Author

V. Limongelli

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Biophysics· 2 Biochemistry· 1

Signature Assays, Organisms & Methods

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Assay:protein structure· 2 Approach:statistical model· 2 Research Focus:chromatin & epigenetic regulation· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Organism:human· 1 Approach:mechanistic / dynamical model· 1 Research Focus:protein folding & dynamics· 1

Frequent Co-Authors

L. Marinelli· 1 shared M. Parrinello· 1 shared P. Conflitti· 1 shared S. Aureli· 1 shared S. Raniolo· 1 shared V. M. D'Amore· 1 shared Z. F. Brotzakis· 1 shared

Activity by Year

2018-2023 · peak 2/yr

Co-Author Collaboration Network

7 top collaborators · 5 mutual co-author links

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1 shared paperBiophysics

L. Marinelli

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Minute-timescale simulations of G Protein Coupled Receptor A2A activation mechanism reveal a receptor pseudo-active state

V. M. D'Amore, P. Conflitti, L. Marinelli, V. Limongelli

This study uses molecular dynamics simulations to reveal a pseudo-active state in the A2A receptor, providing insights into its activation mechanism and signaling pathways.

bioRxiv · Sep 14, 2023Biophysics

Conformational plasticity and allosteric communication networks govern Shelterin protein TPP1 binding to human telomerase

S. Aureli, S. Raniolo, V. Limongelli

This study characterizes the structural properties of TPP1's OB-domain and reveals how conformational plasticity and allosteric communication networks affect TPP1-TERT binding, with implications for disease and therapeutic design.

bioRxiv · Feb 2, 2023 · PreprintBiochemistry

Accelerating the Calculation of Protein-Ligand Binding Free Energy and residence Times using Dynamically Optimized Collective Variables

Z. F. Brotzakis, V. Limongelli, M. Parrinello

This study predicts ligand binding modes and computes binding free energy and unbinding rates using a novel combination of computational methods, revealing water and solvation as dominant slow degrees of freedom.

bioRxiv · Sep 14, 2018Biophysics