CASP 16 实验性蛋白质 - 连接体数据集
Andreas Tosstorff1, Markus G Rudolph1, Jörg Benz1
1Roche Pharmaceutical Research and Early Development (pRED), Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland.
Proteins
|October 3, 2025
概括
这项研究引入了CASP16.16药物发现中的新型蛋白质-配体数据集. 这些基准数据集评估药物相关目标的计算方法.
科学领域:
- 结构生物学 结构生物学
- 药物发现 药物发现 药物发现
- 计算化学计算化学
背景情况:
- CASP (蛋白质结构预测的批判性评估) 实验传统上专注于蛋白质结构预测.
- 药物发现项目的整合到CASP16中标志着对现实世界药物开发挑战的重大扩展.
研究的目的:
- 为CASP16提供实验性蛋白质 - 配体数据集,特别是用于药物发现目标.
- 为制药应用建立评估蛋白质 - 连接体姿势和亲和力预测计算方法的基准.
主要方法:
- 对四种药物标蛋白质的蛋白质-连接体复合物的组装和表征:人体化学酶,人体甲素G,人体自毒素和SARS-CoV-2主要蛋白酶.
- 收集了200多个共同晶体结构 (分辨率<2.7 Å) 和约160个化合物 (纳米到高微分子范围) 的结合亲和度测量.
- 实验方法的详细描述,包括蛋白质生产,结晶和结合试验的开发.
主要成果:
- 创建基准数据集,其中包括具有药学意义的蛋白质-联结体复合体.
- 包括具有具有挑战性特征的系统,例如特定的蛋白质表面,连接体特性和活性位点构造.
- 从实际的药物发现项目中生成数据,提供现实的测试平台.
结论:
- 提出的数据集对于通过提供现实的基准来推进计算药物发现至关重要.
- 这些数据集将有助于评估计算方法对药物研究相关目标的性能.
- 该研究强调了药物发现项目的成功整合到CASP框架.
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