Structural Determinants of Mac1 Inhibition: Lessons from Ligand Binding Patterns

Zenodo (CERN European Organization for Nuclear Research)

Abstract

This dataset accompanies the study "Structural Determinants of Mac1 Inhibition: Lessons from Ligand Binding Patterns" and contains the computational and structural data used to investigate ligand recognition and inhibition mechanisms of the SARS-CoV-2 Macrodomain Mac1. The dataset comprises molecular dynamics simulation data, structural models, ligand-protein interaction analyses used to characterize binding modes and identify key determinants of inhibitor recognition. The analyses focus on understanding how distinct ligand binding patterns influence interactions within the Mac1 active site and contribute to inhibitory activity. Contents Prepared protein–ligand complex structures Molecular dynamics simulation trajectories Representative conformations Ligand binding poses Protein–ligand interaction fingerprints and contact analyses Protein–ligand interaction UMAP analysis Protein-ligand interaction analyses MSA Free energy surfaces

Authors 5

1. Verena Weber Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University

2. Giulia Rossetti Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University

3. Bernhard Lüscher Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University

4. Patricia Korn Aachen Medizinische Fakultät

   RWTH Aachen University

   Affiliation as printed

   Medizinische Fakultät der RWTH Aachen

5. Sarah Knapp Aachen Medizinische Fakultät

   RWTH Aachen University

   Affiliation as printed

   Medizinische Fakultät der RWTH Aachen