World's Best Scientists 2026 revealed!

D-Index & Metrics

Chemistry

D-Index
54
Citations
42208
World Ranking
12431
National Ranking
3312

Carlos Simmerling 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 Carlos Simmerling 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: 136 publications — 9th percentile

9% of scientists in this discipline score the same or lower.

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

Carlos Simmerling 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 Carlos Simmerling 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: 54 D-Index — 31st percentile

31% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2016 - Fellow of the American Chemical Society

Overview

Carlos Simmerling is affiliated with Stony Brook University in the United States. Their research primarily spans the fields of Biochemistry, Genetics and Molecular Biology, and Medicine. Within these broad areas, they focus on several subfields including Molecular Biology, Infectious Diseases, Materials Chemistry, Ecology, and Atomic and Molecular Physics, and Optics.

The main topics of Carlos Simmerling's work encompass Protein Structure and Dynamics, SARS-CoV-2 and COVID-19 Research, RNA and protein synthesis mechanisms, Enzyme Structure and Function, Bacteriophages and microbial interactions, COVID-19 Clinical Research Studies, and Photosynthetic Processes and Mechanisms.

Frequent co-authors include Darya Stepanenko, Lorenzo Casalino, Rommie E. Amaro, Evangelos A. Coutsias, and Lauren Raguette. These collaborations suggest ongoing partnerships with scholars active in molecular biology and computational simulations.

Carlos Simmerling has contributed a number of recent papers to scientific literature. Some notable publications are:

  • AmberTools, 2023, Journal of Chemical Information and Modeling
  • AI-driven multiscale simulations illuminate mechanisms of SARS-CoV-2 spike dynamics, 2021, The International Journal of High Performance Computing Applications
  • The flexibility of ACE2 in the context of SARS-CoV-2 infection, 2020, Biophysical Journal
  • SARS-CoV-2 spike conformation determines plasma neutralizing activity elicited by a wide panel of human vaccines, 2022, Science Immunology
  • Protein storytelling through physics, 2020, Science

Their publications appear regularly in journals such as bioRxiv (Cold Spring Harbor Laboratory), Journal of Chemical Theory and Computation, Biophysical Journal, Journal of Chemical Information and Modeling, and The Journal of Physical Chemistry B. Notably, the most frequent publication venues are bioRxiv with 9 publications and the Journal of Chemical Theory and Computation with 8 publications.

Carlos Simmerling was awarded the title of Fellow of the American Chemical Society in 2016.

Best Publications

  • The Amber biomolecular simulation programs

    David A. Case;Thomas E. Cheatham;Tom Darden;Holger Gohlke

  • ff14SB: Improving the Accuracy of Protein Side Chain and Backbone Parameters from ff99SB

    James A. Maier;Carmenza Martinez;Koushik Kasavajhala;Lauren Wickstrom

  • Comparison of multiple Amber force fields and development of improved protein backbone parameters.

    Viktor Hornak;Robert Abel;Asim Okur;Bentley Strockbine

  • ff19SB: Amino-Acid-Specific Protein Backbone Parameters Trained against Quantum Mechanics Energy Surfaces in Solution.

    Chuan Tian;Koushik Kasavajhala;Kellon A. A. Belfon;Lauren Raguette

  • AmberTools

    Unknown

  • All-Atom Structure Prediction and Folding Simulations of a Stable Protein

    Carlos Simmerling;Bentley Strockbine;Adrian E. Roitberg

  • Improved Generalized Born Solvent Model Parameters for Protein Simulations

    Hai Nguyen;Daniel R. Roe;Carlos Simmerling

  • Generalized Born Model with a Simple, Robust Molecular Volume Correction

    John Mongan;Carlos Simmerling;J. Andrew McCammon;David A. Case

  • HIV-1 protease flaps spontaneously open and reclose in molecular dynamics simulations

    Viktor Hornak;Asim Okur;Robert C. Rizzo;Carlos Simmerling

  • Three-Dimensional Molecular Theory of Solvation Coupled with Molecular Dynamics in Amber

    Tyler Luchko;Sergey Gusarov;Daniel R. Roe;Carlos Simmerling

  • Evaluating the performance of the ff99SB force field based on NMR scalar coupling data.

    Lauren Wickstrom;Asim Okur;Carlos Simmerling

  • Folding simulations for proteins with diverse topologies are accessible in days with a physics-based force field and implicit solvent.

    Hai Nguyen;James Maier;He Huang;Victoria Perrone

  • MOIL: A program for simulations of macromolecules

    Ron Elber;Ron Elber;Adrian Roitberg;Adrian Roitberg;Carlos Simmerling;Carlos Simmerling;Robert Goldstein

  • Improved Efficiency of Replica Exchange Simulations through Use of a Hybrid Explicit/Implicit Solvation Model

    Asim Okur;Lauren Wickstrom;Melinda Layten;Raphäel Geney

  • Secondary structure bias in generalized Born solvent models: comparison of conformational ensembles and free energy of solvent polarization from explicit and implicit solvation.

    Daniel R. Roe;Asim Okur;Lauren Wickstrom;Viktor Hornak

  • Inhibition of the Bacterial Enoyl Reductase FabI by Triclosan: A Structure−Reactivity Analysis of FabI Inhibition by Triclosan Analogues†

    Sharada Sivaraman;Todd J. Sullivan;Francis Johnson;Polina Novichenok

  • Structure of Acyl Carrier Protein Bound to FabI, the FASII Enoyl Reductase from Escherichia coli

    Salma Rafi;Polina Novichenok;Subramaniapillai Kolappan;Xujie Zhang

  • Advances in free-energy-based simulations of protein folding and ligand binding.

    Alberto Perez;Joseph A Morrone;Carlos Simmerling;Ken A Dill

  • Investigation of Salt Bridge Stability in a Generalized Born Solvent Model.

    Raphaël Geney;Melinda Layten;Roberto Gomperts;and Viktor Hornak

  • Modified replica exchange simulation methods for local structure refinement.

    Xiaolin Cheng;Guanglei Cui;Viktor Hornak;Carlos Simmerling

  • AI-driven multiscale simulations illuminate mechanisms of SARS-CoV-2 spike dynamics

    Lorenzo Casalino;Abigail C. Dommer;Zied Gaieb;Emilia P. Barros

  • Targeting structural flexibility in HIV-1 protease inhibitor binding

    Viktor Hornak;Carlos Simmerling

Frequent Co-Authors

Peter J. Tonge
Peter J. Tonge Stony Brook University
Adrian E. Roitberg
Adrian E. Roitberg University of Florida
Ron Elber
Ron Elber The University of Texas at Austin
Daniel P. Raleigh
Daniel P. Raleigh Stony Brook University
Arthur P. Grollman
Arthur P. Grollman Stony Brook University
Steven O. Smith
Steven O. Smith Stony Brook University
David A. Case
David A. Case Rutgers, The State University of New Jersey
Iwao Ojima
Iwao Ojima Stony Brook University
Kevin H. Gardner
Kevin H. Gardner City University of New York
Alberto Perez
Alberto Perez University of Florida

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