Author

Kamila Riedlová

Charles UniversityORCID 0000-0002-9134-2297Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Organism:human· 2 Research Focus:protein folding & dynamics· 2 Assay:protein structure· 2 Approach:statistical model· 2

Frequent Co-Authors

David HokszaiD· 2 shared Gennady M. VerkhivkeriD· 2 shared Lucas Turano· 2 shared Marián NovotnýiD· 2 shared Max Ludwick· 2 shared Vít ŠkrhákiD· 2 shared Will GatliniD· 2 shared Brandon Foley· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

8 top collaborators · 28 mutual co-author links

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2 shared papersBiophysics

David HokszaORCID

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2 papers

Recent·Most cited

BiophysicsbioRxivPreprintMar 23, 2026

Decoding Allosteric Grammar with Explainable AI Integrating Protein Language Models and Energy Landscape Analysis: Neutral Frustration at Allosteric Binding Sites Encodes Regulatory Versatility in Protein Kinases

Will Gatlin, Max Ludwick, Lucas Turano…·Gennady M. Verkhivker

This study uses explainable AI to analyze the energy landscape of protein kinases, revealing that allosteric sites are in neutrally frustrated regions, explaining their detection challenges.

DOI 10.64898/2026.03.21.713412

humanprotein structure

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BiophysicsbioRxivPreprintJan 6, 2026

Protein Language Models and Structure-Based Machine Learning for Prediction of Allosteric Binding Sites in Protein Kinases: An Explainable AI Framework Grounded in Energy Landscape-Encoded Frustration

Kamila Riedlová, Vít Škrhák, Will Gatlin…·Gennady M. Verkhivker

This paper compares sequence-based and structure-based methods for predicting allosteric binding sites in protein kinases, finding that sequence-based models perform poorly on allosteric sites despite good performance on orthosteric ones.

2 citations

humanprotein structure

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