Anh‐Tien Ton

1.9k total citations · 3 hit papers
13 papers, 1.2k citations indexed

About

Anh‐Tien Ton is a scholar working on Molecular Biology, Computational Theory and Mathematics and Materials Chemistry. According to data from OpenAlex, Anh‐Tien Ton has authored 13 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 7 papers in Computational Theory and Mathematics and 5 papers in Materials Chemistry. Recurrent topics in Anh‐Tien Ton's work include Computational Drug Discovery Methods (7 papers), vaccines and immunoinformatics approaches (3 papers) and Protein Structure and Dynamics (3 papers). Anh‐Tien Ton is often cited by papers focused on Computational Drug Discovery Methods (7 papers), vaccines and immunoinformatics approaches (3 papers) and Protein Structure and Dynamics (3 papers). Anh‐Tien Ton collaborates with scholars based in Canada, United Kingdom and United States. Anh‐Tien Ton's co-authors include Artem Cherkasov, Fuqiang Ban, Francesco Gentile, Michael Hsing, Michael Fernández, Martin Gleave, Ulf Norinder, Abraham C. Stern, N.C.J. Strynadka and L.J. Worrall and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and Annals of Neurology.

In The Last Decade

Anh‐Tien Ton

13 papers receiving 1.2k citations

Hit Papers

Rapid Identification of Potential Inhibitors of SARS‐CoV‐... 2020 2026 2022 2024 2020 2020 2022 100 200 300
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. Rapid Identification of Potential Inhibitors of SARS‐CoV‐2 Main Protease by Deep Docking of 1.3 Billion Compounds
    2020 382 citations Anh‐Tien Ton, Francesco Gentile et al. Molecular Informatics profile →
  2. Deep Docking: A Deep Learning Platform for Augmentation of Structure Based Drug Discovery
    2020 259 citations Francesco Gentile, Michael Hsing et al. ACS Central Science profile →
  3. Artificial intelligence–enabled virtual screening of ultra-large chemical libraries with deep docking
    2022 218 citations Francesco Gentile, Michael Fernández et al. Nature Protocols profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Anh‐Tien Ton Canada 12 802 614 386 210 146 13 1.2k
Kaifu Gao United States 17 682 0.9× 659 1.1× 459 1.2× 257 1.2× 105 0.7× 30 1.3k
Michael Hsing Canada 19 600 0.7× 950 1.5× 266 0.7× 178 0.8× 101 0.7× 35 1.6k
Francesco Gentile Canada 17 894 1.1× 849 1.4× 378 1.0× 258 1.2× 162 1.1× 42 1.6k
Adrià Cereto‐Massagué Spain 12 872 1.1× 781 1.3× 181 0.5× 252 1.2× 168 1.2× 20 1.4k
Ana C. Puhl United States 16 378 0.5× 494 0.8× 141 0.4× 165 0.8× 72 0.5× 48 1.0k
Andrea Zaliani Germany 17 737 0.9× 1.1k 1.9× 185 0.5× 310 1.5× 216 1.5× 63 1.8k
Kunqian Yu China 23 326 0.4× 844 1.4× 144 0.4× 197 0.9× 211 1.4× 56 1.4k
María José Ojeda Spain 12 778 1.0× 677 1.1× 140 0.4× 244 1.2× 143 1.0× 20 1.3k
Barry A. Bunin United States 17 491 0.6× 841 1.4× 232 0.6× 100 0.5× 439 3.0× 26 1.3k
Woong‐Hee Shin South Korea 18 455 0.6× 756 1.2× 108 0.3× 174 0.8× 89 0.6× 43 1.1k

Countries citing papers authored by Anh‐Tien Ton

Since Specialization
Citations

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

Fields of papers citing papers by Anh‐Tien Ton

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Anh‐Tien Ton. 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 Anh‐Tien Ton. The network helps show where Anh‐Tien Ton may publish in the future.

