Tomoya Sameshima

1.1k total citations
25 papers, 888 citations indexed

About

Tomoya Sameshima is a scholar working on Molecular Biology, Oncology and Computational Theory and Mathematics. According to data from OpenAlex, Tomoya Sameshima has authored 25 papers receiving a total of 888 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Molecular Biology, 8 papers in Oncology and 5 papers in Computational Theory and Mathematics. Recurrent topics in Tomoya Sameshima's work include Protein Degradation and Inhibitors (6 papers), Computational Drug Discovery Methods (5 papers) and Ubiquitin and proteasome pathways (4 papers). Tomoya Sameshima is often cited by papers focused on Protein Degradation and Inhibitors (6 papers), Computational Drug Discovery Methods (5 papers) and Ubiquitin and proteasome pathways (4 papers). Tomoya Sameshima collaborates with scholars based in Japan, United States and Canada. Tomoya Sameshima's co-authors include Nobuo Cho, Takayuki Hattori, Kenichiro Shimokawa, Mikihiko Naito, Nobumichi Ohoka, Norihito Shibata, Hiroshi Nara, Ikuo Miyahisa, Yasuhiro Imaeda and Osamu Ujikawa and has published in prestigious journals such as Journal of Biological Chemistry, Angewandte Chemie International Edition and Biochemistry.

In The Last Decade

Tomoya Sameshima

24 papers receiving 882 citations

Peers

Tomoya Sameshima
James D. Vasta United States
Laurie A. LeBrun United States
Nobuo Cho Japan
Daniel Scheibe United States
J. Zhu United States
Kevin R. Kupcho United States
James D. Vasta United States
Tomoya Sameshima
Citations per year, relative to Tomoya Sameshima Tomoya Sameshima (= 1×) peers James D. Vasta

