Arun Kumar Somavarapu

582 total citations
18 papers, 481 citations indexed

About

Arun Kumar Somavarapu is a scholar working on Molecular Biology, Physiology and Computational Theory and Mathematics. According to data from OpenAlex, Arun Kumar Somavarapu has authored 18 papers receiving a total of 481 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 11 papers in Physiology and 5 papers in Computational Theory and Mathematics. Recurrent topics in Arun Kumar Somavarapu's work include Alzheimer's disease research and treatments (10 papers), Protein Structure and Dynamics (6 papers) and Computational Drug Discovery Methods (5 papers). Arun Kumar Somavarapu is often cited by papers focused on Alzheimer's disease research and treatments (10 papers), Protein Structure and Dynamics (6 papers) and Computational Drug Discovery Methods (5 papers). Arun Kumar Somavarapu collaborates with scholars based in Denmark, India and United Kingdom. Arun Kumar Somavarapu's co-authors include Kasper P. Kepp, Prasanna Venkatraman, Padma P. Nanaware, Daniel E. Otzen, Ravikanth Nanduri, Sahil Mahajan, Raman Parkesh, Pawan Gupta, Budheswar Dehury and Ning Tang and has published in prestigious journals such as The Journal of Immunology, The Journal of Physical Chemistry B and FEBS Letters.

In The Last Decade

Arun Kumar Somavarapu

18 papers receiving 478 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Arun Kumar Somavarapu Denmark 13 288 247 99 53 52 18 481
Thomas Henriksson United States 7 275 1.0× 284 1.1× 43 0.4× 13 0.2× 8 0.2× 12 425
Benedikt Weber Germany 9 348 1.2× 225 0.9× 38 0.4× 40 0.8× 7 0.1× 10 516
Pravas Kumar Baral Canada 11 394 1.4× 88 0.4× 16 0.2× 15 0.3× 34 0.7× 15 527
Edward Pichinuk Israel 12 245 0.9× 73 0.3× 21 0.2× 8 0.2× 17 0.3× 22 422
Željko M. Svedružić Croatia 14 327 1.1× 114 0.5× 48 0.5× 12 0.2× 8 0.2× 29 441
Michelle R. Gaylord United States 7 205 0.7× 77 0.3× 17 0.2× 12 0.2× 9 0.2× 7 384
Becky Tu‐Sekine United States 13 338 1.2× 40 0.2× 14 0.1× 13 0.2× 42 0.8× 23 540
Jyotsna Bhat India 11 200 0.7× 41 0.2× 62 0.6× 11 0.2× 20 0.4× 16 320
Zenghui Lao China 10 293 1.0× 158 0.6× 53 0.5× 51 1.0× 8 0.2× 13 407
Mads Nygaard Denmark 8 293 1.0× 29 0.1× 22 0.2× 35 0.7× 10 0.2× 11 425

Countries citing papers authored by Arun Kumar Somavarapu

Since Specialization
Citations

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

Fields of papers citing papers by Arun Kumar Somavarapu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Arun Kumar Somavarapu. 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 Arun Kumar Somavarapu. The network helps show where Arun Kumar Somavarapu may publish in the future.

