Ivan Tubert‐Brohman

2.3k total citations · 1 hit paper
13 papers, 1.8k citations indexed

About

Ivan Tubert‐Brohman is a scholar working on Molecular Biology, Computational Theory and Mathematics and Materials Chemistry. According to data from OpenAlex, Ivan Tubert‐Brohman has authored 13 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 6 papers in Computational Theory and Mathematics and 4 papers in Materials Chemistry. Recurrent topics in Ivan Tubert‐Brohman's work include Computational Drug Discovery Methods (5 papers), Chemical Synthesis and Analysis (3 papers) and Protein Structure and Dynamics (3 papers). Ivan Tubert‐Brohman is often cited by papers focused on Computational Drug Discovery Methods (5 papers), Chemical Synthesis and Analysis (3 papers) and Protein Structure and Dynamics (3 papers). Ivan Tubert‐Brohman collaborates with scholars based in United States and Switzerland. Ivan Tubert‐Brohman's co-authors include Woody Sherman, Thijs Beuming, William L. Jorgensen, Cristiano R. W. Guimarães, Matthew P. Repasky, Sathesh Bhat, Jeremy R. Greenwood, Richard A. Friesner, Orlando Acevedo and Robert B. Murphy and has published in prestigious journals such as Journal of the American Chemical Society, Journal of Biological Chemistry and Journal of Medicinal Chemistry.

In The Last Decade

Ivan Tubert‐Brohman

13 papers receiving 1.7k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Improved Docking of Polypeptides with Glide

2013 1.0k citations Ivan Tubert‐Brohman, Woody Sherman et al. Journal of Chemical Information and Modeling profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Ivan Tubert‐Brohman United States	13	506	304	245	176	168	13	1.8k
Chang‐Hwan Lee South Korea	35	414 0.8×	80 0.3×	161 0.7×	213 1.2×	251 1.5×	227	4.3k
Patrick Bryant United States	21	897 1.8×	148 0.5×	350 1.4×	59 0.3×	193 1.1×	68	2.1k
Shikha Gupta India	21	148 0.3×	468 1.5×	277 1.1×	100 0.6×	129 0.8×	83	1.4k
Guang Wu China	25	1.1k 2.2×	91 0.3×	261 1.1×	294 1.7×	60 0.4×	300	3.0k
Jiang Wang United States	30	584 1.2×	297 1.0×	1.0k 4.3×	289 1.6×	203 1.2×	83	3.1k
Mohammed Talbi Morocco	25	405 0.8×	77 0.3×	226 0.9×	150 0.9×	78 0.5×	159	2.4k
Thijs Beuming United States	30	2.5k 4.9×	738 2.4×	325 1.3×	239 1.4×	102 0.6×	47	3.9k
Xiao Li China	30	736 1.5×	539 1.8×	136 0.6×	142 0.8×	22 0.1×	169	2.8k
Lorentz Jäntschi Romania	23	170 0.3×	379 1.2×	129 0.5×	136 0.8×	31 0.2×	223	1.9k
Hiroshi Fujita Japan	24	320 0.6×	87 0.3×	370 1.5×	338 1.9×	107 0.6×	209	2.5k

Countries citing papers authored by Ivan Tubert‐Brohman

Since Specialization

Citations

This map shows the geographic impact of Ivan Tubert‐Brohman's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ivan Tubert‐Brohman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ivan Tubert‐Brohman more than expected).

Fields of papers citing papers by Ivan Tubert‐Brohman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ivan Tubert‐Brohman. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ivan Tubert‐Brohman. The network helps show where Ivan Tubert‐Brohman may publish in the future.

