Hongmao Sun

3.2k total citations
48 papers, 2.2k citations indexed

About

Hongmao Sun is a scholar working on Molecular Biology, Computational Theory and Mathematics and Oncology. According to data from OpenAlex, Hongmao Sun has authored 48 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 26 papers in Computational Theory and Mathematics and 7 papers in Oncology. Recurrent topics in Hongmao Sun's work include Computational Drug Discovery Methods (26 papers), Analytical Chemistry and Chromatography (6 papers) and Pharmacogenetics and Drug Metabolism (5 papers). Hongmao Sun is often cited by papers focused on Computational Drug Discovery Methods (26 papers), Analytical Chemistry and Chromatography (6 papers) and Pharmacogenetics and Drug Metabolism (5 papers). Hongmao Sun collaborates with scholars based in United States, Switzerland and China. Hongmao Sun's co-authors include Anders Wallqvist, Gregory J. Tawa, Junzhou Huang, Yuhong Wang, Ruili Huang, Sheng Wang, Yuzhi Guo, Menghang Xia, Ajit Jadhav and Christopher P. Austin and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and FEBS Letters.

In The Last Decade

Hongmao Sun

48 papers receiving 2.2k citations

Peers

Hongmao Sun
Oliver Korb United Kingdom
Erin S. D. Bolstad United States
Alexander Hillisch Germany
Sun Choi South Korea
William R. Pitt United Kingdom
Daniel Seeliger Germany
James M. Woolven United Kingdom
Paul Labute Canada
Paul C. D. Hawkins United States
María Paula Magariños Argentina
Oliver Korb United Kingdom
Hongmao Sun
Citations per year, relative to Hongmao Sun Hongmao Sun (= 1×) peers Oliver Korb

Countries citing papers authored by Hongmao Sun

Since Specialization
Citations

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

Fields of papers citing papers by Hongmao Sun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hongmao Sun

This figure shows the co-authorship network connecting the top 25 collaborators of Hongmao Sun. A scholar is included among the top collaborators of Hongmao Sun 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 Hongmao Sun. Hongmao Sun 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.
Cuellar, Matthew E., Karavadhi Surendra, Yaqin Zhang, et al.. (2023). An electrophilic fragment screening for the development of small molecules targeting caspase-2. European Journal of Medicinal Chemistry. 259. 115632–115632. 3 indexed citations
2.
Fang, Yuhong, Dingyin Tao, Hongmao Sun, et al.. (2022). Discovery of Novel Small-Molecule Scaffolds for the Inhibition and Activation of WIP1 Phosphatase from a RapidFire Mass Spectrometry High-Throughput Screen. ACS Pharmacology & Translational Science. 5(10). 993–1006. 7 indexed citations
3.
Challa, Anup P., Xin Hu, Yaqin Zhang, et al.. (2022). Virtual Screening for the Discovery of Microbiome β-Glucuronidase Inhibitors to Alleviate Cancer Drug Toxicity. Journal of Chemical Information and Modeling. 62(7). 1783–1793. 9 indexed citations
4.
Sun, Hongmao, Nathan P. Coussens, Carina Danchik, et al.. (2022). Discovery of Small-Molecule VapC1 Nuclease Inhibitors by Virtual Screening and Scaffold Hopping from an Atomic Structure Revealing Protein–Protein Interactions with a Native VapB1 Inhibitor. Journal of Chemical Information and Modeling. 62(5). 1249–1258. 3 indexed citations
5.
Scoles, Daniel R., Mandi Gandelman, Sharan Paul, et al.. (2022). A quantitative high-throughput screen identifies compounds that lower expression of the SCA2-and ALS-associated gene ATXN2. Journal of Biological Chemistry. 298(8). 102228–102228. 9 indexed citations
6.
Gandelman, Mandi, Warunee Dansithong, Stephen C. Kales, et al.. (2021). The AKT modulator A-443654 reduces α-synuclein expression and normalizes ER stress and autophagy. Journal of Biological Chemistry. 297(4). 101191–101191. 13 indexed citations
7.
Sun, Hongmao, Yuhong Wang, Catherine Z. Chen, et al.. (2021). Identification of SARS-CoV-2 viral entry inhibitors using machine learning and cell-based pseudotyped particle assay. Bioorganic & Medicinal Chemistry. 38. 116119–116119. 7 indexed citations
8.
Sun, Hongmao, et al.. (2020). Predictive models for estimating cytotoxicity on the basis of chemical structures. Bioorganic & Medicinal Chemistry. 28(10). 115422–115422. 25 indexed citations
9.
Sun, Hongmao, Edward H. Kerns, Zhengyin Yan, et al.. (2017). Highly predictive and interpretable models for PAMPA permeability. Bioorganic & Medicinal Chemistry. 25(3). 1266–1276. 81 indexed citations
10.
Sun, Hongmao, Ruili Huang, Menghang Xia, et al.. (2016). Prediction of hERG Liability – Using SVM Classification, Bootstrapping and Jackknifing. Molecular Informatics. 36(4). 29 indexed citations
11.
Murai, Junko, Christophe Marchand, Sampada A. Shahane, et al.. (2014). Identification of novel PARP inhibitors using a cell-based TDP1 inhibitory assay in a quantitative high-throughput screening platform. DNA repair. 21. 177–182. 20 indexed citations
12.
Sun, Hongmao, Menghang Xia, Sampada A. Shahane, et al.. (2013). Are hERG channel blockers also phospholipidosis inducers?. Bioorganic & Medicinal Chemistry Letters. 23(16). 4587–4590. 28 indexed citations
13.
Srinivasan, P., Adam Yasgar, Diane K. Luci, et al.. (2013). Disrupting malaria parasite AMA1–RON2 interaction with a small molecule prevents erythrocyte invasion. Nature Communications. 4(1). 2261–2261. 86 indexed citations
14.
Chen, Yi, Zhi Chen, Romyr Dominique, et al.. (2013). Pyrido[2,3-d]pyrimidines: Discovery and preliminary SAR of a novel series of DYRK1B and DYRK1A inhibitors. Bioorganic & Medicinal Chemistry Letters. 23(24). 6610–6615. 48 indexed citations
15.
Singh, Narender, Hongmao Sun, Sidhartha Chaudhury, et al.. (2012). A physicochemical descriptor-based scoring scheme for effective and rapid filtering of kinase-like chemical space. Journal of Cheminformatics. 4(1). 4–4. 20 indexed citations
16.
Sun, Hongmao, Gregory J. Tawa, & Anders Wallqvist. (2011). Classification of scaffold-hopping approaches. Drug Discovery Today. 17(7-8). 310–324. 290 indexed citations
17.
Sun, Hongmao. (2008). Pharmacophore-Based Virtual Screening. Current Medicinal Chemistry. 15(10). 1018–1024. 122 indexed citations
18.
Sun, Hongmao & David C. Fry. (2007). Molecular Modeling of Melanocortin Receptors. Current Topics in Medicinal Chemistry. 7(11). 1042–1051. 5 indexed citations
19.
Sun, Hongmao, Xin‐Jie Chu, Waleed Danho, et al.. (2004). A predictive pharmacophore model of human melanocortin-4 receptor as derived from the solution structures of cyclic peptides. Bioorganic & Medicinal Chemistry. 12(10). 2671–2677. 16 indexed citations
20.

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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