Alberto Cuzzolin

发表

Understanding allosteric interactions in G protein-coupled receptors using Supervised Molecular Dynamics: A prototype study analysing the human A3 adenosine receptor positive allosteric modulator LUF6000.

S. Moro, G. Deganutti, Antonella Ciancetta, 2015, Bioorganic & medicinal chemistry.

Synthesis and preliminary structure-activity relationship study of 2-aryl-2H-pyrazolo[4,3-c]quinolin-3-ones as potential checkpoint kinase 1 (Chk1) inhibitors

M. Sturlese, S. Moro, D. M. Vera, 2017, Journal of enzyme inhibition and medicinal chemistry.

AquaMMapS: An Alternative Tool to Monitor the Role of Water Molecules During Protein–Ligand Association

M. Sturlese, S. Moro, G. Deganutti, 2018, ChemMedChem.

A Deep-Learning Approach toward Rational Molecular Docking Protocol Selection

M. Sturlese, S. Moro, Alberto Cuzzolin, 2020, Molecules.

DockBench as docking selector tool: the lesson learned from D3R Grand Challenge 2015

Stefano Moro, Alberto Cuzzolin, Veronica Salmaso, 2016, Journal of Computer-Aided Molecular Design.

ALK Kinase Domain Mutations in Primary Anaplastic Large Cell Lymphoma: Consequences on NPM-ALK Activity and Sensitivity to Tyrosine Kinase Inhibitors

S. Moro, G. Basso, A. Albiero, 2015, PloS one.

Reconstruction of apo A2A receptor activation pathways reveal ligand-competent intermediates and state-dependent cholesterol hotspots

S. Kelm, G. de Fabritiis, Z. Sands, 2019, Scientific Reports.

DockBench: An Integrated Informatic Platform Bridging the Gap between the Robust Validation of Docking Protocols and Virtual Screening Simulations

Stefano Moro, Rino Ragno, Antonella Ciancetta, 2015, Molecules.

PathwayMap: Molecular Pathway Association with Self-Normalizing Neural Networks

Gianni De Fabritiis, Gerard Martínez-Rosell, Davide Sabbadin, 2018, J. Chem. Inf. Model..

Unbinding Kinetics of Muscarinic M3 Receptor Antagonists Explained by Metadynamics Simulations

M. Mor, A. Rizzi, Alberto Cuzzolin, 2023, J. Chem. Inf. Model..

Exploring Protein-Peptide Recognition Pathways Using a Supervised Molecular Dynamics Approach.

M. Sturlese, S. Moro, V. Salmaso, 2017, Structure.

Computationally driven discovery of SARS-CoV-2 Mpro inhibitors: from design to experimental validation

Pengyu Y. Ren, J. Ponder, M. Sturlese, 2021, Chemical science.

Implementing the “Best Template Searching” tool into Adenosiland platform

S. Moro, M. Floris, Davide Sabbadin, 2013, In Silico Pharmacology.

Deciphering the Complexity of Ligand-Protein Recognition Pathways Using Supervised Molecular Dynamics (SuMD) Simulations

Stefano Moro, Antonella Ciancetta, Davide Sabbadin, 2016, J. Chem. Inf. Model..

Alternative Quality Assessment Strategy to Compare Performances of GPCR-Ligand Docking Protocols: The Human Adenosine A2A Receptor as a Case Study

Stefano Moro, Antonella Ciancetta, Alberto Cuzzolin, 2014, J. Chem. Inf. Model..

New Trends in Inspecting GPCR‐ligand Recognition Process: the Contribution of the Molecular Modeling Section (MMS) at the University of Padova

Antonella Ciancetta, Davide Sabbadin, Andrea Cristiani, 2016, Molecular informatics.

Combining self- and cross-docking as benchmark tools: the performance of DockBench in the D3R Grand Challenge 2

Stefano Moro, Alberto Cuzzolin, Veronica Salmaso, 2017, Journal of Computer-Aided Molecular Design.

SkeleDock: A Web Application for Scaffold Docking in PlayMolecule

Maciej Majewski, Gianni De Fabritiis, Gerard Martínez-Rosell, 2020, J. Chem. Inf. Model..

Can We Still Trust Docking Results? An Extension of the Applicability of DockBench on PDBbind Database

Alberto Cuzzolin, Stefano Moro, Mattia Sturlese, 2019, International journal of molecular sciences.

Exploring the recognition pathway at the human A2A adenosine receptor of the endogenous agonist adenosine using supervised molecular dynamics simulations

S. Moro, Davide Sabbadin, Antonella Ciancetta, 2015 .