Co-authorship network of co-authors of Anh‐Tien Ton

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

All Works

13 of 13 papers shown
1.
Ton, Anh‐Tien, Shoeib Moradi, Jason R. Smith, et al.. (2023). Large-Scale Virtual Screening for the Discovery of SARS-CoV-2 Papain-like Protease (PLpro) Non-covalent Inhibitors. Journal of Chemical Information and Modeling. 63(7). 2158–2169. 11 indexed citations
2.
Lee, Jaeyong, L.J. Worrall, M. Vuckovic, et al.. (2022). X-ray crystallographic characterization of the SARS-CoV-2 main protease polyprotein cleavage sites essential for viral processing and maturation. Nature Communications. 13(1). 5196–5196. 54 indexed citations
3.
Gentile, Francesco, Michael Fernández, Anh‐Tien Ton, et al.. (2022). Artificial intelligence–enabled virtual screening of ultra-large chemical libraries with deep docking. Nature Protocols. 17(3). 672–697. 218 indexed citations breakdown →
4.
Ton, Anh‐Tien, Mohit Pandey, Jason R. Smith, et al.. (2022). Targeting SARS-CoV-2 papain-like protease in the postvaccine era. Trends in Pharmacological Sciences. 43(11). 906–919. 32 indexed citations
5.
Ton, Anh‐Tien, Jane Foo, Kriti Singh, et al.. (2022). Development of VPC-70619, a Small-Molecule N-Myc Inhibitor as a Potential Therapy for Neuroendocrine Prostate Cancer. International Journal of Molecular Sciences. 23(5). 2588–2588. 10 indexed citations
6.
Ton, Anh‐Tien, et al.. (2021). Drugging the ‘undruggable’. Therapeutic targeting of protein–DNA interactions with the use of computer-aided drug discovery methods. Drug Discovery Today. 26(11). 2660–2679. 30 indexed citations
7.
Gentile, Francesco, Michael Fernández, Fuqiang Ban, et al.. (2021). Automated discovery of noncovalent inhibitors of SARS-CoV-2 main protease by consensus Deep Docking of 40 billion small molecules. Chemical Science. 12(48). 15960–15974. 46 indexed citations
8.
Gentile, Francesco, Michael Hsing, Anh‐Tien Ton, et al.. (2020). Deep Docking: A Deep Learning Platform for Augmentation of Structure Based Drug Discovery. ACS Central Science. 6(6). 939–949. 259 indexed citations breakdown →
9.
Lee, Jaeyong, L.J. Worrall, M. Vuckovic, et al.. (2020). Crystallographic structure of wild-type SARS-CoV-2 main protease acyl-enzyme intermediate with physiological C-terminal autoprocessing site. Nature Communications. 11(1). 5877–5877. 154 indexed citations
10.
Ton, Anh‐Tien, Francesco Gentile, Michael Hsing, Fuqiang Ban, & Artem Cherkasov. (2020). Rapid Identification of Potential Inhibitors of SARS‐CoV‐2 Main Protease by Deep Docking of 1.3 Billion Compounds. Molecular Informatics. 39(8). e2000028–e2000028. 382 indexed citations breakdown →
11.
Ton, Anh‐Tien, Hélène Morin, Fuqiang Ban, et al.. (2020). Dual-Inhibitors of N-Myc and AURKA as Potential Therapy for Neuroendocrine Prostate Cancer. International Journal of Molecular Sciences. 21(21). 8277–8277. 20 indexed citations
12.
Khoury, Samar, Marjo Piltonen, Anh‐Tien Ton, et al.. (2019). A functional substitution in the L‐aromatic amino acid decarboxylase enzyme worsens somatic symptoms via a serotonergic pathway. Annals of Neurology. 86(2). 168–180. 11 indexed citations
13.
Cappadocia, Laurent, Anh‐Tien Ton, Riham Ayoubi, et al.. (2017). Molecular basis of interactions between SH3 domain-containing proteins and the proline-rich region of the ubiquitin ligase Itch. Journal of Biological Chemistry. 292(15). 6325–6338. 13 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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