World's Best Scientists 2026 revealed!

D-Index & Metrics

Biology and Biochemistry

D-Index
72
Citations
21460
World Ranking
6209
National Ranking
194

Chemistry

D-Index
72
Citations
20865
World Ranking
5205
National Ranking
963

Luhua Lai publication distribution in Chemistry in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Chemistry in 2026. The highlighted bar marks where Luhua Lai sits on this spectrum.

61–80 publications: 66 scientists 81–100 publications: 302 scientists 101–120 publications: 623 scientists 121–140 publications: 918 scientists 141–160 publications: 1,218 scientists 161–180 publications: 1,350 scientists 181–200 publications: 1,344 scientists 201–220 publications: 1,281 scientists 221–240 publications: 1,216 scientists 241–260 publications: 1,100 scientists 261–280 publications: 979 scientists 281–300 publications: 939 scientists 301–320 publications: 764 scientists 321–340 publications: 643 scientists 341–360 publications: 628 scientists 361–380 publications: 522 scientists 381–400 publications: 459 scientists 401–420 publications: 397 scientists 421–440 publications: 327 scientists 441–460 publications: 270 scientists 461–480 publications: 265 scientists 481–500 publications: 252 scientists 501–520 publications: 201 scientists 521–540 publications: 185 scientists 541–560 publications: 148 scientists 561–580 publications: 148 scientists 581–600 publications: 132 scientists 601–620 publications: 114 scientists 621–640 publications: 104 scientists 641–660 publications: 91 scientists 661–680 publications: 92 scientists 681–700 publications: 73 scientists 701–720 publications: 57 scientists 721–740 publications: 54 scientists 741–760 publications: 67 scientists 761–780 publications: 45 scientists 781–800 publications: 46 scientists 801–820 publications: 39 scientists 821–840 publications: 32 scientists 841–860 publications: 36 scientists 861–880 publications: 29 scientists 881–900 publications: 26 scientists 901–920 publications: 24 scientists 921–940 publications: 14 scientists 941–960 publications: 23 scientists 961–980 publications: 28 scientists 981–1,000 publications: 15 scientists 1,001–1,020 publications: 29 scientists 1,021–1,040 publications: 12 scientists 1,041–1,060 publications: 19 scientists 1,061–1,080 publications: 12 scientists 1,081–1,100 publications: 6 scientists 1,101–1,120 publications: 8 scientists 1,121–1,140 publications: 12 scientists 1,141–1,160 publications: 5 scientists 1,161–1,180 publications: 6 scientists 1,181–1,200 publications: 14 scientists 1,201–1,220 publications: 7 scientists 1,221–1,240 publications: 2 scientists 1,241–1,260 publications: 6 scientists 1,261–1,280 publications: 4 scientists 1,281–1,294 publications: 6 scientists 1,295+ publications: 100 scientists
61 publications 1,295+

This scientist: 290 publications — 61st percentile

61% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,295 publications or more.

Luhua Lai D-index placement in Chemistry in 2026

The chart shows the D-index (discipline H-index) distribution of Chemistry scientists ranked by Research.com in 2026. The highlighted bar marks where Luhua Lai sits on this spectrum.

