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Huanxiang Liu

Huanxiang Liu

D-Index & Metrics

Chemistry

D-Index
48
Citations
9434
World Ranking
15148
National Ranking
2349

Overview

Huanxiang Liu is affiliated with Lanzhou University in China and has contributed extensively to the fields of biochemistry, genetics, and molecular biology with a particular focus on molecular biology and computational approaches.

Their research encompasses several main topics, including:

  • Computational Drug Discovery Methods
  • Protein Structure and Dynamics
  • Machine Learning in Materials Science
  • Cancer Therapeutics and Mechanisms
  • Machine Learning in Bioinformatics
  • RNA and Protein Synthesis Mechanisms
  • Receptor Mechanisms and Signaling

Liu has published in numerous scientific venues, with frequent appearances in:

  • Journal of Chemical Information and Modeling
  • ACS Chemical Neuroscience
  • International Journal of Molecular Sciences
  • Briefings in Bioinformatics
  • Wiley Interdisciplinary Reviews Computational Molecular Science

Selected recent papers include:

  • "MolAICal: a soft tool for 3D drug design of protein targets by artificial intelligence and classical algorithm," 2020, Briefings in Bioinformatics
  • "CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity," 2020, Environmental Health Perspectives
  • "Ligand recognition and allosteric regulation of DRD1-Gs signaling complexes," 2021, Cell
  • "Application advances of deep learning methods for de novo drug design and molecular dynamics simulation," 2021, Wiley Interdisciplinary Reviews Computational Molecular Science
  • "RetroPrime: A Diverse, plausible and Transformer-based method for Single-Step retrosynthesis predictions," 2021, Chemical Engineering Journal

Frequent co-authors in Liu's body of work include:

  • Xiaojun Yao
  • Qianqian Zhang
  • Tingjun Hou
  • Shuoyan Tan
  • Henry H. Y. Tong

Their scholarship bridges computational theory and mathematics with applied molecular sciences, reflecting an interdisciplinary approach. The combination of molecular biology, machine learning, and materials chemistry is evident in their research output.

Overall, the scientific contributions cover fundamental and computational drug discovery methods, detailed studies on protein structure and dynamics, and the integration of machine learning techniques into molecular simulation and retrosynthesis prediction models. This body of work intersects medicine and biochemistry, aiming to advance understanding in molecular mechanisms and therapeutic strategies.

Best Publications

  • Molecular dynamics simulations and novel drug discovery.

    Xuewei Liu;Danfeng Shi;Shuangyan Zhou;Hongli Liu

  • Applicability domains for classification problems: Benchmarking of distance to models for Ames mutagenicity set.

    Iurii Sushko;Sergii Novotarskyi;Robert Körner;Anil Kumar Pandey

  • MolAICal: a soft tool for 3D drug design of protein targets by artificial intelligence and classical algorithm.

    Qifeng Bai;Shuoyan Tan;Tingyang Xu;Huanxiang Liu

  • CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity.

    Kamel Mansouri;Nicole Kleinstreuer;Ahmed M. Abdelaziz;Domenico Alberga

  • Accurate quantitative structure-property relationship model to predict the solubility of C60 in various solvents based on a novel approach using a least-squares support vector machine.

    Huanxiang Liu;Xiaojun Yao;Ruisheng Zhang;Mancang Liu

  • Molecular modeling study of checkpoint kinase 1 inhibitors by multiple docking strategies and prime/MM–GBSA calculation

    Juan Du;Huijun Sun;Lili Xi;Jiazhong Li

  • Diagnosing breast cancer based on support vector machines.

    Huanxiang Liu;Ruisheng Zhang;Feng Luan;Xiaojun Yao

  • Prediction of the isoelectric point of an amino acid based on GA-PLS and SVMs.

    Huanxiang Liu;Ruisheng Zhang;Xiaojun Yao;Mancang Liu

  • The molecular mechanism of bisphenol A (BPA) as an endocrine disruptor by interacting with nuclear receptors: insights from molecular dynamics (MD) simulations.

