An overview of the SAMPL8 host-guest binding challenge.
An overview of the SAMPL8 host-guest binding challenge.
复制标题
DOI：
10.1007/s10822-022-00462-5
复制
发表时间：
2022-10
影响因子：
3.5
通讯作者：
中科院分区：
文献类型：
--
作者：
SAMPL系列挑战旨在将社区集中在特定的建模挑战上，同时测试并有望推动计算方法的进展，以帮助指导药物发现。在这项研究中，我们报告了SAMPL8主客体盲法挑战预测绝对结合亲和力的结果。SAMPL8专注于两个主-客体数据集，一个涉及南瓜CB8(带有一系列常见的滥用药物)，另一个涉及两个不同的Gibb深腔空洞。后一个数据集包括一个以前具有特征的深腔空洞(Temoa)以及一个新的变体(TEETOA)，两者都与一系列相对刚性的碎片状客体结合。挑战参与者使用了相当广泛的方法，尽管其中许多方法是基于分子模拟的，预测精度参差不齐。与之前的一些样本迭代(SAMPL6和SAMPL7)一样，我们发现实现更高精度的一种方法是对结合自由能预测应用经验校正，利用与这些主机结合的先前数据。另一种表现良好的方法是基于MD的混合方法，该方法将权重重新加权到与QM势匹配的力。在空洞和挑战中，使用阿米巴极化力场的炼金术获得了最好的成功，RMSE小于1kcal/mol，而另一种炼金法(ATM/GAFF2-AM1BCC/TIP3P/HREM)的RMSE小于1.75kcal/mol。这里讨论的工作还强调了几个重要的教训；例如，对参考计算的回顾研究证明了预测的结合自由能对乙基采样和/或客体起始姿势的敏感性，为帮助改进未来对这些系统的研究提供了指导。网上版载有补充材料，可在10.1007/s10822-022-00462-5查阅。
The SAMPL series of challenges aim to focus the community on specific modeling challenges, while testing and hopefully driving progress of computational methods to help guide pharmaceutical drug discovery. In this study, we report on the results of the SAMPL8 host–guest blind challenge for predicting absolute binding affinities. SAMPL8 focused on two host–guest datasets, one involving the cucurbituril CB8 (with a series of common drugs of abuse) and another involving two different Gibb deep-cavity cavitands. The latter dataset involved a previously featured deep cavity cavitand (TEMOA) as well as a new variant (TEETOA), both binding to a series of relatively rigid fragment-like guests. Challenge participants employed a reasonably wide variety of methods, though many of these were based on molecular simulations, and predictive accuracy was mixed. As in some previous SAMPL iterations (SAMPL6 and SAMPL7), we found that one approach to achieve greater accuracy was to apply empirical corrections to the binding free energy predictions, taking advantage of prior data on binding to these hosts. Another approach which performed well was a hybrid MD-based approach with reweighting to a force matched QM potential. In the cavitand challenge, an alchemical method using the AMOEBA-polarizable force field achieved the best success with RMSE less than 1 kcal/mol, while another alchemical approach (ATM/GAFF2-AM1BCC/TIP3P/HREM) had RMSE less than 1.75 kcal/mol. The work discussed here also highlights several important lessons; for example, retrospective studies of reference calculations demonstrate the sensitivity of predicted binding free energies to ethyl group sampling and/or guest starting pose, providing guidance to help improve future studies on these systems. The online version contains supplementary material available at 10.1007/s10822-022-00462-5.
登录
查看更多内容
影响因子：
3.5
作者：
Ghorbani M;Hudson PS;Jones MR;Aviat F;Meana-Pañeda R;Klauda JB;Brooks BR
通讯作者：
Brooks BR
从绝对结合自由能计算中的配体选择性预测。
影响因子：
15
作者：
Aldeghi M;Heifetz A;Bodkin MJ;Knapp S;Biggin PC
通讯作者：
Biggin PC
影响因子：
3.5
作者：
Amezcua M;El Khoury L;Mobley DL
通讯作者：
Mobley DL
影响因子：
5.6
作者：
Giannos, Thomas;Lesnik, Samo;Bondar, Ana-Nicoleta
通讯作者：
Bondar, Ana-Nicoleta
影响因子：
4.1
作者：
Basilio, Nuno;Gago, Sandra;Pina, Fernando
通讯作者：
Pina, Fernando