no code implementations • 4 Jul 2022 • Tao Shen, Zhihang Hu, Zhangzhi Peng, Jiayang Chen, Peng Xiong, Liang Hong, Liangzhen Zheng, YiXuan Wang, Irwin King, Sheng Wang, Siqi Sun, Yu Li
When E2Efold-3D is coupled with the experimental techniques, the RNA structure prediction field can be greatly advanced.
1 code implementation • 27 Jun 2022 • Zechen Wang, Liangzhen Zheng, Sheng Wang, Mingzhi Lin, Zhihao Wang, Adams Wai-Kin Kong, Yuguang Mu, Yanjie Wei, Weifeng Li
In this work, we propose a fully differentiable framework for ligand pose optimization based on a hybrid scoring function (SF) combined with a multi-layer perceptron (DeepRMSD) and the traditional AutoDock Vina SF.
no code implementations • 10 May 2021 • Liangzhen Zheng, Haidong Lan, Tao Shen, Jiaxiang Wu, Sheng Wang, Wei Liu, Junzhou Huang
Protein structure prediction has been a grand challenge for over 50 years, owing to its broad scientific and application interests.
1 code implementation • 22 Mar 2021 • Zechen Wang, Liangzhen Zheng, Yang Liu, Yuanyuan Qu, Yong-Qiang Li, Mingwen Zhao, Yuguang Mu, Weifeng Li
In this study, we proposed a simple scoring function (called OnionNet-2) based on convolutional neural network to predict $\triangle$$G$.
2 code implementations • 6 Jun 2019 • Liangzhen Zheng, Jingrong Fan, Yuguang Mu
When compared to a previous CNN-based scoring function, our model shows improvements of 0. 08 and 0. 16 in the correlations (R) and standard deviations (SD) of regression, respectively, between the predicted binding affinities and the experimental measured binding affinities.
Biological Physics Computational Physics Biomolecules