World's Best Scientists 2026 revealed!
Gabriele Cruciani

Gabriele Cruciani

D-Index & Metrics

Chemistry

D-Index
67
Citations
15869
World Ranking
6902
National Ranking
162

Gabriele Cruciani 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 Gabriele Cruciani 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: 644 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: 253 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: 286 publications — 60th percentile

60% of scientists in this discipline score the same or lower.

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

Gabriele Cruciani 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 Gabriele Cruciani 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: 776 scientists 68–69 D-Index: 683 scientists 70–71 D-Index: 647 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: 67 D-Index — 62nd percentile

62% of scientists in this discipline score the same or lower.

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

Overview

Gabriele Cruciani is affiliated with the University of Perugia in Italy and has contributed extensively to the fields of biochemistry, genetics, molecular biology, and medicine. Their work spans multiple subfields including molecular biology, oncology, computational theory and mathematics, infectious diseases, and organic chemistry.

The scientist's research interests focus on several key topics including computational drug discovery methods, protein degradation and inhibitors, peptidase inhibition and analysis, ubiquitin and proteasome pathways, metabolomics and mass spectrometry studies, estrogen and related hormone effects, and protein structure and dynamics.

Recent publications authored or coauthored by Gabriele Cruciani include the following:

  • Understanding the Metabolism of Proteolysis Targeting Chimeras (PROTACs): The Next Step toward Pharmaceutical Applications (2020, Journal of Medicinal Chemistry)
  • SARS-CoV-2 Survival on Surfaces and the Effect of UV-C Light (2021, Viruses)
  • Effects of MTX-23, a Novel PROTAC of Androgen Receptor Splice Variant-7 and Androgen Receptor, on CRPC Resistant to Second-Line Antiandrogen Therapy (2020, Molecular Cancer Therapeutics)
  • SARS-CoV2 infection impairs the metabolism and redox function of cellular glutathione (2021, Redox Biology)
  • Indomethacin-based PROTACs as pan-coronavirus antiviral agents (2021, European Journal of Medicinal Chemistry)

Gabriele Cruciani frequently collaborates with several researchers including:

  • Laura Goracci
  • Simon Cross
  • Massimo Baroni
  • Lydia Siragusa
  • Jenny Desantis

The scientist has published repeatedly in prominent venues, with multiple contributions to:

  • Zenodo (CERN European Organization for Nuclear Research)
  • Journal of Chemical Information and Modeling
  • Journal of Medicinal Chemistry
  • Free Radical Biology and Medicine
  • Scientific Reports

Best Publications

  • Molecular fields in quantitative structure–permeation relationships: the VolSurf approach

    G. Cruciani;P. Crivori;P.-A. Carrupt;B. Testa

  • GRid-INdependent Descriptors (GRIND) : A novel class of alignment-independent three-dimensional molecular Descriptors

    Manuel Pastor;Gabriele Cruciani;Iain McLay;Stephen Pickett

  • Predicting Blood−Brain Barrier Permeation from Three-Dimensional Molecular Structure

    Patrizia Crivori;Gabriele Cruciani;Pierre-Alain Carrupt;Bernard Testa

  • Generating Optimal Linear PLS Estimations (GOLPE): An Advanced Chemometric Tool for Handling 3D‐QSAR Problems

    Massimo Baroni;Gabriele Costantino;Gabriele Cruciani;Daniela Riganelli

  • MetaSite: understanding metabolism in human cytochromes from the perspective of the chemist.

    Gabriele Cruciani;Emanuele Carosati;Benoit De Boeck;Kantharaj Ethirajulu

  • VolSurf: a new tool for the pharmacokinetic optimization of lead compounds.

    Gabriele Cruciani;Manuel Pastor;Wolfgang Guba

  • A common reference framework for analyzing/comparing proteins and ligands. Fingerprints for Ligands and Proteins (FLAP): theory and application.

