Chandran Remya

471 total citations
34 papers, 353 citations indexed

About

Chandran Remya is a scholar working on Computational Theory and Mathematics, Pharmacology and Molecular Biology. According to data from OpenAlex, Chandran Remya has authored 34 papers receiving a total of 353 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computational Theory and Mathematics, 17 papers in Pharmacology and 12 papers in Molecular Biology. Recurrent topics in Chandran Remya's work include Computational Drug Discovery Methods (19 papers), Cholinesterase and Neurodegenerative Diseases (14 papers) and Synthesis and biological activity (7 papers). Chandran Remya is often cited by papers focused on Computational Drug Discovery Methods (19 papers), Cholinesterase and Neurodegenerative Diseases (14 papers) and Synthesis and biological activity (7 papers). Chandran Remya collaborates with scholars based in India, United States and Japan. Chandran Remya's co-authors include C. Sadasivan, K.V. Dileep, R.V. Omkumar, Shaik Anwar, Ayyiliath M. Sajith, M. Haridas, Javier Cerezo, Kam Y. J. Zhang, Afshin Fassihi and Horacio Pérez‐Sánchez and has published in prestigious journals such as Scientific Reports, Biochemical and Biophysical Research Communications and RSC Advances.

In The Last Decade

Chandran Remya

27 papers receiving 352 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chandran Remya India 12 145 132 114 103 50 34 353
Baichen Xiong China 9 233 1.6× 144 1.1× 89 0.8× 157 1.5× 68 1.4× 13 450
Matheus de Freitas Silva Brazil 8 179 1.2× 159 1.2× 172 1.5× 120 1.2× 61 1.2× 14 401
Sandra Gunesch Germany 9 216 1.5× 146 1.1× 59 0.5× 109 1.1× 72 1.4× 11 378
Yuqiong Pei China 9 186 1.3× 140 1.1× 75 0.7× 118 1.1× 61 1.2× 17 346
Lvjie Xu China 13 79 0.5× 219 1.7× 53 0.5× 108 1.0× 71 1.4× 23 472
Jae Pil Lee South Korea 12 233 1.6× 144 1.1× 156 1.4× 90 0.9× 17 0.3× 19 456
Apra Manral India 8 208 1.4× 104 0.8× 185 1.6× 157 1.5× 72 1.4× 10 395
Kazuko Takami Japan 9 130 0.9× 100 0.8× 192 1.7× 77 0.7× 25 0.5× 10 321
Petra Kapková Germany 8 235 1.6× 133 1.0× 154 1.4× 157 1.5× 68 1.4× 11 400
Weiping Lyu China 10 124 0.9× 109 0.8× 91 0.8× 84 0.8× 51 1.0× 26 311

Countries citing papers authored by Chandran Remya

Since Specialization
Citations

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

Fields of papers citing papers by Chandran Remya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chandran Remya

This figure shows the co-authorship network connecting the top 25 collaborators of Chandran Remya. A scholar is included among the top collaborators of Chandran Remya 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 Chandran Remya. Chandran Remya 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.
Remya, Chandran, et al.. (2025). Insights into the structural and biophysical mechanisms of benzamidine-driven inhibition of human lysozyme aggregation. International Journal of Biological Macromolecules. 305(Pt 2). 141139–141139.
2.
Remya, Chandran, et al.. (2025). Molecular blueprints: Guiding drug discovery through protein structure analysis. Advances in protein chemistry and structural biology. 147. 37–99.
3.
Remya, Chandran, et al.. (2025). Design, Synthesis, Characterization and In Vitro Evaluation of Anticholinesterase and Antioxidant Activities of Thiazole–Piperazine Sulphonamide Hybrids. Chemistry & Biodiversity. 22(9). e202500567–e202500567. 1 indexed citations
4.
Remya, Chandran, et al.. (2025). The complex interplay between ligand strain, coulombic interactions, and binding site dynamics of two congeneric AChE inhibitors. Journal of Molecular Structure. 1330. 141479–141479.
5.
Remya, Chandran, et al.. (2025). A Cdk5 inhibitor restores cognitive function and alleviates type 2 diabetes in mice. iScience. 28(4). 112200–112200.
6.
Remya, Chandran, et al.. (2023). Unveiling the molecular basis of lobeline's allosteric regulation of NMDAR: insights from molecular modeling. Scientific Reports. 13(1). 22418–22418.
7.
Remya, Chandran, et al.. (2022). Binding of rosmarinic acid curcumin and capsaicin with PLA2: A comparative study. Biochemical and Biophysical Research Communications. 626. 187–191. 6 indexed citations
8.
Remya, Chandran, K.V. Dileep, Shaik Anwar, et al.. (2021). Neuroprotective derivatives of tacrine that target NMDA receptor and acetyl cholinesterase – Design, synthesis and biological evaluation. Computational and Structural Biotechnology Journal. 19. 4517–4537. 24 indexed citations
9.
Dileep, K.V., Chandran Remya, Pradeep K. Mandal, et al.. (2018). Crystal structure of phospholipase A2 in complex with 1‐naphthaleneacetic acid. IUBMB Life. 70(10). 995–1001. 3 indexed citations
10.
Remya, Chandran, et al.. (2017). Novel tacrine derivatives exhibiting improved acetylcholinesterase inhibition: Design, synthesis and biological evaluation. European Journal of Medicinal Chemistry. 139. 367–377. 49 indexed citations
11.
Remya, Chandran, et al.. (2017). Cellular calcium signaling in the aging brain. Journal of Chemical Neuroanatomy. 95. 95–114. 41 indexed citations
12.
Remya, Chandran, et al.. (2016). An in silico guided identification of nAChR agonists from Withania somnifera. 9(3). 201–213. 14 indexed citations
13.
Dileep, K.V., Chandran Remya, Javier Cerezo, et al.. (2015). Comparative studies on the inhibitory activities of selected benzoic acid derivatives against secretory phospholipase A2, a key enzyme involved in the inflammatory pathway. Molecular BioSystems. 11(7). 1973–1979. 18 indexed citations
14.
Dileep, K.V., et al.. (2015). Rational design and interaction studies of combilexins towards duplex DNA. Molecular BioSystems. 12(3). 860–867. 14 indexed citations
15.
Remya, Chandran, et al.. (2015). Flavanone glycosides as acetylcholinesterase inhibitors: computational and experimental evidence.. PubMed. 76(6). 567–70. 24 indexed citations
16.
Dileep, K.V., et al.. (2013). Inhibitory activity of IAA and IBA against lipoxygenase:in silicoandin vitrovalidation. Molecular Simulation. 40(5). 418–422. 3 indexed citations
17.
Dileep, K.V., et al.. (2013). Interactions of selected indole derivatives with phospholipase A2: in silico and in vitro analysis. Journal of Molecular Modeling. 19(4). 1811–1817. 11 indexed citations
18.
Dileep, K.V., et al.. (2012). Studies of IAA and IBA as fungal α‐amylase inhibitors using enzyme kinetics, molecular modeling and thermodynamics. Starch - Stärke. 64(12). 991–995. 3 indexed citations
19.
Remya, Chandran, et al.. (2012). Design of potent inhibitors of acetylcholinesterase using morin as the starting compound. 6(3-4). 107–117. 35 indexed citations
20.
Remya, Chandran, et al.. (2012). In vitro inhibitory profile of NDGA against AChE and its in silico structural modifications based on ADME profile. Journal of Molecular Modeling. 19(3). 1179–1194. 20 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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