Ruth Nussinov

73.3k total citations · 21 hit papers
795 papers, 54.6k citations indexed

About

Ruth Nussinov is a scholar working on Molecular Biology, Materials Chemistry and Computational Theory and Mathematics. According to data from OpenAlex, Ruth Nussinov has authored 795 papers receiving a total of 54.6k indexed citations (citations by other indexed papers that have themselves been cited), including 716 papers in Molecular Biology, 159 papers in Materials Chemistry and 100 papers in Computational Theory and Mathematics. Recurrent topics in Ruth Nussinov's work include Protein Structure and Dynamics (303 papers), RNA and protein synthesis mechanisms (160 papers) and Enzyme Structure and Function (152 papers). Ruth Nussinov is often cited by papers focused on Protein Structure and Dynamics (303 papers), RNA and protein synthesis mechanisms (160 papers) and Enzyme Structure and Function (152 papers). Ruth Nussinov collaborates with scholars based in United States, Israel and China. Ruth Nussinov's co-authors include Buyong Ma, Haim J. Wolfson, Chung‐Jung Tsai, Sandeep Kumar, Hyunbum Jang, Özlem Keskin, Dina Schneidman‐Duhovny, Attila Gürsoy, Yoel Inbar and Kannan Gunasekaran and has published in prestigious journals such as Cell, Chemical Reviews and Proceedings of the National Academy of Sciences.

In The Last Decade

Ruth Nussinov

786 papers receiving 53.8k citations

Hit Papers

PatchDock and SymmDock: servers for rigid and symmetric d... 1994 2026 2004 2015 2005 2009 1994 2002 2000 500 1000 1.5k 2.0k
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.

