World's Best Scientists 2026 revealed!

D-Index & Metrics

Chemistry

D-Index
90
Citations
29791
World Ranking
2062
National Ranking
366

Overview

Tingjun Hou is affiliated with Zhejiang University in China and has contributed extensively to the fields of biochemistry, genetics, molecular biology, and computer science. Their research spans multiple subfields, including molecular biology, computational theory and mathematics, materials chemistry, pharmacology, and organic chemistry.

The scientist's work focuses on topics such as computational drug discovery methods, machine learning applications in materials science and bioinformatics, protein structure and dynamics, chemical synthesis and analysis, protein degradation and inhibitors, as well as studies related to estrogen and related hormone effects.

Frequent publication venues for Tingjun Hou include the Journal of Chemical Information and Modeling, Briefings in Bioinformatics, the Journal of Medicinal Chemistry, arXiv (Cornell University), and Nature Communications. These journals reflect an interdisciplinary approach bridging chemistry, biology, and computational sciences.

Key recent publications are as follows:

  • ADMETlab 2.0: an integrated online platform for accurate and comprehensive predictions of ADMET properties, 2021, Nucleic Acids Research
  • ADMETlab 3.0: an updated comprehensive online ADMET prediction platform enhanced with broader coverage, improved performance, API functionality and decision support, 2024, Nucleic Acids Research
  • Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models, 2021, Journal of Cheminformatics
  • A unified drug-target interaction prediction framework based on knowledge graph and recommendation system, 2021, Nature Communications
  • InteractionGraphNet: A Novel and Efficient Deep Graph Representation Learning Framework for Accurate Protein-Ligand Interaction Predictions, 2021, Journal of Medicinal Chemistry

Tingjun Hou collaborates frequently with several researchers, including Chang-Yu Hsieh, Yu Kang, Dongsheng Cao, Chao Shen, and Xujun Zhang. These collaborations indicate active engagement with peers in related scientific domains.

Best Publications

  • Assessing the performance of the MM/PBSA and MM/GBSA methods. 1. The accuracy of binding free energy calculations based on molecular dynamics simulations.

    Tingjun Hou;Junmei Wang;Youyong Li;Wei Wang

  • End-Point Binding Free Energy Calculation with MM/PBSA and MM/GBSA: Strategies and Applications in Drug Design

    Ercheng Wang;Huiyong Sun;Junmei Wang;Zhe Wang

  • Assessing the performance of the molecular mechanics/Poisson Boltzmann surface area and molecular mechanics/generalized Born surface area methods. II. the accuracy of ranking poses generated from docking

    Tingjun Hou;Junmei Wang;Youyong Li;Wei Wang

  • Comprehensive evaluation of ten docking programs on a diverse set of protein-ligand complexes: the prediction accuracy of sampling power and scoring power.

    Zhe Wang;Huiyong Sun;Xiaojun Yao;Dan Li

  • Assessing the performance of MM/PBSA and MM/GBSA methods. 4. Accuracies of MM/PBSA and MM/GBSA methodologies evaluated by various simulation protocols using PDBbind data set

    Huiyong Sun;Huiyong Sun;Youyong Li;Sheng Tian;Lei Xu

  • Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models

    Dejun Jiang;Zhenxing Wu;Chang-Yu Hsieh;Guangyong Chen

  • Assessing the performance of the MM/PBSA and MM/GBSA methods. 6. Capability to predict protein-protein binding free energies and re-rank binding poses generated by protein-protein docking.

    Fu Chen;Hui Liu;Huiyong Sun;Peichen Pan

  • Assessing the performance of MM/PBSA and MM/GBSA methods. 5. Improved docking performance using high solute dielectric constant MM/GBSA and MM/PBSA rescoring

    Huiyong Sun;Huiyong Sun;Youyong Li;Mingyun Shen;Sheng Tian

  • The application of in silico drug-likeness predictions in pharmaceutical research

    Sheng Tian;Junmei Wang;Youyong Li;Dan Li

  • Assessing the performance of MM/PBSA and MM/GBSA methods. 3. The impact of force fields and ligand charge models.

    Lei Xu;Huiyong Sun;Youyong Li;Junmei Wang

  • Recent advances in free energy calculations with a combination of molecular mechanics and continuum models

    Junmei M. Wang;Tingjun Hou;Tingjun Hou;Xiaojie Xu

  • ADME evaluation in drug discovery. 1. Applications of genetic algorithms to the prediction of blood-brain partitioning of a large set of drugs.

    Tingjun Hou;Xiaojie Xu

  • Assessing the performance of MM/PBSA and MM/GBSA methods. 7. Entropy effects on the performance of end-point binding free energy calculation approaches

    Huiyong Sun;Lili Duan;Fu Chen;Hui Liu

  • Janus Structures of Transition Metal Dichalcogenides as the Heterojunction Photocatalysts for Water Splitting

    Yujin Ji;Mingye Yang;Haiping Lin;Tingjun Hou

  • ADME Evaluation in Drug Discovery. 4. Prediction of Aqueous Solubility Based on Atom Contribution Approach

    Tingjun Hou;Ke Xia;Wei Zhang;Xiaojie Xu

  • Molecular dynamics and free energy studies on the wild-type and double mutant HIV-1 protease complexed with amprenavir and two amprenavir-related inhibitors: mechanism for binding and drug resistance.

    Unknown

  • ADME evaluation in drug discovery. 7. Prediction of oral absorption by correlation and classification.

    Tingjun Hou;Junmei Wang;Wei Zhang;Xiaojie Xu

  • Recent Development and Application of Virtual Screening in Drug Discovery: An Overview

    Tingjun Hou;Xiaojie Xu

  • ADME Evaluation in Drug Discovery. 5. Correlation of Caco-2 Permeation with Simple Molecular Properties

    Tingjun Hou;Wei Zhang;Ke Xia;Xuebin Qiao

  • Characterization of Domain–Peptide Interaction Interface: Prediction of SH3 Domain-Mediated Protein–Protein Interaction Network in Yeast by Generic Structure-Based Models

    Tingjun Hou;Nan Li;Youyong Li;Wei Wang

  • Characterization of domain-peptide interaction interface: a case study on the amphiphysin-1 SH3 domain.

    Tingjun Hou;Wei Zhang;David A. Case;Wei Wang

  • ADME Evaluation in Drug Discovery. 6. Can Oral Bioavailability in Humans Be Effectively Predicted by Simple Molecular Property-Based Rules?

    Tingjun Hou;Junmei Wang;Wei Zhang;Xiaojie Xu

  • Recent advances in computational prediction of drug absorption and permeability in drug discovery.

    Tingjun Hou;Junmei Wang;Wei Zhang;Wei Wang

Frequent Co-Authors

Youyong Li
Youyong Li Soochow University
Junmei Wang
Junmei Wang University of Pittsburgh
Dong-Sheng Cao
Dong-Sheng Cao Central South University
Huilong Dong
Huilong Dong Soochow University
Shuit-Tong Lee
Shuit-Tong Lee Macau University of Science and Technology
Wei Wang
Wei Wang University of California, San Diego
Feng Zhu
Feng Zhu Zhejiang University
Aiping Lu
Aiping Lu Hong Kong Baptist University
Haiping Lin
Haiping Lin Soochow University, Taiwan
Simon Ming-Yuen Lee
Simon Ming-Yuen Lee University of Macau

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