World's Best Scientists 2026 revealed!

D-Index & Metrics

Chemistry

D-Index
57
Citations
24565
World Ranking
10908
National Ranking
2989

Woody Sherman 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 Woody Sherman 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: 114 publications — 4th percentile

4% of scientists in this discipline score the same or lower.

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

Woody Sherman 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 Woody Sherman 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: 57 D-Index — 39th percentile

39% of scientists in this discipline score the same or lower.

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

Overview

Woody Sherman is affiliated with Psivant Therapeutics in the United States and has contributed extensively to the field of Biochemistry, Genetics, and Molecular Biology with a focus on Molecular Biology as their primary subfield. Their research spans across Computational Theory and Mathematics, Materials Chemistry, Spectroscopy, and Immunology.

Their publication record includes significant work on topics such as Protein Structure and Dynamics, Computational Drug Discovery Methods, Enzyme Structure and Function, Machine Learning in Materials Science, Protein Degradation and Inhibitors, Ubiquitin and proteasome pathways, and Spectroscopy and Quantum Chemical Studies.

Notable recent papers by Woody Sherman include:

  • Alchemical Binding Free Energy Calculations in AMBER20: Advances and Best Practices for Drug Discovery, 2020, Journal of Chemical Information and Modeling
  • Rigorous Free Energy Simulations in Virtual Screening, 2020, Journal of Chemical Information and Modeling
  • Predicting the structural basis of targeted protein degradation by integrating molecular dynamics simulations with structural mass spectrometry, 2022, Nature Communications
  • Improved Alchemical Free Energy Calculations with Optimized Smoothstep Softcore Potentials, 2020, Journal of Chemical Theory and Computation
  • Targeted Protein Degradation: Advances, Challenges, and Prospects for Computational Methods, 2023, Journal of Chemical Information and Modeling

Frequent co-authors include Huafeng Xu, István Kolossváry, Brian K. Radak, Rafal Wiewiora, and Bryce K. Allen, reflecting collaborative work primarily within computational and biochemical research domains.

Woody Sherman's contributions have been published predominantly in the following venues:

  • Journal of Chemical Information and Modeling
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Chemical Biology & Drug Design
  • Journal of Chemical Theory and Computation
  • arXiv (Cornell University)

Best Publications

  • Protein and ligand preparation: parameters, protocols, and influence on virtual screening enrichments

    G. Madhavi Sastry;Matvey Adzhigirey;Tyler Day;Ramakrishna Annabhimoju

  • Novel procedure for modeling ligand/receptor induced fit effects.

    Woody Sherman;Tyler Day;Matthew P Jacobson;Richard A Friesner

  • Prediction of Absolute Solvation Free Energies using Molecular Dynamics Free Energy Perturbation and the OPLS Force Field.

    Devleena Shivakumar;Joshua Williams;Yujie Wu;Wolfgang Damm

  • Accurate and Reliable Prediction of Relative Ligand Binding Potency in Prospective Drug Discovery by Way of a Modern Free-Energy Calculation Protocol and Force Field

    Lingle Wang;Yujie Wu;Yuqing Deng;Byungchan Kim

  • Improved Docking of Polypeptides with Glide

    Ivan Tubert-Brohman;Woody Sherman;Matthew P. Repasky;Thijs Beuming

  • Relative Binding Free Energy Calculations in Drug Discovery: Recent Advances and Practical Considerations

    Zoe Cournia;Bryce Allen;Woody Sherman

  • Use of an Induced Fit Receptor Structure in Virtual Screening

    Woody Sherman;Hege S. Beard;Ramy Farid

  • ConfGen: a conformational search method for efficient generation of bioactive conformers.

    K. Shawn Watts;Pranav Dalal;Robert B. Murphy;Woody Sherman

  • Analysis and comparison of 2D fingerprints: Insights into database screening performance using eight fingerprint methods

    Jianxin Duan;Steven L. Dixon;Jeffrey F. Lowrie;Woody Sherman

  • Probing the alpha-helical structural stability of stapled p53 peptides: molecular dynamics simulations and analysis.

    Zuojun Guo;Udayan Mohanty;Justin Noehre;Tomi K. Sawyer

  • Rational Approaches to Improving Selectivity in Drug Design

    David J. Huggins;Woody Sherman;Bruce Tidor

  • Mechanism of the hydrophobic effect in the biomolecular recognition of arylsulfonamides by carbonic anhydrase.

    Phillip W. Snyder;Jasmin Mecinovic;Demetri T. Moustakas;Samuel W. Thomas

  • Large-Scale Systematic Analysis of 2D Fingerprint Methods and Parameters to Improve Virtual Screening Enrichments

    G. Madhavi Sastry;Jeffrey F. Lowrie;Steven L. Dixon;Woody Sherman

  • Water networks contribute to enthalpy/entropy compensation in protein-ligand binding.

    Benjamin Breiten;Matthew R. Lockett;Woody Sherman;Shuji Fujita

  • Improving the Prediction of Absolute Solvation Free Energies Using the Next Generation OPLS Force Field.

    Devleena Shivakumar;Edward Harder;Wolfgang Damm;Richard A Friesner

  • Novel method for generating structure-based pharmacophores using energetic analysis.

    Noeris K. Salam;Roberto Nuti;Woody Sherman

  • Alchemical Binding Free Energy Calculations in AMBER20: Advances and Best Practices for Drug Discovery.

    Tai Sung Lee;Bryce K. Allen;Timothy J. Giese;Zhenyu Guo

  • Applying physics-based scoring to calculate free energies of binding for single amino acid mutations in protein-protein complexes.

    Hege Beard;Anuradha Cholleti;David Pearlman;Woody Sherman

  • Rapid shape-based ligand alignment and virtual screening method based on atom/feature-pair similarities and volume overlap scoring.

    G. Madhavi Sastry;Steven L. Dixon;Woody Sherman

  • Modeling Local Structural Rearrangements Using FEP/REST: Application to Relative Binding Affinity Predictions of CDK2 Inhibitors.

    Lingle Wang;Yuqing Deng;Jennifer L. Knight;Yujie Wu

  • Affinity enhancement of an in vivo matured therapeutic antibody using structure-based computational design

    Louis A. Clark;P. Ann Boriack-Sjodin;John Eldredge;Christopher Fitch

Frequent Co-Authors

Richard A. Friesner
Richard A. Friesner Columbia University
George M. Whitesides
George M. Whitesides Harvard University
Michael K. Gilson
Michael K. Gilson University of California, San Diego
F. Matthias Bickelhaupt
F. Matthias Bickelhaupt Vrije Universiteit Amsterdam
Adriaan P. IJzerman
Adriaan P. IJzerman Leiden University
Wolfgang Sippl
Wolfgang Sippl Martin Luther University Halle-Wittenberg
Lila M. Gierasch
Lila M. Gierasch University of Massachusetts Amherst
Jiri Gut
Jiri Gut University of California, San Francisco
Rebecca C. Wade
Rebecca C. Wade Heidelberg Institute for Theoretical Studies

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