Viktor S. Stroylov

687 total citations
33 papers, 562 citations indexed

About

Viktor S. Stroylov is a scholar working on Molecular Biology, Computational Theory and Mathematics and Organic Chemistry. According to data from OpenAlex, Viktor S. Stroylov has authored 33 papers receiving a total of 562 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 10 papers in Computational Theory and Mathematics and 7 papers in Organic Chemistry. Recurrent topics in Viktor S. Stroylov's work include Computational Drug Discovery Methods (10 papers), Protein Structure and Dynamics (9 papers) and PARP inhibition in cancer therapy (4 papers). Viktor S. Stroylov is often cited by papers focused on Computational Drug Discovery Methods (10 papers), Protein Structure and Dynamics (9 papers) and PARP inhibition in cancer therapy (4 papers). Viktor S. Stroylov collaborates with scholars based in Russia, Iran and Germany. Viktor S. Stroylov's co-authors include Fedor N. Novikov, Ghermes G. Chilov, Oleg V. Stroganov, Alexey A. Zeifman, Vladimir I. Muronetz, Maria V. Panova, Thomas Haertlé, Boris Brill, Polyxeni Alexiou and Afsar Mian and has published in prestigious journals such as Blood, Scientific Reports and FEBS Letters.

In The Last Decade

Viktor S. Stroylov

33 papers receiving 540 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Viktor S. Stroylov Russia 13 295 165 109 83 62 33 562
Ghermes G. Chilov Russia 16 433 1.5× 163 1.0× 174 1.6× 122 1.5× 100 1.6× 44 798
Akshay Patny United States 12 356 1.2× 141 0.9× 149 1.4× 117 1.4× 18 0.3× 14 682
Natesh Singh France 10 371 1.3× 150 0.9× 51 0.5× 112 1.3× 32 0.5× 16 582
Michele F. Rega United States 17 502 1.7× 90 0.5× 137 1.3× 92 1.1× 25 0.4× 28 762
John Strelow United States 7 247 0.8× 84 0.5× 129 1.2× 65 0.8× 17 0.3× 9 365
Steffen Lang Germany 13 478 1.6× 107 0.6× 110 1.0× 147 1.8× 47 0.8× 19 667
Gary Brandt United States 13 515 1.7× 103 0.6× 145 1.3× 21 0.3× 52 0.8× 15 732
Vincent Galullo United States 10 468 1.6× 90 0.5× 229 2.1× 182 2.2× 31 0.5× 10 724
Dimitrios Spiliotopoulos Switzerland 13 568 1.9× 116 0.7× 69 0.6× 51 0.6× 33 0.5× 24 735
Mahesh Kumar Teli India 13 257 0.9× 97 0.6× 71 0.7× 43 0.5× 46 0.7× 24 527

Countries citing papers authored by Viktor S. Stroylov

Since Specialization
Citations

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

Fields of papers citing papers by Viktor S. Stroylov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Viktor S. Stroylov. 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 Viktor S. Stroylov. The network helps show where Viktor S. Stroylov may publish in the future.

