New computational protein design methods for de novo small molecule binding sites
New computational protein design methods for de novo small molecule binding sites
Protein binding to small molecules is fundamental to many biological processes, yet it remains challenging to predictively design this functionality de novo. Current state-of-the-art computational design methods typically rely on existing small molecule binding sites or protein scaffolds with existing shape complementarity for a target ligand. Here we introduce new methods that utilize pools of discrete contacts between protein side chains and defined small molecule ligand substructures (ligand fragments) observed in the Protein Data Bank. We use the Rosetta Molecular Modeling Suite to recombine protein side chains in these contact pools to generate hundreds of thousands of energetically favorable binding sites for a target ligand. These composite binding sites are built into existing scaffold proteins matching the intended binding site geometry with high accuracy. In addition, we apply pools of side chain rotamers interacting with the target ligand to augment Rosetta's conventional design machinery and improve key metrics known to be predictive of design success. We demonstrate that our method reliably builds diverse binding sites into different scaffold proteins for a variety of target molecules. Our generalizable de novo ligand binding site design method provides a foundation for versatile design of protein to interface previously unattainable molecules for applications in medical diagnostics and synthetic biology.
- University of California, Berkeley United States
- University of California San Francisco United States
- UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- University of California, San Francisco United States
Models, Molecular, Binding Sites, QH301-705.5, Computational Biology, Proteins, Protein Engineering, Biology (General), Algorithms, Software, Research Article, Protein Binding
Models, Molecular, Binding Sites, QH301-705.5, Computational Biology, Proteins, Protein Engineering, Biology (General), Algorithms, Software, Research Article, Protein Binding
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