Muhammad Muddassar

1.5k total citations
69 papers, 1.2k citations indexed

About

Muhammad Muddassar is a scholar working on Organic Chemistry, Molecular Biology and Computational Theory and Mathematics. According to data from OpenAlex, Muhammad Muddassar has authored 69 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Organic Chemistry, 31 papers in Molecular Biology and 21 papers in Computational Theory and Mathematics. Recurrent topics in Muhammad Muddassar's work include Synthesis and biological activity (21 papers), Computational Drug Discovery Methods (20 papers) and Synthesis and Characterization of Heterocyclic Compounds (8 papers). Muhammad Muddassar is often cited by papers focused on Synthesis and biological activity (21 papers), Computational Drug Discovery Methods (20 papers) and Synthesis and Characterization of Heterocyclic Compounds (8 papers). Muhammad Muddassar collaborates with scholars based in Pakistan, Saudi Arabia and South Korea. Muhammad Muddassar's co-authors include Mahmood Ahmed, Farhan Ahmad Pasha, Muhammad Abdul Qadir, Seung Joo Cho, Abdul Hameed, Jamshed Iqbal, Abdullah M. Asiri, Muhammad Nadeem Arshad, Aamer Saeed and Kam Y. J. Zhang and has published in prestigious journals such as PLoS ONE, Biochemical and Biophysical Research Communications and British Journal of Cancer.

In The Last Decade

Muhammad Muddassar

65 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Muhammad Muddassar Pakistan 22 528 433 211 163 116 69 1.2k
Juan Sun China 26 1.2k 2.2× 699 1.6× 143 0.7× 188 1.2× 254 2.2× 106 2.2k
Gamal El‐Din A. Abuo‐Rahma Egypt 31 2.1k 3.9× 1.3k 3.1× 212 1.0× 379 2.3× 340 2.9× 120 3.1k
Juan Antonio Palop Spain 32 1.6k 3.0× 604 1.4× 42 0.2× 133 0.8× 222 1.9× 97 2.9k
Amara Mumtaz Pakistan 20 480 0.9× 299 0.7× 110 0.5× 197 1.2× 95 0.8× 62 1.1k
Cecilia Bossa Italy 27 201 0.4× 680 1.6× 864 4.1× 100 0.6× 47 0.4× 54 2.1k
Vasyl Kovalishyn Ukraine 16 518 1.0× 276 0.6× 320 1.5× 67 0.4× 60 0.5× 64 1.0k
Alexander Sedykh United States 28 141 0.3× 782 1.8× 1.3k 6.0× 163 1.0× 164 1.4× 51 2.3k
Huan‐Qiu Li China 27 1.4k 2.6× 837 1.9× 153 0.7× 204 1.3× 502 4.3× 68 2.4k
Xiaoyun Zhang China 24 272 0.5× 496 1.1× 365 1.7× 46 0.3× 62 0.5× 80 1.5k
Vilma Petrikaitė Lithuania 25 355 0.7× 707 1.6× 78 0.4× 118 0.7× 310 2.7× 89 1.8k

Countries citing papers authored by Muhammad Muddassar

Since Specialization
Citations

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

Fields of papers citing papers by Muhammad Muddassar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Muhammad Muddassar

