Sudhan Debnath

1.6k total citations
57 papers, 1.3k citations indexed

About

Sudhan Debnath is a scholar working on Molecular Biology, Computational Theory and Mathematics and Plant Science. According to data from OpenAlex, Sudhan Debnath has authored 57 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Molecular Biology, 20 papers in Computational Theory and Mathematics and 16 papers in Plant Science. Recurrent topics in Sudhan Debnath's work include Computational Drug Discovery Methods (19 papers), Natural product bioactivities and synthesis (14 papers) and Phytochemistry and Biological Activities (14 papers). Sudhan Debnath is often cited by papers focused on Computational Drug Discovery Methods (19 papers), Natural product bioactivities and synthesis (14 papers) and Phytochemistry and Biological Activities (14 papers). Sudhan Debnath collaborates with scholars based in India, Japan and Saudi Arabia. Sudhan Debnath's co-authors include Biswanath Dinda, Yoshihiro Harigaya, Rajarshi Banik, Sanjoy Chakraborty, Apu Kumar Saha, Pradip Debnath, Bimal Debnath, Sukanta Nama, Amitava Das and Ratul Chakraborty and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and RSC Advances.

In The Last Decade

Sudhan Debnath

55 papers receiving 1.2k citations

Peers

Countries citing papers authored by Sudhan Debnath

Since Specialization

Citations

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

Fields of papers citing papers by Sudhan Debnath

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sudhan Debnath

This figure shows the co-authorship network connecting the top 25 collaborators of Sudhan Debnath. A scholar is included among the top collaborators of Sudhan Debnath 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 Sudhan Debnath. Sudhan Debnath 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

