Kittikhun Wangkanont

1.5k total citations
41 papers, 1.1k citations indexed

About

Kittikhun Wangkanont is a scholar working on Molecular Biology, Organic Chemistry and Computational Theory and Mathematics. According to data from OpenAlex, Kittikhun Wangkanont has authored 41 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 10 papers in Organic Chemistry and 10 papers in Computational Theory and Mathematics. Recurrent topics in Kittikhun Wangkanont's work include Computational Drug Discovery Methods (10 papers), SARS-CoV-2 and COVID-19 Research (6 papers) and Invertebrate Immune Response Mechanisms (6 papers). Kittikhun Wangkanont is often cited by papers focused on Computational Drug Discovery Methods (10 papers), SARS-CoV-2 and COVID-19 Research (6 papers) and Invertebrate Immune Response Mechanisms (6 papers). Kittikhun Wangkanont collaborates with scholars based in Thailand, Japan and United States. Kittikhun Wangkanont's co-authors include Waranyoo Phoolcharoen, Balamurugan Shanmugaraj, Konlavat Siriwattananon, Laura L. Kiessling, Katrina T. Forest, Thanyada Rungrotmongkol, Darryl A. Wesener, Kowit Hengphasatporn, Yasuteru Shigeta and Erin E. Carlson and has published in prestigious journals such as Journal of Biological Chemistry, PLoS ONE and Analytical Chemistry.

In The Last Decade

Kittikhun Wangkanont

37 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kittikhun Wangkanont Thailand 14 453 318 185 182 99 41 1.1k
Gururao Hariprasad India 16 682 1.5× 648 2.0× 50 0.3× 139 0.8× 172 1.7× 54 1.6k
Masaud Shah South Korea 20 441 1.0× 384 1.2× 71 0.4× 379 2.1× 115 1.2× 57 1.2k
Jian Lei China 16 442 1.0× 762 2.4× 96 0.5× 194 1.1× 143 1.4× 42 1.5k
Ma’mon M. Hatmal Jordan 22 729 1.6× 364 1.1× 94 0.5× 85 0.5× 136 1.4× 61 1.7k
Shogo Misumi Japan 22 650 1.4× 313 1.0× 139 0.8× 172 0.9× 44 0.4× 84 1.4k
Nicola G. Wallis United Kingdom 23 908 2.0× 198 0.6× 317 1.7× 101 0.6× 217 2.2× 45 1.8k
Feifei Qi China 16 589 1.3× 889 2.8× 70 0.4× 208 1.1× 170 1.7× 33 1.6k
Ying‐Ta Wu Taiwan 19 696 1.5× 236 0.7× 397 2.1× 188 1.0× 179 1.8× 43 1.4k
Akihiro Sugawara Japan 18 404 0.9× 199 0.6× 291 1.6× 100 0.5× 40 0.4× 60 928
Yingjie Wang China 19 622 1.4× 290 0.9× 102 0.6× 90 0.5× 103 1.0× 53 1.2k