Countries citing papers authored by Tomoya Sameshima

Since Specialization
Citations

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

Fields of papers citing papers by Tomoya Sameshima

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tomoya Sameshima

This figure shows the co-authorship network connecting the top 25 collaborators of Tomoya Sameshima. A scholar is included among the top collaborators of Tomoya Sameshima 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 Tomoya Sameshima. Tomoya Sameshima 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.
Sameshima, Tomoya, Nicole Feric, Isabella Pallotta, et al.. (2025). Establishing a context of use for three-dimensional cardiac tissue derived from human-induced pluripotent stem cell-derived cardiomyocytes using inotropes. Toxicological Sciences. 205(2). 401–416. 1 indexed citations
2.
Hirozane, Yoshihiko, et al.. (2019). Structure-based rational design of staurosporine-based fluorescent probe with broad-ranging kinase affinity for kinase panel application. Bioorganic & Medicinal Chemistry Letters. 29(21). 126641–126641. 11 indexed citations
3.
Tawada, Michiko, Tatsuo Oikawa, Tomoya Sameshima, et al.. (2019). Identification of 2,6-Disubstituted 3H-Imidazo[4,5-b]pyridines as Therapeutic Agents for Dysferlinopathies through Phenotypic Screening on Patient-Derived Induced Pluripotent Stem Cells. Journal of Medicinal Chemistry. 62(20). 9175–9187. 6 indexed citations
4.
Sameshima, Tomoya, Tomoya Yukawa, Yoshihiko Hirozane, et al.. (2019). Small-Scale Panel Comprising Diverse Gene Family Targets To Evaluate Compound Promiscuity. Chemical Research in Toxicology. 33(1). 154–161. 10 indexed citations
5.
Ito, Masahiro, Toshio Tanaka, Noriko Uchiyama, et al.. (2018). Discovery of 3-Benzyl-1-(trans-4-((5-cyanopyridin-2-yl)amino)cyclohexyl)-1-arylurea Derivatives as Novel and Selective Cyclin-Dependent Kinase 12 (CDK12) Inhibitors. Journal of Medicinal Chemistry. 61(17). 7710–7728. 51 indexed citations
6.
Ohoka, Nobumichi, Katsunori Nagai, Kenichiro Shimokawa, et al.. (2018). Derivatization of inhibitor of apoptosis protein (IAP) ligands yields improved inducers of estrogen receptor α degradation. Journal of Biological Chemistry. 293(18). 6776–6790. 84 indexed citations
7.
Shibata, Norihito, Kenichiro Shimokawa, Katsunori Nagai, et al.. (2018). Pharmacological difference between degrader and inhibitor against oncogenic BCR-ABL kinase. Scientific Reports. 8(1). 46 indexed citations
8.
Sameshima, Tomoya, et al.. (2017). High-Throughput Quantitative Intrinsic Thiol Reactivity Evaluation Using a Fluorescence-Based Competitive Endpoint Assay. SLAS DISCOVERY. 22(9). 1168–1174. 8 indexed citations
9.
Niida, Ayumu, Shigekazu Sasaki, Kazuko Yonemori, et al.. (2017). Investigation of the structural requirements of K-Ras(G12D) selective inhibitory peptide KRpep-2d using alanine scans and cysteine bridging. Bioorganic & Medicinal Chemistry Letters. 27(12). 2757–2761. 29 indexed citations
10.
Sakamoto, Kotaro, Yusuke Kamada, Tomoya Sameshima, et al.. (2017). K-Ras(G12D)-selective inhibitory peptides generated by random peptide T7 phage display technology. Biochemical and Biophysical Research Communications. 484(3). 605–611. 88 indexed citations
12.
Shimokawa, Kenichiro, Norihito Shibata, Tomoya Sameshima, et al.. (2017). Targeting the Allosteric Site of Oncoprotein BCR-ABL as an Alternative Strategy for Effective Target Protein Degradation. ACS Medicinal Chemistry Letters. 8(10). 1042–1047. 91 indexed citations
13.
Miyahisa, Ikuo, Tomoya Sameshima, & Mark S. Hixon. (2015). Rapid Determination of the Specificity Constant of Irreversible Inhibitors (kinact/KI) by Means of an Endpoint Competition Assay. Angewandte Chemie International Edition. 54(47). 14099–14102. 44 indexed citations
14.
Miyahisa, Ikuo, Tomoya Sameshima, & Mark S. Hixon. (2015). Rapid Determination of the Specificity Constant of Irreversible Inhibitors (kinact/KI) by Means of an Endpoint Competition Assay. Angewandte Chemie. 127(47). 14305–14308. 2 indexed citations
15.
Sameshima, Tomoya, Ikuo Miyahisa, Misaki Homma, et al.. (2014). A simple and widely applicable hit validation strategy for protein–protein interaction inhibitors based on a quantitative ligand displacement assay. Bioorganic & Medicinal Chemistry Letters. 24(24). 5836–5839. 2 indexed citations
16.
Tanaka, Yuta, Katsuji Aikawa, Goushi Nishida, et al.. (2013). Discovery of Potent Mcl-1/Bcl-xL Dual Inhibitors by Using a Hybridization Strategy Based on Structural Analysis of Target Proteins. Journal of Medicinal Chemistry. 56(23). 9635–9645. 91 indexed citations
17.
Sameshima, Tomoya, Ryo Iizuka, Taro Ueno, et al.. (2010). Single-molecule Study on the Decay Process of the Football-shaped GroEL-GroES Complex Using Zero-mode Waveguides. Journal of Biological Chemistry. 285(30). 23159–23164. 30 indexed citations
18.
Sameshima, Tomoya, Ryo Iizuka, Taro Ueno, & Takashi Funatsu. (2010). Denatured proteins facilitate the formation of the football-shaped GroEL–(GroES)2 complex. Biochemical Journal. 427(2). 247–254. 39 indexed citations
19.
Sameshima, Tomoya, Taro Ueno, Ryo Iizuka, et al.. (2008). Football- and Bullet-shaped GroEL-GroES Complexes Coexist during the Reaction Cycle. Journal of Biological Chemistry. 283(35). 23765–23773. 39 indexed citations
20.
Sato, Yukiko, Takahiro Arakawa, Tomoya Sameshima, et al.. (2006). Multi-reagents high speed exchange flow system for single biomolecutar dynamics real time monitoring.

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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