Tatiana Maximova
Papers
2
Total Citations
37
H-Index
2
About
Tatiana Maximova is a computational structural biologist whose work illuminates the hidden choreography of protein motion. Her research centers on understanding how proteins transition between different functional states—a fundamental question linking structure, dynamics, and biological function. Maximova’s key contribution is the development of a probabilistic roadmap algorithm that uses known protein structures to model these transitions, offering a computationally efficient alternative to traditional molecular dynamics simulations. Her most-cited paper, "Structure-Guided Protein Transition Modeling with a Probabilistic Roadmap Algorithm" (2016, 24 citations), demonstrates how this method can predict plausible pathways between functionally relevant conformations. A follow-up study (2015, 13 citations) extends the approach to multiple-basin proteins, which toggle between several stable states. Though her citation counts are modest, Maximova’s work is notable for its methodological elegance—bridging experimental structural data with computational path planning to reveal the dynamic nature of proteins. Her research provides a powerful toolkit for anyone studying allostery, conformational change, or protein engineering, making complex motions computationally tractable.
Research Focus
Key Achievements
Top Papers
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