Protein 3D Structure and Electron Microscopy Map Retrieval Using 3D‐SURFER2.0 and EM‐SURFER

Han, Xusi; Qing, Wei

doi:10.1002/cpbi.37

Cited by 9 publications

(8 citation statements)

References 43 publications

(50 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We further compared the performance of VESPER using the DOT score and CC with three existing methods, gmfit and fitmap, and EM-SURFER that uses 3DZDs for the map shape search 10 , 14 . gmfit was run with 20 GDFs, which is the setting for map superimposition in the Omokage map search web server where gmfit was used 6 .…”

Section: Resultsmentioning

confidence: 99%

“…Then, from each of the randomly generated placements, local optimization is performed to maximize the correlation between two maps. Previously, we have developed EM-SURFER, a web-based tool for real-time global matching and database search for EM maps 10 , 14 . In EM-SURFER, we used 3D zernike descriptors (3DZD) for the efficient comparison of EM map isosurfaces.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

VESPER: global and local cryo-EM map alignment using local density vectors

et al. 2021

Self Cite

View full text Add to dashboard Cite

An increasing number of density maps of biological macromolecules have been determined by cryo-electron microscopy (cryo-EM) and stored in the public database, EMDB. To interpret the structural information contained in EM density maps, alignment of maps is an essential step for structure modeling, comparison of maps, and for database search. Here, we developed VESPER, which captures the similarity of underlying molecular structures embedded in density maps by taking local gradient directions into consideration. Compared to existing methods, VESPER achieved substantially more accurate global and local alignment of maps as well as database retrieval.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

VESPER: global and local cryo-EM map alignment using local density vectors

et al. 2021

Self Cite

View full text Add to dashboard Cite

show abstract

“…It was demonstrated that 3DZD can distinguish proteins of different folds even at low resolution of 15 Å. A web-based platform for comparing cryo-EM maps was also developed by the same group (Esquivel-Rodríguez et al, 2015 ; Han et al, 2017 ). A similar method utilized 3D Zernike moments to search a database of protein structures for matching protein structures to a cryo-EM map (Yin and Dokholyan, 2011 ).…”

Section: Application Of Shape Similarity Methods In Drug Discoverymentioning

confidence: 99%

Advances in the Development of Shape Similarity Methods and Their Application in Drug Discovery

2018

View full text Add to dashboard Cite

Molecular similarity is a key concept in drug discovery. It is based on the assumption that structurally similar molecules frequently have similar properties. Assessment of similarity between small molecules has been highly effective in the discovery and development of various drugs. Especially, two-dimensional (2D) similarity approaches have been quite popular due to their simplicity, accuracy and efficiency. Recently, the focus has been shifted toward the development of methods involving the representation and comparison of three-dimensional (3D) conformation of small molecules. Among the 3D similarity methods, evaluation of shape similarity is now gaining attention for its application not only in virtual screening but also in molecular target prediction, drug repurposing and scaffold hopping. A wide range of methods have been developed to describe molecular shape and to determine the shape similarity between small molecules. The most widely used methods include atom distance-based methods, surface-based approaches such as spherical harmonics and 3D Zernike descriptors, atom-centered Gaussian overlay based representations. Several of these methods demonstrated excellent virtual screening performance not only retrospectively but also prospectively. In addition to methods assessing the similarity between small molecules, shape similarity approaches have been developed to compare shapes of protein structures and binding pockets. Additionally, shape comparisons between atomic models and 3D density maps allowed the fitting of atomic models into cryo-electron microscopy maps. This review aims to summarize the methodological advances in shape similarity assessment highlighting advantages, disadvantages and their application in drug discovery.

show abstract

“…The 3DZD files of the single-chain and the complex datasets are made available at S1 Data. 3DZD can be also computed for PDB files at the benchmark page of 3D-SURFER (http://kiharalab.org/3d-surfer/batch.php) [25,38].…”

Section: Methodsmentioning

confidence: 99%

“…Protein surface shapes were represented with 3D Zernike Descriptors (3DZD), mathematical moment-based invariants of 3D functions [23]. 3DZD has been demonstrated efficient for various biomolecular structure comparisons [24], including comparisons of EM maps [25]. Another critical difference between the current study and the previous works is that we analyzed protein complexes in comparison with single proteins.…”

Section: Introductionmentioning

confidence: 99%

A global map of the protein shape universe

et al. 2019

Self Cite

View full text Add to dashboard Cite

Proteins are involved in almost all functions in a living cell, and functions of proteins are realized by their tertiary structures. Obtaining a global perspective of the variety and distribution of protein structures lays a foundation for our understanding of the building principle of protein structures. In light of the rapid accumulation of low-resolution structure data from electron tomography and cryo-electron microscopy, here we map and classify three-dimensional (3D) surface shapes of proteins into a similarity space. Surface shapes of proteins were represented with 3D Zernike descriptors, mathematical moment-based invariants, which have previously been demonstrated effective for biomolecular structure similarity search. In addition to single chains of proteins, we have also analyzed the shape space occupied by protein complexes. From the mapping, we have obtained various new insights into the relationship between shapes, main-chain folds, and complex formation. The unique view obtained from shape mapping opens up new ways to understand design principles, functions, and evolution of proteins.

show abstract

Protein 3D Structure and Electron Microscopy Map Retrieval Using 3D‐SURFER2.0 and EM‐SURFER

Cited by 9 publications

References 43 publications

VESPER: global and local cryo-EM map alignment using local density vectors

VESPER: global and local cryo-EM map alignment using local density vectors

Advances in the Development of Shape Similarity Methods and Their Application in Drug Discovery

A global map of the protein shape universe

Contact Info

Product

Resources

About