    Lanlan Li;Qianqian Wang;Yan Zhang;Yuzhen Niu

  • Ligand recognition and allosteric regulation of DRD1-Gs signaling complexes

    Peng Xiao;Wei Yan;Lu Gou;Ya Ni Zhong

  • Application advances of deep learning methods for de novo drug design and molecular dynamics simulation

    Qifeng Bai;Shuo Liu;Yanan Tian;Tingyang Xu

  • QSAR Prediction of Estrogen Activity for a Large Set of Diverse Chemicals under the Guidance of OECD Principles

    Unknown

  • RetroPrime: A Diverse, plausible and Transformer-based method for Single-Step retrosynthesis predictions

    Xiaorui Wang;Yuquan Li;Jiezhong Qiu;Guangyong Chen

  • QSAR models for the prediction of binding affinities to human serum albumin using the heuristic method and a support vector machine.

    C. X. Xue;Ruisheng Zhang;Huanxiang Liu;Xiaojun Yao

  • Molecular Dynamics Simulation, Free Energy Calculation and Structure-Based 3D-QSAR Studies of B-RAF Kinase Inhibitors

    Ying Yang;Jin Qin;Huanxiang Liu;Xiaojun Yao

  • Molecular modeling study on the resistance mechanism of HCV NS3/4A serine protease mutants R155K, A156V and D168A to TMC435

    Weiwei Xue;Dabo Pan;Ying Yang;Huanxiang Liu

  • Influence of Interface Structure on the Properties of ZnO/Graphene Composites: A Theoretical Study by Density Functional Theory Calculations

    Wei Geng;Xuefei Zhao;Huanxiang Liu;Xiaojun Yao

  • Preparation and In vitro Evaluation of Ethosomal Total Alkaloids of Sophora alopecuroides Loaded by a Transmembrane pH-Gradient Method

    Yan Zhou;Yuhui Wei;Huanxiang Liu;Guoqiang Zhang

  • QSAR study of ethyl 2-[(3-methyl-2,5-dioxo(3-pyrrolinyl))amino]-4-(trifluoromethyl) pyrimidine-5-carboxylate: an inhibitor of AP-1 and NF-kappa B mediated gene expression based on support vector machines.

    Huanxiang Liu;Ruisheng Zhang;Xiaojun Yao;Mancang Liu

  • Molecular basis of the interaction for an essential subunit PA-PB1 in influenza virus RNA polymerase: insights from molecular dynamics simulation and free energy calculation.

    Huanxiang Liu;Xiaojun Yao

  • Enhanced photocatalytic properties of titania–graphene nanocomposites: a density functional theory study

    Wei Geng;Huanxiang Liu;Xiaojun Yao

  • Molecular dynamics simulation and free energy calculation studies of the binding mechanism of allosteric inhibitors with p38α MAP kinase.

    Ying Yang;Yulin Shen;Huanxiang Liu;Xiaojun Yao

  • Spectroscopic studies on binding of shikonin to human serum albumin

    Wenying He;Ying Li;Jianniao Tian;Huanxiang Liu

Frequent Co-Authors

Xiaojun Yao
Xiaojun Yao Macau University of Science and Technology
Zhide Hu
Zhide Hu Lanzhou University
Junzhou Huang
Junzhou Huang The University of Texas at Arlington
Roberto Todeschini
Roberto Todeschini University of Milano-Bicocca
Kuo Hsiung Lee
Kuo Hsiung Lee University of Minnesota
Eugene N. Muratov
Eugene N. Muratov University of North Carolina at Chapel Hill
Denis Fourches
Denis Fourches North Carolina State University
Igor V. Tetko
Igor V. Tetko Helmholtz Zentrum München
Dragos Horvath
Dragos Horvath University of Strasbourg
Karl-Werner Schramm
Karl-Werner Schramm Technical University of Munich

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