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2020 – today
- 2023
[j131]Lei Wang, Shao-Hua Shi
, Hui Li, Xiangxiang Zeng, Su-You Liu, Zhao-Qian Liu, Yafeng Deng, Ai-Ping Lu, Tingjun Hou, Dong-Sheng Cao:
Reducing false positive rate of docking-based virtual screening by active learning. Briefings Bioinform. 24(1) (2023)- [j130]Dong Wang, Zhenxing Wu, Chao Shen, Lingjie Bao, Hao Luo, Zhe Wang, Hucheng Yao, De-Xin Kong, Cheng Luo, Tingjun Hou:
Learning with uncertainty to accelerate the discovery of histone lysine-specific demethylase 1A (KDM1A/LSD1) inhibitors. Briefings Bioinform. 24(1) (2023) - [j129]Lingling Wang, Lei Xu, Zhe Wang, Tingjun Hou, Haiping Hao, Huiyong Sun:
Cooperation of structural motifs controls drug selectivity in cyclin-dependent kinases: an advanced theoretical analysis. Briefings Bioinform. 24(1) (2023) - [j128]Shukai Gu, Chao Shen, Jiahui Yu, Hong Zhao, Huanxiang Liu, Liwei Liu, Rong Sheng, Lei Xu, Zhe Wang, Tingjun Hou, Yu Kang:
Can molecular dynamics simulations improve predictions of protein-ligand binding affinity with machine learning? Briefings Bioinform. 24(2) (2023) - [j127]Kai-Yue Ji, Chong Liu, Zhao-Qian Liu, Yafeng Deng, Tingjun Hou, Dong-Sheng Cao:
Comprehensive assessment of nine target prediction web services: which should we choose for target fishing? Briefings Bioinform. 24(2) (2023) - [j126]Yuchen Sun, Tingjun Hou, Xibing He, Viet Hoang Man, Junmei Wang:
Development and test of highly accurate endpoint free energy methods. 2: Prediction of logarithm of n-octanol-water partition coefficient (logP) for druglike molecules using MM-PBSA method. J. Comput. Chem. 44(13): 1300-1311 (2023) - [j125]Yuchen Sun, Xibing He, Tingjun Hou, Lianjin Cai, Viet Hoang Man, Junmei Wang:
Development and test of highly accurate endpoint free energy methods. 1: Evaluation of ABCG2 charge model on solvation free energy prediction and optimization of atom radii suitable for more accurate solvation free energy prediction by the PBSA method. J. Comput. Chem. 44(14): 1334-1346 (2023) - [j124]Kexin Chen, Guangyong Chen, Junyou Li, Yuansheng Huang, Ercheng Wang, Tingjun Hou, Pheng-Ann Heng:
MetaRF: attention-based random forest for reaction yield prediction with a few trails. J. Cheminformatics 15(1): 43 (2023) - [j123]Su-Qing Yang, Liu-Xia Zhang, You-Jin Ge, Jin-Wei Zhang, Jian-Xin Hu, Cheng-Ying Shen, Ai-Ping Lu, Tingjun Hou, Dong-Sheng Cao:
In-silico target prediction by ensemble chemogenomic model based on multi-scale information of chemical structures and protein sequences. J. Cheminformatics 15(1): 48 (2023) - [j122]Xujun Zhang, Chao Shen, Dejun Jiang, Jintu Zhang, Qing Ye, Lei Xu, Tingjun Hou, Peichen Pan, Yu Kang:
TB-IECS: an accurate machine learning-based scoring function for virtual screening. J. Cheminformatics 15(1): 63 (2023) - [j121]Teng-Zhi Long, Shao-Hua Shi, Shao Liu, Ai-Ping Lu, Zhao-Qian Liu, Min Li, Tingjun Hou, Dong-Sheng Cao:
Structural Analysis and Prediction of Hematotoxicity Using Deep Learning Approaches. J. Chem. Inf. Model. 63(1): 111-125 (2023) - [j120]Jintu Zhang, Haotian Zhang, Zhixin Qin, Yu Kang, Xin Hong, Tingjun Hou:
Quasiclassical Trajectory Simulation as a Protocol to Build Locally Accurate Machine Learning Potentials. J. Chem. Inf. Model. 63(4): 1133-1142 (2023) - [j119]Yanqing Duan, Li Fu, Xiao-Chen Zhang, Teng-Zhi Long, Yuan-Hang He, Zhao-Qian Liu, Ai-Ping Lu, Yafeng Deng, Chang-Yu Hsieh, Tingjun Hou, Dong-Sheng Cao:
Improved GNNs for Log D7.4 Prediction by Transferring Knowledge from Low-Fidelity Data. J. Chem. Inf. Model. 63(8): 2345-2359 (2023) - [j118]Jike Wang, Yundian Zeng, Huiyong Sun, Junmei Wang, Xiaorui Wang, Ruofan Jin, Mingyang Wang, Xujun Zhang, Dong-Sheng Cao, Xi Chen, Chang-Yu Hsieh, Tingjun Hou:
Molecular Generation with Reduced Labeling through Constraint Architecture. J. Chem. Inf. Model. 63(11): 3319-3327 (2023) - [j117]Kuerbannisha Amahong, Wei Zhang, Ying Zhou, Song Zhang, Jiayi Yin, Fengcheng Li, Hong-Quan Xu, Tian-Ci Yan, Zi-Xuan Yue, Yu-Hong Liu, Tingjun Hou, Yunqing Qiu, Lin Tao, Lianyi Han, Feng Zhu:
CovInter: interaction data between coronavirus RNAs and host proteins. Nucleic Acids Res. 51(D1): 546-556 (2023) - [j116]Fengcheng Li, Jiayi Yin, Mingkun Lu, Minjie Mou, Zhaorong Li, Zhenyu Zeng, Ying Tan, Shanshan Wang, Xinyi Chu, Haibin Dai, Tingjun Hou, Su Zeng, Yuzong Chen, Feng Zhu:
DrugMAP: molecular atlas and pharma-information of all drugs. Nucleic Acids Res. 51(D1): 1288-1299 (2023) - [j115]Gaoqi Weng, Xuanyan Cai, Dong-Sheng Cao, Hongyan Du, Chao Shen, Yafeng Deng, Qiaojun He, Bo Yang, Dan Li, Tingjun Hou:
PROTAC-DB 2.0: an updated database of PROTACs. Nucleic Acids Res. 51(D1): 1367-1372 (2023) - [j114]Yunxia Wang, Zhen Chen, Ziqi Pan, Shijie Huang, Jin Liu, Weiqi Xia, Hongning Zhang, Mingyue Zheng, Honglin Li, Tingjun Hou, Feng Zhu:
RNAincoder: a deep learning-based encoder for RNA and RNA-associated interaction. Nucleic Acids Res. 51(W1): 509-519 (2023) - [c2]Yiheng Zhu, Zhenqiu Ouyang, Ben Liao, Jialu Wu, Yixuan Wu, Chang-Yu Hsieh, Tingjun Hou, Jian Wu:
MolHF: A Hierarchical Normalizing Flow for Molecular Graph Generation. IJCAI 2023: 5002-5010 - [i4]Zipeng Zhong, Jie Song, Zunlei Feng, Tiantao Liu, Lingxiang Jia, Shaolun Yao, Tingjun Hou, Mingli Song:
Recent advances in artificial intelligence for retrosynthesis. CoRR abs/2301.05864 (2023) - [i3]Yiheng Zhu, Jialu Wu, Chaowen Hu, Jiahuan Yan, Chang-Yu Hsieh, Tingjun Hou, Jian Wu:
Sample-efficient Multi-objective Molecular Optimization with GFlowNets. CoRR abs/2302.04040 (2023) - [i2]Yiheng Zhu, Zhenqiu Ouyang, Ben Liao, Jialu Wu, Yixuan Wu, Chang-Yu Hsieh, Tingjun Hou, Jian Wu:
MolHF: A Hierarchical Normalizing Flow for Molecular Graph Generation. CoRR abs/2305.08457 (2023) - 2022
- [j113]Mingyang Wang, Huiyong Sun, Jike Wang, Jinping Pang, Xin Chai, Lei Xu, Honglin Li, Dongsheng Cao, Tingjun Hou:
Comprehensive assessment of deep generative architectures for de novo drug design. Briefings Bioinform. 23(1) (2022) - [j112]Dejun Jiang, Huiyong Sun, Jike Wang, Chang-Yu Hsieh, Yuquan Li, Zhenxing Wu, Dong-Sheng Cao, Jian Wu, Tingjun Hou:
Out-of-the-box deep learning prediction of quantum-mechanical partial charges by graph representation and transfer learning. Briefings Bioinform. 23(2) (2022) - [j111]Xiao-Chen Zhang, Jia-Cai Yi, Guo-Ping Yang, Chengkun Wu, Tingjun Hou, Dong-Sheng Cao:
ABC-Net: a divide-and-conquer based deep learning architecture for SMILES recognition from molecular images. Briefings Bioinform. 23(2) (2022) - [j110]Rongfan Tang, Pengcheng Chen, Zhe Wang, Lingling Wang, Haiping Hao, Tingjun Hou, Huiyong Sun:
Characterizing the stabilization effects of stabilizers in protein-protein systems with end-point binding free energy calculations. Briefings Bioinform. 23(3) (2022) - [j109]Zhenxing Wu, Dejun Jiang, Jike Wang, Xujun Zhang, Hongyan Du, Lurong Pan, Chang-Yu Hsieh, Dongsheng Cao, Tingjun Hou:
Knowledge-based BERT: a method to extract molecular features like computational chemists. Briefings Bioinform. 23(3) (2022) - [j108]Zhe Wang, Hong Pan, Huiyong Sun, Yu Kang, Huanxiang Liu, Dongsheng Cao, Tingjun Hou:
fastDRH: a webserver to predict and analyze protein-ligand complexes based on molecular docking and MM/PB(GB)SA computation. Briefings Bioinform. 23(5) (2022) - [j107]Jia-Cai Yi, Chengkun Wu, Xiao-Chen Zhang, Xinyi Xiao, Yanlong Qiu, Wentao Zhao, Tingjun Hou, Dong-Sheng Cao:
MICER: a pre-trained encoder-decoder architecture for molecular image captioning. Bioinform. 38(19): 4562-4572 (2022) - [j106]Ning-Ning Wang, Xiang-Gui Wang, Guo-Li Xiong, Zi-Yi Yang, Ai-Ping Lu, Xiang Chen, Shao Liu, Tingjun Hou, Dong-Sheng Cao:
Machine learning to predict metabolic drug interactions related to cytochrome P450 isozymes. J. Cheminformatics 14(1): 23 (2022) - [j105]Yang Yu, Zhe Wang, Lingling Wang, Sheng Tian, Tingjun Hou, Huiyong Sun:
Predicting the mutation effects of protein-ligand interactions via end-point binding free energy calculations: strategies and analyses. J. Cheminformatics 14(1): 56 (2022) - [j104]Gaoang Wang, Jiahui Yu, Hongyan Du, Chao Shen, Xujun Zhang, Yifei Liu, Yangyang Zhang, Dong-Sheng Cao, Peichen Pan, Tingjun Hou:
VGSC-DB: an online database of voltage-gated sodium channels. J. Cheminformatics 14(1): 75 (2022) - [j103]Mingyang Wang, Jike Wang, Gaoqi Weng, Yu Kang, Peichen Pan, Dan Li, Yafeng Deng, Honglin Li, Chang-Yu Hsieh, Tingjun Hou:
ReMODE: a deep learning-based web server for target-specific drug design. J. Cheminformatics 14(1): 84 (2022) - [j102]Jiahui Yu, Jike Wang, Hong Zhao, Junbo Gao, Yu Kang, Dong-Sheng Cao, Zhe Wang, Tingjun Hou:
Organic Compound Synthetic Accessibility Prediction Based on the Graph Attention Mechanism. J. Chem. Inf. Model. 62(12): 2973-2986 (2022) - [j101]Yuwei Yang, Zhenxing Wu, Xiaojun Yao, Yu Kang, Tingjun Hou, Chang-Yu Hsieh, Huanxiang Liu:
Exploring Low-Toxicity Chemical Space with Deep Learning for Molecular Generation. J. Chem. Inf. Model. 62(13): 3191-3199 (2022) - [j100]Qinghua Wang, Zhe Wang, Sheng Tian, Lingling Wang, Rongfan Tang, Yang Yu, Jingxuan Ge, Tingjun Hou, Haiping Hao, Huiyong Sun:
Determination of Molecule Category of Ligands Targeting the Ligand-Binding Pocket of Nuclear Receptors with Structural Elucidation and Machine Learning. J. Chem. Inf. Model. 62(17): 3993-4007 (2022) - [j99]Haiyi Chen, Rui Zhou, Jinping Pang, Yue Guo, Jiawen Chen, Yu Kang, Mojie Duan, Tingjun Hou:
Molecular View on the Dissociation Pathways and Transactivation Regulation Mechanism of Nonsteroidal GR Ligands. J. Chem. Inf. Model. 62(21): 5233-5245 (2022) - [j98]Jialu Wu, Junmei Wang, Zhenxing Wu, Shengyu Zhang, Yafeng Deng, Yu Kang, Dong-Sheng Cao, Chang-Yu Hsieh, Tingjun Hou:
ALipSol: An Attention-Driven Mixture-of-Experts Model for Lipophilicity and Solubility Prediction. J. Chem. Inf. Model. 62(23): 5975-5987 (2022) - [j97]Guo-Li Xiong, Zhi-Jiang Yang, Jia-Cai Yi, Ningning Wang, Lei Wang, Huimin Zhu, Chengkun Wu, Ai-Ping Lu, Xiang Chen, Shao Liu, Tingjun Hou, Dongsheng Cao:
DDInter: an online drug-drug interaction database towards improving clinical decision-making and patient safety. Nucleic Acids Res. 50(D1): 1200-1207 (2022) - [i1]Zipeng Zhong, Jie Song, Zunlei Feng, Tiantao Liu, Lingxiang Jia, Shaolun Yao, Min Wu, Tingjun Hou, Mingli Song:
Root-aligned SMILES for Molecular Retrosynthesis Prediction. CoRR abs/2203.11444 (2022) - 2021
- [j96]Jie Dong, Min-Feng Zhu, Yong-Huan Yun, Ai-Ping Lu, Tingjun Hou, Dong-Sheng Cao:
BioMedR: an R/CRAN package for integrated data analysis pipeline in biomedical study. Briefings Bioinform. 22(1): 474-484 (2021) - [j95]Chao Shen, Ye Hu, Zhe Wang, Xujun Zhang, Haiyang Zhong, Gaoang Wang, Xiaojun Yao, Lei Xu, Dong-Sheng Cao, Tingjun Hou:
Can machine learning consistently improve the scoring power of classical scoring functions? Insights into the role of machine learning in scoring functions. Briefings Bioinform. 22(1): 497-514 (2021) - [j94]Chao Shen, Ye Hu, Zhe Wang, Xujun Zhang, Jinping Pang, Gaoang Wang, Haiyang Zhong, Lei Xu, Dong-Sheng Cao, Tingjun Hou:
Beware of the generic machine learning-based scoring functions in structure-based virtual screening. Briefings Bioinform. 22(3) (2021) - [j93]Jike Wang, Dong-Sheng Cao, Cunchen Tang, Lei Xu, Qiaojun He, Bo Yang, Xi Chen, Huiyong Sun, Tingjun Hou:
DeepAtomicCharge: a new graph convolutional network-based architecture for accurate prediction of atomic charges. Briefings Bioinform. 22(3) (2021) - [j92]Guo-Li Xiong, Wen-Ling Ye, Chao Shen, Ai-Ping Lu, Tingjun Hou, Dong-Sheng Cao:
Improving structure-based virtual screening performance via learning from scoring function components. Briefings Bioinform. 22(3) (2021) - [j91]Zi-Yi Yang, Zhi-Jiang Yang, Ai-Ping Lu, Tingjun Hou, Dong-Sheng Cao:
Scopy: an integrated negative design python library for desirable HTS/VS database design. Briefings Bioinform. 22(3) (2021) - [j90]Zhenxing Wu, Minfeng Zhu, Yu Kang, Elaine Lai-Han Leung, Tailong Lei, Chao Shen, Dejun Jiang, Zhe Wang, Dong-Sheng Cao, Tingjun Hou:
Do we need different machine learning algorithms for QSAR modeling? A comprehensive assessment of 16 machine learning algorithms on 14 QSAR data sets. Briefings Bioinform. 22(4) (2021) - [j89]Zi-Yi Yang, Jie Dong, Zhi-Jiang Yang, Mingzhu Yin, Hong-Li Jiang, Ai-Ping Lu, Xiang Chen, Tingjun Hou, Dong-Sheng Cao:
ChemFLuo: a web-server for structure analysis and identification of fluorescent compounds. Briefings Bioinform. 22(4) (2021) - [j88]Li Fu, Zi-Yi Yang, Zhi-Jiang Yang, Ming-Zhu Yin, Ai-Ping Lu, Xiang Chen, Shao Liu, Tingjun Hou, Dong-Sheng Cao:
QSAR-assisted-MMPA to expand chemical transformation space for lead optimization. Briefings Bioinform. 22(5) (2021) - [j87]Chao Shen, Gaoqi Weng, Xujun Zhang, Elaine Lai-Han Leung, Xiaojun Yao, Jinping Pang, Xin Chai, Dan Li, Ercheng Wang, Dong-Sheng Cao, Tingjun Hou:
Accuracy or novelty: what can we gain from target-specific machine-learning-based scoring functions in virtual screening? Briefings Bioinform. 22(5) (2021) - [j86]Zhenxing Wu, Dejun Jiang, Chang-Yu Hsieh, Guangyong Chen, Ben Liao, Dong-Sheng Cao, Tingjun Hou:
Hyperbolic relational graph convolution networks plus: a simple but highly efficient QSAR-modeling method. Briefings Bioinform. 22(5) (2021) - [j85]Zi-Yi Yang, Zhi-Jiang Yang, Yue Zhao, Ming-Zhu Yin, Ai-Ping Lu, Xiang Chen, Shao Liu, Tingjun Hou, Dong-Sheng Cao:
PySmash: Python package and individual executable program for representative substructure generation and application. Briefings Bioinform. 22(5) (2021) - [j84]Qing Ye, Xin Chai, Dejun Jiang, Liu Yang, Chao Shen, Xujun Zhang, Dan Li, Dong-Sheng Cao, Tingjun Hou:
Identification of active molecules against Mycobacterium tuberculosis through machine learning. Briefings Bioinform. 22(5) (2021) - [j83]Chengkun Wu, Xiao-Chen Zhang, Zhi-Jiang Yang, Ai-Ping Lu, Tingjun Hou, Dong-Sheng Cao:
Learning to SMILES: BAN-based strategies to improve latent representation learning from molecules. Briefings Bioinform. 22(6) (2021) - [j82]Xiao-Chen Zhang, Chengkun Wu, Zhi-Jiang Yang, Zhen-Xing Wu, Jia-Cai Yi, Chang-Yu Hsieh, Tingjun Hou, Dong-Sheng Cao:
MG-BERT: leveraging unsupervised atomic representation learning for molecular property prediction. Briefings Bioinform. 22(6) (2021) - [j81]Jike Wang, Huiyong Sun, Jiawen Chen, Dejun Jiang, Zhe Wang, Zhenxing Wu, Xi Chen, Dong-Sheng Cao, Tingjun Hou:
DeepChargePredictor: a web server for predicting QM-based atomic charges via state-of-the-art machine-learning algorithms. Bioinform. 37(22): 4255-4257 (2021) - [j80]Xujun Zhang, Chao Shen, Xueying Guo, Zhe Wang, Gaoqi Weng, Qing Ye, Gaoang Wang, Qiaojun He, Bo Yang, Dong-Sheng Cao, Tingjun Hou:
ASFP (Artificial Intelligence based Scoring Function Platform): a web server for the development of customized scoring functions. J. Cheminformatics 13(1): 6 (2021) - [j79]Dejun Jiang, Zhenxing Wu, Chang-Yu Hsieh, Guangyong Chen, Ben Liao, Zhe Wang, Chao Shen, Dong-Sheng Cao, Jian Wu, Tingjun Hou:
Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models. J. Cheminformatics 13(1): 12 (2021) - [j78]Chao Shen, Xueping Hu, Junbo Gao, Xujun Zhang, Haiyang Zhong, Zhe Wang, Lei Xu, Yu Kang, Dong-Sheng Cao, Tingjun Hou:
The impact of cross-docked poses on performance of machine learning classifier for protein-ligand binding pose prediction. J. Cheminformatics 13(1): 81 (2021) - [j77]Zi-Yi Yang, Li Fu, Ai-Ping Lu, Shao Liu, Tingjun Hou, Dong-Sheng Cao:
Semi-automated workflow for molecular pair analysis and QSAR-assisted transformation space expansion. J. Cheminformatics 13(1): 86 (2021) - [j76]Ercheng Wang, Weitao Fu, Dejun Jiang, Huiyong Sun, Junmei Wang, Xujun Zhang, Gaoqi Weng, Hui Liu, Peng Tao, Tingjun Hou:
VAD-MM/GBSA: A Variable Atomic Dielectric MM/GBSA Model for Improved Accuracy in Protein-Ligand Binding Free Energy Calculations. J. Chem. Inf. Model. 61(6): 2844-2856 (2021) - [j75]Hongyan Du, Junbo Gao, Gaoqi Weng, Jun-Jie Ding, Xin Chai, Jinping Pang, Yu Kang, Dan Li, Dong-Sheng Cao, Tingjun Hou:
CovalentInDB: a comprehensive database facilitating the discovery of covalent inhibitors. Nucleic Acids Res. 49(Database-Issue): D1122-D1129 (2021) - [j74]Gaoqi Weng, Chao Shen, Dong-Sheng Cao, Junbo Gao, Xiaowu Dong, Qiaojun He, Bo Yang, Dan Li, Jian Wu, Tingjun Hou:
PROTAC-DB: an online database of PROTACs. Nucleic Acids Res. 49(Database-Issue): D1381-D1387 (2021) - [j73]Guo-Li Xiong, Zhenxing Wu, Jia-Cai Yi, Li Fu, Zhi-Jiang Yang, Chang-Yu Hsieh, Mingzhu Yin, Xiangxiang Zeng, Chengkun Wu, Ai-Ping Lu, Xiang Chen, Tingjun Hou, Dong-Sheng Cao:
ADMETlab 2.0: an integrated online platform for accurate and comprehensive predictions of ADMET properties. Nucleic Acids Res. 49(Webserver-Issue): 5-14 (2021) - [j72]Jike Wang, Chang-Yu Hsieh, Mingyang Wang, Xiaorui Wang, Zhenxing Wu, Dejun Jiang, Benben Liao, Xujun Zhang, Bo Yang, Qiaojun He, Dongsheng Cao, Xi Chen, Tingjun Hou:
Multi-constraint molecular generation based on conditional transformer, knowledge distillation and reinforcement learning. Nat. Mach. Intell. 3(10): 914-922 (2021) - 2020
- [j71]Chao Shen, Zhe Wang, Xiaojun Yao, Youyong Li, Tailong Lei, Ercheng Wang, Lei Xu, Feng Zhu, Dan Li, Tingjun Hou:
Comprehensive assessment of nine docking programs on type II kinase inhibitors: prediction accuracy of sampling power, scoring power and screening power. Briefings Bioinform. 21(1): 282-297 (2020) - [j70]Jike Wang, Dong-Sheng Cao, Cunchen Tang, Xi Chen, Huiyong Sun, Tingjun Hou:
Fast and accurate prediction of partial charges using Atom-Path-Descriptor-based machine learning. Bioinform. 36(18): 4721-4728 (2020) - [j69]Dejun Jiang, Tailong Lei, Zhe Wang, Chao Shen, Dong-Sheng Cao, Tingjun Hou:
ADMET evaluation in drug discovery. 20. Prediction of breast cancer resistance protein inhibition through machine learning. J. Cheminformatics 12(1): 16 (2020) - [j68]Li Fu, Lu Liu, Zhi-Jiang Yang, Pan Li, Jun-Jie Ding, Yong-Huan Yun, Ai-Ping Lu, Tingjun Hou, Dong-Sheng Cao:
Systematic Modeling of log D7.4 Based on Ensemble Machine Learning, Group Contribution, and Matched Molecular Pair Analysis. J. Chem. Inf. Model. 60(1): 63-76 (2020) - [j67]Zi-Yi Yang, Jie Dong, Zhi-Jiang Yang, Ai-Ping Lu, Tingjun Hou, Dong-Sheng Cao:
Structural Analysis and Identification of False Positive Hits in Luciferase-Based Assays. J. Chem. Inf. Model. 60(4): 2031-2043 (2020) - [j66]Wen-Ling Ye, Chao Shen, Guo-Li Xiong, Jun-Jie Ding, Ai-Ping Lu, Tingjun Hou, Dong-Sheng Cao:
Improving Docking-Based Virtual Screening Ability by Integrating Multiple Energy Auxiliary Terms from Molecular Docking Scoring. J. Chem. Inf. Model. 60(9): 4216-4230 (2020) - [j65]Ercheng Wang, Hui Liu, Junmei Wang, Gaoqi Weng, Huiyong Sun, Zhe Wang, Yu Kang, Tingjun Hou:
Development and Evaluation of MM/GBSA Based on a Variable Dielectric GB Model for Predicting Protein-Ligand Binding Affinities. J. Chem. Inf. Model. 60(11): 5353-5365 (2020)
2010 – 2019
- 2019
- [j64]Zhe Wang, Xuwen Wang, Youyong Li, Tailong Lei, Ercheng Wang, Dan Li, Yu Kang, Feng Zhu, Tingjun Hou:
farPPI: a webserver for accurate prediction of protein-ligand binding structures for small-molecule PPI inhibitors by MM/PB(GB)SA methods. Bioinform. 35(10): 1777-1779 (2019) - [j63]Ye Jin, Mojie Duan, Xuwen Wang, Xiaotian Kong, Wenfang Zhou, Huiyong Sun, Hui Liu, Dan Li, Huidong Yu, Youyong Li, Tingjun Hou:
Communication between the Ligand-Binding Pocket and the Activation Function-2 Domain of Androgen Receptor Revealed by Molecular Dynamics Simulations. J. Chem. Inf. Model. 59(2): 842-857 (2019) - [j62]Zi-Yi Yang, Zhi-Jiang Yang, Jie Dong, Liang-Liang Wang, Liu-Xia Zhang, Jun-Jie Ding, Xiao-Qin Ding, Ai-Ping Lu, Tingjun Hou, Dong-Sheng Cao:
Structural Analysis and Identification of Colloidal Aggregators in Drug Discovery. J. Chem. Inf. Model. 59(9): 3714-3726 (2019) - [j61]Zhenxing Wu, Tailong Lei, Chao Shen, Zhe Wang, Dong-Sheng Cao, Tingjun Hou:
ADMET Evaluation in Drug Discovery. 19. Reliable Prediction of Human Cytochrome P450 Inhibition Using Artificial Intelligence Approaches. J. Chem. Inf. Model. 59(11): 4587-4601 (2019) - [j60]Gaoqi Weng, Ercheng Wang, Zhe Wang, Hui Liu, Feng Zhu, Dan Li, Tingjun Hou:
HawkDock: a web server to predict and analyze the protein-protein complex based on computational docking and MM/GBSA. Nucleic Acids Res. 47(Webserver-Issue): W322-W330 (2019) - 2018
- [j59]Wenfang Zhou, Mojie Duan, Weitao Fu, Jinping Pang, Qin Tang, Huiyong Sun, Lei Xu, Shan Chang, Dan Li, Tingjun Hou:
Discovery of Novel Androgen Receptor Ligands by Structure-based Virtual Screening and Bioassays. Genom. Proteom. Bioinform. 16(6): 416-427 (2018) - [j58]Jun Shang, Ben Hu, Junmei Wang, Feng Zhu, Yu Kang, Dan Li, Huiyong Sun, De-Xin Kong, Tingjun Hou:
Cheminformatic Insight into the Differences between Terrestrial and Marine Originated Natural Products. J. Chem. Inf. Model. 58(6): 1182-1193 (2018) - [j57]Na Liu, Wenfang Zhou, Yue Guo, Junmei Wang, Weitao Fu, Huiyong Sun, Dan Li, Mojie Duan, Tingjun Hou:
Molecular Dynamics Simulations Revealed the Regulation of Ligands to the Interactions between Androgen Receptor and Its Coactivator. J. Chem. Inf. Model. 58(8): 1652-1661 (2018) - 2017
- [j56]Jun Shang, Huiyong Sun, Hui Liu, Fu Chen, Sheng Tian, Peichen Pan, Dan Li, De-Xin Kong, Tingjun Hou:
