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Structural Determinants of Mac1 Inhibition: Lessons from Ligand Binding Patterns2026 Zenodo (CERN European Organization for Nuclear Research) article Computer Science Computational Drug Discovery Methods Open access
Verena Weber, Giulia Rossetti, Bernhard Lüscher, Patricia Korn, Sarah Knapp
0citations -
Structural Determinants of Mac1 Inhibition: Lessons from Ligand Binding Patterns2026 Zenodo (CERN European Organization for Nuclear Research) article Computer Science Computational Drug Discovery Methods Open access
Verena Weber, Giulia Rossetti, Bernhard Lüscher, Patricia Korn, Sarah Knapp
0citations -
Ligand Pose Predictions for Human G Protein-Coupled Receptors: Insights from the Amber-Based Hybrid Molecular Mechanics/Coarse-Grained Approach2020 Journal of Chemical Information and Modeling article Computer Science Computational Drug Discovery Methods
Ksenia Korshunova, Zeineb Si Chaib, Alejandro Giorgetti, Mercedes Alfonso‐Prieto, Paolo Carloni
16citations -
Navigating the complexities of docking tools with nicotinic receptors and acetylcholine binding proteins in the realm of neonicotinoids2024 Ecotoxicology and Environmental Safety article Computer Science Computational Drug Discovery Methods Open access
Zakaria Bouchouireb, Damien Olivier‐Jimenez, Titouan Jaunet‐Lahary, Steeve Hervé Thany, Jean‐Yves Le Questel
14citations -
Enhanced Sampling Approach to the Induced-Fit Docking Problem in Protein–Ligand Binding: The Case of Mono-ADP-Ribosylation Hydrolase Inhibitors2021 Journal of Chemical Theory and Computation article Computer Science Computational Drug Discovery Methods Open access
Qianqian Zhao, Riccardo Capelli, Paolo Carloni, Bernhard Lüscher, Jinyu Li, Giulia Rossetti
28citations -
Anticancer Potential of Colebrookea oppositifolia Flower Extract Against Breast and Prostate Cancer: An Integrated LC-MS, Network Pharmacology, Molecular Dynamics, PCA, and MM-GBSA Approach
Ranbir Yadav, Fatima Iftikhar Shah, Asad Abbas, Ralf Weiskirchen, Prabhat Jha, Anita Tiwari, +5 more
0citations -
Reproducibility Archive for Explainable Machine Learning Integrating Quantum Mechanical Descriptors and Matched Molecular Pair Analysis for Scaffold-Generalizable Discovery of Soluble Epoxide Hydrolase Inhibitors.2026 Zenodo (CERN European Organization for Nuclear Research) dataset Computer Science Computational Drug Discovery Methods Open access
Dileep Kumar, Ajwin Joseph Martin, Maria Grishina, Mohd Shahbaaz
0citations -
Reproducibility Archive for Explainable Machine Learning Integrating Quantum Mechanical Descriptors and Matched Molecular Pair Analysis for Scaffold-Generalizable Discovery of Soluble Epoxide Hydrolase Inhibitors.2026 Zenodo (CERN European Organization for Nuclear Research) dataset Computer Science Computational Drug Discovery Methods Open access
Dileep Kumar, Ajwin Joseph Martin, Maria Grishina, Mohd Shahbaaz
0citations -
Identifying Novel Inhibitors for Hepatic Organic Anion Transporting Polypeptides by Machine Learning-Based Virtual Screening2022 Journal of Chemical Information and Modeling article Computer Science Computational Drug Discovery Methods Open access
Alzbeta Tuerkova, Brandon J. Bongers, Ulf Norinder, Orsolya Ungvári, Virág Székely, Andrey Tarnovskiy, +4 more
24citations -
Fi-score: a novel approach to characterise protein topology and aid in drug discovery studies2020 bioRxiv (Cold Spring Harbor Laboratory) preprint Computer Science Computational Drug Discovery Methods Open access
Austė Kanapeckaitė, Claudia Beaurivage, MATTHEW J. HANCOCK, Erik Verschueren
2citations