Per-Ola Norrby, Ph.D.
Affiliations: | 1994-2000 | Medicinal Chemistry | Royal Danish School of Pharmacy |
| 2000-2006 | Chemistry (Organic chemistry) | Technical University of Denmark, Kongens Lyngby, Denmark | |
| 2006-2014 | Chemistry (Organic chemistry) | University of Gothenburg, Gothenburg, Västra Götalands län, Sweden | |
| 2014- | Data Science & Modelling | AstraZeneca Gothenburg, Sweden |
Area:
molecular modeling, homogeneous catalysis, reaction mechanismsWebsite:
https://www.linkedin.com/in/per-ola-norrby-a456403/Google:
"Per-Ola Norrby"Bio:
Twitter: @PeONor
Mastodon: https://mstdn.social/@peonor
1992: PhD, Organic Chemistry, Royal institute of technology (KTH), Stockholm, Sweden (advisor: Björn Åkermark)
1992-1993: Postdoc, The Scripps Research Institute, La Jolla, CA, USA (advisor: K. Barry Sharpless)
1994-1996: Postdoc, Royal Danish School of Pharmacy (DFH), Copenhagen, Denmark (advisor: Tommy Liljefors)
Mean distance: 7.37 | S | N | B | C | P |
Parents
Sign in to add mentor| Björn Åkermark | grad student | 1992 | KTH Royal Institute of Technology | |
| (Development of Molecular Mechanics for Use in (η3-Allyl) Palladium Chemistry) | ||||
| K. Barry Sharpless | post-doc | 1992-1993 | Scripps Institute | |
| Tommy Liljefors | post-doc | 1994-1996 | Danish School of Pharmacy (Neurotree) | |
Children
Sign in to add trainee| Eric C Hansen | grad student | ||
| Helena Hagelin-Weaver | grad student | 1999 | KTH Royal Institute of Technology |
| Peter Fristrup | grad student | 2003-2006 | Technical University of Denmark |
| Mårten S. G. Ahlquist | grad student | 2004-2007 | Technical University of Denmark |
| Sten Nilsson Lill | post-doc | 2009-2010 | University of Gothenburg |
| Carl-Johan Wallentin | post-doc | 2013-2014 | University of Gothenburg |
Collaborators
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Publications
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| Saebi M, Nan B, Herr JE, et al. (2023) On the use of real-world datasets for reaction yield prediction. Chemical Science. 14: 4997-5005 |
| Maloney MP, Coley CW, Genheden S, et al. (2023) Negative Data in Data Sets for Machine Learning Training. Organic Letters. 25: 2945-2947 |
| Maloney MP, Coley CW, Genheden S, et al. (2023) Negative Data in Data Sets for Machine Learning Training. The Journal of Organic Chemistry. 88: 5239-5241 |
| Wahlers J, Rosales AR, Berkel N, et al. (2022) A Quantum-Guided Molecular Mechanics Force Field for the Ferrocene Scaffold. The Journal of Organic Chemistry. 87: 12334-12341 |
| Di Tommaso EM, Norrby PO, Olofsson B. (2022) Explaining Regio-Divergent Vinylations with Vinylbenziodoxolones. Angewandte Chemie (International Ed. in English) |
| Quinn TR, Patel HN, Koh KH, et al. (2022) Automated fitting of transition state force fields for biomolecular simulations. Plos One. 17: e0264960 |
| Wahlers J, Margalef J, Hansen E, et al. (2021) Proofreading experimentally assigned stereochemistry through Q2MM predictions in Pd-catalyzed allylic aminations. Nature Communications. 12: 6719 |
| Quinn TR, Steussy CN, Haines BE, et al. (2021) Microsecond timescale MD simulations at the transition state of HMGR predict remote allosteric residues. Chemical Science. 12: 6413-6418 |
| Lidskog A, Dawaigher S, Solano Arribas C, et al. (2021) Experimental and Computational Models for Side Chain Discrimination in Peptide-Protein Interactions. Chemistry (Weinheim An Der Bergstrasse, Germany) |
| Wahlers J, Maloney M, Salahi F, et al. (2021) Stereoselectivity Predictions for the Pd-Catalyzed 1,4-Conjugate Addition Using Quantum-Guided Molecular Mechanics. The Journal of Organic Chemistry |