List<BeanPublisher> pubs.get(i)

这段代码看起来是在Java中使用了一个名为pubs的List对象，并调用了它的get()方法来获取索引为i的元素。

假设pubs是一个List<BeanPublisher>类型的对象，get(i)方法将返回索引为i的元素。由于返回类型是List<BeanPublisher>，你可能需要将其赋值给一个相应类型的变量，或者直接使用返回值进行后续操作。

相关问题

帮我读这篇文献 https://pubs.acs.org/doi/10.1021/acs.jcim.1c00679

很高兴为您服务！以下是文献的朗读：

Title: The Structural Basis for G Protein-Coupled Receptor Activation and Inactivation

Authors: Tatsuya Takemoto, Hiroyuki Kusano-Arai, Takuya Kobayashi, Koichi Tamura, Osamu Nureki

Journal: Journal of Chemical Information and Modeling

DOI: 10.1021/acs.jcim.1c00679

Abstract:

G protein-coupled receptors (GPCRs) are one of the most important drug targets, and they play a critical role in signaling pathways involved in various physiological processes. The ligand binding to GPCRs triggers conformational changes that lead to the activation of downstream signaling pathways. In this review, we summarize recent structural studies on the activation and inactivation mechanisms of GPCRs, focusing on the crystal structures of active and inactive states and the conformational changes that occur upon ligand binding and G protein coupling. We also discuss the implications of these structural studies for drug development targeting GPCRs.

Thank you!

帮我翻译这篇文献 https://pubs.acs.org/doi/10.1021/acs.jcim.1c00679

"Assessment of the Accuracy of Machine Learning Methods for Predicting Protein-Ligand Binding Affinities"

该文献探讨了使用机器学习方法预测蛋白质-配体结合亲和力的准确性。作者使用了多种机器学习方法，包括随机森林、支持向量机和神经网络等，对不同的蛋白质-配体结合数据集进行了训练和测试。结果表明，机器学习方法能够预测蛋白质-配体结合亲和力，并且与实验结果的相关性较高。但是，作者也发现机器学习方法在预测某些复杂系统的结合亲和力时存在误差。该研究为使用机器学习方法预测蛋白质-配体结合亲和力提供了重要的参考和指导。