Multi‐LZerD: Multiple protein docking for asymmetric complexes

Esquivel‐Rodríguez, Juan; Yang, Yuxin; Kihara, Daisuke

doi:10.1002/prot.24079

Cited by 83 publications

(79 citation statements)

References 44 publications

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“…Although these methods have been successfully applied in a couple of cases, the application has been limited to a small number of PPIs, which is partly due to the limited number of known structures of PPIs. To augment the limited structure data of PPIs, a potential future direction is to use computational protein-protein docking programs [105, 106] to model PPIs, which are now available for various types of PPIs [104, 107]. …”

Section: Discussionmentioning

confidence: 99%

In silico structure-based approaches to discover protein-protein interaction-targeting drugs

Shin

Christoffer

Kihara

2017

Methods

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A core concept behind modern drug discovery is finding a small molecule that modulates a function of a target protein. This concept has been successfully applied since the mid-1970s. However, the efficiency of drug discovery is decreasing because the druggable target space in the human proteome is limited. Recently, protein-protein interaction (PPI) has been identified as an emerging target space for drug discovery. PPI plays a pivotal role in biological pathways including diseases. Current human interactome research suggests that the number of PPIs ranges from 130,000 to 650,000, and only a small number of them have been targeted as drug targets. For traditional drug targets, in silico structure-based methods have been successful in many cases. However, their performance suffers on PPI interfaces because PPI interfaces are different in five major aspects: From a geometric standpoint, they have relatively large interface regions, flat geometry, and the interface surface shape tends to fluctuate upon binding. Also, their interactions are dominated by hydrophobic atoms, which is different from traditional binding-pocket-targeted drugs. Finally, PPI targets usually lack natural molecules that bind to the target PPI interface. Here, we first summarize characteristics of PPI interfaces and their known binders. Then, we will review existing in silico structure-based approaches for discovering small molecules that bind to PPI interfaces.

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Section: Discussionmentioning

confidence: 99%

In silico structure-based approaches to discover protein-protein interaction-targeting drugs

Shin

Christoffer

Kihara

2017

Methods

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“…EMLZerD fits multiple high-resolution structures into an EM map. It first uses a multiple protein-protein docking method, Multi-LZerD (Esquivel-Rodríguez et al, 2012), to generate a couple hundred candidate models of the protein complex. Then, each candidate model is compared with an EM map, using their 3DZD shape profiles, to select the best-fitted models.…”

Section: Rigid Fitting Methodsmentioning

confidence: 99%

Computational methods for constructing protein structure models from 3D electron microscopy maps

Esquivel‐Rodríguez

2013

Journal of Structural Biology

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Protein structure determination by cryo-electron microscopy (EM) has made significant progress in the past decades. Resolutions of EM maps have been improving as evidenced by recently reported structures that are solved at high resolutions close to 3 Å. Computational methods play a key role in interpreting EM data. Among many computational procedures applied to an EM map to obtain protein structure information, in this article we focus on reviewing computational methods that model protein three-dimensional (3D) structures from a 3D EM density map that is constructed from two-dimensional (2D) maps. The computational methods we discuss range from de novo methods, which identify structural elements in an EM map, to structure fitting methods, where known high resolution structures are fit into a low-resolution EM map. A list of available computational tools is also provided.

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“…The detailed algorithm and the benchmark results of multiple protein docking is provided elsewhere 28,29 . Here, we provide a brief explanation of the algorithm and the pseudo-code of Multi-LZerD (Figure 2).…”

Section: Experimental Methodsmentioning

confidence: 99%

Fitting Multimeric Protein Complexes into Electron Microscopy Maps Using 3D Zernike Descriptors

Esquivel‐Rodríguez

Kihara

2012

J. Phys. Chem. B

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A novel computational method for fitting high-resolution structures of multiple proteins into a cryoelectron microscopy map is presented. The method named EMLZerD generates a pool of candidate multiple protein docking conformations of component proteins, which are later compared with a provided electron microscopy (EM) density map to select the ones that fit well into the EM map. The comparison of docking conformations and the EM map is performed using the 3D Zernike descriptor (3DZD), a mathematical series expansion of three-dimensional functions. The 3DZD provides a unified representation of the surface shape of multimeric protein complex models and EM maps, which allows a convenient, fast quantitative comparison of the three dimensional structural data. Out of 19 multimeric complexes tested, near native complex structures with a root mean square deviation of less than 2.5 Å were obtained for 14 cases while medium range resolution structures with correct topology were computed for the additional 5 cases.

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Multi‐LZerD: Multiple protein docking for asymmetric complexes

Cited by 83 publications

References 44 publications

In silico structure-based approaches to discover protein-protein interaction-targeting drugs

In silico structure-based approaches to discover protein-protein interaction-targeting drugs

Computational methods for constructing protein structure models from 3D electron microscopy maps

Fitting Multimeric Protein Complexes into Electron Microscopy Maps Using 3D Zernike Descriptors

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