9I9C

CRYSTAL STRUCTURE OF HUMAN MONOACYLGLYCEROL LIPASE WITH COMPOUND 29

This is a non-PDB format compatible entry.

Summary for 9I9C

• Entry DOI: 10.2210/pdb9i9c/pdb
• Related: 9I3Y 9I56 9I5J
• Descriptor: Monoglyceride lipase, 1,2-ETHANEDIOL, [2-(4-cyclopentylpyridin-3-yl)-1,3-benzoxazol-6-yl]-[6-(3-cyclopropyl-1,2,4-triazol-1-yl)-2-azaspiro[3.3]heptan-2-yl]methanone, ... (4 entities in total)
• Functional Keywords: alpha/beta hydrolase, serine esterase, hydrolase
• Biological source: Homo sapiens (human)
• Total number of polymer chains: 1
• Total formula weight: 36084.24

Authors

Walter, A.,Atz, K.,Stenzhorn, Y.,Nippa, D.,Grether, U.,Kuhn, B.,Martin, R.,Benz, J. (deposition date: 2025-02-06, release date: 2025-12-10)

Primary citation

Nippa, D.F.,Atz, K.,Stenzhorn, Y.,Muller, A.T.,Tosstorff, A.,Benz, J.,Binch, H.,Burkler, M.,Haider, A.,Heer, D.,Hochstrasser, R.,Kramer, C.,Reutlinger, M.,Schneider, P.,Shema, T.,Topp, A.,Walter, A.,Wittwer, M.B.,Wolfard, J.,Kuhn, B.,van der Stelt, M.,Martin, R.E.,Grether, U.,Schneider, G.
Expediting hit-to-lead progression in drug discovery through reaction prediction and multi-dimensional optimization.
Nat Commun, 2025

PubMed Abstract: The rapid and economical synthesis of novel bioactive compounds remains a hurdle in drug discovery efforts. This study demonstrates an integrated medicinal chemistry workflow that effectively diversifies hit and lead structures, enabling an acceleration of the critical hit-to-lead optimization phase. Employing high-throughput experimentation (HTE), we generated a comprehensive data set encompassing 13,490 novel Minisci-type C-H alkylation reactions. These data served as the foundation for training deep graph neural networks to accurately predict reaction outcomes. Scaffold-based enumeration of potential Minisci reaction products, starting from moderate inhibitors of monoacylglycerol lipase (MAGL), yielded a virtual library containing 26,375 molecules. This virtual chemical library was evaluated using reaction prediction, physicochemical property assessment, and structure-based scoring, identifying 212 MAGL inhibitor candidates. Of these, 14 compounds were synthesized and exhibited subnanomolar activity, representing a potency improvement of up to 4500 times over the original hit compound. These ligands also showed favorable pharmacological profiles. Co-crystallization of three computationally designed ligands with the MAGL protein provided structural insights into their binding modes. This study demonstrates the potential of combining miniaturized HTE with deep learning and optimization of molecular properties to reduce cycle times in hit-to-lead progression.

PubMed: 41290653
DOI: 10.1038/s41467-025-66324-4

Experimental method

X-RAY DIFFRACTION (1.49 Å)