  1. PatchDock and SymmDock: servers for rigid and symmetric docking
    2005 2.4k citations Ruth Nussinov, Haim J. Wolfson et al. Nucleic Acids Research profile →
  2. The role of dynamic conformational ensembles in biomolecular recognition
    2009 1.6k citations Ruth Nussinov et al. profile →
  3. Shape complementarity at protein–protein interfaces
    1994 1.1k citations Haim J. Wolfson, Ruth Nussinov et al. profile →
  4. Principles of docking: An overview of search algorithms and a guide to scoring functions
    2002 921 citations Buyong Ma, Haim J. Wolfson et al. profile →
  5. Factors enhancing protein thermostability
    2000 783 citations Sandeep Kumar, Ruth Nussinov et al. profile →
  6. Is allostery an intrinsic property of all dynamic proteins?
    2004 725 citations Buyong Ma, Ruth Nussinov et al. profile →
  7. Aβ(1–42) fibril structure illuminates self-recognition and replication of amyloid in Alzheimer's disease
    2015 698 citations Yiling Xiao, Buyong Ma et al. Nature Structural & Molecular Biology profile →
  8. Induced fit, conformational selection and independent dynamic segments: an extended view of binding events
    2010 657 citations Ruth Nussinov et al. profile →
  9. Structure and dynamics of molecular networks: A novel paradigm of drug discovery
    2013 602 citations Ruth Nussinov et al. profile →
  10. FireDock: a web server for fast interaction refinement in molecular docking
    2008 579 citations Ruth Nussinov, Haim J. Wolfson et al. Nucleic Acids Research profile →
  11. Allostery in Disease and in Drug Discovery
    2013 564 citations Ruth Nussinov, Chung‐Jung Tsai profile →
  12. FireDock: Fast interaction refinement in molecular docking
    2007 559 citations Ruth Nussinov, Haim J. Wolfson et al. profile →
  13. Folding funnels, binding funnels, and protein function
    1999 526 citations Chung‐Jung Tsai, Sandeep Kumar et al. Protein Science profile →
  14. Principles of Protein−Protein Interactions: What are the Preferred Ways For Proteins To Interact?
    2008 517 citations Özlem Keskin, Attila Gürsoy et al. Chemical Reviews profile →
  15. Folding and binding cascades: Dynamic landscapes and population shifts
    2000 509 citations Sandeep Kumar, Buyong Ma et al. Protein Science profile →
  16. deepDR: a network-based deep learning approach toin silicodrug repositioning
    2019 374 citations Xiangxiang Zeng, Ruth Nussinov et al. profile →
  17. Anticancer drug resistance: An update and perspective
    2021 272 citations Ruth Nussinov, Chung‐Jung Tsai et al. profile →
  18. Target identification among known drugs by deep learning from heterogeneous networks
    2020 257 citations Xiangxiang Zeng, Ruth Nussinov et al. profile →
  19. Accurate prediction of molecular properties and drug targets using a self-supervised image representation learning framework
    2022 160 citations Xiangxiang Zeng, Kenli Li et al. profile →
  20. Deep generative molecular design reshapes drug discovery
    2022 145 citations Xiangxiang Zeng, Ruth Nussinov et al. profile →
  21. Molecular principles underlying aggressive cancers
    2025 17 citations Ruth Nussinov, Hyunbum Jang et al. Signal Transduction and Targeted Therapy profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ruth Nussinov United States 112 44.1k 10.6k 9.9k 6.0k 3.5k 795 54.6k
Erik Lindahl Sweden 54 40.9k 0.9× 12.0k 1.1× 5.0k 0.5× 2.6k 0.4× 3.1k 0.9× 197 71.6k
David Eisenberg United States 120 46.7k 1.1× 10.0k 0.9× 3.4k 0.3× 12.3k 2.1× 2.5k 0.7× 409 62.2k
Janet M. Thornton United Kingdom 117 70.9k 1.6× 20.5k 1.9× 7.1k 0.7× 2.8k 0.5× 4.5k 1.3× 488 92.5k
David van der Spoel Sweden 57 31.8k 0.7× 12.3k 1.2× 4.3k 0.4× 2.1k 0.4× 2.6k 0.7× 168 61.7k
Tom Darden United States 28 33.8k 0.8× 9.7k 0.9× 4.4k 0.4× 2.0k 0.3× 3.0k 0.9× 49 55.7k
David A. Case United States 96 52.2k 1.2× 14.9k 1.4× 9.8k 1.0× 1.9k 0.3× 5.2k 1.5× 340 81.1k
Alexander D. MacKerell United States 93 38.9k 0.9× 9.1k 0.9× 5.5k 0.6× 1.5k 0.3× 2.4k 0.7× 473 57.6k
Andrej Săli United States 107 50.4k 1.1× 11.4k 1.1× 4.8k 0.5× 1.6k 0.3× 4.5k 1.3× 381 66.1k
Jeremy C. Smith United States 92 32.0k 0.7× 7.8k 0.7× 3.3k 0.3× 1.7k 0.3× 4.2k 1.2× 848 58.8k
J. Andrew McCammon United States 118 50.8k 1.2× 13.7k 1.3× 9.7k 1.0× 1.4k 0.2× 2.6k 0.7× 841 71.8k

Countries citing papers authored by Ruth Nussinov

Since Specialization
Citations

This map shows the geographic impact of Ruth Nussinov'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 Ruth Nussinov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ruth Nussinov more than expected).

Fields of papers citing papers by Ruth Nussinov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ruth Nussinov. 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 Ruth Nussinov. The network helps show where Ruth Nussinov may publish in the future.