#	Work	Indexed citations
1	Discovery of Potential Selective HDAC8 Binders: Using Combination of Pharmacophore‐Based–Structure‐Based Virtual Screening, ADME Filtration, and Molecular Dynamics Studies 2025 ·ChemistrySelect ·(unknown), (unknown), (unknown), Swapan Majumdar, Sudhan Debnath	0
2	In silico approach for identification of potential tetracyclic triterpenoids from mushroom as HMG-CoA reductase inhibitor 2024 ·SHILAP Revista de lepidopterología ·(unknown), (unknown), (unknown), (unknown), Sudhan Debnath, Bimal Debnath, Rajat Ghosh	3
3	Repurposing of DrugBank molecules as dual non-hydroxamate HDAC8 and HDAC2 inhibitors by pharmacophore modeling, molecular docking, and molecular dynamics studies 2024 ·Journal of Biomolecular Structure and Dynamics ·(unknown), Sudhan Debnath, Rajat Ghosh, (unknown), (unknown), (unknown), (unknown), Arun K. Nandi, (unknown), Arabinda Ghosh, Samir Kumar Sil	1
4	Identification of phytoconstituents from Dicliptera paniculata and study of antibacterial activity guided by molecular docking 2024 ·In Silico Pharmacology ·(unknown), Sudhan Debnath, (unknown), Rajat Ghosh, Bimal Debnath	1
5	Virtual screening, molecular dynamics simulations, and in vitro validation of EGFR inhibitors as breast cancer therapeutics 2024 ·Bioorganic Chemistry ·(unknown), Sudhan Debnath, (unknown), (unknown), R. Amutha, Amitava Das	5
6	α-Glucosidase inhibitory potential of Oroxylum indicum using molecular docking, molecular dynamics, and in vitro evaluation 2024 ·Saudi Pharmaceutical Journal ·(unknown), (unknown), Sudhan Debnath, Bimal Debnath, Rajat Ghosh, Magdi E. A. Zaki, Sami A. Al‐Hussain	4
7	New hydrazide derivatives of N‐amino‐11‐azaartemisinin as promising epidermal growth factor receptor inhibitors for therapeutic development in triple‐negative breast cancer 2024 ·Archiv der Pharmazie ·(unknown), (unknown), (unknown), (unknown), (unknown), (unknown), Varun Rawat, Mohammad Hassam, (unknown), Ram Awatar Maurya, (unknown), Sudhan Debnath, Amitava Das, (unknown), Ved Prakash Verma	4
8	Potential peptidyl arginine deiminase type 4 inhibitors from Morinda citrifolia: a structure-based drug design approach 2023 ·In Silico Pharmacology ·(unknown), Rajat Ghosh, Sudhan Debnath, (unknown)	0
9	COVID-19 X-ray image segmentation by modified whale optimization algorithm with population reduction 2021 ·Computers in Biology and Medicine ·Sanjoy Chakraborty, Apu Kumar Saha, Sukanta Nama, Sudhan Debnath	83
10	Bis-indolylation of aldehydes and ketones using silica-supported FeCl₃: molecular docking studies of bisindoles by targeting SARS-CoV-2 main protease binding sites 2021 ·RSC Advances ·(unknown), Sudhan Debnath, Ankita Chakraborty, Swapan Majumdar	22
11	Potentiality of Moringa oleifera against SARS-CoV-2: identified by a rational computer aided drug design method 2021 ·Journal of Biomolecular Structure and Dynamics ·(unknown), (unknown), Pradip Debnath, Sudhan Debnath	18
12	A hybrid whale optimization algorithm for global optimization 2021 ·Journal of Ambient Intelligence and Humanized Computing ·Sanjoy Chakraborty, Apu Kumar Saha, Sushmita Sharma, Ratul Chakraborty, Sudhan Debnath	58
13	Structure-Based Virtual Screening and Molecular Dynamics Simulation to Identify Potential SARS-CoV-2 Spike Receptor Inhibitors from Natural Compound Database 2021 ·Pharmaceutical Chemistry Journal ·(unknown), (unknown), Ashutosh Sharma, (unknown), Sudhan Debnath	8
14	Identification of potential inhibitors of SARS-CoV-2 main protease and spike receptor from 10 important spices through structure-based virtual screening and molecular dynamic study 2020 ·Journal of Biomolecular Structure and Dynamics ·(unknown), Pradip Debnath, Bimal Debnath, (unknown), Sudhan Debnath	50
15	In silico design, synthesis and activity of potential drug-like chrysin scaffold-derived selective EGFR inhibitors as anticancer agents 2019 ·Computational Biology and Chemistry ·Sudhan Debnath, (unknown), (unknown), (unknown), (unknown), Amitava Das	21
16	Gene therapy cures the anemia and lethal bone marrow failure in a mouse model of RPS19-deficient Diamond-Blackfan anemia 2014 ·Haematologica ·Pekka Jaako, Sudhan Debnath, Karin Olsson, Ute Modlich, Michael Rothe, Axel Schambach, Johan Flygare, Stefan Karlsson	27
17	Naturally Occurring Triterpenoid Saponins 2010 ·Chemistry & Biodiversity ·Biswanath Dinda, Sudhan Debnath, (unknown), Yoshihiro Harigaya	129
18	Iridoid glucosides from leaves and stem barks ofParkia javanica 2009 ·Journal of Asian Natural Products Research ·Biswanath Dinda, (unknown), Sudhan Debnath, Biplab Ghosh, Shiho Arima, Noriko Sato, Yoshihiro Harigaya	9
19	Naturally Occurring Secoiridoids and Bioactivity of Naturally Occurring Iridoids and Secoiridoids. A Review. Part 2. 2007 ·ChemInform ·Biswanath Dinda, Sudhan Debnath, Yoshihiro Harigaya	3
20	Chemical constituents of Mussaenda incana 2005 ·Indian Journal of Chemistry Section B-organic Chemistry Including Medicinal Chemistry ·Biswanath Dinda, Sudhan Debnath, (unknown), Shiho Arima, (unknown), Yoshihiro Harigaya	8

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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