Author

Chiara Pallara

ORCID 0000-0003-3005-343XUnclaimed 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 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Research Focus:protein design· 1 Assay:protein sequence· 1 Approach:statistical model· 1

Frequent Co-Authors

Anna M. Díaz-RoviraiD· 2 shared Lucía DíaziD· 2 shared Vı́ctor GuallariD· 2 shared Alexis MolinaiD· 1 shared Carles Perez‐LopeziD· 1 shared Eva Bosse-Doenecke· 1 shared Gregor HoffmanniD· 1 shared Ina Coburger· 1 shared

Activity by Year

2025-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 35 mutual co-author links

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2 shared papersBiochemistry

Anna M. Díaz-RoviraORCID

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2 papers

Recent·Most cited

BiochemistryInternational Journal of Molecular SciencesPeer-reviewedMay 14, 2025

Efficient Design of Affilin(R) Protein Binders for HER3

Anna M. Díaz-Rovira, Jonathan Lotze, Gregor Hoffmann…·Sergi Rodà

This study combines AI/physics-based computation and phage display to design high-affinity Affilin(R) proteins targeting HER3, achieving successful theranostic candidates with high affinity and stability.

2 citations

protein sequencedeep learning

𝕏 PostBluesky

BiophysicsbioRxivPreprintApr 11, 2025

Characterization of PROTACs by Ternary Complex Landscape Exploration using Monte Carlo simulations

Anna M. Díaz-Rovira, Carles Perez‐Lopez, Jordi Martín-Pérez…·Vı́ctor Guallar

The paper uses Monte Carlo simulations to analyze the dynamic energy landscapes of PROTAC ternary complexes, identifying stable conformations and supporting PROTAC optimization.

DOI 10.1101/2025.04.11.648328

deep learningstatistical model

𝕏 PostBluesky