Co-authorship network of co-authors of Ruth Nussinov

This figure shows the co-authorship network connecting the top 25 collaborators of Ruth Nussinov. A scholar is included among the top collaborators of Ruth Nussinov 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 Ruth Nussinov. Ruth Nussinov is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Nussinov, Ruth, et al.. (2025). Allostery in Disease: Anticancer Drugs, Pockets, and the Tumor Heterogeneity Challenge. Journal of Molecular Biology. 437(20). 169050–169050. 4 indexed citations
2.
Liu, Yonglan, Wengang Zhang, Hyunbum Jang, & Ruth Nussinov. (2025). mTOR Variants Activation Discovers PI3K-like Cryptic Pocket, Expanding Allosteric, Mutant-Selective Inhibitor Designs. Journal of Chemical Information and Modeling. 65(2). 966–980. 3 indexed citations
3.
Xu, Junlin, Changcheng Lu, Shuting Jin, et al.. (2025). Deep learning-based cell-specific gene regulatory networks inferred from single-cell multiome data. Nucleic Acids Research. 53(5). 8 indexed citations
4.
Nussinov, Ruth, et al.. (2025). Molecular principles underlying aggressive cancers. Signal Transduction and Targeted Therapy. 10(1). 42–42. 17 indexed citations breakdown →
5.
Nussinov, Ruth, Thomas Weichhart, Zodwa Dlamini, et al.. (2024). Directions to overcome therapy resistance in cancer. Trends in Pharmacological Sciences. 45(6). 467–471. 7 indexed citations
6.
Zeng, Li, Kenli Li, Zhimin Fu, et al.. (2024). A molecular video-derived foundation model for scientific drug discovery. Nature Communications. 15(1). 9696–9696. 17 indexed citations
7.
Ma, Buyong, et al.. (2021). Conformational Ensemble of TteAdoCbl Riboswitch Provides Stable Structural Elements for Conformation Selection and Population Shift in Cobalamin Recognition. The Journal of Physical Chemistry B. 125(10). 2589–2596. 6 indexed citations
8.
He, Yanan, Pragati Agnihotri, Sneha Rangarajan, et al.. (2020). Peptide–MHC Binding Reveals Conserved Allosteric Sites in MHC Class I- and Class II-Restricted T Cell Receptors (TCRs). Journal of Molecular Biology. 432(24). 166697–166697. 12 indexed citations
9.
Yang, Xinping, Hui Cheng, Jianhong Chen, et al.. (2019). Head and Neck Cancers Promote an Inflammatory Transcriptome through Coactivation of Classic and Alternative NF-κB Pathways. Cancer Immunology Research. 7(11). 1760–1774. 26 indexed citations
10.
Ruff, William, Carina Dehner, Odelya E. Pagovich, et al.. (2019). Pathogenic Autoreactive T and B Cells Cross-React with Mimotopes Expressed by a Common Human Gut Commensal to Trigger Autoimmunity. Cell Host & Microbe. 26(1). 100–113.e8. 109 indexed citations
11.
Zhang, Mingzhen, Zhigang Li, Hyunbum Jang, et al.. (2018). Calmodulin (CaM) Activates PI3Kα by Targeting the “Soft” CaM-Binding Motifs in Both the nSH2 and cSH2 Domains of p85α. The Journal of Physical Chemistry B. 122(49). 11137–11146. 16 indexed citations
12.
Tsai, Chung‐Jung & Ruth Nussinov. (2017). Allostery modulates the beat rate of a cardiac pacemaker. Journal of Biological Chemistry. 292(15). 6429–6430. 6 indexed citations
13.
Nussinov, Ruth. (2016). Introduction to Protein Ensembles and Allostery. Chemical Reviews. 116(11). 6263–6266. 99 indexed citations
14.
Xiao, Yiling, Buyong Ma, Dan McElheny, et al.. (2015). Aβ(1–42) fibril structure illuminates self-recognition and replication of amyloid in Alzheimer's disease. Nature Structural & Molecular Biology. 22(6). 499–505. 698 indexed citations breakdown →
15.
Gazit, Ehud & Ruth Nussinov. (2008). Nanostructure Design. Methods in molecular biology. 474. v–vii. 6 indexed citations
16.
Shulman‐Peleg, Alexandra, Ruth Nussinov, & Haim J. Wolfson. (2004). Recognition of Functional Sites in Protein Structures. Journal of Molecular Biology. 339(3). 607–633. 214 indexed citations
17.
Ma, Buyong & Ruth Nussinov. (2002). Molecular dynamics simulations of alanine rich β‐sheet oligomers: Insight into amyloid formation. Protein Science. 11(10). 2335–2350. 142 indexed citations
18.
Kumar, Sandeep & Ruth Nussinov. (2001). How do thermophilic proteins deal with heat?. Cellular and Molecular Life Sciences. 58(9). 1216–1233. 350 indexed citations
19.
Fischer, Daniel, Haim J. Wolfson, & Ruth Nussinov. (1993). Spatial, Sequence-Order-Independent Structural Comparison of α/β Proteins: Evolutionaiy Implications. Journal of Biomolecular Structure and Dynamics. 11(2). 367–380. 8 indexed citations
20.
Nussinov, Ruth, Akinori Sarai, Gary W. Smythers, David Wang, & Robert L. Jernigan. (1989). Strong Patterns in Homooligomer Tracts Occurrences in Non-Coding and in Potential Regulatory Sites in Eukaryotic Genomes. Journal of Biomolecular Structure and Dynamics. 7(3). 707–722. 6 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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