John Karanicolas

9.2k total citations · 4 hit papers
66 papers, 4.3k citations indexed

About

John Karanicolas is a scholar working on Molecular Biology, Computational Theory and Mathematics and Materials Chemistry. According to data from OpenAlex, John Karanicolas has authored 66 papers receiving a total of 4.3k indexed citations (citations by other indexed papers that have themselves been cited), including 57 papers in Molecular Biology, 16 papers in Computational Theory and Mathematics and 12 papers in Materials Chemistry. Recurrent topics in John Karanicolas's work include Protein Structure and Dynamics (23 papers), Computational Drug Discovery Methods (16 papers) and Monoclonal and Polyclonal Antibodies Research (10 papers). John Karanicolas is often cited by papers focused on Protein Structure and Dynamics (23 papers), Computational Drug Discovery Methods (16 papers) and Monoclonal and Polyclonal Antibodies Research (10 papers). John Karanicolas collaborates with scholars based in United States, China and Russia. John Karanicolas's co-authors include Charles L. Brooks, Michael Feig, David Baker, Stuart A. Sievers, David Eisenberg, Rhiju Das, David K. Johnson, Michael J. Thompson, Magdalena I. Ivanova and Eric J. Deeds and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

John Karanicolas

62 papers receiving 4.3k citations

Hit Papers

align trajectories

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.

MMTSB Tool Set: enhanced sampling and multiscale modeling methods for applications in structural biology

2004 761 citations John Karanicolas et al. profile →
Structure-based design of non-natural amino-acid inhibitors of amyloid fibril formation

2011 389 citations John Karanicolas et al. profile →
The 3D profile method for identifying fibril-forming segments of proteins

2006 340 citations John Karanicolas et al. Proceedings of the National Academy of Sciences profile →
Atomic accuracy in predicting and designing noncanonical RNA structure

2010 273 citations John Karanicolas et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
John Karanicolas United States	29	3.6k	988	463	457	284	66	4.3k
Ting Ran China	19	4.1k 1.2×	706 0.7×	653 1.4×	344 0.8×	360 1.3×	60	5.7k
Oxana V. Galzitskaya Russia	33	4.1k 1.2×	1.3k 1.3×	572 1.2×	783 1.7×	331 1.2×	204	5.3k
Sebastian Kmiecik Poland	29	2.7k 0.8×	972 1.0×	512 1.1×	183 0.4×	217 0.8×	83	3.5k
A.E. Sauer-Eriksson Sweden	34	3.9k 1.1×	914 0.9×	209 0.5×	510 1.1×	320 1.1×	87	5.0k
Shibasish Chowdhury India	16	3.3k 0.9×	987 1.0×	405 0.9×	133 0.3×	475 1.7×	41	4.6k
Xiao Zhu United States	5	2.9k 0.8×	635 0.6×	324 0.7×	144 0.3×	287 1.0×	5	4.0k
Duncan Poole United States	4	3.0k 0.9×	659 0.7×	534 1.2×	124 0.3×	351 1.2×	5	4.3k
Kannan Gunasekaran United States	24	2.5k 0.7×	730 0.7×	283 0.6×	232 0.5×	226 0.8×	39	2.9k
Guoming Xiong United States	5	2.9k 0.8×	888 0.9×	402 0.9×	129 0.3×	438 1.5×	7	4.1k

Countries citing papers authored by John Karanicolas

Since Specialization

Citations

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

Fields of papers citing papers by John Karanicolas

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of John Karanicolas

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

All Works

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20 of 20 papers shown

Rico, Mario C., Carmen Merali, Carlos A. Barrero, et al.. (2023). Secreted folate receptor γ drives fibrogenesis in metabolic dysfunction–associated steatohepatitis by amplifying TGFβ signaling in hepatic stellate cells. Science Translational Medicine. 15(715). eade2966–eade2966. 11 indexed citations

Karanicolas, John, et al.. (2023). Novel Substrate Prediction for the TAM Family of RTKs Using Phosphoproteomics and Structure-Based Modeling. ACS Chemical Biology. 19(1). 117–128.

