A defined structural unit enables de novo design of small-molecule–binding proteins
By N. Polizzi, William F. DeGrado. 2020
133 citations recorded by the source corpus.
A new tool in the protein design toolbox Protein design can compute protein folds from first principles. However, designing new proteins that are functional remains challenging, in part because designing binding interactions requires simultaneous optimization of protein sequence and protein-ligand conformation. Polizzi and DeGrado designed proteins from scratch that bind a small-molecule drug (see the Perspective by Peacock). They introduced a new structural element called a van der Mer (vdM), which tracks the orientation of a chemical group relative to the backbone of a contacting residue. Assuming proteins bind ligands using interactions similar to intraprotein packing, they determined statistically preferred vdMs from a large set of structures in the Protein Data Bank. By including weighted vdMs in their computations, they designed two of six de novo proteins that bind the drug apixaban. A drug-protein x-ray crystal structure confirmed the designed model. Science, this issue p. 1227; see also p. 1166 An innovative representation of protein–chemical-group interactions enables design of proteins that bind the blood-thinning drug apixaban. The de novo design of proteins that bind highly functionalized small molecules represents a great challenge. To enable computational design of binders, we developed a unit of protein structure—a van der Mer (vdM)—that maps the backbone of each amino acid to statistically preferred positions of interacting chemical groups. Using vdMs, we designed six de novo proteins to bind the drug apixaban; two bound with low and submicromolar affinity. X-ray crystallography and mutagenesis confirmed a structure with a precisely designed cavity that forms favorable interactions in the drug–protein complex. vdMs may enable design of functional proteins for applications in sensing, medicine, and catalysis.
Subfields: Materials Chemistry, Molecular Biology
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In Materials Chemistry
- Robin Pearce
- Yang Zhang
- Arash Vahdat
- Anima Anandkumar
- Thomas F. Miller
- Zhuoran Qiao
- Weili Nie
- Jianyi Yang
In Molecular Biology
- Robin Pearce
- Yang Zhang
- Anima Anandkumar
- Weili Nie
- Arash Vahdat
- Thomas F. Miller
- Zhuoran Qiao
- Jianyi Yang
Citations in the corpus
- State-specific protein–ligand complex structure prediction with a multiscale deep generative model (2022, positive): “The capability of inpainting cropped structures without template information shows immediate applicability for de novo ligand-binding protein design 46 , since the NeuralPLexer network can be viably adapted to jointly generate binding-site backbones and sequences in the absence of protein sequence…”
- Deep learning techniques have significantly impacted protein structure prediction and protein design. (2021, background): “The past few years have seen rapid progress in de novo protein design, where proteins with increasingly complex structural characteristics and functions have been created [46–50,51 ,52–56].”