Dima Kozakov

15.7k total citations · 6 hit papers
129 papers, 10.1k citations indexed

About

Dima Kozakov is a scholar working on Molecular Biology, Computational Theory and Mathematics and Materials Chemistry. According to data from OpenAlex, Dima Kozakov has authored 129 papers receiving a total of 10.1k indexed citations (citations by other indexed papers that have themselves been cited), including 118 papers in Molecular Biology, 55 papers in Computational Theory and Mathematics and 44 papers in Materials Chemistry. Recurrent topics in Dima Kozakov's work include Protein Structure and Dynamics (76 papers), Computational Drug Discovery Methods (55 papers) and Enzyme Structure and Function (42 papers). Dima Kozakov is often cited by papers focused on Protein Structure and Dynamics (76 papers), Computational Drug Discovery Methods (55 papers) and Enzyme Structure and Function (42 papers). Dima Kozakov collaborates with scholars based in United States, Russia and Israel. Dima Kozakov's co-authors include Sándor Vajda, Dmitri Beglov, David R. Hall, Kathryn A. Porter, Christine Yueh, Ryan Brenke, Dzmitry Padhorny, Bing Xia, Tanggis Bohnuud and Stephen R. Comeau and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Chemical Society Reviews.

In The Last Decade

Dima Kozakov

127 papers receiving 10.0k citations

Hit Papers

5 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

The ClusPro web server for protein–protein docking

2017 2.2k citations Dima Kozakov, David R. Hall et al. Nature Protocols profile →
PIPER: An FFT‐based protein docking program with pairwise potentials

2006 630 citations Dima Kozakov, Sándor Vajda et al. profile →
How good is automated protein docking?

2013 556 citations Dima Kozakov, Dmitri Beglov et al. profile →
The FTMap family of web servers for determining and characterizing ligand-binding hot spots of proteins

2015 463 citations Dima Kozakov, David R. Hall et al. Nature Protocols profile →
Performance and Its Limits in Rigid Body Protein-Protein Docking

2020 446 citations Israel Desta, Kathryn A. Porter et al. profile →
New additions to the ClusPro server motivated by CAPRI

2016 409 citations Sándor Vajda, Dmitri Beglov et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Dima Kozakov United States	44	7.7k	2.1k	1.3k	1.2k	1.0k	129	10.1k
Dina Schneidman‐Duhovny United States	41	7.2k 0.9×	1.3k 0.6×	1.8k 1.5×	862 0.7×	701 0.7×	84	10.0k
Maxim Totrov United States	44	6.2k 0.8×	2.8k 1.3×	1.5k 1.2×	724 0.6×	621 0.6×	117	9.0k
Dmitri Beglov United States	30	5.1k 0.7×	1.2k 0.6×	626 0.5×	877 0.7×	752 0.7×	51	6.9k
Marc A. Martı́-Renom Spain	45	11.5k 1.5×	980 0.5×	1.6k 1.3×	583 0.5×	897 0.9×	123	15.4k
David B. Ascher Australia	46	6.9k 0.9×	2.6k 1.2×	853 0.7×	564 0.5×	537 0.5×	187	11.8k
Gabriel Studer Switzerland	17	9.5k 1.2×	977 0.5×	953 0.8×	505 0.4×	1.1k 1.1×	22	15.2k
Koushik Kasavajhala United States	7	6.7k 0.9×	1.4k 0.7×	1.3k 1.1×	422 0.3×	500 0.5×	9	9.4k
Martino Bertoni Switzerland	11	8.4k 1.1×	904 0.4×	841 0.7×	462 0.4×	1.0k 1.0×	17	13.5k
Min‐Yi Shen United States	14	7.6k 1.0×	900 0.4×	1.3k 1.1×	546 0.4×	782 0.8×	20	10.4k
András Fiser United States	43	8.0k 1.0×	951 0.4×	1.9k 1.5×	571 0.5×	1.2k 1.1×	144	11.3k

Countries citing papers authored by Dima Kozakov

Since Specialization

Citations

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

Fields of papers citing papers by Dima Kozakov

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dima Kozakov

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Jones, George, et al.. (2025). E-FTMap: A Protein Structure Based Pharmacophore Identification Server for Guiding Fragment Expansion. Journal of Molecular Biology. 437(15). 168956–168956.

