Aurijit Sarkar

647 total citations
19 papers, 491 citations indexed

About

Aurijit Sarkar is a scholar working on Molecular Biology, Computational Theory and Mathematics and Pharmacology. According to data from OpenAlex, Aurijit Sarkar has authored 19 papers receiving a total of 491 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 5 papers in Computational Theory and Mathematics and 4 papers in Pharmacology. Recurrent topics in Aurijit Sarkar's work include Computational Drug Discovery Methods (5 papers), Antibiotic Resistance in Bacteria (4 papers) and Proteoglycans and glycosaminoglycans research (4 papers). Aurijit Sarkar is often cited by papers focused on Computational Drug Discovery Methods (5 papers), Antibiotic Resistance in Bacteria (4 papers) and Proteoglycans and glycosaminoglycans research (4 papers). Aurijit Sarkar collaborates with scholars based in United States, Germany and Sweden. Aurijit Sarkar's co-authors include Glen E. Kellogg, Umesh R. Desai, Ruth Brenk, Daniel Muthas, Stefan Schmitt, Akul Y. Mehta, Philip D. Mosier, Qibing Zhou, Preetpal S. Sidhu and May H. Abdel Aziz and has published in prestigious journals such as Journal of Biological Chemistry, PLoS ONE and Journal of Medicinal Chemistry.

In The Last Decade

Aurijit Sarkar

17 papers receiving 487 citations

Peers

Aurijit Sarkar

CTM

P. Brear United Kingdom

J. Santeri Puranen Finland

Stefan O. Ochiana United States

Y. Yosaatmadja New Zealand

Mei-Chu Lo United States

Sina Sareth United States

Stephan K. Grant United States

Gonzalo E. González‐Páez United States

J. Wielens Australia

Cuiting Peng China

P. Brear United Kingdom

Aurijit Sarkar

483 ×1.6

76 ×0.7

CTM

87 ×0.8

34 ×0.4

73 ×1.5

Citations per year, relative to Aurijit Sarkar Aurijit Sarkar (= 1×) peers P. Brear

Countries citing papers authored by Aurijit Sarkar

Since Specialization

Citations

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

Fields of papers citing papers by Aurijit Sarkar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aurijit Sarkar

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

All Works

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19 of 19 papers shown

Ali, Liaqat, et al.. (2025). A benzoxazolyl urea inhibits VraS and enhances antimicrobials against vancomycin intermediate-resistant Staphylococcus aureus. Bioorganic & Medicinal Chemistry Letters. 120. 130113–130113.

Sarkar, Aurijit, et al.. (2022). β-Lactamase Suppression as a Strategy to Target Methicillin-Resistant Staphylococcus aureus : Proof of Concept. ACS Omega. 7(50). 46213–46221. 3 indexed citations

Carlson, Travis J, et al.. (2021). Challenges in Drug Discovery for Intracellular Bacteria. Pathogens. 10(9). 1172–1172. 16 indexed citations

Sarkar, Aurijit. (2019). Enabling design of screening libraries for antibiotic discovery by modeling ChEMBL data. European Journal of Pharmaceutical Sciences. 143. 105166–105166. 2 indexed citations

Sarkar, Aurijit & Sylvie Garneau‐Tsodikova. (2019). Resisting resistance: gearing up for war. MedChemComm. 10(9). 1512–1516. 4 indexed citations

Sarkar, Aurijit, Wenbo Yu, Umesh R. Desai, Alexander D. MacKerell, & Philip D. Mosier. (2016). Estimating glycosaminoglycan–protein interaction affinity: water dominates the specific antithrombin–heparin interaction. Glycobiology. 26(10). 1041–1047. 16 indexed citations

Sarkar, Aurijit & Umesh R. Desai. (2015). A Simple Method for Discovering Druggable, Specific Glycosaminoglycan-Protein Systems. Elucidation of Key Principles from Heparin/Heparan Sulfate-Binding Proteins. PLoS ONE. 10(10). e0141127–e0141127. 38 indexed citations

Sarkar, Aurijit & Ruth Brenk. (2015). To Hit or Not to Hit, That Is the Question – Genome-wide Structure-Based Druggability Predictions for Pseudomonas aeruginosa Proteins. PLoS ONE. 10(9). e0137279–e0137279. 8 indexed citations

Sarkar, Aurijit, Vy M. Tran, Thao Kim Nu Nguyen, et al.. (2015). Chemoenzymatically Prepared Heparan Sulfate Containing Rare 2-O-Sulfonated Glucuronic Acid Residues. ACS Chemical Biology. 10(6). 1485–1494. 16 indexed citations

10.

Sankaranarayanan, Nehru Viji, Aurijit Sarkar, Umesh R. Desai, & Philip D. Mosier. (2014). Designing “High-Affinity, High-Specificity” Glycosaminoglycan Sequences Through Computerized Modeling. Methods in molecular biology. 1229. 289–314. 19 indexed citations

11.

Mehta, Akul Y., et al.. (2014). Allosteric Inhibition of Human Factor XIa: Discovery of Monosulfated Benzofurans as a Class of Promising Inhibitors. Journal of Medicinal Chemistry. 57(8). 3559–3569. 22 indexed citations

12.

Sidhu, Preetpal S., May H. Abdel Aziz, Aurijit Sarkar, et al.. (2013). Designing Allosteric Regulators of Thrombin. Exosite 2 Features Multiple Subsites That Can Be Targeted by Sulfated Small Molecules for Inducing Inhibition. Journal of Medicinal Chemistry. 56(12). 5059–5070. 46 indexed citations

13.

Sarkar, Aurijit, et al.. (2012). Computational analysis of structure-based interactions and ligand properties can predict efflux effects on antibiotics. European Journal of Medicinal Chemistry. 52. 98–110. 10 indexed citations

14.

Alphey, M.S., Lisa Pirrie, Leah S. Torrie, et al.. (2012). Allosteric Competitive Inhibitors of the Glucose-1-phosphate Thymidylyltransferase (RmlA) from Pseudomonas aeruginosa. ACS Chemical Biology. 8(2). 387–396. 40 indexed citations

15.

Farzan, Shohreh F., Laura M Palermo, Christine C. Yokoyama, et al.. (2011). Premature Activation of the Paramyxovirus Fusion Protein before Target Cell Attachment with Corruption of the Viral Fusion Machinery. Journal of Biological Chemistry. 286(44). 37945–37954. 32 indexed citations

16.

Muthas, Daniel, et al.. (2011). DrugPred: A Structure-Based Approach To Predict Protein Druggability Developed Using an Extensive Nonredundant Data Set. Journal of Chemical Information and Modeling. 51(11). 2829–2842. 68 indexed citations

17.

Sarkar, Aurijit & Glen E. Kellogg. (2010). Hydrophobicity - Shake Flasks, Protein Folding and Drug Discovery. Current Topics in Medicinal Chemistry. 10(1). 67–83. 114 indexed citations

18.

Li, Qianbin, Adnan M. Al‐Ayoubi, Hui Zheng, et al.. (2009). Structure–activity relationship (SAR) studies of 3-(2-amino-ethyl)-5-(4-ethoxy-benzylidene)-thiazolidine-2,4-dione: Development of potential substrate-specific ERK1/2 inhibitors. Bioorganic & Medicinal Chemistry Letters. 19(21). 6042–6046. 37 indexed citations

19.

Sarkar, Aurijit & Glen E. Kellogg. (2009). Book Review of Computational Drug Design. A Guide for Computational and Medicinal Chemists. Journal of Medicinal Chemistry. 52(15). 4977–4977.

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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