Co-authorship network of co-authors of Viktor S. Stroylov

This figure shows the co-authorship network connecting the top 25 collaborators of Viktor S. Stroylov. A scholar is included among the top collaborators of Viktor S. Stroylov 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 Viktor S. Stroylov. Viktor S. Stroylov 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.
Stroylov, Viktor S., et al.. (2023). Substituted cinnamides: Characterization of non-toxic inhibitors of alpha-synuclein aggregation. Mendeleev Communications. 33(3). 334–336. 2 indexed citations
2.
Stroylov, Viktor S., et al.. (2023). Does the SARS-CoV-2 Spike Receptor-Binding Domain Hamper the Amyloid Transformation of Alpha-Synuclein after All?. Biomedicines. 11(2). 498–498. 4 indexed citations
3.
Novikov, Fedor N., et al.. (2021). Inhibition of SYK and cSrc kinases can protect bone and cartilage in preclinical models of osteoarthritis and rheumatoid arthritis. Scientific Reports. 11(1). 23120–23120. 13 indexed citations
4.
Stroylov, Viktor S., et al.. (2020). Computational modeling and target synthesis of monomethoxy-substituted o-diphenylisoxazoles with unexpectedly high antimitotic microtubule destabilizing activity. Bioorganic & Medicinal Chemistry Letters. 30(23). 127608–127608. 12 indexed citations
5.
Тимофеев, В. И., et al.. (2020). Structure-based inhibitors targeting the alpha-helical domain of the Spiroplasma melliferum histone-like HU protein. Scientific Reports. 10(1). 15128–15128. 10 indexed citations
6.
Sagnou, Marina, Fedor N. Novikov, Polyxeni Alexiou, et al.. (2020). Novel curcumin derivatives as P-glycoprotein inhibitors: Molecular modeling, synthesis and sensitization of multidrug resistant cells to doxorubicin. European Journal of Medicinal Chemistry. 198. 112331–112331. 41 indexed citations
7.
Stroylov, Viktor S., Maria V. Panova, & Filip V. Toukach. (2020). Comparison of Methods for Bulk Automated Simulation of Glycosidic Bond Conformations. International Journal of Molecular Sciences. 21(20). 7626–7626. 8 indexed citations
8.
Stroylov, Viktor S., et al.. (2017). Inhibition of Prion Propagation by 3,4‐Dimethoxycinnamic Acid. Phytotherapy Research. 31(7). 1046–1055. 23 indexed citations
9.
Stroylov, Viktor S., et al.. (2017). Modeling comparative selectivity profiles of kinase inhibitors using FEP/MD protocol. Mendeleev Communications. 27(4). 349–351. 1 indexed citations
10.
Zeifman, Alexey A., et al.. (2015). Modeling of the Diels–Alder reaction enantioselectivity by quantum mechanics and molecular mechanics. Mendeleev Communications. 25(4). 269–270. 5 indexed citations
11.
Zeifman, Alexey A., et al.. (2015). An explicit account of solvation is essential for modeling Suzuki–Miyaura coupling in protic solvents. Dalton Transactions. 44(40). 17795–17799. 5 indexed citations
12.
Mian, Afsar, Alireza Rafiei, Isabella Haberbosch, et al.. (2014). PF-114, a potent and selective inhibitor of native and mutated BCR/ABL is active against Philadelphia chromosome-positive (Ph+) leukemias harboring the T315I mutation. Leukemia. 29(5). 1104–1114. 50 indexed citations
13.
Zeifman, Alexey A., Fedor N. Novikov, Viktor S. Stroylov, et al.. (2013). 2,3‐Dihydroxy‐quinoxaline induces ATPase activity of Herpes Simplex Virus thymidine kinase. FEBS Letters. 588(3). 509–511. 2 indexed citations
14.
Mian, Afsar, Anahita Rafiei, Isabella Haberbosch, et al.. (2013). PF-114, a Novel Selective Pan BCR/ABL Inhibitor Targets The T315I and Suppress Models Of Advanced Ph+ ALL. Blood. 122(21). 3907–3907. 3 indexed citations
15.
Novikov, Fedor N., et al.. (2012). Lead Finder docking and virtual screening evaluation with Astex and DUD test sets. Journal of Computer-Aided Molecular Design. 26(6). 725–735. 36 indexed citations
16.
Zeifman, Alexey A., Viktor S. Stroylov, Fedor N. Novikov, et al.. (2011). Hit clustering can improve virtual fragment screening: CDK2 and PARP1 case studies. Journal of Molecular Modeling. 18(6). 2553–2566. 7 indexed citations
17.
Stroganov, Oleg V., Fedor N. Novikov, Alexey A. Zeifman, Viktor S. Stroylov, & Ghermes G. Chilov. (2011). TSAR, a new graph–theoretical approach to computational modeling of protein side‐chain flexibility: Modeling of ionization properties of proteins. Proteins Structure Function and Bioinformatics. 79(9). 2693–2710. 26 indexed citations
18.
Novikov, Fedor N., et al.. (2011). CSAR Scoring Challenge Reveals the Need for New Concepts in Estimating Protein–Ligand Binding Affinity. Journal of Chemical Information and Modeling. 51(9). 2090–2096. 22 indexed citations
19.
Novikov, Fedor N., et al.. (2009). Developing novel approaches to improve binding energy estimation and virtual screening: a PARP case study. Journal of Molecular Modeling. 15(11). 1337–1347. 15 indexed citations
20.
Novikov, Fedor N., Viktor S. Stroylov, Oleg V. Stroganov, & Ghermes G. Chilov. (2009). Improving performance of docking-based virtual screening by structural filtration. Journal of Molecular Modeling. 16(7). 1223–1230. 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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