Learning from nature: from a marine natural product to synthetic cyclooxygenase-1 inhibitors by automated de novo design

  • The repertoire of natural products offers tremendous opportunities for chemical biology and drug discovery. Natural product-inspired synthetic molecules represent an ecologically and economically sustainable alternative to the direct utilization of natural products. De novo design with machine intelligence bridges the gap between the worlds of bioactive natural products and synthetic molecules. On employing the compound Marinopyrrole A from marine Streptomyces as a design template, the algorithm constructs innovative small molecules that can be synthesized in three steps, following the computationally suggested synthesis route. Computational activity prediction reveals cyclooxygenase (COX) as a putative target of both Marinopyrrole A and the de novo designs. The molecular designs are experimentally confirmed as selective COX-1 inhibitors with nanomolar potency. X-ray structure analysis reveals the binding of the most selective compound to COX-1. This molecular design approach provides a blueprint for natural product-inspired hit and lead identification for drug discovery with machine intelligence.
Metadaten
Author:Lukas FriedrichORCiDGND, Gino CingolaniORCiD, Ying-Hui Ko, Mariaclara Iaselli, Morena MiciacciaORCiD, Maria Grazia Perrone, Konstantin NeukirchORCiD, Veronika Bobinger, Daniel MerkORCiDGND, Robert Klaus HofstetterORCiD, Oliver WerzORCiDGND, Andreas KoeberleORCiDGND, Antonio ScilimatiORCiD, Gisbert SchneiderORCiDGND
URN:urn:nbn:de:hebis:30:3-639855
DOI:https://doi.org/10.1002/advs.202100832
ISSN:2198-3844
Parent Title (English):Advanced science
Publisher:Wiley-VCH
Place of publication:Weinheim
Document Type:Article
Language:English
Date of Publication (online):2021/06/27
Date of first Publication:2021/06/27
Publishing Institution:Universit├Ątsbibliothek Johann Christian Senckenberg
Release Date:2023/05/03
Volume:8
Issue:16, art. 2100832
Article Number:2100832
Page Number:12
First Page:1
Last Page:12
Note:
This work was financially supported by ETH RETHINK initiative and a Novartis FreeNovation grant AI in Drug Discovery (to G.S.), the NIH grants R01 GM100888, S10 OD017987, S10 OD023479 (to G.C.), and Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), project number 316213987, SFB 1278 PolyTarget (projects A04, C02; to O.W.) and project number 239748522, SFB 1127 ChemBioSys (project A04; to O.W.).
Note:
Data Availability Statement

PDB-ID: 7JXT. Protein Data Bank: www.pdb.org.
HeBIS-PPN:508541492
Institutes:Biochemie, Chemie und Pharmazie
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 54 Chemie / 540 Chemie und zugeordnete Wissenschaften
5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Sammlungen:Universit├Ątspublikationen
Licence (German):License LogoCreative Commons - Namensnennung 4.0