Merging Allosteric and Active Site Binding Motifs: De novo Generation of Target Selectivity and Potency via Natural-Product-Derived Fragments

By Jan Lanz, Rainer Riedl. 2014

39 citations recorded by the source corpus.

The de novo design of molecules from scratch with tailored biological activity is still the major intellectual challenge in chemical biology and drug discovery. Herein we validate natural‐product‐derived fragments (NPDFs) as excellent molecular seeds for the targeted de novo discovery of lead structures for the modulation of therapeutically relevant proteins. The application of this de novo approach delivered, in synergy with the combination of allosteric and active site binding motifs, highly selective and ligand‐efficient non‐zinc‐binding (3: 4‐{[5‐(2‐{[(3‐methoxyphenyl)methyl]carbamoyl}eth‐1‐yn‐1‐yl)‐2,4‐dioxo‐1,2,3,4‐tetrahydropyrimidin‐1‐yl]methyl}benzoic acid) as well as zinc‐binding (4: 4‐({5‐[2‐({[3‐(3‐carboxypropoxy)phenyl]methyl}carbamoyl)eth‐1‐yn‐1‐yl]‐2,4‐dioxo‐1,2,3,4‐tetrahydropyrimidin‐1‐yl}methyl)benzoic acid) uracil‐based MMP‐13 inhibitors presenting IC50 values of 11 nM (3: LE=0.35) and 6 nM (4: LE=0.31).

Subfields: Molecular Biology, Oncology, Pharmacology, Generative Models, Computational Chemistry & Drug Discovery

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

1. Kai Blin
2. Philippe Schwaller
3. Marnix H. Medema
4. Nadine Ziemert
5. Maria Sorokina
6. Marwin H. S. Segler
7. Djork-Arné Clevert
8. Marcy J. Balunas

In Oncology

1. Marcy J. Balunas

In Pharmacology

1. Kai Blin
2. Marnix H. Medema
3. Nadine Ziemert
4. Maria Sorokina
5. Marcy J. Balunas
6. Andrea Volkamer

In Generative Models

1. Marwin H. S. Segler
2. Sergey I. Nikolenko

In Computational Chemistry & Drug Discovery

1. Philippe Schwaller
2. Marwin H. S. Segler

Citations in the corpus

• A Role for Fragment-Based Drug Design in Developing Novel Lead Compounds for Central Nervous System Targets (2015, neutral): “To create selective lead compounds, a naturally derived fragment was docked in the allosteric pocket of the matrix metalloproteinase 13 (MMP-13) enzyme, then elongated until the molecule simultaneously occupied the orthosteric pocket (46).”
• Artificial Intelligence For Natural Product Drug Discovery (2023, background): “Virtually all computational drug discovery approaches have been successfully applied to elucidate targets of natural products, including docking 54 , clustering 55 , bioactivity fingerprints 56 , pharmacophores 57 and machine learning 58 .”