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Three-Dimensional Graph Matching to Identify Secondary Structure Correspondence of Medium-Resolution Cryo-EM Density Maps
| Content Provider | MDPI |
|---|---|
| Author | Behkamal, Bahareh Naghibzadeh, Mahmoud Saberi, Mohammad Reza Tehranizadeh, Zeinab Amiri Pagnani, Andrea Nasr, Kamal Al |
| Copyright Year | 2021 |
| Description | Cryo-electron microscopy (cryo-EM) is a structural technique that has played a significant role in protein structure determination in recent years. Compared to the traditional methods of X-ray crystallography and NMR spectroscopy, cryo-EM is capable of producing images of much larger protein complexes. However, cryo-EM reconstructions are limited to medium-resolution (~4–10 Å) for some cases. At this resolution range, a cryo-EM density map can hardly be used to directly determine the structure of proteins at atomic level resolutions, or even at their amino acid residue backbones. At such a resolution, only the position and orientation of secondary structure elements (SSEs) such as α-helices and β-sheets are observable. Consequently, finding the mapping of the secondary structures of the modeled structure (SSEs-A) to the cryo-EM map (SSEs-C) is one of the primary concerns in cryo-EM modeling. To address this issue, this study proposes a novel automatic computational method to identify SSEs correspondence in three-dimensional (3D) space. Initially, through a modeling of the target sequence with the aid of extracting highly reliable features from a generated 3D model and map, the SSEs matching problem is formulated as a 3D vector matching problem. Afterward, the 3D vector matching problem is transformed into a 3D graph matching problem. Finally, a similarity-based voting algorithm combined with the principle of least conflict (PLC) concept is developed to obtain the SSEs correspondence. To evaluate the accuracy of the method, a testing set of 25 experimental and simulated maps with a maximum of 65 SSEs is selected. Comparative studies are also conducted to demonstrate the superiority of the proposed method over some state-of-the-art techniques. The results demonstrate that the method is efficient, robust, and works well in the presence of errors in the predicted secondary structures of the cryo-EM images. |
| Starting Page | 1773 |
| e-ISSN | 2218273X |
| DOI | 10.3390/biom11121773 |
| Journal | Biomolecules |
| Issue Number | 12 |
| Volume Number | 11 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2021-11-26 |
| Access Restriction | Open |
| Subject Keyword | Biomolecules Mathematical and Computational Biology Protein Cryo-electron Microscopy Modeled Structure Secondary Structure Elements 3d Vector Matching 3d Graph Matching Similarity-based Voting Algorithm |
| Content Type | Text |
| Resource Type | Article |