Paul, Kiran, Abhishek Gupta, Vandana Kumari, et al.. (2022). Integrative genome-wide analysis reveals EIF3A as a key downstream regulator of translational repressor protein Musashi 2 (MSI2). NAR Cancer. 4(2). zcac015–zcac015. 9 indexed citations

Pangeni, Rajendra P., Evgeny Izumchenko, Jindan Yu, et al.. (2022). The role of NSD1, NSD2, and NSD3 histone methyltransferases in solid tumors. Cellular and Molecular Life Sciences. 79(6). 285–285. 36 indexed citations

Malhotra, Shipra, et al.. (2022). Structural Plasticity Is a Feature of Rheostat Positions in the Human Na+/Taurocholate Cotransporting Polypeptide (NTCP). International Journal of Molecular Sciences. 23(6). 3211–3211. 9 indexed citations

Serebriiskii, Ilya G., et al.. (2021). Efficient Hit-to-Lead Searching of Kinase Inhibitor Chemical Space via Computational Fragment Merging. Journal of Chemical Information and Modeling. 61(12). 5967–5987. 7 indexed citations

Kirubakaran, Palani, et al.. (2021). Rationalizing PROTAC-Mediated Ternary Complex Formation Using Rosetta. Journal of Chemical Information and Modeling. 61(3). 1368–1382. 93 indexed citations

Deeds, Eric J., et al.. (2020). Machine learning classification can reduce false positives in structure-based virtual screening. Proceedings of the National Academy of Sciences. 117(31). 18477–18488. 138 indexed citations

Lan, Lan, Jiajun Liu, Amber R. Smith, et al.. (2020). Identification and Validation of an Aspergillus nidulans Secondary Metabolite Derivative as an Inhibitor of the Musashi-RNA Interaction. Cancers. 12(8). 2221–2221. 15 indexed citations

10.

Keohane, Colleen E., et al.. (2020). Target-Based Design of Promysalin Analogues Identifies a New Putative Binding Cleft in Succinate Dehydrogenase. ACS Infectious Diseases. 6(6). 1372–1377. 10 indexed citations

11.

Wu, Xiaoqing, Lan Lan, Shuang Han, et al.. (2020). Targeting the interaction between RNA-binding protein HuR and FOXQ1 suppresses breast cancer invasion and metastasis. Communications Biology. 3(1). 193–193. 80 indexed citations

12.

Cheng, Hong, et al.. (2020). Computational Design of an Allosteric Antibody Switch by Deletion and Rescue of a Complex Structural Constellation. ACS Central Science. 6(3). 390–403. 10 indexed citations

13.

Malhotra, Shipra, et al.. (2020). A clinically relevant polymorphism in the Na+/taurocholate cotransporting polypeptide (NTCP) occurs at a rheostat position. Journal of Biological Chemistry. 296. 100047–100047. 22 indexed citations

14.

Tyne, Daria Van, Abigail L. Manson, Mark M. Huycke, et al.. (2019). Impact of antibiotic treatment and host innate immune pressure on enterococcal adaptation in the human bloodstream. Science Translational Medicine. 11(487). 35 indexed citations

15.

Reilly, Sean W., Aladdin Riad, Chia‐Ju Hsieh, et al.. (2019). Leveraging a Low-Affinity Diazaspiro Orthosteric Fragment to Reduce Dopamine D₃ Receptor (D₃R) Ligand Promiscuity across Highly Conserved Aminergic G-Protein-Coupled Receptors (GPCRs). Journal of Medicinal Chemistry. 62(10). 5132–5147. 15 indexed citations

16.

Röder, Heinrich, et al.. (2019). Isothermal Analysis of ThermoFluor Data can readily provide Quantitative Binding Affinities. Scientific Reports. 9(1). 2650–2650. 96 indexed citations

17.

Kaiser, Christine, M. Paola Castaldi, Steven L. Kazmirski, et al.. (2018). Modulating Antibody Structure and Function through Directed Mutations and Chemical Rescue. ACS Synthetic Biology. 7(4). 1152–1162. 6 indexed citations

18.

Keohane, Colleen E., A. Duncan Steele, Christian Fetzer, et al.. (2018). Promysalin Elicits Species-Selective Inhibition of Pseudomonas aeruginosa by Targeting Succinate Dehydrogenase. Journal of the American Chemical Society. 140(5). 1774–1782. 81 indexed citations

19.

Karanicolas, John, et al.. (2017). “Solvent hydrogen‐bond occlusion”: A new model of polar desolvation for biomolecular energetics. Journal of Computational Chemistry. 38(16). 1321–1331. 4 indexed citations

20.

Malhotra, Shipra & John Karanicolas. (2016). When Does Chemical Elaboration Induce a Ligand To Change Its Binding Mode?. Journal of Medicinal Chemistry. 60(1). 128–145. 38 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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