40–41 D-Index: 289 scientists 42–43 D-Index: 612 scientists 44–45 D-Index: 808 scientists 46–47 D-Index: 776 scientists 48–49 D-Index: 835 scientists 50–51 D-Index: 861 scientists 52–53 D-Index: 872 scientists 54–55 D-Index: 933 scientists 56–57 D-Index: 1,051 scientists 58–59 D-Index: 930 scientists 60–61 D-Index: 882 scientists 62–63 D-Index: 834 scientists 64–65 D-Index: 731 scientists 66–67 D-Index: 775 scientists 68–69 D-Index: 683 scientists 70–71 D-Index: 646 scientists 72–73 D-Index: 561 scientists 74–75 D-Index: 501 scientists 76–77 D-Index: 437 scientists 78–79 D-Index: 388 scientists 80–81 D-Index: 354 scientists 82–83 D-Index: 292 scientists 84–85 D-Index: 275 scientists 86–87 D-Index: 254 scientists 88–89 D-Index: 235 scientists 90–91 D-Index: 185 scientists 92–93 D-Index: 192 scientists 94–95 D-Index: 155 scientists 96–97 D-Index: 163 scientists 98–99 D-Index: 125 scientists 100–101 D-Index: 105 scientists 102–103 D-Index: 105 scientists 104–105 D-Index: 112 scientists 106–107 D-Index: 88 scientists 108–109 D-Index: 68 scientists 110–111 D-Index: 69 scientists 112–113 D-Index: 65 scientists 114–115 D-Index: 79 scientists 116–117 D-Index: 61 scientists 118–119 D-Index: 44 scientists 120–121 D-Index: 37 scientists 122–123 D-Index: 40 scientists 124–125 D-Index: 33 scientists 126–127 D-Index: 26 scientists 128–129 D-Index: 34 scientists 130–131 D-Index: 35 scientists 132–133 D-Index: 25 scientists 134–135 D-Index: 27 scientists 136–137 D-Index: 17 scientists 138–139 D-Index: 16 scientists 140–141 D-Index: 20 scientists 142–143 D-Index: 20 scientists 144–145 D-Index: 15 scientists 146–147 D-Index: 9 scientists 148–149 D-Index: 9 scientists 150–151 D-Index: 16 scientists 152–153 D-Index: 11 scientists 154–155 D-Index: 9 scientists 156–157 D-Index: 3 scientists 158 D-Index: 3 scientists 159+ D-Index: 98 scientists
40 D-Index 159+

This scientist: 72 D-Index — 71st percentile

71% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 159 D-Index or more.

Overview

Luhua Lai is affiliated with Peking University in China, focusing primarily on research within the broad field of Biochemistry, Genetics and Molecular Biology, with a specific emphasis on Molecular Biology, Computational Theory and Mathematics, Materials Chemistry, Organic Chemistry, and Pharmacology. Their work spans multiple interdisciplinary subfields with notable contributions in areas that connect computational methods and chemical sciences.

The scientist has contributed to many topics in the research landscape, notably:

  • Computational Drug Discovery Methods
  • Protein Structure and Dynamics
  • Chemical Synthesis and Analysis
  • Machine Learning in Materials Science
  • Enzyme Structure and Function
  • Click Chemistry and Applications
  • Machine Learning in Bioinformatics

Among Luhua Lai's recent publications are several papers across high-impact venues, such as:

  • Transfer Learning for Drug Discovery, 2020, Journal of Medicinal Chemistry
  • Scutellaria baicalensis extract and baicalein inhibit replication of SARS-CoV-2 and its 3C-like protease in vitro, 2021, Journal of Enzyme Inhibition and Medicinal Chemistry
  • Automatic retrosynthetic route planning using template-free models, 2020, Chemical Science
  • Prediction of liquid-liquid phase separating proteins using machine learning, 2022, BMC Bioinformatics
  • Structure-based de novo drug design using 3D deep generative models, 2021, Chemical Science

Lai's publications commonly appear in several prominent scholarly venues, including:

  • IEEE Transactions on Systems Man and Cybernetics Systems
  • Journal of Chemical Information and Modeling
  • bioRxiv (Cold Spring Harbor Laboratory)
  • arXiv (Cornell University)
  • Chemical Science

Coauthor collaborations play a role in Lai's research output, with frequent partners being:

  • Enrique Herrera-Viedma
  • Karen Panetta
  • Giancarlo Fortino
  • David Mendonça
  • Tadahiko Murata

The focus of Luhua Lai's work integrates computational techniques such as machine learning with traditional disciplines of molecular biology and chemistry to explore drug discovery, protein dynamics, and chemical synthesis. This intersection supports ongoing advancements in designing and predicting biological and chemical phenomena at the molecular level.

Best Publications

  • Further development and validation of empirical scoring functions for structure-based binding affinity prediction

    Renxiao Wang;Luhua Lai;Shaomeng Wang

  • PharmMapper 2017 update: a web server for potential drug target identification with a comprehensive target pharmacophore database.

