James Delproposto

1.6k total citations · 2 hit papers
14 papers, 1.2k citations indexed

About

James Delproposto is a scholar working on Molecular Biology, Virology and Oncology. According to data from OpenAlex, James Delproposto has authored 14 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 2 papers in Virology and 2 papers in Oncology. Recurrent topics in James Delproposto's work include Protein Degradation and Inhibitors (3 papers), Ubiquitin and proteasome pathways (3 papers) and Computational Drug Discovery Methods (2 papers). James Delproposto is often cited by papers focused on Protein Degradation and Inhibitors (3 papers), Ubiquitin and proteasome pathways (3 papers) and Computational Drug Discovery Methods (2 papers). James Delproposto collaborates with scholars based in United States, China and Taiwan. James Delproposto's co-authors include Jeanne A. Stuckey, Krishnapriya Chinnaswamy, William Clay Brown, Janet L. Smith, Chao‐Yie Yang, Shaomeng Wang, Mi Wang, Richard Kühn, Craig M. Ogata and David L. Akey and has published in prestigious journals such as Science, PLoS ONE and Journal of Molecular Biology.

In The Last Decade

James Delproposto

14 papers receiving 1.2k citations

Hit Papers

Flavivirus NS1 Structures Reveal Surfaces for Association... 2014 2026 2018 2022 2014 2019 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
James Delproposto United States 12 782 297 226 210 175 14 1.2k
John P. Priestle Switzerland 18 889 1.1× 303 1.0× 158 0.7× 169 0.8× 61 0.3× 32 1.4k
Fabio Zuccotto United Kingdom 15 591 0.8× 169 0.6× 141 0.6× 165 0.8× 40 0.2× 25 1.1k
Ian Crandall Canada 24 464 0.6× 564 1.9× 96 0.4× 95 0.5× 60 0.3× 71 1.5k
Edgar Deu United States 17 478 0.6× 282 0.9× 221 1.0× 114 0.5× 61 0.3× 28 900
James M. Bennett United Kingdom 24 1.2k 1.5× 52 0.2× 213 0.9× 189 0.9× 200 1.1× 48 2.0k
Michael J. Miley United States 21 659 0.8× 187 0.6× 208 0.9× 173 0.8× 22 0.1× 33 1.5k
Barbara Clough United Kingdom 25 733 0.9× 509 1.7× 120 0.5× 116 0.6× 46 0.3× 38 1.8k
Rebecca S. Bamert Australia 17 467 0.6× 115 0.4× 392 1.7× 79 0.4× 102 0.6× 34 1.0k
Alexis Kaushansky United States 24 564 0.7× 854 2.9× 247 1.1× 104 0.5× 54 0.3× 57 1.6k
Prakasha Kempaiah United States 18 271 0.3× 494 1.7× 75 0.3× 257 1.2× 78 0.4× 63 1.2k

Countries citing papers authored by James Delproposto

Since Specialization
Citations

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

Fields of papers citing papers by James Delproposto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of James Delproposto

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

All Works

14 of 14 papers shown
1.
Aguilar, Angelo, Ke Zheng, Tianfeng Xu, et al.. (2019). Structure-Based Discovery of M-89 as a Highly Potent Inhibitor of the Menin-Mixed Lineage Leukemia (Menin-MLL) Protein–Protein Interaction. Journal of Medicinal Chemistry. 62(13). 6015–6034. 27 indexed citations
2.
Hu, Jiantao, Biao Hu, Mingliang Wang, et al.. (2019). Discovery of ERD-308 as a Highly Potent Proteolysis Targeting Chimera (PROTAC) Degrader of Estrogen Receptor (ER). Journal of Medicinal Chemistry. 62(3). 1420–1442. 192 indexed citations
3.
Han, Xin, Chao Wang, Chong Qin, et al.. (2019). Discovery of ARD-69 as a Highly Potent Proteolysis Targeting Chimera (PROTAC) Degrader of Androgen Receptor (AR) for the Treatment of Prostate Cancer. Journal of Medicinal Chemistry. 62(2). 941–964. 303 indexed citations breakdown →
4.
Guerra, Alfredo J., Ou Zhang, My‐Hang Huynh, et al.. (2018). Structural basis of Toxoplasma gondii perforin-like protein 1 membrane interaction and activity during egress. PLoS Pathogens. 14(12). e1007476–e1007476. 9 indexed citations
5.
Yang, Chao‐Yie, James Delproposto, Krishnapriya Chinnaswamy, et al.. (2016). Conformational Sampling and Binding Site Assessment of Suppression of Tumorigenicity 2 Ectodomain. PLoS ONE. 11(1). e0146522–e0146522. 10 indexed citations
6.
Yang, Chao‐Yie, James G. Phillips, Jeanne A. Stuckey, et al.. (2016). Buried Hydrogen Bond Interactions Contribute to the High Potency of Complement Factor D Inhibitors. ACS Medicinal Chemistry Letters. 7(12). 1092–1096. 20 indexed citations
7.
Morgan, Christopher E., et al.. (2015). The First Crystal Structure of the UP1 Domain of hnRNP A1 Bound to RNA Reveals a New Look for an Old RNA Binding Protein. Journal of Molecular Biology. 427(20). 3241–3257. 32 indexed citations
8.
Smith, Richard D., Kelly L. Damm‐Ganamet, James B. Dunbar, et al.. (2015). CSAR Benchmark Exercise 2013: Evaluation of Results from a Combined Computational Protein Design, Docking, and Scoring/Ranking Challenge. Journal of Chemical Information and Modeling. 56(6). 1022–1031. 43 indexed citations
9.
Akey, David L., William Clay Brown, Somnath Dutta, et al.. (2014). Flavivirus NS1 Structures Reveal Surfaces for Associations with Membranes and the Immune System. Science. 343(6173). 881–885. 327 indexed citations breakdown →
10.
Dunbar, James B., Richard D. Smith, Kelly L. Damm‐Ganamet, et al.. (2013). CSAR Data Set Release 2012: Ligands, Affinities, Complexes, and Docking Decoys. Journal of Chemical Information and Modeling. 53(8). 1842–1852. 90 indexed citations
11.
Brown, William Clay, et al.. (2011). New ligation-independent cloning vectors compatible with a high-throughput platform for parallel construct expression evaluation using baculovirus-infected insect cells. Protein Expression and Purification. 77(1). 34–45. 12 indexed citations
12.
McQuade, Thomas J., et al.. (2008). A nonradioactive high-throughput assay for screening and characterization of adenylation domains for nonribosomal peptide combinatorial biosynthesis. Analytical Biochemistry. 386(2). 244–250. 59 indexed citations
13.
Delproposto, James, Chinmay Y. Majmudar, Janet L. Smith, & William Clay Brown. (2008). Mocr: A novel fusion tag for enhancing solubility that is compatible with structural biology applications. Protein Expression and Purification. 63(1). 40–49. 50 indexed citations
14.
Weiss, Andrew, James Delproposto, & Craig N. Giroux. (2004). High-throughput phenotypic profiling of gene–environment interactions by quantitative growth curve analysis in Saccharomyces cerevisiae. Analytical Biochemistry. 327(1). 23–34. 34 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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