Name
Title | ||
|---|---|---|
DEPACT and PACMatch: A Workflow of Designing De Novo Protein Pockets to Bind Small Molecules |
Abstract | ||
|---|---|---|
Engineering of new functional proteins such as enzymes and biosensors involves the design of new protein pockets for the specific binding of small molecules. Here, we report a workflow composed of two new computational methods to execute this task. The DEPACT (Design Pocket as a Cluster based on Templates) method is a data-driven approach to design and evaluate small-molecule-binding pockets as isolated clusters, while the PACMatch method is a computational approach to match pocket residues in a cluster model to positions on given protein scaffolds. Using DEPACT and its scoring function, pocket clusters of natural-pocket-like chemical compositions and protein-ligand interaction strength can be designed. DEPACT can design pocket clusters containing water- or metal-ion-mediated protein-ligand interactions. While being able to efficiently treat relatively large pocket cluster models (e.g., of around 10 pocket residues), PACMatch outperforms previous methods in test cases of recovering the native positions of pocket residues in natural enzyme-substrate complexes. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1021/acs.jcim.1c01398 | JOURNAL OF CHEMICAL INFORMATION AND MODELING |
DocType | Volume | Issue |
Journal | 62 | 4 |
ISSN | Citations | PageRank |
1549-9596 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yaoxi Chen | 1 | 0 | 0.34 |
| Quan Chen | 2 | 0 | 0.34 |
| Haiyan Liu | 3 | 0 | 0.34 |