Comparative analyses of structural features and scaffold diversity for purchasable compound libraries. J. Cheminformatics 9(1): 25:1-25:16 (2017) - [j55]Ting Feng, Fu Chen, Yu Kang, Huiyong Sun, Hui Liu, Dan Li, Feng Zhu, Tingjun Hou:
HawkRank: a new scoring function for protein-protein docking based on weighted energy terms. J. Cheminformatics 9(1): 66:1-66:15 (2017) - [j54]Sheng Tian, Xu Wang, Linlang Li, Xiaohu Zhang, Youyong Li, Feng Zhu, Tingjun Hou, Xuechu Zhen:
Discovery of Novel and Selective Adenosine A2A Receptor Antagonists for Treating Parkinson's Disease through Comparative Structure-Based Virtual Screening. J. Chem. Inf. Model. 57(6): 1474-1487 (2017) - [j53]Huiyong Sun, Youyong Li, Mingyun Shen, Dan Li, Yu Kang, Tingjun Hou:
Characterizing Drug-Target Residence Time with Metadynamics: How To Achieve Dissociation Rate Efficiently without Losing Accuracy against Time-Consuming Approaches. J. Chem. Inf. Model. 57(8): 1895-1906 (2017) - 2016
- [j52]Hui Liu, Tingjun Hou:
CaFE: a tool for binding affinity prediction using end-point free energy methods. Bioinform. 32(14): 2216-2218 (2016) - [j51]Tailong Lei, Youyong Li, Yunlong Song, Dan Li, Huiyong Sun, Tingjun Hou:
ADMET evaluation in drug discovery: 15. Accurate prediction of rat oral acute toxicity using relevance vector machine and consensus modeling. J. Cheminformatics 8(1): 6:1-6:19 (2016) - 2015
- [j50]Nan Li, Richard I. Ainsworth, Bo Ding, Tingjun Hou, Wei Wang:
Using Hierarchical Virtual Screening To Combat Drug Resistance of the HIV-1 Protease. J. Chem. Inf. Model. 55(7): 1400-1412 (2015) - [j49]Yu Zhang, Lei Xu, Zhiqiang Zhang, Zhiyu Zhang, Longtai Zheng, Dan Li, Youyong Li, Feng Liu, Kunqian Yu, Tingjun Hou, Xuechu Zhen:
Structure-Activity Relationships and Anti-inflammatory Activities of N-Carbamothioylformamide Analogues as MIF Tautomerase Inhibitors. J. Chem. Inf. Model. 55(9): 1994-2004 (2015) - [j48]Peichen Pan, Sheng Tian, Huiyong Sun, Xiaotian Kong, Wenfang Zhou, Dan Li, Youyong Li, Tingjun Hou:
Identification and Preliminary SAR Analysis of Novel Type-I Inhibitors of TIE-2 via Structure-Based Virtual Screening and Biological Evaluation in in vitro Models. J. Chem. Inf. Model. 55(12): 2693-2704 (2015) - 2014
- [j47]Qian Zhang, Wei Zhang, Youyong Li, Junmei Wang, Jian Zhang, Tingjun Hou:
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Assessing an Ensemble Docking-Based Virtual Screening Strategy for Kinase Targets by Considering Protein Flexibility. J. Chem. Inf. Model. 54(10): 2664-2679 (2014) - [j45]Huiyong Sun, Youyong Li, Sheng Tian, Junmei Wang, Tingjun Hou:
P-loop Conformation Governed Crizotinib Resistance in G2032R-Mutated ROS1 Tyrosine Kinase: Clues from Free Energy Landscape. PLoS Comput. Biol. 10(7) (2014) - 2013
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Drug-likeness analysis of traditional Chinese medicines: 2. Characterization of scaffold architectures for drug-like compounds, non-drug-like compounds, and natural compounds from traditional Chinese medicines. J. Cheminformatics 5: 5 (2013) - [j42]Shunye Zhou, Youyong Li, Tingjun Hou:
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