Working Paper
Authors
- Ina Poehner
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Heidelberg Institute for Theoretical Studies (HITS gGmbH)
, - Antonio Quotadamo Tydock Pharma (Italy) & University of Modena and Reggio Emilia, Clinical and Experimental Medicine PhD Program - Italy ,
- Joanna Panecka-Hofman Heidelberg Institute for Theoretical Studies & University of Warsaw, Faculty of Physics - Poland ,
- Rosaria Luciani University of Modena and Reggio Emilia ,
- Matteo Santucci University of Modena and Reggio Emilia ,
- Pasquale Linciano University of Modena and Reggio Emilia ,
- Giacomo Landi University of Siena ,
- Flavio Di Pisa University of Siena ,
- Lucia Dello Iacono University of Siena ,
- Cecilia Pozzi University of Siena ,
- Stefano Mangani University of Siena ,
- Sheraz Gul Fraunhofer Institute for Molecular Biology and Applied Ecology ,
- Gesa Witt Fraunhofer Institute for Molecular Biology and Applied Ecology ,
- Bernhard Ellinger Fraunhofer Institute for Molecular Biology and Applied Ecology ,
- Maria Kuzikov Fraunhofer Institute for Molecular Biology and Applied Ecology ,
- Nuno Santarem University of Porto ,
- Anabela Cordeiro-da-Silva University of Porto ,
- Maria Paola Costi University of Modena and Reggio Emilia ,
- Alberto Venturelli Tydock Pharma (Italy) ,
- Rebecca Wade Heidelberg Institute for Theoretical Studies & Heidelberg University
Abstract
The optimization of compounds with multiple targets is a difficult multidimensional problem in the drug discovery cycle. Here, we present a systematic, multidisciplinary approach to the development of selective anti-parasitic compounds. Computational fragment-based design of novel pteridine derivatives along with iterations of crystallographic structure determination allowed for the derivation of a structure-activity relationship for multitarget inhibition. The approach yielded compounds showing apparent picomolar inhibition of T. brucei pteridine reductase 1 (PTR1), nanomolar inhibition of L. major PTR1, and selective submicromolar inhibition of parasite dihydrofolate reductase (DHFR) versus human DHFR. Moreover, by combining design for polypharmacology with a property-based on-parasite optimization, we found three compounds that exhibited micromolar EC50 values against T. brucei brucei, whilst retaining their target inhibition. Our results provide a basis for the further development of pteridine-based compounds, and we expect our multitarget approach to be generally applicable to the design and optimization of anti-infective agents.
Version notes
Further additions to and clarifications of methodological details for enzyme inhibition and anti-parasitic assays; correction of TbPTR1 (cpds 3b, 3c, 4c) and LmPTR1 IC50 values (1h); addition of selected dose-response curves and compound NMR spectra (Supporting Information)
Content
Supplementary material
pteridine-manuscript Supporting Information
Supplemental Figures S1-9, Supplemental Tables S1-12, Supplemental experimental procedures and compound characterization, NMR spectra of compounds
Supplementary weblinks
Additional supplementary data on FAIRDOMHub
QikProp prediction results for synthesized and in silico pteridines and corresponding SOP. PAINS filtering results, Python modules for correlating QikProp data with experimental activities and for computing a multiple correlation between target and parasite inhibition. Compound library construction data and SOP, prepared docking receptors (PDB) with SOP, all Glide XP rigid-body docking results as PDB files of the receptor-ligand complexes and SOP as well as selected discussed induced fit docking results and corresponding SOP.
