From Experiments to a Fast Easy-to-Use Computational Methodology to Predict Human Aldehyde Oxidase Selectivity and Metabolic Reactions

Author:

Cruciani Gabriele12ORCID,Milani Nicolò1ORCID,Benedetti Paolo12ORCID,Lepri Susan1,Cesarini Lucia1ORCID,Baroni Massimo3ORCID,Spyrakis Francesca4ORCID,Tortorella Sara25ORCID,Mosconi Edoardo26,Goracci Laura12ORCID

Affiliation:

1. Department of Chemistry, Biology and Biotechnology, University of Perugia, via Elce di Sotto 8, 06123 Perugia, Italy

2. Consortium for Computational Molecular and Materials Sciences (CMS), via Elce di Sotto 8, 06123 Perugia, Italy

3. Molecular Discovery Ltd, Centennial Park, Borehamwood, Hertfordshire, United Kingdom

4. Department of Drug Science and Technology, University of Turin, via P. Giuria 9, 10125 Turin, Italy

5. Molecular Horizon srl, via Montelino 32, 06084 Bettona, Italy

6. Computational Laboratory for Hybrid/Organic Photovoltaics, National Research Council−Institute of Molecular Science and Technologies, Via Elce di Sotto 8, I-06123 Perugia, Italy

Publisher

American Chemical Society (ACS)

Subject

Drug Discovery,Molecular Medicine

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