Countries citing papers authored by Kittikhun Wangkanont

Since Specialization
Citations

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

Fields of papers citing papers by Kittikhun Wangkanont

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kittikhun Wangkanont

This figure shows the co-authorship network connecting the top 25 collaborators of Kittikhun Wangkanont. A scholar is included among the top collaborators of Kittikhun Wangkanont 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 Kittikhun Wangkanont. Kittikhun Wangkanont 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.
Nishii, Yuji, Qing‐Feng Xu‐Xu, Masahiro Miura, et al.. (2025). Unveiling the antiviral inhibitory activity of ebselen and ebsulfur derivatives on SARS-CoV-2 using machine learning-based QSAR, LB-PaCS-MD, and experimental assay. Scientific Reports. 15(1). 6956–6956. 6 indexed citations
2.
Hengphasatporn, Kowit, et al.. (2025). Structure and catalytic activity of a dihydrofolate reductase-like enzyme from Leptospira interrogans. International Journal of Biological Macromolecules. 298. 139931–139931. 1 indexed citations
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Sanachai, Kamonpan, et al.. (2025). Design, synthesis, and antiviral activity of fragmented-lapatinib aminoquinazoline analogs towards SARS-CoV-2 inhibition. European Journal of Medicinal Chemistry. 286. 117303–117303. 3 indexed citations
6.
Saeeng, Rungnapha, et al.. (2025). Design and Evaluation of Andrographolide Analogues as SARS-CoV-2 Main Protease Inhibitors: Molecular Modeling and in vitro Studies. Drug Design Development and Therapy. Volume 19. 3907–3924. 2 indexed citations
7.
Khongchareonporn, Nanthika, Kiat Ruxrungtham, Chutitorn Ketloy, et al.. (2024). Overlaid Lateral Flow Immunoassay for the Simultaneous Detection of Two Variant-Specific SARS-CoV-2 Neutralizing Antibodies. Analytical Chemistry. 96(14). 5407–5415. 8 indexed citations
8.
Luckanagul, Jittima Amie, et al.. (2024). Optimizing protein delivery rate from silk fibroin hydrogel using silk fibroin-mimetic peptides conjugation. Scientific Reports. 14(1). 4428–4428. 4 indexed citations
9.
Wangkanont, Kittikhun, Kowit Hengphasatporn, Ryuhei Harada, et al.. (2024). Alpha and gamma mangostins inhibit wild-type B SARS-CoV-2 more effectively than the SARS-CoV-2 variants and the major target is unlikely the 3C-like protease. Heliyon. 10(11). e31987–e31987. 1 indexed citations
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Maiuthed, Arnatchai, Wongsakorn Phongsopitanun, Roonglawan Rattanajak, et al.. (2023). N-Containing α-Mangostin Analogs via Smiles Rearrangement as the Promising Cytotoxic, Antitrypanosomal, and SARS-CoV-2 Main Protease Inhibitory Agents. Molecules. 28(3). 1104–1104. 5 indexed citations
12.
Rungrotmongkol, Thanyada, et al.. (2023). Computational design of novel nanobodies targeting the receptor binding domain of variants of concern of SARS-CoV-2. PLoS ONE. 18(10). e0293263–e0293263. 8 indexed citations
13.
Chunsrivirot, Surasak, et al.. (2022). Molecular properties and ligand specificity of zebrafish intelectin-2. Fish & Shellfish Immunology. 123. 528–536. 2 indexed citations
14.
Chunsrivirot, Surasak, et al.. (2022). Biochemical and ligand binding properties of recombinant Xenopus laevis cortical granule lectin-1. Heliyon. 8(8). e10396–e10396. 1 indexed citations
15.
Pengsakul, Theerakamol, Morakot Kaewthamasorn, Kittikhun Wangkanont, et al.. (2021). Global diversity of the gene encoding the Pfs25 protein—a Plasmodium falciparum transmission-blocking vaccine candidate. Parasites & Vectors. 14(1). 571–571. 4 indexed citations
16.
Wangkanont, Kittikhun, et al.. (2021). Streptococcus agalactiae amylomaltase offers insight into the transglycosylation mechanism and the molecular basis of thermostability among amylomaltases. Scientific Reports. 11(1). 6740–6740. 15 indexed citations
17.
Shanmugaraj, Balamurugan, Konlavat Siriwattananon, Kittikhun Wangkanont, & Waranyoo Phoolcharoen. (2020). Perspectives on monoclonal antibody therapy as potential therapeutic intervention for Coronavirus disease-19 (COVID-19). Asian Pacific Journal of Allergy and Immunology. 38(1). 10–18. 351 indexed citations
18.
Wangkanont, Kittikhun, Katrina T. Forest, & Laura L. Kiessling. (2015). The non-detergent sulfobetaine-201 acts as a pharmacological chaperone to promote folding and crystallization of the type II TGF-β receptor extracellular domain. Protein Expression and Purification. 115. 19–25. 5 indexed citations
19.
Wesener, Darryl A., Kittikhun Wangkanont, Ryan McBride, et al.. (2015). Recognition of microbial glycans by human intelectin-1. Nature Structural & Molecular Biology. 22(8). 603–610. 118 indexed citations
20.
Wangkanont, Kittikhun, et al.. (2010). A general glycomimetic strategy yields non-carbohydrate inhibitors of DC-SIGN. Chemical Communications. 46(36). 6747–6747. 51 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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