Co-authorship network of co-authors of Arun Kumar Somavarapu

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

All Works

18 of 18 papers shown
1.
Monti, Michele, Edoardo Milanetti, Mattia Miotto, et al.. (2024). Two Receptor Binding Strategy of SARS-CoV-2 Is Mediated by Both the N-Terminal and Receptor-Binding Spike Domain. The Journal of Physical Chemistry B. 128(2). 451–464. 8 indexed citations
2.
Somavarapu, Arun Kumar, et al.. (2023). Drug repurposing screens identify compounds that inhibit α-synuclein oligomers' membrane disruption and block antibody interactions. Chemical Science. 14(11). 3030–3047. 2 indexed citations
3.
Farzadfard, Azad, Georg Meisl, Arun Kumar Somavarapu, et al.. (2022). The C-terminal tail of α-synuclein protects against aggregate replication but is critical for oligomerization. Communications Biology. 5(1). 123–123. 45 indexed citations
4.
Otzen, Daniel E., Jannik Nedergaard Pedersen, Arun Kumar Somavarapu, et al.. (2021). Cys-labeling kinetics of membrane protein GlpG: a role for specific SDS binding and micelle changes?. Biophysical Journal. 120(18). 4115–4128. 5 indexed citations
5.
Dehury, Budheswar, Arun Kumar Somavarapu, & Kasper P. Kepp. (2020). A computer-simulated mechanism of familial Alzheimer’s disease: Mutations enhance thermal dynamics and favor looser substrate-binding to γ-secretase. Journal of Structural Biology. 212(3). 107648–107648. 17 indexed citations
6.
Diggelen, Femke van, Arun Kumar Somavarapu, Carsten Scavenius, et al.. (2019). The interactome of stabilized α‐synuclein oligomers and neuronal proteins. FEBS Journal. 287(10). 2037–2054. 10 indexed citations
7.
Tang, Ning, Arun Kumar Somavarapu, & Kasper P. Kepp. (2018). Molecular Recipe for γ-Secretase Modulation from Computational Analysis of 60 Active Compounds. ACS Omega. 3(12). 18078–18088. 17 indexed citations
8.
Somavarapu, Arun Kumar, Kaare Teilum, Jingdong Zhang, et al.. (2017). The Pathogenic A2V Mutant Exhibits Distinct Aggregation Kinetics, Metal Site Structure, and Metal Exchange of the Cu2+–Aβ Complex. Chemistry - A European Journal. 23(55). 13591–13595. 17 indexed citations
9.
Somavarapu, Arun Kumar & Kasper P. Kepp. (2017). Membrane Dynamics of γ-Secretase Provides a Molecular Basis for β-Amyloid Binding and Processing. ACS Chemical Neuroscience. 8(11). 2424–2436. 39 indexed citations
10.
Somavarapu, Arun Kumar & Kasper P. Kepp. (2016). The dynamic mechanism of presenilin-1 function: Sensitive gate dynamics and loop unplugging control protein access. Neurobiology of Disease. 89. 147–156. 41 indexed citations
11.
Somavarapu, Arun Kumar & Kasper P. Kepp. (2016). Loss of stability and hydrophobicity of presenilin 1 mutations causing Alzheimer's disease. Journal of Neurochemistry. 137(1). 101–111. 44 indexed citations
12.
Somavarapu, Arun Kumar & Kasper P. Kepp. (2015). Direct Correlation of Cell Toxicity to Conformational Ensembles of Genetic Aβ Variants. ACS Chemical Neuroscience. 6(12). 1990–1996. 14 indexed citations
13.
Nanduri, Ravikanth, et al.. (2015). ONRLDB—manually curated database of experimentally validated ligands for orphan nuclear receptors: insights into new drug discovery. Database. 2015. bav112–bav112. 13 indexed citations
14.
Somavarapu, Arun Kumar & Kasper P. Kepp. (2015). The Dependence of Amyloid‐β Dynamics on Protein Force Fields and Water Models. ChemPhysChem. 16(15). 3278–3289. 104 indexed citations
15.
Somavarapu, Arun Kumar, et al.. (2014). Structural interrogation of phosphoproteome identified by mass spectrometry reveals allowed and disallowed regions of phosphoconformation. BMC Structural Biology. 14(1). 9–9. 8 indexed citations
16.
Dkhar, Hedwin Kitdorlang, Ravikanth Nanduri, Sahil Mahajan, et al.. (2014). Mycobacterium tuberculosis Keto-Mycolic Acid and Macrophage Nuclear Receptor TR4 Modulate Foamy Biogenesis in Granulomas: A Case of a Heterologous and Noncanonical Ligand-Receptor Pair. The Journal of Immunology. 193(1). 295–305. 54 indexed citations
17.
18.
Nanaware, Padma P., et al.. (2013). Discovery of multiple interacting partners of gankyrin, a proteasomal chaperone and an oncoprotein—Evidence for a common hot spot site at the interface and its functional relevance. Proteins Structure Function and Bioinformatics. 82(7). 1283–1300. 31 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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