Xiao, Zhangping, Fangyuan Cao, Xinyue Zhang, et al.. (2025). Identification of Actionable Targeted Protein Degradation Effector Sites through Site-Specific Ligand Incorporation-Induced Proximity (SLIP). Journal of the American Chemical Society. 147(25). 21549–21559. 1 indexed citations

Li, Yong, David Yin-wei Lin, Bharath Srinivasan, et al.. (2025). Modulating the Binding Kinetics of Bruton’s Tyrosine Kinase Inhibitors through Transition-State Effects. Journal of the American Chemical Society. 147(31). 27876–27891. 1 indexed citations

Zhu, Y., George Jones, Carlos Simmerling, et al.. (2024). MHC-Fine: Fine-tuned AlphaFold for precise MHC-peptide complex prediction. Biophysical Journal. 123(17). 2902–2909. 5 indexed citations

Blum, Benjamin C., Weiwei Lin, Jacob Porter, et al.. (2024). Multiomic profiling of chronically activated CD4+ T cells identifies drivers of exhaustion and metabolic reprogramming. PLoS Biology. 22(12). e3002943–e3002943. 4 indexed citations

Desta, Israel, Sergei Kotelnikov, George Jones, et al.. (2023). The ClusPro AbEMap web server for the prediction of antibody epitopes. Nature Protocols. 18(6). 1814–1840. 14 indexed citations

Davila, Ana, Zichang Xu, Songling Li, et al.. (2022). AbAdapt: an adaptive approach to predicting antibody–antigen complex structures from sequence. Bioinformatics Advances. 2(1). vbac015–vbac015. 21 indexed citations

Havugimana, Pierre C., Raghuveera Kumar Goel, Sadhna Phanse, et al.. (2022). Scalable multiplex co-fractionation/mass spectrometry platform for accelerated protein interactome discovery. Nature Communications. 13(1). 4043–4043. 48 indexed citations

Kounde, Cyrille S., Milon Mondal, Jake L. Greenfield, et al.. (2022). Light-mediated multi-target protein degradation using arylazopyrazole photoswitchable PROTACs (AP-PROTACs). Chemical Communications. 58(78). 10933–10936. 35 indexed citations

10.

Wang, Jinan, Andrey Alekseenko, Dima Kozakov, & Yinglong Miao. (2019). Improved Modeling of Peptide-Protein Binding Through Global Docking and Accelerated Molecular Dynamics Simulations. Frontiers in Molecular Biosciences. 6. 112–112. 70 indexed citations

11.

Beglov, Dmitri, David Hall, Amanda Wakefield, et al.. (2018). Exploring the structural origins of cryptic sites on proteins. Proceedings of the National Academy of Sciences. 115(15). E3416–E3425. 93 indexed citations

12.

Padhorny, Dzmitry, et al.. (2018). Glucose regulation in the methylotrophic yeast Hansenula (Ogataea) polymorpha is mediated by a putative transceptor Gcr1. The International Journal of Biochemistry & Cell Biology. 103. 25–34. 2 indexed citations

13.

Padhorny, Dzmitry, David R. Hall, Artem B. Mamonov, et al.. (2017). Protein–ligand docking using FFT based sampling: D3R case study. Journal of Computer-Aided Molecular Design. 32(1). 225–230. 11 indexed citations

14.

Padhorny, Dzmitry, Andrey Kazennov, Brandon S. Zerbe, et al.. (2016). Protein–protein docking by fast generalized Fourier transforms on 5D rotational manifolds. Proceedings of the National Academy of Sciences. 113(30). E4286–93. 44 indexed citations

15.

Kozakov, Dima, David R. Hall, Stefan Jehle, et al.. (2015). Ligand deconstruction: Why some fragment binding positions are conserved and others are not. Proceedings of the National Academy of Sciences. 112(20). E2585–94. 56 indexed citations

16.

Mottarella, Scott E., Dmitri Beglov, Natalia Beglova, et al.. (2014). Docking Server for the Identification of Heparin Binding Sites on Proteins. Journal of Chemical Information and Modeling. 54(7). 2068–2078. 54 indexed citations

17.

Naser‐Moghadasi, Mohammad, Dima Kozakov, Pirooz Vakili, Sándor Vajda, & Ioannis Ch. Paschalidis. (2013). A new distributed algorithm for side-chain positioning in the process of protein docking. PubMed. 78. 739–744. 3 indexed citations

18.

Bohnuud, Tanggis, Scott E. Mottarella, Dmitri Beglov, et al.. (2012). FTMAP: extended protein mapping with user-selected probe molecules. Nucleic Acids Research. 40(W1). W271–W275. 119 indexed citations

19.

Vajda, Sándor & Dima Kozakov. (2009). Convergence and combination of methods in protein–protein docking. Current Opinion in Structural Biology. 19(2). 164–170. 164 indexed citations

20.

Kozakov, Dima, Karl H. Clodfelter, Sándor Vajda, & Carlos J. Camacho. (2005). Optimal Clustering for Detecting Near-Native Conformations in Protein Docking. Biophysical Journal. 89(2). 867–875. 111 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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