- 对准确预测蛋白质动力学,多链复合体和功能的现有挑战进行分析.
- 通过主要数据库和网络 (例如,AlphaFold蛋白质结构数据库,ESM Metagenomic Atlas,3D-Beacons网络) 检查数据的可访问性.
主要成果:
- 已经取得了重大进展,扩大了对蛋白质结构信息的获取.
- 主要挑战仍然存在,包括捕获蛋白质动态,预测多链结构,解释功能和评估模型准确性.
- 数据库和网络对于FAIR数据访问和更广泛的科学应用至关重要.
结论:
- 跨学科的合作对于克服当前蛋白质结构预测的局限性至关重要.
- 持续发展需要强大的培训材料,促进合作,以及开放的数据共享实践.
- 进一步的进展将加深对蛋白质功能的理解,加速疾病病原和药物开发方面的发现.
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