    Xia Wang;Yihang Shen;Shiwei Wang;Shiliang Li

  • Computation of Octanol−Water Partition Coefficients by Guiding an Additive Model with Knowledge

    Tiejun Cheng;Yuan Zhao;Xun Li;Fu Lin

  • A New Atom-Additive Method for Calculating Partition Coefficients

    Renxiao Wang;and Ying Fu;Luhua Lai

  • LigBuilder: A Multi-Purpose Program for Structure-Based Drug Design

    Renxiao Wang;Ying Gao;Luhua Lai

  • Arabidopsis pollen tube integrity and sperm release are regulated by RALF-mediated signaling

    Zengxiang Ge;Tabata Bergonci;Tabata Bergonci;Yuling Zhao;Yanjiao Zou

  • SCORE: A New Empirical Method for Estimating the Binding Affinity of a Protein-Ligand Complex

    Renxiao Wang;Liang Liu;Luhua Lai;Youqi Tang

  • Sequence-based prediction of protein protein interaction using a deep-learning algorithm.

    Tanlin Sun;Bo Zhou;Luhua Lai;Jianfeng Pei

  • Biosynthesis, Purification, and Substrate Specificity of Severe Acute Respiratory Syndrome Coronavirus 3C-like Proteinase

    Keqiang Fan;Ping Wei;Qian Feng;Sidi Chen

  • Deep Learning for Drug-Induced Liver Injury.

    Youjun Xu;Ziwei Dai;Fangjin Chen;Shuaishi Gao

  • CavityPlus: a web server for protein cavity detection with pharmacophore modelling, allosteric site identification and covalent ligand binding ability prediction.

    Youjun Xu;Shiwei Wang;Qiwan Hu;Shuaishi Gao

  • Synthesis, fungicidal activity, and 3D-QSAR of pyridazinone-substituted 1,3,4-oxadiazoles and 1,3,4-thiadiazoles.

    Xia-Juan Zou;Lu-Hua Lai;Gui-Yu Jin;Zu-Xing Zhang

  • A protein engineered to bind uranyl selectively and with femtomolar affinity

    Lu Zhou;Mike Bosscher;Changsheng Zhang;Salih Özçubukçu

  • Transfer Learning for Drug Discovery

    Chenjing Cai;Shiwei Wang;Youjun Xu;Weilin Zhang

  • Scutellaria baicalensis extract and baicalein inhibit replication of SARS-CoV-2 and its 3C-like protease in vitro .

    Hongbo Liu;Fei Ye;Qi Sun;Hao Liang

  • CH···O Hydrogen Bonds at Protein-Protein Interfaces

    Lin Jiang;Luhua Lai

  • Calculating partition coefficient by atom-additive method

    Renxiao Wang;Ying Gao;Luhua Lai

  • Deep Learning Based Regression and Multiclass Models for Acute Oral Toxicity Prediction with Automatic Chemical Feature Extraction

    Youjun Xu;Jianfeng Pei;Luhua Lai

  • LigBuilder 2: A Practical de Novo Drug Design Approach

    Yaxia Yuan;Jianfeng Pei;Luhua Lai

  • Finding multiple target optimal intervention in disease‐related molecular network

    Kun Yang;Hongjun Bai;Qi Ouyang;Luhua Lai

  • Formation of amyloid fibrils from fully reduced hen egg white lysozyme.

    Aoneng Cao;Daoying Hu;Luhua Lai

  • Automatic retrosynthetic route planning using template-free models

    Kangjie Lin;Youjun Xu;Jianfeng Pei;Luhua Lai

  • Scutellaria baicalensis extract and baicalein inhibit replication of SARS-CoV-2 and its 3C-like protease in vitro

    Hongbo Liu;Fei Ye;Qi Sun;Hao Liang

Frequent Co-Authors

Qian Wang
Qian Wang Peking University
Hualiang Jiang
Hualiang Jiang Chinese Academy of Sciences
Zhirong Liu
Zhirong Liu Peking University
Xu Shen
Xu Shen Nanjing University of Chinese Medicine
Sung-Hou Kim
Sung-Hou Kim University of California, Berkeley
Jason W. Locasale
Jason W. Locasale Duke University
Xin Liu
Xin Liu Chinese Academy of Sciences
Li-Jia Qu
Li-Jia Qu Peking University
Xun Xu
Xun Xu Beijing Genomics Institute
huanming yang
huanming yang Beijing Genomics Institute

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