This figure shows the co-authorship network connecting the top 25 collaborators of Muhammad Muddassar. A scholar is included among the top collaborators of Muhammad Muddassar 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 Muhammad Muddassar. Muhammad Muddassar 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.
Ahmed, Mahmood, Muhammad Naeem, Khairia Mohammed Al‐Ahmary, et al.. (2025). Exploring the potential of biphenyls as promising multi-enzyme inhibitors: Synthesis, molecular docking, and dynamic simulation studies. Journal of Molecular Structure. 1342. 142690–142690.
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Alharthy, Rima D., et al.. (2023). Binding selectivity analysis of AURKs inhibitors through molecular dynamics simulation studies. PLoS ONE. 18(12). e0295741–e0295741. 2 indexed citations
5.
Muddassar, Muhammad, et al.. (2023). Anaphylactic Reaction by Local Anesthesia; Knowledge and Attitude among the Dental Practitioners. 17(2). 117–119. 1 indexed citations
6.
Batool, Maria, Ciara Keating, Sundus Javed, et al.. (2023). A Cross-Sectional Study of Potential Antimicrobial Resistance and Ecology in Gastrointestinal and Oral Microbial Communities of Young Normoweight Pakistani Individuals. Microorganisms. 11(2). 279–279. 6 indexed citations
7.
Qadir, Muhammad Abdul, Mahmood Ahmed, Muhammad Ahmad, et al.. (2023). Exploring the Potential of New Benzamide-Acetamide Pharmacophore Containing Sulfonamide as Urease Inhibitors: Structure–Activity Relationship, Kinetics Mechanism, and In Silico Studies. ACS Omega. 8(48). 46165–46181. 10 indexed citations
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Furqan, Muhammad, Rahim Ullah, Muhammad Muddassar, et al.. (2021). CCT245718, a dual FLT3/Aurora A inhibitor overcomes D835Y-mediated resistance to FLT3 inhibitors in acute myeloid leukaemia cells. British Journal of Cancer. 125(7). 966–974. 12 indexed citations
10.
Alharthy, Rima D., Saadia Naseem, Mahmood Ahmed, et al.. (2018). Investigations of Structural Requirements for BRD4 Inhibitors through Ligand- and Structure-Based 3D QSAR Approaches. Molecules. 23(7). 1527–1527. 15 indexed citations
11.
Saeed, Aamer, Sumera Zaib, Saba Ashraf, et al.. (2015). Synthesis, cholinesterase inhibition and molecular modelling studies of coumarin linked thiourea derivatives. Bioorganic Chemistry. 63. 58–63. 48 indexed citations
12.
Tsuchiya, Ayako, Miwako Asanuma, Go Hirai, et al.. (2013). CDC25A-inhibitory RE derivatives bind to pocket adjacent to the catalytic site. Molecular BioSystems. 9(5). 1026–1034. 3 indexed citations
13.
al‐Rashida, Mariya, Rizwan Raza, Ghulam Abbas, et al.. (2013). Identification of novel chromone based sulfonamides as highly potent and selective inhibitors of alkaline phosphatases. European Journal of Medicinal Chemistry. 66. 438–449. 37 indexed citations
14.
Muddassar, Muhammad, et al.. (2010). Structural studies of B-type Aurora kinase inhibitors using computational methods. Acta Pharmacologica Sinica. 31(2). 244–258. 10 indexed citations
15.
Muddassar, Muhammad, Yong Seo Cho, Gyochang Keum, et al.. (2010). Identification of novel antitubercular compounds through hybrid virtual screening approach. Bioorganic & Medicinal Chemistry. 18(18). 6914–6921. 25 indexed citations
16.
Pasha, Farhan Ahmad, Muhammad Muddassar, & Seung Joo Cho. (2009). Molecular Docking and 3D QSAR Studies of Chk2 Inhibitors. Chemical Biology & Drug Design. 73(3). 292–300. 15 indexed citations
17.
Pasha, Farhan Ahmad, et al.. (2008). Mechanism based QSAR studies of N-phenylbenzamides as antimicrobial agents. Environmental Toxicology and Pharmacology. 26(2). 128–135. 14 indexed citations
18.
Pasha, Farhan Ahmad, et al.. (2008). Hologram and 3D-quantitative structure toxicity relationship studies of azo dyes. Journal of Molecular Modeling. 14(4). 293–302. 21 indexed citations
19.
Muddassar, Muhammad, et al.. (2008). Receptor Guided 3D‐QSAR: A Useful Approach for Designing of IGF‐1R Inhibitors. BioMed Research International. 2008(1). 837653–837653. 9 indexed citations
20.
Khaliq, Shazia, et al.. (2007). Change in colony morphology and kinetics of tylosin production after UV and gamma irradiation mutagenesis of Streptomyces fradiae NRRL-2702. Microbiological Research. 164(4). 469–477. 42 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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