Co-authorship network of co-authors of Ivan Tubert‐Brohman

This figure shows the co-authorship network connecting the top 25 collaborators of Ivan Tubert‐Brohman. A scholar is included among the top collaborators of Ivan Tubert‐Brohman based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ivan Tubert‐Brohman. Ivan Tubert‐Brohman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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13 of 13 papers shown

Konze, Kyle D., Pieter H. Bos, Markus K. Dahlgren, et al.. (2019). Reaction-Based Enumeration, Active Learning, and Free Energy Calculations To Rapidly Explore Synthetically Tractable Chemical Space and Optimize Potency of Cyclin-Dependent Kinase 2 Inhibitors. Journal of Chemical Information and Modeling. 59(9). 3782–3793. 91 indexed citations

Murphy, Robert B., Matthew P. Repasky, Jeremy R. Greenwood, et al.. (2016). WScore: A Flexible and Accurate Treatment of Explicit Water Molecules in Ligand–Receptor Docking. Journal of Medicinal Chemistry. 59(9). 4364–4384. 64 indexed citations

Tubert‐Brohman, Ivan, et al.. (2013). Improved Docking of Polypeptides with Glide. Journal of Chemical Information and Modeling. 53(7). 1689–1699. 1024 indexed citations breakdown →

Repasky, Matthew P., Robert B. Murphy, Jay L. Banks, et al.. (2012). Docking performance of the glide program as evaluated on the Astex and DUD datasets: a complete set of glide SP results and selected results for a new scoring function integrating WaterMap and glide. Journal of Computer-Aided Molecular Design. 26(6). 787–799. 129 indexed citations

Lütz, Stephan, Ivan Tubert‐Brohman, Yonggang Yang, & Markus Meuwly. (2011). Water-assisted Proton Transfer in Ferredoxin I. Journal of Biological Chemistry. 286(27). 23679–23687. 15 indexed citations

Tubert‐Brohman, Ivan, et al.. (2009). Molecular Mechanics Force Field for Octahedral Organometallic Compounds with Inclusion of the Trans Influence. Journal of Chemical Theory and Computation. 5(3). 530–539. 31 indexed citations

Truncik, C. J. S., et al.. (2008). Construction of model Hamiltonians for adiabatic quantum computation and its application to finding low-energy conformations of lattice protein models. Physical Review A. 78(1). 72 indexed citations

Barreiro, Gabriela, et al.. (2007). Search for Non-Nucleoside Inhibitors of HIV-1 Reverse Transcriptase Using Chemical Similarity, Molecular Docking, and MM-GB/SA Scoring. Journal of Chemical Information and Modeling. 47(6). 2416–2428. 75 indexed citations

Tubert‐Brohman, Ivan, Orlando Acevedo, & William L. Jorgensen. (2006). Elucidation of Hydrolysis Mechanisms for Fatty Acid Amide Hydrolase and Its Lys142Ala Variant via QM/MM Simulations. Journal of the American Chemical Society. 128(51). 16904–16913. 73 indexed citations

10.

Sattelmeyer, Kurt W., Ivan Tubert‐Brohman, & William L. Jorgensen. (2006). NO-MNDO: Reintroduction of the Overlap Matrix into MNDO. Journal of Chemical Theory and Computation. 2(2). 413–419. 31 indexed citations

11.

Tubert‐Brohman, Ivan, Cristiano R. W. Guimarães, & William L. Jorgensen. (2005). Extension of the PDDG/PM3 Semiempirical Molecular Orbital Method to Sulfur, Silicon, and Phosphorus. Journal of Chemical Theory and Computation. 1(5). 817–823. 62 indexed citations

12.

Guimarães, Cristiano R. W., Marina Udier–Blagović, Ivan Tubert‐Brohman, & William L. Jorgensen. (2005). Effects of Arg90 Neutralization on the Enzyme-Catalyzed Rearrangement of Chorismate to Prephenate. Journal of Chemical Theory and Computation. 1(4). 617–625. 22 indexed citations

13.

Tubert‐Brohman, Ivan, Cristiano R. W. Guimarães, Matthew P. Repasky, & William L. Jorgensen. (2003). Extension of the PDDG/PM3 and PDDG/MNDO semiempirical molecular orbital methods to the halogens. Journal of Computational Chemistry. 25(1). 138–150. 66 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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