    Massimo Baroni;Gabriele Cruciani;Simone Sciabola;Francesca Perruccio

  • Vitamin E: Emerging aspects and new directions.

    Francesco Galli;Angelo Azzi;Marc Birringer;Joan M. Cook-Mills

  • Antileishmanial Chalcones: Statistical Design, Synthesis, and Three-Dimensional Quantitative Structure−Activity Relationship Analysis

    Simon Feldbæk Nielsen;Søren Brøgger Christensen;Gabriele Cruciani;and Arsalan Kharazmi

  • New and original pKa prediction method using grid molecular interaction fields.

    Francesca Milletti;Loriano Storchi;Gianluca Sforna;Gabriele Cruciani

  • Hydrogen Bonding Interactions of Covalently Bonded Fluorine Atoms: From Crystallographic Data to a New Angular Function in the GRID Force Field

    Emanuele Carosati;Simone Sciabola;Gabriele Cruciani

  • Computational approaches to identifying and characterizing protein binding sites for ligand design.

    Stefan Henrich;Outi M. H. Salo-Ahen;Bingding Huang;Friedrich F. Rippmann

  • GRID/CPCA: a new computational tool to design selective ligands.

    Mika A. Kastenholz;Manuel Pastor;Gabriele Cruciani;and Eric E. J. Haaksma

  • A Novel Approach for Predicting P-glycoprotein (ABCB1) Inhibition Using Molecular Interaction Fields

    Fabio Broccatelli;Emanuele Carosati;Annalisa Neri;Maria Frosini

  • Comparative Molecular Field Analysis Using GRID Force-Field and GOLPE Variable Selection Methods in a Study of Inhibitors of Glycogen Phosphorylase b

    Gabriele Cruciani;Kimberly A. Watson

  • Predicting Drug Metabolism: A Site of Metabolism Prediction Tool Applied to the Cytochrome P450 2C9

    Ismael Zamora;Lovisa Afzelius;Gabriele Cruciani

  • Smart region definition: a new way to improve the predictive ability and interpretability of three-dimensional quantitative structure-activity relationships.

    Manuel Pastor;Gabriele Cruciani;Sergio Clementi

  • Tautomer enumeration and stability prediction for virtual screening on large chemical databases.

    Francesca Milletti;Loriano Storchi;Gianluca Sforna;Simon Cross

  • 1,4-Dihydropyridine Scaffold in Medicinal Chemistry, The Story So Far And Perspectives (Part 2): Action in Other Targets and Antitargets

    E. Carosati;Pierfranco Ioan;Matteo Micucci;F. Broccatelli

  • LC/MS lipid profiling from human serum: a new method for global lipid extraction.

    Roberto Maria Pellegrino;Alessandra Di Veroli;Aurora Valeri;Laura Goracci

  • Predictive ability of regression models. Part II: Selection of the best predictive PLS model

    Massimo Baroni;Sergio Clementi;Gabriele Cruciani;Gabriele Costantino

  • Predictive ability of regression models. Part I: Standard deviation of prediction errors (SDEP)†

    Gabriele Cruciani;Massimo Baroni;Sergio Clementi;Gabrielle Costantino

Frequent Co-Authors

Giorgio Palù
Giorgio Palù University of Padua
Rebecca C. Wade
Rebecca C. Wade Heidelberg Institute for Theoretical Studies
Pierre-Alain Carrupt
Pierre-Alain Carrupt École Polytechnique Fédérale de Lausanne
Bernard Testa
Bernard Testa University of Lausanne
Valerio Nobili
Valerio Nobili Sapienza University of Rome
Stefano Alcaro
Stefano Alcaro Magna Graecia University
Francesco Ortuso
Francesco Ortuso Magna Graecia University
Chiara Dall’Asta
Chiara Dall’Asta University of Parma
Simon S. Cross
Simon S. Cross University of Sheffield
Glenn W. Kaatz
Glenn W. Kaatz Wayne State University

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